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3 Commits

Author SHA1 Message Date
Willem Jiang 0fdfbae435 Merge branch 'main' into copilot/fix-lint-frontend-job 2026-06-07 21:42:16 +08:00
copilot-swe-agent[bot] 150d03f2e7 fix(frontend): avoid render-time subtask context mutation 2026-06-07 13:35:28 +00:00
copilot-swe-agent[bot] 9593214065 Initial plan 2026-06-07 13:20:20 +00:00
209 changed files with 1363 additions and 19001 deletions
-1
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@@ -21,7 +21,6 @@ INFOQUEST_API_KEY=your-infoquest-api-key
# DEEPSEEK_API_KEY=your-deepseek-api-key
# NOVITA_API_KEY=your-novita-api-key # OpenAI-compatible, see https://novita.ai
# MINIMAX_API_KEY=your-minimax-api-key # OpenAI-compatible, see https://platform.minimax.io
# STEPFUN_API_KEY=your-stepfun-api-key # OpenAI-compatible, see https://platform.stepfun.com
# VLLM_API_KEY=your-vllm-api-key # OpenAI-compatible
# FEISHU_APP_ID=your-feishu-app-id
# FEISHU_APP_SECRET=your-feishu-app-secret
+72
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@@ -0,0 +1,72 @@
# Path-based PR auto-labeling config for actions/labeler@v5.
# Each key is a label (must exist — see .github/labels.yml); the globs decide
# when it is applied. A PR can match several areas, which is expected.
"area:frontend":
- changed-files:
- any-glob-to-any-file:
- "frontend/**"
"area:backend":
- changed-files:
- any-glob-to-any-file:
- "backend/app/**"
- "backend/packages/harness/deerflow/runtime/**"
- "backend/packages/harness/deerflow/persistence/**"
- "backend/packages/harness/deerflow/config/**"
- "backend/packages/harness/deerflow/tools/**"
- "backend/packages/harness/deerflow/guardrails/**"
- "backend/packages/harness/deerflow/tracing/**"
- "backend/packages/harness/deerflow/models/**"
- "backend/packages/harness/deerflow/utils/**"
- "backend/packages/harness/deerflow/uploads/**"
"area:agents":
- changed-files:
- any-glob-to-any-file:
- "backend/packages/harness/deerflow/agents/**"
- "backend/packages/harness/deerflow/subagents/**"
- "backend/packages/harness/deerflow/reflection/**"
- "backend/langgraph.json"
- "backend/**/prompts/**"
"area:sandbox":
- changed-files:
- any-glob-to-any-file:
- "docker/**"
- "backend/packages/harness/deerflow/sandbox/**"
- "backend/Dockerfile"
- "frontend/Dockerfile"
"area:skills":
- changed-files:
- any-glob-to-any-file:
- "skills/**"
- "backend/packages/harness/deerflow/skills/**"
- "frontend/src/core/skills/**"
"area:mcp":
- changed-files:
- any-glob-to-any-file:
- "backend/packages/harness/deerflow/mcp/**"
- "frontend/src/core/mcp/**"
"area:ci":
- changed-files:
- any-glob-to-any-file:
- ".github/**"
- "scripts/**"
"area:docs":
- changed-files:
- any-glob-to-any-file:
- "docs/**"
- "**/*.md"
"area:deps":
- changed-files:
- any-glob-to-any-file:
- "backend/pyproject.toml"
- "backend/uv.lock"
- "frontend/package.json"
- "frontend/pnpm-lock.yaml"
+44
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@@ -0,0 +1,44 @@
name: Issue Triage
# Ensures every newly opened issue carries `needs-triage`, even blank or
# API-created ones that bypass the issue templates. Creates the label if it is
# somehow missing, so the workflow is self-healing.
on:
issues:
types: [opened]
permissions:
issues: write
jobs:
needs-triage:
runs-on: ubuntu-latest
steps:
- name: Add needs-triage label
uses: actions/github-script@v7
with:
script: |
const { owner, repo } = context.repo;
const issue_number = context.payload.issue.number;
const current = (context.payload.issue.labels || []).map(l => l.name);
if (current.includes('needs-triage')) {
core.info('Issue already has needs-triage; nothing to do.');
return;
}
// Self-heal: create the label if it does not exist yet.
try {
await github.rest.issues.createLabel({
owner, repo, name: 'needs-triage', color: 'fef2c0',
description: 'Awaiting maintainer triage',
});
} catch (e) {
if (e.status !== 422) throw e; // 422 = already exists
}
await github.rest.issues.addLabels({
owner, repo, issue_number, labels: ['needs-triage'],
});
core.info(`Added needs-triage to #${issue_number}.`);
+28
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@@ -0,0 +1,28 @@
name: PR Labeler
# Applies area:* labels based on which files a PR changes (see .github/labeler.yml).
# Uses pull_request_target so it also works on fork PRs. SAFE: actions/labeler
# only reads the changed-file list via the API — it never checks out or runs PR code.
on:
pull_request_target:
types: [opened, synchronize, reopened, ready_for_review]
permissions:
contents: read
pull-requests: write
concurrency:
group: pr-labeler-${{ github.event.pull_request.number }}
cancel-in-progress: true
jobs:
label:
if: github.event.pull_request.draft == false
runs-on: ubuntu-latest
steps:
- name: Apply area labels
uses: actions/labeler@v5
with:
configuration-path: .github/labeler.yml
sync-labels: true
+164
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@@ -0,0 +1,164 @@
name: PR Triage
# Two responsibilities, both pure-metadata (no PR code is checked out or run):
# 1. On open/sync: apply size/* + risk:* labels, and needs-validation when the
# PR touches the front/back contract surface (backend API, SSE, agents, or
# the frontend streaming client). A `skip-validation` label opts out.
# 2. On maintainer review: apply the `reviewing` label.
#
# All labels are managed within their own namespace — labels outside size/*,
# risk:*, needs-validation and reviewing are never touched here.
on:
pull_request_target:
types: [opened, synchronize, reopened, ready_for_review]
pull_request_review:
types: [submitted]
permissions:
contents: read
pull-requests: write
concurrency:
group: pr-triage-${{ github.event.pull_request.number }}
cancel-in-progress: false
jobs:
size-and-risk:
if: github.event_name == 'pull_request_target' && github.event.pull_request.draft == false
runs-on: ubuntu-latest
steps:
- name: Label size, risk and validation need
uses: actions/github-script@v7
with:
script: |
const pr = context.payload.pull_request;
const { owner, repo } = context.repo;
const prNumber = pr.number;
// ---- size, from additions + deletions ----
const churn = (pr.additions || 0) + (pr.deletions || 0);
const sizeLabel =
churn < 20 ? 'size/XS' :
churn < 100 ? 'size/S' :
churn < 300 ? 'size/M' :
churn < 700 ? 'size/L' : 'size/XL';
// ---- changed paths ----
const files = await github.paginate(github.rest.pulls.listFiles, {
owner, repo, pull_number: prNumber, per_page: 100,
});
const paths = files.map(f => f.filename);
const matches = (re) => paths.some(p => re.test(p));
const docsOnly = paths.length > 0 && paths.every(p =>
/\.(md|mdx|txt)$/i.test(p) || p.startsWith('docs/') ||
/\.(png|jpe?g|gif|svg|webp|ico)$/i.test(p));
const highRisk = matches(
/^backend\/app\/gateway\//) || matches(
/^backend\/packages\/harness\/deerflow\/(agents|subagents|sandbox)\//) || matches(
/(^|\/)langgraph\.json$/) || matches(
/(^|\/)(auth|authz|security)/i) || matches(
/(pyproject\.toml|uv\.lock|package\.json|pnpm-lock\.yaml)$/) || matches(
/^docker\//) || matches(
/^\.github\/workflows\//);
const riskLabel = docsOnly ? 'risk:low' : (highRisk ? 'risk:high' : 'risk:medium');
// needs-validation: front/back contract surface
const contractSurface =
matches(/^backend\/app\/gateway\//) ||
matches(/^backend\/packages\/harness\/deerflow\/(agents|subagents)\//) ||
matches(/(^|\/)langgraph\.json$/) ||
matches(/^frontend\/src\/core\/(api|threads|messages)\//);
const current = (pr.labels || []).map(l => l.name);
const hasSkip = current.includes('skip-validation');
const desired = [sizeLabel, riskLabel];
if (contractSurface && !hasSkip) desired.push('needs-validation');
const managed = (name) =>
name.startsWith('size/') || name.startsWith('risk:') || name === 'needs-validation';
const toRemove = current.filter(l => managed(l) && !desired.includes(l));
const toAdd = desired.filter(l => !current.includes(l));
for (const name of toRemove) {
try {
await github.rest.issues.removeLabel({ owner, repo, issue_number: prNumber, name });
} catch (e) {
if (e.status !== 404) throw e;
}
}
if (toAdd.length) {
await github.rest.issues.addLabels({ owner, repo, issue_number: prNumber, labels: toAdd });
}
core.info(`size=${sizeLabel} risk=${riskLabel} churn=${churn} ` +
`validation=${desired.includes('needs-validation')} ` +
`(+${toAdd.join(',') || '-'} / -${toRemove.join(',') || '-'})`);
first-time:
if: github.event_name == 'pull_request_target' && github.event.action == 'opened'
runs-on: ubuntu-latest
steps:
- name: Label first-time contributors
uses: actions/github-script@v7
with:
script: |
const pr = context.payload.pull_request;
const { owner, repo } = context.repo;
const assoc = pr.author_association;
const isBot = pr.user.type === 'Bot';
core.info(`author=${pr.user.login} association=${assoc} bot=${isBot}`);
// FIRST_TIME_CONTRIBUTOR = no prior merged commit to this repo;
// FIRST_TIMER = no prior commit anywhere on GitHub. Either counts.
if (isBot || !['FIRST_TIME_CONTRIBUTOR', 'FIRST_TIMER'].includes(assoc)) {
core.info('Not a first-time contributor; skipping.');
return;
}
await github.rest.issues.addLabels({
owner, repo, issue_number: pr.number, labels: ['first-time-contributor'],
});
core.info(`Added first-time-contributor to #${pr.number}.`);
reviewing:
if: github.event_name == 'pull_request_review'
runs-on: ubuntu-latest
steps:
- name: Add reviewing label for maintainer reviews
uses: actions/github-script@v7
with:
script: |
const { owner, repo } = context.repo;
const prNumber = context.payload.pull_request.number;
const reviewer = context.payload.review.user.login;
const { data: perm } = await github.rest.repos.getCollaboratorPermissionLevel({
owner, repo, username: reviewer,
});
if (!['admin', 'write', 'maintain'].includes(perm.permission)) {
core.info(`Reviewer ${reviewer} (${perm.permission}) is not a maintainer; skipping.`);
return;
}
const { data: labels } = await github.rest.issues.listLabelsOnIssue({
owner, repo, issue_number: prNumber,
});
if (labels.some(l => l.name === 'reviewing')) {
core.info('Already labeled reviewing; skipping.');
return;
}
try {
await github.rest.issues.addLabels({
owner, repo, issue_number: prNumber, labels: ['reviewing'],
});
core.info(`Added "reviewing" (reviewer ${reviewer}).`);
} catch (e) {
// 403 is expected for review events on some fork PR contexts.
if (e.status === 403) core.info('No permission to label (expected on some fork PRs).');
else throw e;
}
-108
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@@ -1,108 +0,0 @@
name: Replay E2E (front-back contract)
# Guards the front-back contract via record/replay (no API key in CI):
# Layer 1 — backend golden: replay a recorded trace through the real gateway,
# assert the SSE event sequence matches the committed golden.
# Layer 2 — full-stack render: real Next.js frontend + real gateway (replay
# model) + Chromium; assert the replayed turns render in the browser.
# Triggered by changes on EITHER side of the contract so a backend change can no
# longer pass without the frontend-facing checks running.
on:
push:
branches: ["main"]
paths:
- "frontend/**"
- "backend/app/gateway/**"
- "backend/packages/harness/**"
- "backend/tests/fixtures/replay/**"
- "backend/tests/replay_provider.py"
- "backend/tests/_replay_fixture.py"
- "backend/tests/seed_runs_router.py"
- "backend/tests/test_replay_golden.py"
- "backend/scripts/run_replay_gateway.py"
- ".github/workflows/replay-e2e.yml"
pull_request:
types: [opened, synchronize, reopened, ready_for_review]
paths:
- "frontend/**"
- "backend/app/gateway/**"
- "backend/packages/harness/**"
- "backend/tests/fixtures/replay/**"
- "backend/tests/replay_provider.py"
- "backend/tests/_replay_fixture.py"
- "backend/tests/seed_runs_router.py"
- "backend/tests/test_replay_golden.py"
- "backend/scripts/run_replay_gateway.py"
- ".github/workflows/replay-e2e.yml"
concurrency:
group: replay-e2e-${{ github.event.pull_request.number || github.ref }}
cancel-in-progress: true
permissions:
contents: read
jobs:
backend-replay-golden:
name: Layer 1 — backend golden (no API key)
if: github.event_name != 'pull_request' || github.event.pull_request.draft == false
runs-on: ubuntu-latest
timeout-minutes: 15
steps:
- uses: actions/checkout@v6
- name: Set up Python
uses: actions/setup-python@v6
with:
python-version: "3.12"
- name: Install uv
uses: astral-sh/setup-uv@v7
- name: Install backend dependencies
working-directory: backend
run: uv sync --group dev
- name: Replay golden (backend SSE contract)
working-directory: backend
run: PYTHONPATH=. uv run pytest tests/test_replay_golden.py -v
fullstack-replay-render:
name: Layer 2 — full-stack render (no API key)
if: github.event_name != 'pull_request' || github.event.pull_request.draft == false
runs-on: ubuntu-latest
timeout-minutes: 25
steps:
- uses: actions/checkout@v6
- name: Set up Python
uses: actions/setup-python@v6
with:
python-version: "3.12"
- name: Install uv
uses: astral-sh/setup-uv@v7
- name: Install backend dependencies (replay gateway)
working-directory: backend
run: uv sync --group dev
- name: Setup Node.js
uses: actions/setup-node@v4
with:
node-version: "22"
- name: Enable Corepack
run: corepack enable
- name: Use pinned pnpm version
run: corepack prepare pnpm@10.26.2 --activate
- name: Install frontend dependencies
working-directory: frontend
run: pnpm install --frozen-lockfile
- name: Install Playwright Chromium
working-directory: frontend
run: npx playwright install chromium --with-deps
- name: Full-stack replay render (DOM assertions are the gate)
working-directory: frontend
run: pnpm exec playwright test -c playwright.real-backend.config.ts
- name: Upload report + render artifact
uses: actions/upload-artifact@v4
if: ${{ !cancelled() }}
with:
name: replay-render
path: |
frontend/playwright-report/
frontend/test-results/
retention-days: 7
-223
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@@ -1,223 +0,0 @@
name: Triage
# One workflow for all event-driven PR/issue labeling. Replaces the former
# pr-labeler / pr-triage / issue-triage workflows (and drops actions/labeler).
#
# Design notes:
# * All jobs are pure-metadata: they read changed-file lists / PR fields / the
# review payload via the API and write labels. PR code is NEVER checked out
# or executed, so pull_request_target is safe here.
# * Each job only reconciles labels in namespaces IT owns
# (area:* / size/* / risk:* / needs-validation). It never touches labels
# applied by maintainers or other tools (bug, priority, etc.). first-time-
# contributor and reviewing are add-only.
# * State is read LIVE (listFiles + listLabelsOnIssue) at run time, not from
# the (stale) event payload, so rapid synchronize events converge instead
# of thrashing.
on:
pull_request_target:
types: [opened, synchronize, reopened, ready_for_review]
pull_request_review:
types: [submitted]
issues:
types: [opened]
permissions:
contents: read
pull-requests: write
issues: write
jobs:
# ── PR: area / size / risk / needs-validation / first-time ─────────────────
pr-labels:
if: github.event_name == 'pull_request_target' && github.event.pull_request.draft == false
runs-on: ubuntu-latest
concurrency:
group: triage-pr-${{ github.event.pull_request.number }}
cancel-in-progress: true
steps:
- name: Apply PR labels from live state
uses: actions/github-script@v8
with:
script: |
const pr = context.payload.pull_request;
const { owner, repo } = context.repo;
const num = pr.number;
// ---- live changed files ----
const files = await github.paginate(github.rest.pulls.listFiles, {
owner, repo, pull_number: num, per_page: 100,
});
const paths = files.map(f => f.filename);
const m = (re) => paths.some(p => re.test(p));
// ---- area: replaces .github/labeler.yml (path -> area) ----
const AREA_RULES = [
['area:frontend', [/^frontend\//]],
['area:backend', [/^backend\/app\//, /^backend\/packages\/harness\/deerflow\/(runtime|persistence|config|tools|guardrails|tracing|models|utils|uploads)\//]],
['area:agents', [/^backend\/packages\/harness\/deerflow\/(agents|subagents|reflection)\//, /(^|\/)langgraph\.json$/, /^backend\/.*\/prompts\//]],
['area:sandbox', [/^docker\//, /^backend\/packages\/harness\/deerflow\/sandbox\//, /(^|\/)Dockerfile$/]],
['area:skills', [/^skills\//, /^backend\/packages\/harness\/deerflow\/skills\//, /^frontend\/src\/core\/skills\//]],
['area:mcp', [/^backend\/packages\/harness\/deerflow\/mcp\//, /^frontend\/src\/core\/mcp\//]],
['area:ci', [/^\.github\//, /^scripts\//]],
['area:docs', [/^docs\//, /\.mdx?$/]],
['area:deps', [/(^|\/)(pyproject\.toml|uv\.lock|package\.json|pnpm-lock\.yaml)$/]],
];
const areaLabels = AREA_RULES
.filter(([, res]) => res.some(re => m(re)))
.map(([label]) => label);
// ---- size: additions+deletions, excluding lockfiles/snapshots ----
const EXCLUDE_SIZE = /(^|\/)(uv\.lock|pnpm-lock\.yaml|package-lock\.json)$|\.snap$/;
const churn = files
.filter(f => !EXCLUDE_SIZE.test(f.filename))
.reduce((s, f) => s + (f.additions || 0) + (f.deletions || 0), 0);
const sizeLabel =
churn < 20 ? 'size/XS' :
churn < 100 ? 'size/S' :
churn < 300 ? 'size/M' :
churn < 700 ? 'size/L' : 'size/XL';
// ---- risk ----
const docsOnly = paths.length > 0 && paths.every(p =>
/\.(md|mdx|txt)$/i.test(p) || p.startsWith('docs/') ||
/\.(png|jpe?g|gif|svg|webp|ico)$/i.test(p));
const highRisk =
m(/^backend\/app\/gateway\//) ||
m(/^backend\/packages\/harness\/deerflow\/(agents|subagents|sandbox)\//) ||
m(/(^|\/)langgraph\.json$/) ||
m(/(^|\/)(auth|authz|security)/i) ||
m(/(pyproject\.toml|uv\.lock|package\.json|pnpm-lock\.yaml)$/) ||
m(/^docker\//) ||
m(/^\.github\/workflows\//);
const riskLabel = docsOnly ? 'risk:low' : (highRisk ? 'risk:high' : 'risk:medium');
// ---- needs-validation: front/back contract surface ----
const contract =
m(/^backend\/app\/gateway\//) ||
m(/^backend\/packages\/harness\/deerflow\/(agents|subagents)\//) ||
m(/(^|\/)langgraph\.json$/) ||
m(/^frontend\/src\/core\/(api|threads|messages)\//);
// ---- live current labels (NOT the stale event payload) ----
const current = (await github.paginate(github.rest.issues.listLabelsOnIssue, {
owner, repo, issue_number: num, per_page: 100,
})).map(l => l.name);
const hasSkip = current.includes('skip-validation');
// Reconcile ONLY namespaces we own; never touch others.
const owned = (n) =>
n.startsWith('area:') || n.startsWith('size/') ||
n.startsWith('risk:') || n === 'needs-validation';
const desired = new Set([...areaLabels, sizeLabel, riskLabel]);
if (contract && !hasSkip) desired.add('needs-validation');
const toRemove = current.filter(n => owned(n) && !desired.has(n));
const toAdd = [...desired].filter(n => !current.includes(n));
// first-time-contributor: add-only, on opened, real users only.
if (context.payload.action === 'opened' &&
pr.user.type === 'User' &&
['FIRST_TIME_CONTRIBUTOR', 'FIRST_TIMER'].includes(pr.author_association) &&
!current.includes('first-time-contributor')) {
toAdd.push('first-time-contributor');
}
for (const name of toRemove) {
try {
await github.rest.issues.removeLabel({ owner, repo, issue_number: num, name });
} catch (e) {
if (e.status !== 404) throw e;
}
}
if (toAdd.length) {
await github.rest.issues.addLabels({ owner, repo, issue_number: num, labels: toAdd });
}
core.info(`area=[${areaLabels.join(',')}] ${sizeLabel} ${riskLabel} churn=${churn} ` +
`validation=${desired.has('needs-validation')} ` +
`(+${toAdd.join(',') || '-'} / -${toRemove.join(',') || '-'})`);
# ── PR: reviewing label on a maintainer's human review ─────────────────────
reviewing:
if: github.event_name == 'pull_request_review'
runs-on: ubuntu-latest
concurrency:
group: triage-review-${{ github.event.pull_request.number }}
cancel-in-progress: false
steps:
- name: Add reviewing label for maintainer reviews
uses: actions/github-script@v8
with:
script: |
const { owner, repo } = context.repo;
const num = context.payload.pull_request.number;
const review = context.payload.review;
const assoc = review.author_association; // payload field; no API call
const type = review.user && review.user.type;
// author_association is NONE for every automated reviewer
// (Copilot, CodeRabbit, Codex, Sourcery, ...), so this allowlist
// drops them all without a denylist — and never calls the
// collaborators API that 404s on "Copilot is not a user".
// user.type === 'User' guards the rare bot-added-as-collaborator case.
if (!['OWNER', 'MEMBER', 'COLLABORATOR'].includes(assoc) || type !== 'User') {
core.info(`reviewer ${review.user && review.user.login} assoc=${assoc} type=${type}; skipping.`);
return;
}
const labels = (await github.paginate(github.rest.issues.listLabelsOnIssue, {
owner, repo, issue_number: num, per_page: 100,
})).map(l => l.name);
if (labels.includes('reviewing')) {
core.info('Already labeled reviewing; skipping.');
return;
}
try {
await github.rest.issues.addLabels({
owner, repo, issue_number: num, labels: ['reviewing'],
});
core.info('Added "reviewing".');
} catch (e) {
if (e.status === 403) core.info('No permission to label (expected on some fork PRs).');
else throw e;
}
# ── Issue: needs-triage on every new issue ────────────────────────────────
issue-triage:
if: github.event_name == 'issues'
runs-on: ubuntu-latest
concurrency:
group: triage-issue-${{ github.event.issue.number }}
cancel-in-progress: false
steps:
- name: Add needs-triage label
uses: actions/github-script@v8
with:
script: |
const { owner, repo } = context.repo;
const issue_number = context.payload.issue.number;
// Read live labels (not the event payload) so labels added at creation
// time via the API or by another automation are seen — consistent with
// the live-state reads in the PR jobs above.
const current = (await github.paginate(github.rest.issues.listLabelsOnIssue, {
owner, repo, issue_number, per_page: 100,
})).map(l => l.name);
if (current.includes('needs-triage')) {
core.info('Issue already has needs-triage; nothing to do.');
return;
}
// Self-heal: create the label if it does not exist yet.
try {
await github.rest.issues.createLabel({
owner, repo, name: 'needs-triage', color: 'fef2c0',
description: 'Awaiting maintainer triage',
});
} catch (e) {
if (e.status !== 422) throw e; // 422 = already exists
}
await github.rest.issues.addLabels({
owner, repo, issue_number, labels: ['needs-triage'],
});
core.info(`Added needs-triage to #${issue_number}.`);
-7
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@@ -247,9 +247,6 @@ Access: http://localhost:2026
The unified nginx endpoint is same-origin by default and does not emit browser CORS headers. If you run a split-origin or port-forwarded browser client, set `GATEWAY_CORS_ORIGINS` to comma-separated exact origins such as `http://localhost:3000`; the Gateway then applies the CORS allowlist and matching CSRF origin checks.
> [!IMPORTANT]
> The Gateway holds run state (RunManager and the stream bridge) in process, so production defaults to a single Gateway worker (`GATEWAY_WORKERS=1`). Raising the worker count without a shared cross-worker stream bridge — which is not yet available — breaks run cancellation, SSE reconnects, request de-duplication, and IM channels, because nginx uses no sticky sessions and each worker keeps its own run state. Scale a single worker up with more CPU/RAM (or move the database and sandbox onto dedicated tiers) instead of raising `GATEWAY_WORKERS`.
See [CONTRIBUTING.md](CONTRIBUTING.md) for detailed Docker development guide.
#### Option 2: Local Development
@@ -343,8 +340,6 @@ See the [MCP Server Guide](backend/docs/MCP_SERVER.md) for detailed instructions
DeerFlow supports receiving tasks from messaging apps. Channels auto-start when configured — no public IP required for any of them.
DeerFlow can also expose user-owned IM channel connections in the workspace UI. When `channel_connections` is enabled, logged-in users can bind Telegram, Slack, or Discord from the sidebar / Settings > Channels. It reuses the existing outbound `channels.*` transports, so no public IP or provider callback URL is required. Incoming IM messages then run under the connected DeerFlow user account. See [IM Channel Connections](backend/docs/IM_CHANNEL_CONNECTIONS.md) for setup and security notes.
| Channel | Transport | Difficulty |
|---------|-----------|------------|
| Telegram | Bot API (long-polling) | Easy |
@@ -590,8 +585,6 @@ A standard Agent Skill is a structured capability module — a Markdown file tha
Skills are loaded progressively — only when the task needs them, not all at once. This keeps the context window lean and makes DeerFlow work well even with token-sensitive models.
Users can explicitly activate an enabled skill for a single turn by starting the request with `/skill-name`, for example `/data-analysis analyze uploads/foo.csv`. DeerFlow loads that skill's `SKILL.md` as hidden current-turn context while leaving the base prompt limited to skill metadata. Slash activation respects disabled skills, custom-agent skill whitelists, and existing channel commands such as `/new` and `/help`.
When you install `.skill` archives through the Gateway, DeerFlow accepts standard optional frontmatter metadata such as `version`, `author`, and `compatibility` instead of rejecting otherwise valid external skills.
Tools follow the same philosophy. DeerFlow comes with a core toolset — web search, web fetch, file operations, bash execution — and supports custom tools via MCP servers and Python functions. Swap anything. Add anything.
-5
View File
@@ -24,10 +24,5 @@ config.yaml
# Langgraph
.langgraph_api
# Sandbox runtime working dir — pre-created and excluded from uvicorn reload
# (scripts/serve.sh, docker/dev-entrypoint.sh). Anchored so it does not match
# the source package backend/packages/harness/deerflow/sandbox/.
/sandbox/
# Claude Code settings
.claude/settings.local.json
+23 -38
View File
@@ -192,7 +192,7 @@ from deerflow.config import get_app_config
### Middleware Chain
Lead-agent middlewares are assembled in strict append order across `packages/harness/deerflow/agents/middlewares/tool_error_handling_middleware.py` (`build_lead_runtime_middlewares`) and `packages/harness/deerflow/agents/lead_agent/agent.py` (`build_middlewares`):
Lead-agent middlewares are assembled in strict append order across `packages/harness/deerflow/agents/middlewares/tool_error_handling_middleware.py` (`build_lead_runtime_middlewares`) and `packages/harness/deerflow/agents/lead_agent/agent.py` (`_build_middlewares`):
1. **ThreadDataMiddleware** - Creates per-thread directories under the user's isolation scope (`backend/.deer-flow/users/{user_id}/threads/{thread_id}/user-data/{workspace,uploads,outputs}`); resolves `user_id` via `get_effective_user_id()` (falls back to `"default"` in no-auth mode); Web UI thread deletion now follows LangGraph thread removal with Gateway cleanup of the local thread directory
2. **UploadsMiddleware** - Tracks and injects newly uploaded files into conversation
@@ -202,17 +202,16 @@ Lead-agent middlewares are assembled in strict append order across `packages/har
6. **GuardrailMiddleware** - Pre-tool-call authorization via pluggable `GuardrailProvider` protocol (optional, if `guardrails.enabled` in config). Evaluates each tool call and returns error ToolMessage on deny. Three provider options: built-in `AllowlistProvider` (zero deps), OAP policy providers (e.g. `aport-agent-guardrails`), or custom providers. See [docs/GUARDRAILS.md](docs/GUARDRAILS.md) for setup, usage, and how to implement a provider.
7. **SandboxAuditMiddleware** - Audits sandboxed shell/file operations for security logging before tool execution continues
8. **ToolErrorHandlingMiddleware** - Converts tool exceptions into error `ToolMessage`s so the run can continue instead of aborting
9. **SkillActivationMiddleware** - Detects strict `/skill-name task` syntax on the latest real user message, resolves only enabled and runtime-allowed skills, reads `SKILL.md` from trusted skill storage, injects the skill body as hidden current-turn model context, and records a `middleware:skill_activation` audit event with skill name, category, path, and content hash
10. **SummarizationMiddleware** - Context reduction when approaching token limits (optional, if enabled)
11. **TodoListMiddleware** - Task tracking with `write_todos` tool (optional, if plan_mode)
12. **TokenUsageMiddleware** - Records token usage metrics when token tracking is enabled (optional); subagent usage is cached by `tool_call_id` only while token usage is enabled and merged back into the dispatching AIMessage by message position rather than message id
13. **TitleMiddleware** - Auto-generates thread title after first complete exchange and normalizes structured message content before prompting the title model
14. **MemoryMiddleware** - Queues conversations for async memory update (filters to user + final AI responses)
15. **ViewImageMiddleware** - Injects base64 image data before LLM call (conditional on vision support)
16. **DeferredToolFilterMiddleware** - Hides deferred (MCP) tool schemas from the bound model using a build-time deferred-name set + catalog hash, reading per-thread promotions from `ThreadState.promoted` (hash-scoped, no ContextVar); a tool becomes bound on subsequent turns after `tool_search` returns its schema (optional, if `tool_search.enabled`)
17. **SubagentLimitMiddleware** - Truncates excess `task` tool calls from model response to enforce `MAX_CONCURRENT_SUBAGENTS` limit (optional, if `subagent_enabled`)
18. **LoopDetectionMiddleware** - Detects repeated tool-call loops; hard-stop responses clear both structured `tool_calls` and raw provider tool-call metadata before forcing a final text answer
19. **ClarificationMiddleware** - Intercepts `ask_clarification` tool calls, interrupts via `Command(goto=END)` (must be last)
9. **SummarizationMiddleware** - Context reduction when approaching token limits (optional, if enabled)
10. **TodoListMiddleware** - Task tracking with `write_todos` tool (optional, if plan_mode)
11. **TokenUsageMiddleware** - Records token usage metrics when token tracking is enabled (optional); subagent usage is cached by `tool_call_id` only while token usage is enabled and merged back into the dispatching AIMessage by message position rather than message id
12. **TitleMiddleware** - Auto-generates thread title after first complete exchange and normalizes structured message content before prompting the title model
13. **MemoryMiddleware** - Queues conversations for async memory update (filters to user + final AI responses)
14. **ViewImageMiddleware** - Injects base64 image data before LLM call (conditional on vision support)
15. **DeferredToolFilterMiddleware** - Hides deferred (MCP) tool schemas from the bound model using a build-time deferred-name set + catalog hash, reading per-thread promotions from `ThreadState.promoted` (hash-scoped, no ContextVar); a tool becomes bound on subsequent turns after `tool_search` returns its schema (optional, if `tool_search.enabled`)
16. **SubagentLimitMiddleware** - Truncates excess `task` tool calls from model response to enforce `MAX_CONCURRENT_SUBAGENTS` limit (optional, if `subagent_enabled`)
17. **LoopDetectionMiddleware** - Detects repeated tool-call loops; hard-stop responses clear both structured `tool_calls` and raw provider tool-call metadata before forcing a final text answer
18. **ClarificationMiddleware** - Intercepts `ask_clarification` tool calls, interrupts via `Command(goto=END)` (must be last)
### Configuration System
@@ -264,7 +263,7 @@ CORS is same-origin by default when requests enter through nginx on port 2026. S
| **Uploads** (`/api/threads/{id}/uploads`) | `POST /` - upload files (auto-converts PDF/PPT/Excel/Word); `GET /list` - list; `DELETE /{filename}` - delete |
| **Threads** (`/api/threads/{id}`) | `DELETE /` - remove DeerFlow-managed local thread data after LangGraph thread deletion; unexpected failures are logged server-side and return a generic 500 detail |
| **Artifacts** (`/api/threads/{id}/artifacts`) | `GET /{path}` - serve artifacts; active content types (`text/html`, `application/xhtml+xml`, `image/svg+xml`) are always forced as download attachments to reduce XSS risk; `?download=true` still forces download for other file types |
| **Suggestions** (`/api/threads/{id}/suggestions`) | `POST /` - generate follow-up questions; rich list/block model content is normalized and inline reasoning (`<think>...</think>`, including unclosed/truncated blocks from reasoning models like MiniMax-M3) is stripped before JSON parsing |
| **Suggestions** (`/api/threads/{id}/suggestions`) | `POST /` - generate follow-up questions; rich list/block model content is normalized before JSON parsing |
| **Thread Runs** (`/api/threads/{id}/runs`) | `POST /` - create background run; `POST /stream` - create + SSE stream; `POST /wait` - create + block; `GET /` - list runs; `GET /{rid}` - run details; `POST /{rid}/cancel` - cancel; `GET /{rid}/join` - join SSE; `GET /{rid}/messages` - paginated messages `{data, has_more}`; `GET /{rid}/events` - full event stream; `GET /../messages` - thread messages with feedback; `GET /../token-usage` - aggregate tokens |
| **Feedback** (`/api/threads/{id}/runs/{rid}/feedback`) | `PUT /` - upsert feedback; `DELETE /` - delete user feedback; `POST /` - create feedback; `GET /` - list feedback; `GET /stats` - aggregate stats; `DELETE /{fid}` - delete specific |
| **Runs** (`/api/runs`) | `POST /stream` - stateless run + SSE; `POST /wait` - stateless run + block; `GET /{rid}/messages` - paginated messages by run_id `{data, has_more}` (cursor: `after_seq`/`before_seq`); `GET /{rid}/feedback` - list feedback by run_id |
@@ -306,7 +305,6 @@ Proxied through nginx: `/api/langgraph/*` → Gateway LangGraph-compatible runti
**Concurrency**: `MAX_CONCURRENT_SUBAGENTS = 3` enforced by `SubagentLimitMiddleware` (truncates excess tool calls in `after_model`), 15-minute timeout
**Flow**: `task()` tool → `SubagentExecutor` → background thread → poll 5s → SSE events → result
**Events**: `task_started`, `task_running`, `task_completed`/`task_failed`/`task_timed_out`
**Deferred MCP tools** (if `tool_search.enabled`): `SubagentExecutor._build_initial_state` assembles deferral after policy filtering via the shared `assemble_deferred_tools` (fail-closed), appends the `tool_search` tool, injects the `<available-deferred-tools>` section into the subagent's `SystemMessage`, and threads the setup to `_create_agent`, which attaches `DeferredToolFilterMiddleware` through `build_subagent_runtime_middlewares(deferred_setup=...)`. Subagents thus withhold full MCP schemas until promotion, same as the lead agent; each task run gets a fresh `ThreadState` so promotion is isolated per run
### Tool System (`packages/harness/deerflow/tools/`)
@@ -349,7 +347,6 @@ Proxied through nginx: `/api/langgraph/*` → Gateway LangGraph-compatible runti
- **Format**: Directory with `SKILL.md` (YAML frontmatter: name, description, license, allowed-tools)
- **Loading**: `load_skills()` recursively scans `skills/{public,custom}` for `SKILL.md`, parses metadata, and reads enabled state from extensions_config.json
- **Injection**: Enabled skills listed in agent system prompt with container paths
- **Slash activation**: `/skill-name task` loads that enabled skill's `SKILL.md` for the current model call only. The resolver rejects leading whitespace, missing separators, reserved channel commands (`/new`, `/help`, `/bootstrap`, `/status`, `/models`, `/memory`), disabled skills, and skills outside a custom agent's whitelist.
- **Installation**: `POST /api/skills/install` extracts .skill ZIP archive to custom/ directory
### Model Factory (`packages/harness/deerflow/models/factory.py`)
@@ -369,7 +366,8 @@ Proxied through nginx: `/api/langgraph/*` → Gateway LangGraph-compatible runti
### IM Channels System (`app/channels/`)
Bridges external messaging platforms (Feishu, Slack, Telegram, Discord, DingTalk) to the DeerFlow agent via Gateway's LangGraph-compatible API.
Bridges external messaging platforms (Feishu, Slack, Telegram, DingTalk) to the DeerFlow agent via Gateway's LangGraph-compatible API.
**Architecture**: Channels communicate with Gateway through the `langgraph-sdk` HTTP client (same as the frontend), ensuring threads are created and managed server-side. The internal SDK client injects process-local internal auth plus a matching CSRF cookie/header pair so Gateway accepts state-changing thread/run requests from channel workers without relying on browser session cookies.
@@ -379,21 +377,18 @@ Bridges external messaging platforms (Feishu, Slack, Telegram, Discord, DingTalk
- `manager.py` - Core dispatcher: creates threads via `client.threads.create()`, routes commands, keeps Slack/Telegram on `client.runs.wait()`, and uses `client.runs.stream(["messages-tuple", "values"])` for Feishu incremental outbound updates
- `base.py` - Abstract `Channel` base class (start/stop/send lifecycle)
- `service.py` - Manages lifecycle of all configured channels from `config.yaml`
- `slack.py` / `feishu.py` / `telegram.py` / `discord.py` / `dingtalk.py` - Platform-specific implementations (`feishu.py` tracks the running card `message_id` in memory and patches the same card in place; `dingtalk.py` optionally uses AI Card streaming for in-place updates when `card_template_id` is configured)
- `app/gateway/routers/channel_connections.py` - Browser-facing user connection and disconnect APIs
- `deerflow.persistence.channel_connections` - SQL-backed user-owned connection, optional credential, connect state, and conversation store
- `slack.py` / `feishu.py` / `telegram.py` / `dingtalk.py` - Platform-specific implementations (`feishu.py` tracks the running card `message_id` in memory and patches the same card in place; `dingtalk.py` optionally uses AI Card streaming for in-place updates when `card_template_id` is configured)
**Message Flow**:
1. External platform -> Channel impl -> `MessageBus.publish_inbound()`
2. `ChannelManager._dispatch_loop()` consumes from queue
3. For user-owned channel connections, incoming messages carry `connection_id`, `owner_user_id`, and `workspace_id`; `owner_user_id` becomes the DeerFlow run `user_id`, while the raw platform user id remains `channel_user_id`
4. For chat: look up/create thread through Gateway's LangGraph-compatible API
5. Feishu chat: `runs.stream()`accumulate AI text → publish multiple outbound updates (`is_final=False`) → publish final outbound (`is_final=True`)
6. Slack/Telegram chat: `runs.wait()` → extract final response → publish outbound
7. Feishu channel sends one running reply card up front, then patches the same card for each outbound update (card JSON sets `config.update_multi=true` for Feishu's patch API requirement)
8. DingTalk AI Card mode (when `card_template_id` configured): `runs.stream()` → create card with initial text → stream updates via `PUT /v1.0/card/streaming` → finalize on `is_final=True`. Falls back to `sampleMarkdown` if card creation or streaming fails
9. For commands (`/new`, `/status`, `/models`, `/memory`, `/help`): handle locally or query Gateway API
10. Outbound → channel callbacks → platform reply
3. For chat: look up/create thread through Gateway's LangGraph-compatible API
4. Feishu chat: `runs.stream()` → accumulate AI text → publish multiple outbound updates (`is_final=False`) → publish final outbound (`is_final=True`)
5. Slack/Telegram chat: `runs.wait()`extract final response → publish outbound
6. Feishu channel sends one running reply card up front, then patches the same card for each outbound update (card JSON sets `config.update_multi=true` for Feishu's patch API requirement)
7. DingTalk AI Card mode (when `card_template_id` configured): `runs.stream()` → create card with initial text → stream updates via `PUT /v1.0/card/streaming` → finalize on `is_final=True`. Falls back to `sampleMarkdown` if card creation or streaming fails
8. For commands (`/new`, `/status`, `/models`, `/memory`, `/help`): handle locally or query Gateway API
9. Outbound → channel callbacks → platform reply
**Configuration** (`config.yaml` -> `channels`):
- `langgraph_url` - LangGraph-compatible Gateway API base URL (default: `http://localhost:8001/api`)
@@ -401,16 +396,6 @@ Bridges external messaging platforms (Feishu, Slack, Telegram, Discord, DingTalk
- In Docker Compose, IM channels run inside the `gateway` container, so `localhost` points back to that container. Use `http://gateway:8001/api` for `langgraph_url` and `http://gateway:8001` for `gateway_url`, or set `DEER_FLOW_CHANNELS_LANGGRAPH_URL` / `DEER_FLOW_CHANNELS_GATEWAY_URL`.
- Per-channel configs: `feishu` (app_id, app_secret), `slack` (bot_token, app_token), `telegram` (bot_token), `dingtalk` (client_id, client_secret, optional `card_template_id` for AI Card streaming)
**User-owned channel connections** (`config.yaml` -> `channel_connections`):
- Disabled by default. It is a user-binding layer on top of the existing `channels.*` runtime config, not a replacement for provider bot credentials.
- No public IP, OAuth callback URL, or provider webhook route is required by the current implementation.
- Telegram uses a deep-link `/start <code>` flow over the existing long-polling worker. Slack uses `/connect <code>` over the existing Socket Mode worker. Discord uses `/connect <code>` over the existing Gateway worker.
- Frontend APIs: `GET /api/channels/providers`, `GET /api/channels/connections`, `POST /api/channels/{provider}/connect`, and `DELETE /api/channels/connections/{connection_id}`.
- Browser APIs remain protected by normal Gateway auth/CSRF. Provider messages arrive through the already-configured channel workers.
- Slack replies use the configured operator bot token from `channels.slack` unless a future provider-token flow stores per-connection credentials.
- Telegram, Slack, and Discord workers resolve incoming platform identities to connection records before reaching `ChannelManager`.
- See `backend/docs/IM_CHANNEL_CONNECTIONS.md` for provider setup and operational notes.
### Memory System (`packages/harness/deerflow/agents/memory/`)
@@ -507,7 +492,7 @@ Both can be modified at runtime via Gateway API endpoints or `DeerFlowClient` me
- `"messages-tuple"` — per-chunk update: for AI text this is a **delta** (concat per `id` to rebuild the full message); tool calls and tool results are emitted once each
- `"custom"` — forwarded from `StreamWriter`
- `"end"` — stream finished (carries cumulative `usage` counted once per message id)
- Agent created lazily via `create_agent()` + `build_middlewares()`, same as `make_lead_agent`
- Agent created lazily via `create_agent()` + `_build_middlewares()`, same as `make_lead_agent`
- Supports `checkpointer` parameter for state persistence across turns
- `reset_agent()` forces agent recreation (e.g. after memory or skill changes)
- See [docs/STREAMING.md](docs/STREAMING.md) for the full design: why Gateway and DeerFlowClient are parallel paths, LangGraph's `stream_mode` semantics, the per-id dedup invariants, and regression testing strategy
-7
View File
@@ -18,10 +18,3 @@ KNOWN_CHANNEL_COMMANDS: frozenset[str] = frozenset(
"/help",
}
)
def is_known_channel_command(text: str) -> bool:
"""Return whether text starts with a registered channel control command."""
if not text.startswith("/"):
return False
return text.split(maxsplit=1)[0].lower() in KNOWN_CHANNEL_COMMANDS
+4 -2
View File
@@ -14,7 +14,7 @@ from typing import Any
import httpx
from app.channels.base import Channel
from app.channels.commands import is_known_channel_command
from app.channels.commands import KNOWN_CHANNEL_COMMANDS
from app.channels.message_bus import InboundMessage, InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
logger = logging.getLogger(__name__)
@@ -59,7 +59,9 @@ def _normalize_allowed_users(allowed_users: Any) -> set[str]:
def _is_dingtalk_command(text: str) -> bool:
return is_known_channel_command(text)
if not text.startswith("/"):
return False
return text.split(maxsplit=1)[0].lower() in KNOWN_CHANNEL_COMMANDS
def _extract_text_from_rich_text(rich_text_list: list) -> str:
+3 -91
View File
@@ -10,24 +10,13 @@ from pathlib import Path
from typing import Any
from app.channels.base import Channel
from app.channels.commands import is_known_channel_command
from app.channels.message_bus import InboundMessage, InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
from app.channels.message_bus import InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
logger = logging.getLogger(__name__)
_DISCORD_MAX_MESSAGE_LEN = 2000
def _extract_connect_code(text: str) -> str | None:
parts = text.strip().split()
if len(parts) < 2:
return None
command = parts[0].lower()
if command in {"/connect", "connect"}:
return parts[1]
return None
class DiscordChannel(Channel):
"""Discord bot channel.
@@ -80,7 +69,6 @@ class DiscordChannel(Channel):
self._discord_loop: asyncio.AbstractEventLoop | None = None
self._main_loop: asyncio.AbstractEventLoop | None = None
self._discord_module = None
self._connection_repo = config.get("connection_repo")
async def start(self) -> None:
if self._running:
@@ -298,10 +286,6 @@ class DiscordChannel(Channel):
text = text.replace(bot_mention or "", "").replace(alt_mention or "", "").replace(standard_mention or "", "").strip()
# Don't return early if text is empty — still process the mention (e.g., create thread)
connect_code = _extract_connect_code(text)
if connect_code and await self._bind_connection_from_connect_code(message, connect_code):
return
# --- Determine thread/channel routing and typing target ---
thread_id = None
chat_id = None
@@ -316,7 +300,7 @@ class DiscordChannel(Channel):
# If this is a known active thread, process normally
if thread_id in self._active_thread_ids:
msg_type = InboundMessageType.COMMAND if is_known_channel_command(text) else InboundMessageType.CHAT
msg_type = InboundMessageType.COMMAND if text.startswith("/") else InboundMessageType.CHAT
inbound = self._make_inbound(
chat_id=chat_id,
user_id=str(message.author.id),
@@ -330,7 +314,6 @@ class DiscordChannel(Channel):
},
)
inbound.topic_id = thread_id
inbound = await self._attach_connection_identity(inbound, guild_id=str(guild.id) if guild else None)
self._publish(inbound)
# Start typing indicator in the thread
if typing_target:
@@ -424,7 +407,7 @@ class DiscordChannel(Channel):
chat_id = channel_id
typing_target = message.channel # Type into the channel
msg_type = InboundMessageType.COMMAND if is_known_channel_command(text) else InboundMessageType.CHAT
msg_type = InboundMessageType.COMMAND if text.startswith("/") else InboundMessageType.CHAT
inbound = self._make_inbound(
chat_id=chat_id,
user_id=str(message.author.id),
@@ -438,7 +421,6 @@ class DiscordChannel(Channel):
},
)
inbound.topic_id = thread_id
inbound = await self._attach_connection_identity(inbound, guild_id=str(guild.id) if guild else None)
# Start typing indicator in the correct target (thread or channel)
if typing_target:
@@ -453,76 +435,6 @@ class DiscordChannel(Channel):
future = asyncio.run_coroutine_threadsafe(self.bus.publish_inbound(inbound), self._main_loop)
future.add_done_callback(lambda f: logger.exception("[Discord] publish_inbound failed", exc_info=f.exception()) if f.exception() else None)
async def _attach_connection_identity(self, inbound: InboundMessage, guild_id: str | None = None) -> InboundMessage:
if self._connection_repo is None:
return inbound
connection = None
if guild_id:
connection = await self._connection_repo.find_connection_by_external_identity(
provider="discord",
external_account_id=inbound.user_id,
workspace_id=guild_id,
)
if connection is None:
connection = await self._connection_repo.find_connection_by_external_identity(
provider="discord",
external_account_id=inbound.user_id,
workspace_id=None,
)
if connection is None:
return inbound
inbound.connection_id = connection["id"]
inbound.owner_user_id = connection["owner_user_id"]
inbound.workspace_id = connection.get("workspace_id")
return inbound
async def _bind_connection_from_connect_code(self, message, code: str) -> bool:
if self._connection_repo is None or not code:
return False
state = await self._connection_repo.consume_oauth_state(provider="discord", state=code)
if state is None:
await self._send_connection_reply(message, "Discord connection code is invalid or expired.")
return True
guild = getattr(message, "guild", None)
channel = getattr(message, "channel", None)
author = getattr(message, "author", None)
user_id = str(getattr(author, "id", "") or "")
if not user_id:
await self._send_connection_reply(message, "Discord connection could not be completed from this message.")
return True
guild_id = str(getattr(guild, "id", "") or "") or None
await self._connection_repo.upsert_connection(
owner_user_id=state["owner_user_id"],
provider="discord",
external_account_id=user_id,
external_account_name=getattr(author, "display_name", None) or getattr(author, "name", None),
workspace_id=guild_id,
workspace_name=getattr(guild, "name", None) if guild is not None else None,
metadata={
"guild_id": guild_id,
"channel_id": str(getattr(channel, "id", "") or ""),
},
status="connected",
)
await self._send_connection_reply(message, "Discord connected to DeerFlow.")
return True
@staticmethod
async def _send_connection_reply(message, text: str) -> None:
channel = getattr(message, "channel", None)
send = getattr(channel, "send", None)
if send is None:
return
try:
await send(text)
except Exception:
logger.exception("[Discord] failed to send connection reply")
def _run_client(self) -> None:
self._discord_loop = asyncio.new_event_loop()
asyncio.set_event_loop(self._discord_loop)
+4 -2
View File
@@ -11,7 +11,7 @@ import time
from typing import Any, Literal
from app.channels.base import Channel
from app.channels.commands import is_known_channel_command
from app.channels.commands import KNOWN_CHANNEL_COMMANDS
from app.channels.message_bus import (
PENDING_CLARIFICATION_METADATA_KEY,
RESOLVED_FROM_PENDING_CLARIFICATION_METADATA_KEY,
@@ -30,7 +30,9 @@ PENDING_CLARIFICATION_TTL_SECONDS = 30 * 60
def _is_feishu_command(text: str) -> bool:
return is_known_channel_command(text)
if not text.startswith("/"):
return False
return text.split(maxsplit=1)[0].lower() in KNOWN_CHANNEL_COMMANDS
class FeishuChannel(Channel):
+32 -179
View File
@@ -8,7 +8,6 @@ import mimetypes
import re
import time
from collections.abc import Awaitable, Callable, Mapping
from dataclasses import dataclass
from pathlib import Path
from typing import Any
@@ -27,13 +26,8 @@ from app.channels.message_bus import (
from app.channels.store import ChannelStore
from app.gateway.csrf_middleware import CSRF_COOKIE_NAME, CSRF_HEADER_NAME, generate_csrf_token
from app.gateway.internal_auth import create_internal_auth_headers
from deerflow.config.agents_config import load_agent_config
from deerflow.config.paths import make_safe_user_id
from deerflow.runtime.user_context import get_effective_user_id
from deerflow.skills.slash import parse_slash_skill_reference
from deerflow.skills.storage import get_or_new_skill_storage
from deerflow.skills.storage.skill_storage import SkillStorage
from deerflow.utils.messages import ORIGINAL_USER_CONTENT_KEY
logger = logging.getLogger(__name__)
@@ -130,16 +124,6 @@ class InvalidChannelSessionConfigError(ValueError):
"""Raised when IM channel session overrides contain invalid agent config."""
class SlashSkillCommandResolutionError(RuntimeError):
"""Raised when IM slash-skill command resolution cannot complete safely."""
@dataclass(frozen=True, slots=True)
class _SlashSkillCommandResolution:
route_to_chat: bool = False
failure_message: str | None = None
def _is_thread_busy_error(exc: BaseException | None) -> bool:
if exc is None:
return False
@@ -426,46 +410,6 @@ def _format_artifact_text(artifacts: list[str]) -> str:
_OUTPUTS_VIRTUAL_PREFIX = "/mnt/user-data/outputs/"
def _unknown_command_reply(command: str | None = None) -> str:
available = " | ".join(sorted(KNOWN_CHANNEL_COMMANDS))
if command:
return f"Unknown command: /{command}. Available commands: {available}"
return f"Unknown command. Available commands: {available}"
def _human_input_message(content: str, *, original_content: str | None = None) -> dict[str, Any]:
message: dict[str, Any] = {"role": "human", "content": content}
if original_content is not None and original_content != content:
message["additional_kwargs"] = {ORIGINAL_USER_CONTENT_KEY: original_content}
return message
def _resolve_slash_skill_command(
text: str,
available_skills: set[str] | None = None,
storage: SkillStorage | Callable[[], SkillStorage] | None = None,
) -> _SlashSkillCommandResolution | None:
reference = parse_slash_skill_reference(text)
if reference is None:
return None
try:
resolved_storage = storage() if callable(storage) else storage or get_or_new_skill_storage()
skills = resolved_storage.load_skills(enabled_only=False)
skill = next((candidate for candidate in skills if candidate.name == reference.name), None)
if skill is None:
return None
if not skill.enabled:
return _SlashSkillCommandResolution(failure_message=f"Skill `/{reference.name}` is installed but disabled. Enable it before using slash activation.")
if available_skills is not None and reference.name not in available_skills:
return _SlashSkillCommandResolution(failure_message=f"Skill `/{reference.name}` is not available for this agent.")
return _SlashSkillCommandResolution(route_to_chat=True)
except Exception as exc:
logger.exception("[Manager] failed to resolve slash skill command")
raise SlashSkillCommandResolutionError("Failed to resolve slash skill command. Please check the skill configuration.") from exc
def _resolve_attachments(thread_id: str, artifacts: list[str]) -> list[ResolvedAttachment]:
"""Resolve virtual artifact paths to host filesystem paths with metadata.
@@ -670,7 +614,6 @@ class ChannelManager:
assistant_id: str = DEFAULT_ASSISTANT_ID,
default_session: dict[str, Any] | None = None,
channel_sessions: dict[str, Any] | None = None,
connection_repo: Any | None = None,
) -> None:
self.bus = bus
self.store = store
@@ -680,9 +623,7 @@ class ChannelManager:
self._assistant_id = assistant_id
self._default_session = _as_dict(default_session)
self._channel_sessions = dict(channel_sessions or {})
self._connection_repo = connection_repo
self._client = None # lazy init — langgraph_sdk async client
self._skill_storage: SkillStorage | None = None
self._csrf_token = generate_csrf_token()
self._semaphore: asyncio.Semaphore | None = None
self._running = False
@@ -730,16 +671,12 @@ class ChannelManager:
configurable["checkpoint_ns"] = ""
configurable["thread_id"] = thread_id
# ``user_id`` drives DeerFlow-owned memory, files, and thread buckets.
# For browser-connected IM channels, prefer the DeerFlow account that
# owns the connection. Preserve the raw platform user under
# ``channel_user_id`` for platform-facing lookups and audits.
# ``user_id`` drives user-scoped filesystem buckets that only accept
# ``[A-Za-z0-9_-]``, so normalize the channel id and keep the raw value
# under ``channel_user_id`` for platform-facing lookups.
run_context_identity: dict[str, Any] = {"thread_id": thread_id}
if msg.owner_user_id:
run_context_identity["user_id"] = make_safe_user_id(msg.owner_user_id)
elif msg.user_id:
run_context_identity["user_id"] = make_safe_user_id(msg.user_id)
if msg.user_id:
run_context_identity["user_id"] = make_safe_user_id(msg.user_id)
run_context_identity["channel_user_id"] = msg.user_id
run_context = _merge_dicts(
@@ -759,21 +696,6 @@ class ChannelManager:
return assistant_id, run_config, run_context
def _resolve_available_skill_names(self, msg: InboundMessage) -> set[str] | None:
thread_id = self.store.get_thread_id(msg.channel_name, msg.chat_id, topic_id=msg.topic_id) or ""
_, _, run_context = self._resolve_run_params(msg, thread_id)
if run_context.get("is_bootstrap"):
return {"bootstrap"}
agent_name = run_context.get("agent_name")
if not isinstance(agent_name, str) or not agent_name.strip():
return None
agent_config = load_agent_config(_normalize_custom_agent_name(agent_name))
if agent_config and agent_config.skills is not None:
return set(agent_config.skills)
return None
# -- LangGraph SDK client (lazy) ----------------------------------------
def _get_client(self):
@@ -791,11 +713,6 @@ class ChannelManager:
)
return self._client
def _get_skill_storage(self) -> SkillStorage:
if self._skill_storage is None:
self._skill_storage = get_or_new_skill_storage()
return self._skill_storage
# -- lifecycle ---------------------------------------------------------
async def start(self) -> None:
@@ -865,14 +782,6 @@ class ChannelManager:
exc,
)
await self._send_error(msg, str(exc))
except SlashSkillCommandResolutionError as exc:
logger.warning(
"Slash skill command resolution failed for %s (chat=%s): %s",
msg.channel_name,
msg.chat_id,
exc,
)
await self._send_error(msg, str(exc))
except Exception:
logger.exception(
"Error handling message from %s (chat=%s)",
@@ -883,27 +792,10 @@ class ChannelManager:
# -- chat handling -----------------------------------------------------
async def _lookup_thread_id(self, msg: InboundMessage) -> str | None:
if msg.connection_id and self._connection_repo is not None:
return await self._connection_repo.get_thread_id(
msg.connection_id,
msg.chat_id,
msg.topic_id,
)
return self.store.get_thread_id(msg.channel_name, msg.chat_id, topic_id=msg.topic_id)
async def _store_thread_id(self, msg: InboundMessage, thread_id: str) -> None:
if msg.connection_id and msg.owner_user_id and self._connection_repo is not None:
await self._connection_repo.set_thread_id(
connection_id=msg.connection_id,
owner_user_id=msg.owner_user_id,
provider=msg.channel_name,
external_conversation_id=msg.chat_id,
external_topic_id=msg.topic_id,
thread_id=thread_id,
)
return
async def _create_thread(self, client, msg: InboundMessage) -> str:
"""Create a new thread through Gateway and store the mapping."""
thread = await client.threads.create()
thread_id = thread["thread_id"]
self.store.set_thread_id(
msg.channel_name,
msg.chat_id,
@@ -911,12 +803,6 @@ class ChannelManager:
topic_id=msg.topic_id,
user_id=msg.user_id,
)
async def _create_thread(self, client, msg: InboundMessage) -> str:
"""Create a new thread through Gateway and store the mapping."""
thread = await client.threads.create()
thread_id = thread["thread_id"]
await self._store_thread_id(msg, thread_id)
logger.info("[Manager] new thread created through Gateway: thread_id=%s for chat_id=%s topic_id=%s", thread_id, msg.chat_id, msg.topic_id)
return thread_id
@@ -926,7 +812,7 @@ class ChannelManager:
# Look up existing DeerFlow thread.
# topic_id may be None (e.g. Telegram private chats) — the store
# handles this by using the "channel:chat_id" key without a topic suffix.
thread_id = await self._lookup_thread_id(msg)
thread_id = self.store.get_thread_id(msg.channel_name, msg.chat_id, topic_id=msg.topic_id)
if thread_id:
logger.info("[Manager] reusing thread: thread_id=%s for topic_id=%s", thread_id, msg.topic_id)
@@ -950,11 +836,9 @@ class ChannelManager:
if extra_context:
run_context.update(extra_context)
original_text = msg.text
uploaded = await _ingest_inbound_files(thread_id, msg)
if uploaded:
msg.text = f"{_format_uploaded_files_block(uploaded)}\n\n{msg.text}".strip()
human_message = _human_input_message(msg.text, original_content=original_text)
if self._channel_supports_streaming(msg.channel_name):
await self._handle_streaming_chat(
@@ -964,7 +848,6 @@ class ChannelManager:
assistant_id,
run_config,
run_context,
human_message,
)
return
@@ -973,7 +856,7 @@ class ChannelManager:
result = await client.runs.wait(
thread_id,
assistant_id,
input={"messages": [human_message]},
input={"messages": [{"role": "human", "content": msg.text}]},
config=run_config,
context=run_context,
multitask_strategy="reject",
@@ -1013,8 +896,6 @@ class ChannelManager:
artifacts=artifacts,
attachments=attachments,
thread_ts=msg.thread_ts,
connection_id=msg.connection_id,
owner_user_id=msg.owner_user_id,
metadata=_response_metadata(msg.metadata, pending_clarification=pending_clarification),
)
logger.info("[Manager] publishing outbound message to bus: channel=%s, chat_id=%s", msg.channel_name, msg.chat_id)
@@ -1028,7 +909,6 @@ class ChannelManager:
assistant_id: str,
run_config: dict[str, Any],
run_context: dict[str, Any],
human_message: dict[str, Any],
) -> None:
logger.info("[Manager] invoking runs.stream(thread_id=%s, text=%r)", thread_id, msg.text[:100])
@@ -1044,7 +924,7 @@ class ChannelManager:
async for chunk in client.runs.stream(
thread_id,
assistant_id,
input={"messages": [human_message]},
input={"messages": [{"role": "human", "content": msg.text}]},
config=run_config,
context=run_context,
stream_mode=["messages-tuple", "values"],
@@ -1078,8 +958,6 @@ class ChannelManager:
text=latest_text,
is_final=False,
thread_ts=msg.thread_ts,
connection_id=msg.connection_id,
owner_user_id=msg.owner_user_id,
metadata=_response_metadata(msg.metadata),
)
)
@@ -1126,8 +1004,6 @@ class ChannelManager:
attachments=attachments,
is_final=True,
thread_ts=msg.thread_ts,
connection_id=msg.connection_id,
owner_user_id=msg.owner_user_id,
metadata=_response_metadata(msg.metadata, pending_clarification=pending_clarification),
)
)
@@ -1135,20 +1011,11 @@ class ChannelManager:
# -- command handling --------------------------------------------------
async def _handle_command(self, msg: InboundMessage) -> None:
raw_text = msg.text
text = raw_text.strip()
text = msg.text.strip()
parts = text.split(maxsplit=1)
reply: str | None = None
if not parts:
command = None
reply = _unknown_command_reply()
else:
command = parts[0].lower().removeprefix("/")
command = parts[0].lower().lstrip("/")
if reply is None and not raw_text.startswith("/"):
reply = _unknown_command_reply(command)
if reply is None and command == "bootstrap":
if command == "bootstrap":
from dataclasses import replace as _dc_replace
chat_text = parts[1] if len(parts) > 1 else "Initialize workspace"
@@ -1156,21 +1023,27 @@ class ChannelManager:
await self._handle_chat(chat_msg, extra_context={"is_bootstrap": True})
return
if reply is None and command == "new":
if command == "new":
# Create a new thread through Gateway
client = self._get_client()
thread = await client.threads.create()
new_thread_id = thread["thread_id"]
await self._store_thread_id(msg, new_thread_id)
self.store.set_thread_id(
msg.channel_name,
msg.chat_id,
new_thread_id,
topic_id=msg.topic_id,
user_id=msg.user_id,
)
reply = "New conversation started."
elif reply is None and command == "status":
thread_id = await self._lookup_thread_id(msg)
elif command == "status":
thread_id = self.store.get_thread_id(msg.channel_name, msg.chat_id, topic_id=msg.topic_id)
reply = f"Active thread: {thread_id}" if thread_id else "No active conversation."
elif reply is None and command == "models":
elif command == "models":
reply = await self._fetch_gateway("/api/models", "models")
elif reply is None and command == "memory":
elif command == "memory":
reply = await self._fetch_gateway("/api/memory", "memory")
elif reply is None and command == "help":
elif command == "help":
reply = (
"Available commands:\n"
"/bootstrap — Start a bootstrap session (enables agent setup)\n"
@@ -1178,36 +1051,18 @@ class ChannelManager:
"/status — Show current thread info\n"
"/models — List available models\n"
"/memory — Show memory status\n"
"/<skill-name> <task> — Activate an enabled skill for one turn\n"
"/help — Show this help"
)
elif reply is None:
slash_resolution = await asyncio.to_thread(
lambda: _resolve_slash_skill_command(
raw_text,
self._resolve_available_skill_names(msg),
self._get_skill_storage,
)
)
if slash_resolution and slash_resolution.failure_message:
reply = slash_resolution.failure_message
elif slash_resolution and slash_resolution.route_to_chat:
from dataclasses import replace as _dc_replace
chat_msg = _dc_replace(msg, msg_type=InboundMessageType.CHAT)
await self._handle_chat(chat_msg)
return
else:
reply = _unknown_command_reply(command)
else:
available = " | ".join(sorted(KNOWN_CHANNEL_COMMANDS))
reply = f"Unknown command: /{command}. Available commands: {available}"
outbound = OutboundMessage(
channel_name=msg.channel_name,
chat_id=msg.chat_id,
thread_id=await self._lookup_thread_id(msg) or "",
thread_id=self.store.get_thread_id(msg.channel_name, msg.chat_id) or "",
text=reply,
thread_ts=msg.thread_ts,
connection_id=msg.connection_id,
owner_user_id=msg.owner_user_id,
metadata=_slim_metadata(msg.metadata),
)
await self.bus.publish_outbound(outbound)
@@ -1243,11 +1098,9 @@ class ChannelManager:
outbound = OutboundMessage(
channel_name=msg.channel_name,
chat_id=msg.chat_id,
thread_id=await self._lookup_thread_id(msg) or "",
thread_id=self.store.get_thread_id(msg.channel_name, msg.chat_id) or "",
text=error_text,
thread_ts=msg.thread_ts,
connection_id=msg.connection_id,
owner_user_id=msg.owner_user_id,
metadata=_slim_metadata(msg.metadata),
)
await self.bus.publish_outbound(outbound)
-14
View File
@@ -44,12 +44,6 @@ class InboundMessage:
Messages sharing the same ``topic_id`` within a ``chat_id`` will
reuse the same DeerFlow thread. When ``None``, each message
creates a new thread (one-shot Q&A).
connection_id: Optional DeerFlow channel connection id. When present,
conversation mapping is scoped by the connection instead of the
legacy global ``channel_name:chat_id[:topic_id]`` key.
owner_user_id: DeerFlow user id that owns the channel connection.
Platform user ids stay in ``user_id``.
workspace_id: Optional external workspace/guild/team id.
files: Optional list of file attachments (platform-specific dicts).
metadata: Arbitrary extra data from the channel.
created_at: Unix timestamp when the message was created.
@@ -62,9 +56,6 @@ class InboundMessage:
msg_type: InboundMessageType = InboundMessageType.CHAT
thread_ts: str | None = None
topic_id: str | None = None
connection_id: str | None = None
owner_user_id: str | None = None
workspace_id: str | None = None
files: list[dict[str, Any]] = field(default_factory=list)
metadata: dict[str, Any] = field(default_factory=dict)
created_at: float = field(default_factory=time.time)
@@ -104,9 +95,6 @@ class OutboundMessage:
is_final: Whether this is the final message in the response stream.
thread_ts: Optional platform thread identifier for threaded replies.
metadata: Arbitrary extra data.
connection_id: Optional DeerFlow channel connection id used for
connection-specific outbound credentials.
owner_user_id: DeerFlow user id that owns the channel connection.
created_at: Unix timestamp.
"""
@@ -118,8 +106,6 @@ class OutboundMessage:
attachments: list[ResolvedAttachment] = field(default_factory=list)
is_final: bool = True
thread_ts: str | None = None
connection_id: str | None = None
owner_user_id: str | None = None
metadata: dict[str, Any] = field(default_factory=dict)
created_at: float = field(default_factory=time.time)
+3 -33
View File
@@ -52,31 +52,6 @@ def _resolve_service_url(config: dict[str, Any], config_key: str, env_key: str,
return default
def _merge_channel_connection_runtime_config(channels_config: dict[str, Any], app_config: AppConfig) -> None:
connection_config = getattr(app_config, "channel_connections", None)
if connection_config is None or not getattr(connection_config, "enabled", False):
return
def _make_connection_repo(app_config: AppConfig):
connection_config = getattr(app_config, "channel_connections", None)
if connection_config is None or not getattr(connection_config, "enabled", False):
return None
try:
from deerflow.persistence.channel_connections import ChannelConnectionRepository
from deerflow.persistence.engine import get_session_factory
except Exception:
logger.exception("Failed to import channel connection repository")
return None
session_factory = get_session_factory()
if session_factory is None:
logger.warning("Channel connections are enabled but database persistence is not available")
return None
return ChannelConnectionRepository(session_factory)
class ChannelService:
"""Manages the lifecycle of all configured IM channels.
@@ -84,10 +59,9 @@ class ChannelService:
instantiates enabled channels, and starts the ChannelManager dispatcher.
"""
def __init__(self, channels_config: dict[str, Any] | None = None, *, connection_repo: Any | None = None) -> None:
def __init__(self, channels_config: dict[str, Any] | None = None) -> None:
self.bus = MessageBus()
self.store = ChannelStore()
self._connection_repo = connection_repo
config = dict(channels_config or {})
langgraph_url = _resolve_service_url(config, "langgraph_url", _CHANNELS_LANGGRAPH_URL_ENV, DEFAULT_LANGGRAPH_URL)
gateway_url = _resolve_service_url(config, "gateway_url", _CHANNELS_GATEWAY_URL_ENV, DEFAULT_GATEWAY_URL)
@@ -100,7 +74,6 @@ class ChannelService:
gateway_url=gateway_url,
default_session=default_session if isinstance(default_session, dict) else None,
channel_sessions=channel_sessions,
connection_repo=connection_repo,
)
self._channels: dict[str, Any] = {} # name -> Channel instance
self._config = config
@@ -117,9 +90,8 @@ class ChannelService:
# extra fields are allowed by AppConfig (extra="allow")
extra = app_config.model_extra or {}
if "channels" in extra:
channels_config = dict(extra["channels"] or {})
_merge_channel_connection_runtime_config(channels_config, app_config)
return cls(channels_config=channels_config, connection_repo=_make_connection_repo(app_config))
channels_config = extra["channels"]
return cls(channels_config=channels_config)
async def start(self) -> None:
"""Start the manager and all enabled channels."""
@@ -197,8 +169,6 @@ class ChannelService:
try:
config = dict(config)
config["channel_store"] = self.store
if self._connection_repo is not None:
config["connection_repo"] = self._connection_repo
channel = channel_cls(bus=self.bus, config=config)
self._channels[name] = channel
await channel.start()
+16 -179
View File
@@ -9,7 +9,6 @@ from typing import Any
from markdown_to_mrkdwn import SlackMarkdownConverter
from app.channels.base import Channel
from app.channels.commands import is_known_channel_command
from app.channels.message_bus import InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
logger = logging.getLogger(__name__)
@@ -33,30 +32,6 @@ def _normalize_allowed_users(allowed_users: Any) -> set[str]:
return {str(user_id) for user_id in values if str(user_id)}
def _strip_leading_slack_bot_mention(text: str, bot_user_id: str | None) -> str:
if not bot_user_id:
return text
if not text.startswith("<@"):
return text
end = text.find(">")
if end <= 2:
return text
mentioned_user_id = text[2:end].split("|", 1)[0].lstrip("!")
if mentioned_user_id != bot_user_id:
return text
return text[end + 1 :].lstrip()
def _extract_connect_code(text: str) -> str | None:
parts = text.strip().split()
if len(parts) < 2:
return None
command = parts[0].lower()
if command in {"/connect", "connect"}:
return parts[1]
return None
class SlackChannel(Channel):
"""Slack IM channel using Socket Mode (WebSocket, no public IP).
@@ -74,10 +49,6 @@ class SlackChannel(Channel):
self._web_client = None
self._loop: asyncio.AbstractEventLoop | None = None
self._allowed_users = _normalize_allowed_users(config.get("allowed_users", []))
self._connection_repo = config.get("connection_repo")
self._web_client_factory = config.get("web_client_factory")
configured_bot_user_id = config.get("bot_user_id")
self._bot_user_id = str(configured_bot_user_id).lstrip("@") if configured_bot_user_id else None
async def start(self) -> None:
if self._running:
@@ -92,35 +63,15 @@ class SlackChannel(Channel):
return
self._SocketModeResponse = SocketModeResponse
if self._web_client_factory is None:
self._web_client_factory = WebClient
bot_token = self.config.get("bot_token", "")
app_token = self.config.get("app_token", "")
if self._connection_repo is not None and self.config.get("event_delivery") == "http":
self._loop = asyncio.get_event_loop()
self._running = True
self.bus.subscribe_outbound(self._on_outbound)
logger.info("Slack channel started in HTTP Events mode")
return
if not bot_token or not app_token:
logger.error("Slack channel requires bot_token and app_token")
return
self._web_client = self._web_client_factory(token=bot_token)
if self._bot_user_id is None:
try:
auth_info = await asyncio.to_thread(self._web_client.auth_test)
user_id = auth_info.get("user_id") if isinstance(auth_info, dict) else None
if user_id is None:
auth_get = getattr(auth_info, "get", None)
user_id = auth_get("user_id") if callable(auth_get) else None
if isinstance(user_id, str) and user_id:
self._bot_user_id = user_id
except Exception:
logger.warning("[Slack] failed to resolve bot user id; app mention text may include the bot mention", exc_info=True)
self._web_client = WebClient(token=bot_token)
self._socket_client = SocketModeClient(
app_token=app_token,
web_client=self._web_client,
@@ -145,8 +96,7 @@ class SlackChannel(Channel):
logger.info("Slack channel stopped")
async def send(self, msg: OutboundMessage, *, _max_retries: int = 3) -> None:
web_client = await self._get_web_client_for_message(msg)
if not web_client:
if not self._web_client:
return
kwargs: dict[str, Any] = {
@@ -159,12 +109,11 @@ class SlackChannel(Channel):
last_exc: Exception | None = None
for attempt in range(_max_retries):
try:
await asyncio.to_thread(web_client.chat_postMessage, **kwargs)
await asyncio.to_thread(self._web_client.chat_postMessage, **kwargs)
# Add a completion reaction to the thread root
if msg.thread_ts:
await asyncio.to_thread(
self._add_reaction_with_client,
web_client,
self._add_reaction,
msg.chat_id,
msg.thread_ts,
"white_check_mark",
@@ -188,8 +137,7 @@ class SlackChannel(Channel):
if msg.thread_ts:
try:
await asyncio.to_thread(
self._add_reaction_with_client,
web_client,
self._add_reaction,
msg.chat_id,
msg.thread_ts,
"x",
@@ -201,8 +149,7 @@ class SlackChannel(Channel):
raise last_exc
async def send_file(self, msg: OutboundMessage, attachment: ResolvedAttachment) -> bool:
web_client = await self._get_web_client_for_message(msg)
if not web_client:
if not self._web_client:
return False
try:
@@ -215,7 +162,7 @@ class SlackChannel(Channel):
if msg.thread_ts:
kwargs["thread_ts"] = msg.thread_ts
await asyncio.to_thread(web_client.files_upload_v2, **kwargs)
await asyncio.to_thread(self._web_client.files_upload_v2, **kwargs)
logger.info("[Slack] file uploaded: %s to channel=%s", attachment.filename, msg.chat_id)
return True
except Exception:
@@ -224,23 +171,12 @@ class SlackChannel(Channel):
# -- internal ----------------------------------------------------------
async def _get_web_client_for_message(self, msg: OutboundMessage):
if msg.connection_id and self._connection_repo is not None:
credentials = await self._connection_repo.get_credentials(msg.connection_id)
access_token = credentials.get("access_token") if credentials else None
if not access_token:
return self._web_client
if self._web_client_factory is None:
from slack_sdk import WebClient
self._web_client_factory = WebClient
return self._web_client_factory(token=access_token)
return self._web_client
@staticmethod
def _add_reaction_with_client(web_client, channel_id: str, timestamp: str, emoji: str) -> None:
def _add_reaction(self, channel_id: str, timestamp: str, emoji: str) -> None:
"""Add an emoji reaction to a message (best-effort, non-blocking)."""
if not self._web_client:
return
try:
web_client.reactions_add(
self._web_client.reactions_add(
channel=channel_id,
timestamp=timestamp,
name=emoji,
@@ -249,12 +185,6 @@ class SlackChannel(Channel):
if "already_reacted" not in str(exc):
logger.warning("[Slack] failed to add reaction %s: %s", emoji, exc)
def _add_reaction(self, channel_id: str, timestamp: str, emoji: str) -> None:
"""Add an emoji reaction to a message (best-effort, non-blocking)."""
if not self._web_client:
return
self._add_reaction_with_client(self._web_client, channel_id, timestamp, emoji)
def _send_running_reply(self, channel_id: str, thread_ts: str) -> None:
"""Send a 'Working on it......' reply in the thread (called from SDK thread)."""
if not self._web_client:
@@ -280,26 +210,17 @@ class SlackChannel(Channel):
if event_type != "events_api":
return
if self._bot_user_id is None:
authorization = next((item for item in req.payload.get("authorizations", []) if isinstance(item, dict)), None)
user_id = authorization.get("user_id") if authorization else None
if isinstance(user_id, str) and user_id:
self._bot_user_id = user_id
event = req.payload.get("event", {})
etype = event.get("type", "")
# Handle message events (DM or @mention)
if etype in ("message", "app_mention"):
self._handle_message_event(
event,
team_id=req.payload.get("team_id") or req.payload.get("team") or event.get("team"),
)
self._handle_message_event(event)
except Exception:
logger.exception("Error processing Slack event")
def _handle_message_event(self, event: dict, *, team_id: str | None = None) -> None:
def _handle_message_event(self, event: dict) -> None:
# Ignore bot messages
if event.get("bot_id") or event.get("subtype"):
return
@@ -312,28 +233,13 @@ class SlackChannel(Channel):
return
text = event.get("text", "").strip()
if event.get("type") == "app_mention":
text = _strip_leading_slack_bot_mention(text, self._bot_user_id)
if not text:
return
connect_code = _extract_connect_code(text)
if connect_code:
if self._loop and self._loop.is_running():
asyncio.run_coroutine_threadsafe(
self._bind_connection_from_connect_code(
event=event,
team_id=str(team_id or event.get("team") or ""),
code=connect_code,
),
self._loop,
)
return
channel_id = event.get("channel", "")
thread_ts = event.get("thread_ts") or event.get("ts", "")
if is_known_channel_command(text):
if text.startswith("/"):
msg_type = InboundMessageType.COMMAND
else:
msg_type = InboundMessageType.CHAT
@@ -355,73 +261,4 @@ class SlackChannel(Channel):
self._add_reaction(channel_id, event.get("ts", thread_ts), "eyes")
# Send "running" reply first (fire-and-forget from SDK thread)
self._send_running_reply(channel_id, thread_ts)
if self._connection_repo is None:
asyncio.run_coroutine_threadsafe(self.bus.publish_inbound(inbound), self._loop)
else:
asyncio.run_coroutine_threadsafe(self._publish_inbound_with_connection(inbound, team_id=team_id), self._loop)
async def _publish_inbound_with_connection(self, inbound, *, team_id: str | None = None) -> None:
inbound = await self._attach_connection_identity(inbound, team_id=team_id)
await self.bus.publish_inbound(inbound)
async def _attach_connection_identity(self, inbound, *, team_id: str | None = None):
if self._connection_repo is None:
return inbound
workspace_id = str(team_id or inbound.metadata.get("team_id") or "")
if not workspace_id:
return inbound
connection = await self._connection_repo.find_connection_by_external_identity(
provider="slack",
external_account_id=inbound.user_id,
workspace_id=workspace_id,
)
if connection is None:
return inbound
inbound.connection_id = connection["id"]
inbound.owner_user_id = connection["owner_user_id"]
inbound.workspace_id = connection.get("workspace_id")
return inbound
async def _bind_connection_from_connect_code(self, *, event: dict, team_id: str, code: str) -> bool:
if self._connection_repo is None or not code:
return False
channel_id = str(event.get("channel") or "")
thread_ts = str(event.get("thread_ts") or event.get("ts") or "")
state = await self._connection_repo.consume_oauth_state(provider="slack", state=code)
if state is None:
self._post_connection_reply(channel_id, "Slack connection code is invalid or expired.", thread_ts)
return True
user_id = str(event.get("user") or "")
if not user_id or not team_id:
self._post_connection_reply(channel_id, "Slack connection could not be completed from this message.", thread_ts)
return True
await self._connection_repo.upsert_connection(
owner_user_id=state["owner_user_id"],
provider="slack",
external_account_id=user_id,
workspace_id=team_id,
metadata={
"team_id": team_id,
"channel_id": channel_id,
},
status="connected",
)
self._post_connection_reply(channel_id, "Slack connected to DeerFlow.", thread_ts)
return True
def _post_connection_reply(self, channel_id: str, text: str, thread_ts: str | None = None) -> None:
if not self._web_client or not channel_id:
return
kwargs: dict[str, Any] = {"channel": channel_id, "text": text}
if thread_ts:
kwargs["thread_ts"] = thread_ts
try:
self._web_client.chat_postMessage(**kwargs)
except Exception:
logger.exception("[Slack] failed to send connection reply in channel=%s", channel_id)
asyncio.run_coroutine_threadsafe(self.bus.publish_inbound(inbound), self._loop)
+2 -119
View File
@@ -35,7 +35,6 @@ class TelegramChannel(Channel):
pass
# chat_id -> last sent message_id for threaded replies
self._last_bot_message: dict[str, int] = {}
self._connection_repo = config.get("connection_repo")
async def start(self) -> None:
if self._running:
@@ -61,17 +60,12 @@ class TelegramChannel(Channel):
# Command handlers
app.add_handler(CommandHandler("start", self._cmd_start))
app.add_handler(CommandHandler("bootstrap", self._cmd_generic))
app.add_handler(CommandHandler("new", self._cmd_generic))
app.add_handler(CommandHandler("status", self._cmd_generic))
app.add_handler(CommandHandler("models", self._cmd_generic))
app.add_handler(CommandHandler("memory", self._cmd_generic))
app.add_handler(CommandHandler("help", self._cmd_generic))
# Slash skill commands are dynamic and cannot all be pre-registered
# with Telegram, so route unknown slash commands through chat handling.
app.add_handler(MessageHandler(filters.TEXT & filters.COMMAND, self._on_text))
# General message handler
app.add_handler(MessageHandler(filters.TEXT & ~filters.COMMAND, self._on_text))
@@ -177,26 +171,6 @@ class TelegramChannel(Channel):
logger.exception("[Telegram] failed to send file: %s", attachment.filename)
return False
async def process_webhook_update(self, payload: dict[str, Any]) -> bool:
if not self._application:
return False
try:
from telegram import Update
except ImportError:
logger.error("python-telegram-bot is not installed. Install it with: uv add python-telegram-bot")
return False
update = Update.de_json(payload, self._application.bot)
if update is None:
return False
if self._tg_loop and self._tg_loop.is_running():
future = asyncio.run_coroutine_threadsafe(self._application.process_update(update), self._tg_loop)
await asyncio.wrap_future(future)
else:
await self._application.process_update(update)
return True
# -- helpers -----------------------------------------------------------
async def _send_running_reply(self, chat_id: str, reply_to_message_id: int) -> None:
@@ -254,99 +228,10 @@ class TelegramChannel(Channel):
return True
return user_id in self._allowed_users
@staticmethod
def _telegram_display_name(user) -> str:
full_name = getattr(user, "full_name", None)
if isinstance(full_name, str) and full_name:
return full_name
username = getattr(user, "username", None)
if isinstance(username, str) and username:
return username
return str(getattr(user, "id", ""))
async def _bind_connection_from_start_token(self, update, state_token: str) -> bool:
if self._connection_repo is None or not state_token:
return False
state = await self._connection_repo.consume_oauth_state(provider="telegram", state=state_token)
if state is None:
await update.message.reply_text("Telegram connection link is invalid or expired.")
return True
owner_user_id = state["owner_user_id"]
user_id = str(update.effective_user.id)
chat_id = str(update.effective_chat.id)
connection = await self._connection_repo.upsert_connection(
owner_user_id=owner_user_id,
provider="telegram",
external_account_id=user_id,
external_account_name=self._telegram_display_name(update.effective_user),
workspace_id=chat_id,
workspace_name=None,
metadata={
"chat_id": chat_id,
"chat_type": update.effective_chat.type,
"telegram_username": getattr(update.effective_user, "username", None),
},
status="connected",
)
logger.info("[Telegram] bound chat=%s user=%s to DeerFlow user=%s connection=%s", chat_id, user_id, owner_user_id, connection["id"])
await update.message.reply_text("Telegram connected to DeerFlow.")
return True
async def _attach_connection_identity(self, inbound: InboundMessage) -> InboundMessage:
if self._connection_repo is None:
return inbound
connection = await self._connection_repo.find_connection_by_external_identity(
provider="telegram",
external_account_id=inbound.user_id,
workspace_id=inbound.chat_id,
)
if connection is None:
return inbound
inbound.connection_id = connection["id"]
inbound.owner_user_id = connection["owner_user_id"]
inbound.workspace_id = connection.get("workspace_id")
return inbound
def _get_bot_username(self, context) -> str | None:
bot = getattr(context, "bot", None)
username = getattr(bot, "username", None)
if not username and self._application is not None:
username = getattr(getattr(self._application, "bot", None), "username", None)
return str(username) if username else None
@staticmethod
def _strip_bot_username_from_leading_command(text: str, bot_username: str | None) -> str:
username = (bot_username or "").lstrip("@").lower()
if not username or not text.startswith("/"):
return text
parts = text.split(maxsplit=1)
command_token = parts[0]
if "@" not in command_token:
return text
command_name, addressed_username = command_token[1:].rsplit("@", 1)
if not command_name or addressed_username.lower() != username:
return text
normalized = f"/{command_name}"
if len(parts) > 1:
normalized = f"{normalized} {parts[1]}"
return normalized
async def _cmd_start(self, update, context) -> None:
"""Handle /start command."""
if not self._check_user(update.effective_user.id):
return
args = getattr(context, "args", []) if context is not None else []
if args:
handled = await self._bind_connection_from_start_token(update, str(args[0]))
if handled:
return
await update.message.reply_text("Welcome to DeerFlow! Send me a message to start a conversation.\nType /help for available commands.")
async def _process_incoming_with_reply(self, chat_id: str, msg_id: int, inbound: InboundMessage) -> None:
@@ -358,7 +243,7 @@ class TelegramChannel(Channel):
if not self._check_user(update.effective_user.id):
return
text = self._strip_bot_username_from_leading_command(update.message.text.strip(), self._get_bot_username(context))
text = update.message.text
chat_id = str(update.effective_chat.id)
user_id = str(update.effective_user.id)
msg_id = str(update.message.message_id)
@@ -382,7 +267,6 @@ class TelegramChannel(Channel):
thread_ts=msg_id,
)
inbound.topic_id = topic_id
inbound = await self._attach_connection_identity(inbound)
if self._main_loop and self._main_loop.is_running():
fut = asyncio.run_coroutine_threadsafe(self._process_incoming_with_reply(chat_id, update.message.message_id, inbound), self._main_loop)
@@ -395,7 +279,7 @@ class TelegramChannel(Channel):
if not self._check_user(update.effective_user.id):
return
text = self._strip_bot_username_from_leading_command(update.message.text.strip(), self._get_bot_username(context))
text = update.message.text.strip()
if not text:
return
@@ -425,7 +309,6 @@ class TelegramChannel(Channel):
thread_ts=msg_id,
)
inbound.topic_id = topic_id
inbound = await self._attach_connection_identity(inbound)
if self._main_loop and self._main_loop.is_running():
fut = asyncio.run_coroutine_threadsafe(self._process_incoming_with_reply(chat_id, update.message.message_id, inbound), self._main_loop)
+1 -2
View File
@@ -22,7 +22,6 @@ from cryptography.hazmat.primitives import padding
from cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes
from app.channels.base import Channel
from app.channels.commands import is_known_channel_command
from app.channels.message_bus import InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
logger = logging.getLogger(__name__)
@@ -621,7 +620,7 @@ class WechatChannel(Channel):
chat_id=chat_id,
user_id=chat_id,
text=text,
msg_type=InboundMessageType.COMMAND if is_known_channel_command(text) else InboundMessageType.CHAT,
msg_type=InboundMessageType.COMMAND if text.startswith("/") else InboundMessageType.CHAT,
thread_ts=thread_ts,
files=files,
metadata={
+1 -2
View File
@@ -8,7 +8,6 @@ from collections.abc import Awaitable, Callable
from typing import Any, cast
from app.channels.base import Channel
from app.channels.commands import is_known_channel_command
from app.channels.message_bus import (
InboundMessageType,
MessageBus,
@@ -271,7 +270,7 @@ class WeComChannel(Channel):
user_id = (body.get("from") or {}).get("userid")
inbound_type = InboundMessageType.COMMAND if is_known_channel_command(text) else InboundMessageType.CHAT
inbound_type = InboundMessageType.COMMAND if text.startswith("/") else InboundMessageType.CHAT
inbound = self._make_inbound(
chat_id=user_id, # keep user's conversation in memory
user_id=user_id,
-25
View File
@@ -6,7 +6,6 @@ from contextlib import asynccontextmanager
from fastapi import FastAPI
from fastapi.middleware.cors import CORSMiddleware
from app.gateway.auth_disabled import warn_if_auth_disabled_enabled
from app.gateway.auth_middleware import AuthMiddleware
from app.gateway.config import get_gateway_config
from app.gateway.csrf_middleware import CSRFMiddleware, get_configured_cors_origins
@@ -16,7 +15,6 @@ from app.gateway.routers import (
artifacts,
assistants_compat,
auth,
channel_connections,
channels,
feedback,
mcp,
@@ -174,7 +172,6 @@ async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]:
startup_config = get_app_config()
apply_logging_level(startup_config.log_level)
logger.info("Configuration loaded successfully")
warn_if_auth_disabled_enabled()
except Exception as e:
error_msg = f"Failed to load configuration during gateway startup: {e}"
logger.exception(error_msg)
@@ -182,25 +179,6 @@ async def lifespan(app: FastAPI) -> AsyncGenerator[None, None]:
config = get_gateway_config()
logger.info(f"Starting API Gateway on {config.host}:{config.port}")
# Pre-warm tiktoken encoding cache so the first memory-injection request
# never blocks on the BPE data download (which hits an OpenAI/Azure URL
# that may be unreachable in restricted networks — see issue #3402).
try:
from deerflow.agents.memory.prompt import warm_tiktoken_cache
warmed = await asyncio.wait_for(
asyncio.to_thread(warm_tiktoken_cache),
timeout=5,
)
if warmed:
logger.info("tiktoken encoding cache warmed successfully")
else:
logger.warning("tiktoken encoding cache warm-up failed; token counting will use character-based fallback")
except TimeoutError:
logger.warning("tiktoken encoding cache warm-up timed out; token counting will use character-based fallback")
except Exception:
logger.warning("tiktoken warm-up skipped", exc_info=True)
# Initialize LangGraph runtime components (StreamBridge, RunManager, checkpointer, store)
async with langgraph_runtime(app, startup_config):
logger.info("LangGraph runtime initialised")
@@ -379,9 +357,6 @@ This gateway provides runtime endpoints for agent runs plus custom endpoints for
# Suggestions API is mounted at /api/threads/{thread_id}/suggestions
app.include_router(suggestions.router)
# User-facing IM channel connection API is mounted at /api/channels
app.include_router(channel_connections.router)
# Channels API is mounted at /api/channels
app.include_router(channels.router)
-54
View File
@@ -1,54 +0,0 @@
"""Shared helpers for local/E2E auth-disabled mode."""
from __future__ import annotations
import logging
import os
from types import SimpleNamespace
AUTH_DISABLED_ENV_VAR = "DEER_FLOW_AUTH_DISABLED"
AUTH_DISABLED_USER_ID = "e2e-user"
AUTH_DISABLED_USER_EMAIL = "e2e@test.local"
AUTH_SOURCE_SESSION = "session"
AUTH_SOURCE_INTERNAL = "internal"
AUTH_SOURCE_AUTH_DISABLED = "auth_disabled"
_PRODUCTION_ENV_VARS: tuple[str, ...] = ("DEER_FLOW_ENV", "ENVIRONMENT")
_PRODUCTION_ENV_VALUES: frozenset[str] = frozenset({"prod", "production"})
logger = logging.getLogger(__name__)
def is_explicit_production_environment() -> bool:
return any(os.environ.get(name, "").strip().lower() in _PRODUCTION_ENV_VALUES for name in _PRODUCTION_ENV_VARS)
def is_auth_disabled_requested() -> bool:
return os.environ.get(AUTH_DISABLED_ENV_VAR) == "1"
def is_auth_disabled() -> bool:
return is_auth_disabled_requested() and not is_explicit_production_environment()
def warn_if_auth_disabled_enabled() -> None:
if not is_auth_disabled():
return
logger.warning(
"%s=1 is active: authentication is bypassed and anonymous requests run as synthetic admin user %r. Do not enable this in shared or production deployments.",
AUTH_DISABLED_ENV_VAR,
AUTH_DISABLED_USER_ID,
)
def get_auth_disabled_user():
return SimpleNamespace(
id=AUTH_DISABLED_USER_ID,
email=AUTH_DISABLED_USER_EMAIL,
password_hash=None,
system_role="admin",
needs_setup=False,
token_version=0,
)
+22 -39
View File
@@ -17,13 +17,6 @@ from starlette.responses import JSONResponse
from starlette.types import ASGIApp
from app.gateway.auth.errors import AuthErrorCode, AuthErrorResponse
from app.gateway.auth_disabled import (
AUTH_SOURCE_AUTH_DISABLED,
AUTH_SOURCE_INTERNAL,
AUTH_SOURCE_SESSION,
get_auth_disabled_user,
is_auth_disabled,
)
from app.gateway.authz import _ALL_PERMISSIONS, AuthContext
from app.gateway.internal_auth import INTERNAL_AUTH_HEADER_NAME, get_internal_user, is_valid_internal_auth_token
from deerflow.runtime.user_context import reset_current_user, set_current_user
@@ -87,38 +80,8 @@ class AuthMiddleware(BaseHTTPMiddleware):
if is_valid_internal_auth_token(request.headers.get(INTERNAL_AUTH_HEADER_NAME)):
internal_user = get_internal_user()
auth_source = AUTH_SOURCE_SESSION
access_token = request.cookies.get("access_token")
# Non-public path: require session cookie
if internal_user is not None:
user = internal_user
auth_source = AUTH_SOURCE_INTERNAL
elif access_token:
# Strict JWT validation: reject junk/expired tokens with 401
# right here instead of silently passing through. This closes
# the "junk cookie bypass" gap (AUTH_TEST_PLAN test 7.5.8):
# without this, non-isolation routes like /api/models would
# accept any cookie-shaped string as authentication.
#
# We call the *strict* resolver so that fine-grained error
# codes (token_expired, token_invalid, user_not_found, …)
# propagate from AuthErrorCode, not get flattened into one
# generic code. BaseHTTPMiddleware doesn't let HTTPException
# bubble up, so we catch and render it as JSONResponse here.
from app.gateway.deps import get_current_user_from_request
try:
user = await get_current_user_from_request(request)
except HTTPException as exc:
if not is_auth_disabled():
return JSONResponse(status_code=exc.status_code, content={"detail": exc.detail})
user = get_auth_disabled_user()
auth_source = AUTH_SOURCE_AUTH_DISABLED
elif is_auth_disabled():
user = get_auth_disabled_user()
auth_source = AUTH_SOURCE_AUTH_DISABLED
else:
if internal_user is None and not request.cookies.get("access_token"):
return JSONResponse(
status_code=401,
content={
@@ -129,12 +92,32 @@ class AuthMiddleware(BaseHTTPMiddleware):
},
)
# Strict JWT validation: reject junk/expired tokens with 401
# right here instead of silently passing through. This closes
# the "junk cookie bypass" gap (AUTH_TEST_PLAN test 7.5.8):
# without this, non-isolation routes like /api/models would
# accept any cookie-shaped string as authentication.
#
# We call the *strict* resolver so that fine-grained error
# codes (token_expired, token_invalid, user_not_found, …)
# propagate from AuthErrorCode, not get flattened into one
# generic code. BaseHTTPMiddleware doesn't let HTTPException
# bubble up, so we catch and render it as JSONResponse here.
from app.gateway.deps import get_current_user_from_request
if internal_user is not None:
user = internal_user
else:
try:
user = await get_current_user_from_request(request)
except HTTPException as exc:
return JSONResponse(status_code=exc.status_code, content={"detail": exc.detail})
# Stamp both request.state.user (for the contextvar pattern)
# and request.state.auth (so @require_permission's "auth is
# None" branch short-circuits instead of running the entire
# JWT-decode + DB-lookup pipeline a second time per request).
request.state.user = user
request.state.auth_source = auth_source
request.state.auth = AuthContext(user=user, permissions=_ALL_PERMISSIONS)
token = set_current_user(user)
try:
-5
View File
@@ -14,8 +14,6 @@ from starlette.middleware.base import BaseHTTPMiddleware
from starlette.responses import JSONResponse
from starlette.types import ASGIApp
from app.gateway.auth_disabled import is_auth_disabled
CSRF_COOKIE_NAME = "csrf_token"
CSRF_HEADER_NAME = "X-CSRF-Token"
CSRF_TOKEN_LENGTH = 64 # bytes
@@ -40,9 +38,6 @@ def should_check_csrf(request: Request) -> bool:
if request.method not in ("POST", "PUT", "DELETE", "PATCH"):
return False
if is_auth_disabled():
return False
path = request.url.path.rstrip("/")
# Exempt /api/v1/auth/me endpoint
if path == "/api/v1/auth/me":
-11
View File
@@ -331,17 +331,6 @@ async def get_current_user_from_request(request: Request):
Raises HTTPException 401 if not authenticated.
"""
state = getattr(request, "state", None)
state_user = getattr(state, "user", None)
from app.gateway.auth_disabled import AUTH_SOURCE_AUTH_DISABLED, AUTH_SOURCE_INTERNAL, AUTH_SOURCE_SESSION
if state_user is not None and getattr(state, "auth_source", None) in {
AUTH_SOURCE_SESSION,
AUTH_SOURCE_AUTH_DISABLED,
AUTH_SOURCE_INTERNAL,
}:
return state_user
from app.gateway.auth import decode_token
from app.gateway.auth.errors import AuthErrorCode, AuthErrorResponse, TokenError, token_error_to_code
-7
View File
@@ -20,7 +20,6 @@ from langgraph_sdk import Auth
from app.gateway.auth.errors import TokenError
from app.gateway.auth.jwt import decode_token
from app.gateway.auth_disabled import AUTH_DISABLED_USER_ID, is_auth_disabled
from app.gateway.deps import get_local_provider
auth = Auth()
@@ -39,9 +38,6 @@ def _check_csrf(request) -> None:
if method.upper() not in _CSRF_METHODS:
return
if is_auth_disabled():
return
cookie_token = request.cookies.get("csrf_token")
header_token = request.headers.get("x-csrf-token")
@@ -70,9 +66,6 @@ async def authenticate(request):
# are rejected early, even if the cookie carries a valid JWT.
_check_csrf(request)
if is_auth_disabled():
return AUTH_DISABLED_USER_ID
token = request.cookies.get("access_token")
if not token:
raise Auth.exceptions.HTTPException(
+48 -73
View File
@@ -1,6 +1,5 @@
"""CRUD API for custom agents."""
import asyncio
import logging
import re
import shutil
@@ -214,60 +213,47 @@ async def create_agent_endpoint(request: AgentCreateRequest) -> AgentResponse:
user_id = get_effective_user_id()
paths = get_paths()
def _create_agent() -> AgentResponse | None:
# Worker thread: base-dir resolution, existence checks, directory/file
# creation, read-back, and failure cleanup are all blocking filesystem
# IO that must stay off the event loop.
agent_dir = paths.user_agent_dir(user_id, normalized_name)
legacy_dir = paths.agent_dir(normalized_name)
agent_dir = paths.user_agent_dir(user_id, normalized_name)
legacy_dir = paths.agent_dir(normalized_name)
if legacy_dir.exists():
return None # signals 409 to the caller
try:
try:
agent_dir.mkdir(parents=True, exist_ok=False)
except FileExistsError:
return None # signals 409 to the caller
# Write config.yaml
config_data: dict = {"name": normalized_name}
if request.description:
config_data["description"] = request.description
if request.model is not None:
config_data["model"] = request.model
if request.tool_groups is not None:
config_data["tool_groups"] = request.tool_groups
if request.skills is not None:
config_data["skills"] = request.skills
config_file = agent_dir / "config.yaml"
with open(config_file, "w", encoding="utf-8") as f:
yaml.dump(config_data, f, default_flow_style=False, allow_unicode=True)
# Write SOUL.md
soul_file = agent_dir / "SOUL.md"
soul_file.write_text(request.soul, encoding="utf-8")
logger.info(f"Created agent '{normalized_name}' at {agent_dir}")
agent_cfg = load_agent_config(normalized_name, user_id=user_id)
return _agent_config_to_response(agent_cfg, include_soul=True, user_id=user_id)
except Exception:
# Clean up partial state on failure before surfacing the error.
if agent_dir.exists():
shutil.rmtree(agent_dir)
raise
try:
response = await asyncio.to_thread(_create_agent)
except Exception as e:
logger.error(f"Failed to create agent '{request.name}': {e}", exc_info=True)
raise HTTPException(status_code=500, detail=f"Failed to create agent: {str(e)}")
if response is None:
if agent_dir.exists() or legacy_dir.exists():
raise HTTPException(status_code=409, detail=f"Agent '{normalized_name}' already exists")
return response
try:
agent_dir.mkdir(parents=True, exist_ok=True)
# Write config.yaml
config_data: dict = {"name": normalized_name}
if request.description:
config_data["description"] = request.description
if request.model is not None:
config_data["model"] = request.model
if request.tool_groups is not None:
config_data["tool_groups"] = request.tool_groups
if request.skills is not None:
config_data["skills"] = request.skills
config_file = agent_dir / "config.yaml"
with open(config_file, "w", encoding="utf-8") as f:
yaml.dump(config_data, f, default_flow_style=False, allow_unicode=True)
# Write SOUL.md
soul_file = agent_dir / "SOUL.md"
soul_file.write_text(request.soul, encoding="utf-8")
logger.info(f"Created agent '{normalized_name}' at {agent_dir}")
agent_cfg = load_agent_config(normalized_name, user_id=user_id)
return _agent_config_to_response(agent_cfg, include_soul=True, user_id=user_id)
except HTTPException:
raise
except Exception as e:
# Clean up on failure
if agent_dir.exists():
shutil.rmtree(agent_dir)
logger.error(f"Failed to create agent '{request.name}': {e}", exc_info=True)
raise HTTPException(status_code=500, detail=f"Failed to create agent: {str(e)}")
@router.put(
@@ -442,30 +428,19 @@ async def delete_agent(name: str) -> None:
name = _normalize_agent_name(name)
user_id = get_effective_user_id()
paths = get_paths()
agent_dir = paths.user_agent_dir(user_id, name)
def _remove_agent_dir() -> tuple[str, str]:
# Runs in a worker thread: resolving the base dir, probing the directory
# (`exists`), and removing it (`rmtree`) are all blocking filesystem IO
# that must stay off the event loop.
agent_dir = paths.user_agent_dir(user_id, name)
if not agent_dir.exists():
outcome = "legacy" if paths.agent_dir(name).exists() else "missing"
return outcome, str(agent_dir)
shutil.rmtree(agent_dir)
return "deleted", str(agent_dir)
if not agent_dir.exists():
if paths.agent_dir(name).exists():
raise HTTPException(
status_code=409,
detail=(f"Agent '{name}' only exists in the legacy shared layout and is not scoped to a user. Run scripts/migrate_user_isolation.py to move legacy agents into the per-user layout before deleting."),
)
raise HTTPException(status_code=404, detail=f"Agent '{name}' not found")
try:
outcome, agent_dir = await asyncio.to_thread(_remove_agent_dir)
shutil.rmtree(agent_dir)
logger.info(f"Deleted agent '{name}' from {agent_dir}")
except Exception as e:
logger.error(f"Failed to delete agent '{name}': {e}", exc_info=True)
raise HTTPException(status_code=500, detail=f"Failed to delete agent: {str(e)}")
if outcome == "legacy":
raise HTTPException(
status_code=409,
detail=(f"Agent '{name}' only exists in the legacy shared layout and is not scoped to a user. Run scripts/migrate_user_isolation.py to move legacy agents into the per-user layout before deleting."),
)
if outcome == "missing":
raise HTTPException(status_code=404, detail=f"Agent '{name}' not found")
logger.info(f"Deleted agent '{name}' from {agent_dir}")
-10
View File
@@ -341,19 +341,9 @@ async def change_password(request: Request, response: Response, body: ChangePass
- Re-issues session cookie with new token_version
"""
from app.gateway.auth.password import hash_password_async, verify_password_async
from app.gateway.auth_disabled import AUTH_SOURCE_AUTH_DISABLED
user = await get_current_user_from_request(request)
if getattr(request.state, "auth_source", None) == AUTH_SOURCE_AUTH_DISABLED:
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=AuthErrorResponse(
code=AuthErrorCode.INVALID_CREDENTIALS,
message="Password changes are not available when DEER_FLOW_AUTH_DISABLED=1.",
).model_dump(),
)
if user.password_hash is None:
raise HTTPException(status_code=status.HTTP_400_BAD_REQUEST, detail=AuthErrorResponse(code=AuthErrorCode.INVALID_CREDENTIALS, message="OAuth users cannot change password").model_dump())
@@ -1,294 +0,0 @@
"""Browser-facing APIs for user-owned IM channel bindings."""
from __future__ import annotations
import secrets
from datetime import UTC, datetime, timedelta
from typing import Any
from fastapi import APIRouter, HTTPException, Request, Response
from pydantic import BaseModel, Field
from deerflow.config.channel_connections_config import ChannelConnectionsConfig
from deerflow.persistence.channel_connections import ChannelConnectionRepository
from deerflow.persistence.engine import get_session_factory
router = APIRouter(prefix="/api/channels", tags=["channel-connections"])
_STATE_TTL_SECONDS = 600
class ChannelProviderResponse(BaseModel):
provider: str
display_name: str
enabled: bool
configured: bool
connectable: bool
unavailable_reason: str | None = None
auth_mode: str
connection_status: str
class ChannelProvidersResponse(BaseModel):
enabled: bool
providers: list[ChannelProviderResponse]
class ChannelConnectionResponse(BaseModel):
id: str
provider: str
status: str
external_account_id: str | None = None
external_account_name: str | None = None
workspace_id: str | None = None
workspace_name: str | None = None
scopes: list[str] = Field(default_factory=list)
metadata: dict[str, Any] = Field(default_factory=dict)
class ChannelConnectionsResponse(BaseModel):
connections: list[ChannelConnectionResponse]
class ChannelConnectResponse(BaseModel):
provider: str
mode: str
url: str | None = None
code: str
instruction: str
expires_in: int
_PROVIDER_META: dict[str, dict[str, str]] = {
"telegram": {"display_name": "Telegram", "auth_mode": "deep_link"},
"slack": {"display_name": "Slack", "auth_mode": "binding_code"},
"discord": {"display_name": "Discord", "auth_mode": "binding_code"},
}
_RUNTIME_REQUIREMENTS: dict[str, tuple[str, ...]] = {
"telegram": ("bot_token",),
"slack": ("bot_token", "app_token"),
"discord": ("bot_token",),
}
def _get_user_id(request: Request) -> str:
user = getattr(request.state, "user", None)
if user is None:
raise HTTPException(status_code=401, detail="Authentication required")
return str(user.id)
def _get_app_config():
from deerflow.config.app_config import get_app_config
return get_app_config()
def _get_channel_connections_config(request: Request) -> ChannelConnectionsConfig:
config = getattr(request.app.state, "channel_connections_config", None)
if isinstance(config, ChannelConnectionsConfig):
return config
return _get_app_config().channel_connections
def _get_channels_config(request: Request) -> dict[str, Any]:
state_config = getattr(request.app.state, "channels_config", None)
if isinstance(state_config, dict):
return state_config
app_config = _get_app_config()
extra = app_config.model_extra or {}
channels_config = extra.get("channels")
return dict(channels_config) if isinstance(channels_config, dict) else {}
def _get_repository(request: Request, config: ChannelConnectionsConfig) -> ChannelConnectionRepository:
repo = getattr(request.app.state, "channel_connection_repo", None)
if isinstance(repo, ChannelConnectionRepository):
return repo
sf = get_session_factory()
if sf is None:
raise HTTPException(status_code=503, detail="Channel connection persistence is not available")
repo = ChannelConnectionRepository(sf)
request.app.state.channel_connection_repo = repo
return repo
def _provider_config(config: ChannelConnectionsConfig, provider: str):
provider_config = getattr(config, provider, None)
if provider_config is None:
raise HTTPException(status_code=404, detail="Unknown channel provider")
return provider_config
def _runtime_channel_configured(provider: str, channels_config: dict[str, Any]) -> bool:
runtime_config = channels_config.get(provider)
if not isinstance(runtime_config, dict) or not runtime_config.get("enabled", False):
return False
return all(str(runtime_config.get(key) or "").strip() for key in _RUNTIME_REQUIREMENTS[provider])
def _runtime_unavailable_reason(provider: str) -> str:
keys = " and ".join(f"channels.{provider}.{key}" for key in _RUNTIME_REQUIREMENTS[provider])
return f"Enable and configure channels.{provider} with {keys}."
def _provider_unavailable_reason(
config: ChannelConnectionsConfig,
channels_config: dict[str, Any],
provider: str,
) -> str | None:
provider_config = _provider_config(config, provider)
if not provider_config.enabled:
return None
if not provider_config.configured:
if provider == "telegram":
return "Configure channel_connections.telegram.bot_username for Telegram deep links."
return f"Configure channel_connections.{provider}."
if not _runtime_channel_configured(provider, channels_config):
return _runtime_unavailable_reason(provider)
return None
def _provider_status(
config: ChannelConnectionsConfig,
channels_config: dict[str, Any],
provider: str,
) -> tuple[dict[str, bool], str | None]:
declared = config.provider_status(provider)
unavailable_reason = _provider_unavailable_reason(config, channels_config, provider)
configured = declared["configured"] and _runtime_channel_configured(provider, channels_config)
return {"enabled": declared["enabled"], "configured": configured}, unavailable_reason
def _new_binding_code() -> str:
return secrets.token_hex(4)
async def _create_state(
repo: ChannelConnectionRepository,
*,
owner_user_id: str,
provider: str,
) -> str:
state = _new_binding_code()
await repo.create_oauth_state(
owner_user_id=owner_user_id,
provider=provider,
state=state,
expires_at=datetime.now(UTC) + timedelta(seconds=_STATE_TTL_SECONDS),
)
return state
def _connect_instruction(provider: str, code: str) -> str:
if provider == "telegram":
return f"Send /start {code} to the DeerFlow Telegram bot."
if provider == "slack":
return f"Send /connect {code} to the DeerFlow Slack bot."
if provider == "discord":
return f"Send /connect {code} to the DeerFlow Discord bot."
raise HTTPException(status_code=404, detail="Unknown channel provider")
def _connect_url(config: ChannelConnectionsConfig, provider: str, code: str) -> str | None:
if provider == "telegram":
provider_config = _provider_config(config, provider)
return f"https://t.me/{provider_config.bot_username}?start={code}"
if provider in {"slack", "discord"}:
return None
raise HTTPException(status_code=404, detail="Unknown channel provider")
@router.get("/providers", response_model=ChannelProvidersResponse)
async def get_channel_providers(request: Request) -> ChannelProvidersResponse:
config = _get_channel_connections_config(request)
channels_config = _get_channels_config(request)
repo = None
if config.enabled:
try:
repo = _get_repository(request, config)
except HTTPException as exc:
if exc.status_code != 503:
raise
owner_user_id = _get_user_id(request)
connections = await repo.list_connections(owner_user_id) if repo is not None else []
by_provider = {item["provider"]: item for item in connections}
providers: list[ChannelProviderResponse] = []
for provider, meta in _PROVIDER_META.items():
status, unavailable_reason = _provider_status(config, channels_config, provider)
connection = by_provider.get(provider)
providers.append(
ChannelProviderResponse(
provider=provider,
display_name=meta["display_name"],
enabled=status["enabled"],
configured=status["configured"],
connectable=status["enabled"] and status["configured"] and unavailable_reason is None,
unavailable_reason=unavailable_reason,
auth_mode=meta["auth_mode"],
connection_status=connection["status"] if connection else "not_connected",
)
)
return ChannelProvidersResponse(enabled=config.enabled, providers=providers)
@router.get("/connections", response_model=ChannelConnectionsResponse)
async def get_channel_connections(request: Request) -> ChannelConnectionsResponse:
config = _get_channel_connections_config(request)
if not config.enabled:
return ChannelConnectionsResponse(connections=[])
repo = _get_repository(request, config)
rows = await repo.list_connections(_get_user_id(request))
return ChannelConnectionsResponse(connections=[ChannelConnectionResponse(**row) for row in rows])
@router.delete("/connections/{connection_id}", status_code=204)
async def disconnect_channel_connection(connection_id: str, request: Request) -> Response:
config = _get_channel_connections_config(request)
if not config.enabled:
raise HTTPException(status_code=400, detail="Channel connections are disabled")
repo = _get_repository(request, config)
disconnected = await repo.disconnect_connection(
connection_id=connection_id,
owner_user_id=_get_user_id(request),
)
if not disconnected:
raise HTTPException(status_code=404, detail="Channel connection not found")
return Response(status_code=204)
@router.post("/{provider}/connect", response_model=ChannelConnectResponse)
async def connect_channel_provider(provider: str, request: Request) -> ChannelConnectResponse:
config = _get_channel_connections_config(request)
channels_config = _get_channels_config(request)
if not config.enabled:
raise HTTPException(status_code=400, detail="Channel connections are disabled")
status, unavailable_reason = _provider_status(config, channels_config, provider)
if not status["enabled"]:
raise HTTPException(status_code=400, detail="Channel provider is not enabled")
if unavailable_reason:
raise HTTPException(status_code=400, detail=unavailable_reason)
if not status["configured"]:
raise HTTPException(status_code=400, detail="Channel provider is not configured")
repo = _get_repository(request, config)
code = await _create_state(
repo,
owner_user_id=_get_user_id(request),
provider=provider,
)
return ChannelConnectResponse(
provider=provider,
mode=_PROVIDER_META[provider]["auth_mode"],
url=_connect_url(config, provider, code),
code=code,
instruction=_connect_instruction(provider, code),
expires_in=_STATE_TTL_SECONDS,
)
+4 -89
View File
@@ -1,10 +1,9 @@
import json
import logging
import os
from pathlib import Path
from typing import Literal
from fastapi import APIRouter, HTTPException, Request, status
from fastapi import APIRouter, HTTPException
from pydantic import BaseModel, Field
from deerflow.config.extensions_config import ExtensionsConfig, get_extensions_config, reload_extensions_config
@@ -13,11 +12,6 @@ logger = logging.getLogger(__name__)
router = APIRouter(prefix="/api", tags=["mcp"])
_MCP_STDIO_COMMAND_ALLOWLIST_ENV = "DEER_FLOW_MCP_STDIO_COMMAND_ALLOWLIST"
_DEFAULT_MCP_STDIO_COMMAND_ALLOWLIST = frozenset({"npx", "uvx"})
_SHELL_METACHARS = frozenset(";|&`$<>\n\r")
class McpOAuthConfigResponse(BaseModel):
"""OAuth configuration for an MCP server."""
@@ -72,78 +66,6 @@ class McpConfigUpdateRequest(BaseModel):
_MASKED_VALUE = "***"
async def _require_admin_user(request: Request) -> None:
"""Require the authenticated caller to be an admin user.
``AuthMiddleware`` normally stamps ``request.state.user`` before the
request reaches this router. Falling back to the strict dependency keeps
this route safe even in tests or alternative ASGI compositions that mount
the router without the global middleware.
"""
user = getattr(request.state, "user", None)
if user is None:
from app.gateway.deps import get_current_user_from_request
user = await get_current_user_from_request(request)
if getattr(user, "system_role", None) != "admin":
raise HTTPException(
status_code=status.HTTP_403_FORBIDDEN,
detail="Admin privileges required to manage MCP configuration.",
)
def _allowed_stdio_commands() -> set[str]:
"""Return executable names allowed for API-managed stdio MCP servers."""
raw = os.environ.get(_MCP_STDIO_COMMAND_ALLOWLIST_ENV)
base = set(_DEFAULT_MCP_STDIO_COMMAND_ALLOWLIST)
if raw is None:
return base
extra = {item.strip() for item in raw.split(",") if item.strip()}
return base | extra
def _stdio_command_name(command: str | None, *, server_name: str) -> str:
"""Normalize and validate a stdio command field from the API boundary."""
if command is None or not command.strip():
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=f"MCP server '{server_name}' with stdio transport requires a command.",
)
stripped = command.strip()
has_path_separator = "/" in stripped or "\\" in stripped
if stripped != command or has_path_separator or any(ch.isspace() for ch in stripped) or any(ch in stripped for ch in _SHELL_METACHARS):
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=(f"MCP server '{server_name}' command must be a single executable name; put parameters in args instead."),
)
return stripped
def _validate_mcp_update_request(request: McpConfigUpdateRequest) -> None:
"""Validate API-submitted MCP config before it is persisted.
Local config files can still express arbitrary advanced setups, but the
HTTP API is an untrusted boundary. Restricting stdio commands here reduces
the blast radius of a compromised authenticated browser session.
"""
allowed_commands = _allowed_stdio_commands()
for name, server in request.mcp_servers.items():
transport_type = (server.type or "stdio").lower()
if transport_type != "stdio":
continue
command_name = _stdio_command_name(server.command, server_name=name)
if command_name not in allowed_commands:
allowed = ", ".join(sorted(allowed_commands)) or "<none>"
raise HTTPException(
status_code=status.HTTP_400_BAD_REQUEST,
detail=(f"MCP server '{name}' uses disallowed stdio command '{command_name}'. Allowed commands: {allowed}. Configure {_MCP_STDIO_COMMAND_ALLOWLIST_ENV} to extend this list."),
)
def _mask_server_config(server: McpServerConfigResponse) -> McpServerConfigResponse:
"""Return a copy of server config with sensitive fields masked.
@@ -240,7 +162,7 @@ def _merge_preserving_secrets(
summary="Get MCP Configuration",
description="Retrieve the current Model Context Protocol (MCP) server configurations.",
)
async def get_mcp_configuration(request: Request) -> McpConfigResponse:
async def get_mcp_configuration() -> McpConfigResponse:
"""Get the current MCP configuration.
Returns:
@@ -261,8 +183,6 @@ async def get_mcp_configuration(request: Request) -> McpConfigResponse:
}
```
"""
await _require_admin_user(request)
config = get_extensions_config()
servers = {name: _mask_server_config(McpServerConfigResponse(**server.model_dump())) for name, server in config.mcp_servers.items()}
@@ -275,7 +195,7 @@ async def get_mcp_configuration(request: Request) -> McpConfigResponse:
summary="Update MCP Configuration",
description="Update Model Context Protocol (MCP) server configurations and save to file.",
)
async def update_mcp_configuration(request: Request, body: McpConfigUpdateRequest) -> McpConfigResponse:
async def update_mcp_configuration(request: McpConfigUpdateRequest) -> McpConfigResponse:
"""Update the MCP configuration.
This will:
@@ -308,9 +228,6 @@ async def update_mcp_configuration(request: Request, body: McpConfigUpdateReques
```
"""
try:
await _require_admin_user(request)
_validate_mcp_update_request(body)
# Get the current config path (or determine where to save it)
config_path = ExtensionsConfig.resolve_config_path()
@@ -338,7 +255,7 @@ async def update_mcp_configuration(request: Request, body: McpConfigUpdateReques
# Merge incoming server configs with raw on-disk secrets
merged_servers: dict[str, McpServerConfigResponse] = {}
for name, incoming in body.mcp_servers.items():
for name, incoming in request.mcp_servers.items():
raw_server = raw_servers.get(name)
if raw_server is not None:
merged_servers[name] = _merge_preserving_secrets(
@@ -366,8 +283,6 @@ async def update_mcp_configuration(request: Request, body: McpConfigUpdateReques
servers = {name: _mask_server_config(McpServerConfigResponse(**server.model_dump())) for name, server in reloaded_config.mcp_servers.items()}
return McpConfigResponse(mcp_servers=servers)
except HTTPException:
raise
except Exception as e:
logger.error(f"Failed to update MCP configuration: {e}", exc_info=True)
raise HTTPException(status_code=500, detail=f"Failed to update MCP configuration: {str(e)}")
+1 -28
View File
@@ -1,6 +1,5 @@
import json
import logging
import re
from fastapi import APIRouter, Depends, Request
from langchain_core.messages import HumanMessage, SystemMessage
@@ -31,31 +30,6 @@ class SuggestionsResponse(BaseModel):
suggestions: list[str] = Field(default_factory=list, description="Suggested follow-up questions")
# Matches a complete <think>...</think> block (case-insensitive, spans newlines).
_THINK_BLOCK_RE = re.compile(r"<think\b[^>]*>.*?</think\s*>", re.IGNORECASE | re.DOTALL)
# Matches a dangling, unclosed <think> (model truncated at max_tokens mid-thought).
_OPEN_THINK_RE = re.compile(r"<think\b[^>]*>", re.IGNORECASE)
def _strip_think_blocks(text: str) -> str:
"""Remove reasoning-model ``<think>...</think>`` blocks from the response.
Reasoning models such as MiniMax-M3 inline their chain-of-thought into the
message ``content`` wrapped in ``<think>...</think>`` (``reasoning_split``
defaults to false), rather than exposing a separate ``reasoning_content``
field. The thinking text frequently contains ``[`` / ``]`` characters, which
corrupted the downstream ``find('[')`` / ``rfind(']')`` JSON extraction and
produced empty suggestions. We strip the reasoning before parsing so only
the actual answer remains.
"""
text = _THINK_BLOCK_RE.sub("", text)
# Drop any unclosed <think> (and everything after it) left by truncation.
open_match = _OPEN_THINK_RE.search(text)
if open_match:
text = text[: open_match.start()]
return text.strip()
def _strip_markdown_code_fence(text: str) -> str:
stripped = text.strip()
if not stripped.startswith("```"):
@@ -67,8 +41,7 @@ def _strip_markdown_code_fence(text: str) -> str:
def _parse_json_string_list(text: str) -> list[str] | None:
candidate = _strip_think_blocks(text)
candidate = _strip_markdown_code_fence(candidate)
candidate = _strip_markdown_code_fence(text)
start = candidate.find("[")
end = candidate.rfind("]")
if start == -1 or end == -1 or end <= start:
+4 -16
View File
@@ -17,7 +17,7 @@ import uuid
from typing import Any
from fastapi import APIRouter, HTTPException, Request
from langgraph.checkpoint.base import empty_checkpoint, uuid6
from langgraph.checkpoint.base import empty_checkpoint
from pydantic import BaseModel, Field, field_validator
from app.gateway.authz import require_permission
@@ -536,21 +536,9 @@ async def update_thread_state(thread_id: str, body: ThreadStateUpdateRequest, re
metadata["step"] = metadata.get("step", 0) + 1
metadata["writes"] = {body.as_node: body.values}
# Assign a new checkpoint ID so aput performs an INSERT rather than an
# in-place REPLACE of the existing row. Use uuid6 (time-ordered) rather
# than uuid4 (random) so the new ID is always lexicographically greater
# than the previous one — LangGraph's checkpointers determine the "latest"
# checkpoint by max(checkpoint_ids) string order, matching the uuid6 epoch.
checkpoint["id"] = str(uuid6())
# aput requires checkpoint_ns in the config — use the same config used for the
# read (which always includes checkpoint_ns=""). The fresh checkpoint ID is
# assigned above via checkpoint["id"]; keep checkpoint_id out of the config so
# the write is keyed by the new checkpoint payload rather than the prior read.
# All supported savers (InMemorySaver, AsyncSqliteSaver, AsyncPostgresSaver)
# persist and echo back checkpoint["id"] verbatim — none mint their own — so
# the new_config below carries the uuid6 we assigned here. (Regression-locked
# by test_update_thread_state_inserts_new_checkpoint_each_call.)
# read (which always includes checkpoint_ns=""). Do NOT include checkpoint_id
# so that aput generates a fresh checkpoint ID for the new snapshot.
write_config: dict[str, Any] = {
"configurable": {
"thread_id": thread_id,
@@ -569,7 +557,7 @@ async def update_thread_state(thread_id: str, body: ThreadStateUpdateRequest, re
# Sync title changes through the ThreadMetaStore abstraction so /threads/search
# reflects them immediately in both sqlite and memory backends.
if thread_store and body.values and "title" in body.values:
if body.values and "title" in body.values:
new_title = body.values["title"]
if new_title: # Skip empty strings and None
try:
+4 -22
View File
@@ -228,13 +228,10 @@ Get current MCP server configurations.
GET /api/mcp/config
```
Requires an authenticated admin session. Sensitive env/header/OAuth secret
values are masked in the response.
**Response:**
```json
{
"mcp_servers": {
"mcpServers": {
"github": {
"enabled": true,
"type": "stdio",
@@ -258,15 +255,10 @@ PUT /api/mcp/config
Content-Type: application/json
```
Requires an authenticated admin session. API-managed `stdio` MCP servers may
only use allowed executable names for `command` (default: `npx`, `uvx`). Set
`DEER_FLOW_MCP_STDIO_COMMAND_ALLOWLIST` to a comma-separated list when a
deployment needs additional trusted launchers.
**Request Body:**
```json
{
"mcp_servers": {
"mcpServers": {
"github": {
"enabled": true,
"type": "stdio",
@@ -284,18 +276,8 @@ deployment needs additional trusted launchers.
**Response:**
```json
{
"mcp_servers": {
"github": {
"enabled": true,
"type": "stdio",
"command": "npx",
"args": ["-y", "@modelcontextprotocol/server-github"],
"env": {
"GITHUB_TOKEN": "***"
},
"description": "GitHub operations"
}
}
"success": true,
"message": "MCP configuration updated"
}
```
+2 -2
View File
@@ -113,7 +113,7 @@ models:
base_url: https://api.minimax.io/v1
max_tokens: 4096
temperature: 1.0 # MiniMax requires temperature in (0.0, 1.0]
supports_vision: false # M2.7 is text-only; M3 supports vision
supports_vision: true
- name: minimax-m2.7-highspeed
display_name: MiniMax M2.7 Highspeed
@@ -123,7 +123,7 @@ models:
base_url: https://api.minimax.io/v1
max_tokens: 4096
temperature: 1.0 # MiniMax requires temperature in (0.0, 1.0]
supports_vision: false # M2.7 is text-only; M3 supports vision
supports_vision: true
- name: openrouter-gemini-2.5-flash
display_name: Gemini 2.5 Flash (OpenRouter)
use: langchain_openai:ChatOpenAI
-84
View File
@@ -1,84 +0,0 @@
# IM Channel Connections
DeerFlow supports user-owned IM channel bindings for Telegram, Slack, and Discord. The feature reuses the existing `channels.*` runtime configuration, so it works in local and private deployments with the same outbound transports already supported by DeerFlow.
No public IP, OAuth callback URL, or provider webhook is required in this implementation.
## Configuration
Configure the actual IM bots under the existing `channels` block:
```yaml
channels:
telegram:
enabled: true
bot_token: $TELEGRAM_BOT_TOKEN
slack:
enabled: true
bot_token: $SLACK_BOT_TOKEN
app_token: $SLACK_APP_TOKEN
discord:
enabled: true
bot_token: $DISCORD_BOT_TOKEN
```
Then enable user bindings in `channel_connections`:
```yaml
channel_connections:
enabled: true
telegram:
enabled: true
bot_username: $TELEGRAM_BOT_USERNAME
slack:
enabled: true
discord:
enabled: true
```
`channel_connections` does not duplicate provider secrets. It only controls the browser-facing connect UI and stores per-user binding records. Telegram needs `bot_username` only so the frontend can open a deep link.
## Connect Flow
Telegram:
- The frontend creates a short one-time code.
- The Connect button opens `https://t.me/<bot_username>?start=<code>`.
- The existing Telegram long-polling worker receives `/start <code>` and binds that Telegram chat/user to the current DeerFlow user.
Slack:
- The frontend creates a short one-time code.
- The UI shows `Send /connect <code> to the DeerFlow Slack bot.`
- The existing Slack Socket Mode worker receives the message and binds the Slack user/team to the current DeerFlow user.
Discord:
- The frontend creates a short one-time code.
- The UI shows `Send /connect <code> to the DeerFlow Discord bot.`
- The existing Discord Gateway worker receives the message and binds the Discord user/guild to the current DeerFlow user.
Codes expire after 10 minutes and are single-use.
## Runtime Model
Connection records live in SQL tables under `deerflow.persistence.channel_connections`:
- `channel_connections`: owner user, provider identity, workspace/guild/team, status, metadata.
- `channel_oauth_states`: one-time connect codes and Telegram deep-link state.
- `channel_conversations`: connection-scoped IM conversation to DeerFlow thread mapping.
- `channel_credentials`: reserved for future provider-token flows, not used by the local/private binding flow.
Incoming messages that resolve to a connection carry `connection_id`, `owner_user_id`, and `workspace_id`. `ChannelManager` uses `owner_user_id` as the DeerFlow run user id and preserves the raw platform user id as `channel_user_id`.
## Security Notes
- Browser APIs remain authenticated and CSRF-protected.
- Connect codes are random, short-lived, and single-use.
- Provider bot tokens remain in `channels.*` and are never returned to the browser.
- This implementation does not add public provider callback or webhook routes.
-120
View File
@@ -1,120 +0,0 @@
# Record/Replay E2E — front-back contract verification
Deterministic, **key-free** end-to-end checks that a backend change can't
silently break the frontend (and vice-versa). Two complementary layers, fed by a
single recording.
## Why
The mock-based frontend e2e hand-writes the backend's JSON/SSE, so a backend
schema or SSE change passes green ("fake green"). These layers replay a recorded
**real** run against the **real** backend (and, for Layer 2, the real frontend),
so contract drift turns the build red instead.
## The two layers
- **Layer 1 — backend golden** (`tests/test_replay_golden.py`): replays a fixture
through the real FastAPI gateway with `ReplayChatModel` and asserts the streamed
SSE event sequence equals a committed golden. Fast, no browser. Guards protocol
*shape*.
- **Layer 2 — full-stack render** (`frontend/tests/e2e-real-backend/`): real
Next.js + real gateway (replay model) + Chromium; asserts the replayed
auto-title and a follow-up suggestion render in the browser. Guards semantic
*render*. (Complementary to Layer 1 — neither subsumes the other.)
Layer 2 also hosts **cross-stack contract scenarios** — the dangerous class
where a backend change silently breaks a frontend assumption and *both sides'
unit tests stay green*. See below.
## Cross-stack scenario: multi-run render order (`multi-run-order.spec.ts`)
Regression guard for issue **#3352** (after context compression, refreshing a
thread rendered history out of order). Root cause was a front-back desync:
backend `RunManager.list_by_thread` returns runs **newest-first** (PR #2932),
while the frontend (`core/threads/hooks.ts`) iterated runs and **prepended** each
loaded page — inverting chronological order once the checkpoint no longer held
the older messages. The backend ordering test was green throughout, and the
frontend regression unit test hardcodes "backend returns newest-first" in a mock,
so only a *real frontend against a real backend* catches the desync.
This scenario does **not** record a conversation. It uses a **test-only seeder**
(`tests/seed_runs_router.py`, mounted on the replay gateway only when
`DEERFLOW_ENABLE_TEST_SEED=1`) to stand up a thread with ≥2 runs and per-run
message events — and deliberately **no checkpoint**, which is the #3352
precondition: it forces the frontend's per-run reload path to be the sole source
of truth so the ordering bug becomes observable. The seeder writes through the
gateway's own run/event stores using the request's auth context, so the real
`list_by_thread``/runs/{id}/messages` → prepend path runs live. Reverting the
#3354 frontend fix turns this spec red.
## How replay works
`tests/replay_provider.py::ReplayChatModel` returns recorded assistant turns keyed
by a **normalized hash of the model caller + conversation**. The conversation is
human / ai / tool messages — role, text, tool-call name+args; with
`<system-reminder>`, dates, UUIDs, tmp paths stripped. The caller is the stable
source of the model call (`lead_agent`, `middleware:title`, `suggest_agent`,
`subagent:*`, etc.). A miss raises loudly rather than passing silently.
**The system prompt is excluded from the match key.** The lead-agent system
prompt is a living, frequently-edited implementation detail — its wording changes
across PRs (e.g. #3195 added a "File Editing Workflow" section). Hashing it would
make every fixture go stale and red-fail unrelated PRs the moment anyone edits the
prompt. The conversation flow (user input → tool calls → results → answer) is the
stable contract that identifies a recorded turn. The caller still stays in the
key so two different model users with identical conversation text do not compete
for the same replay bucket. (This mirrors how open-design's mock picker keys on
the user prompt, not the system internals.) Combined with pinning skills +
extensions empty and disabling memory/summarization
(`tests/_replay_fixture.py::build_config_yaml`), a fixture replays the same across
machines, days, prompt edits, and CI. Replaying needs **no API key**.
A swallowed hash-miss keeps the SSE *event shapes* identical (the gateway wraps it
into a normal assistant error message), so the Layer-1 golden can't catch a miss
by shape alone — it inspects `replay_provider.replay_misses()` and fails loud
instead. Layer-2 already fails on a miss (the recorded turns never render).
## Record a new scenario (needs a real key — dev machine only)
Recording drives the **real frontend** so captured inputs match exactly what the
browser sends; fixtures contain no API key.
```bash
# 1. drive the real frontend against a real-model gateway, capturing model calls
OPENAI_API_KEY=... OPENAI_API_BASE=<openai-compatible-endpoint>/v1 \
DEERFLOW_RECORD_OUT=/tmp/rec/turns.jsonl RECORD_MODEL=<model> \
bash -c 'cd frontend && pnpm exec playwright test -c playwright.record.config.ts'
# 2. stitch the capture into a fixture
cd backend && uv run python scripts/build_fixture_from_jsonl.py \
--jsonl /tmp/rec/turns.jsonl --meta /tmp/rec/turns.jsonl.meta.json \
--out tests/fixtures/replay/<scenario>.<mode>.json --model <model>
# 3. regenerate the committed golden
DEERFLOW_WRITE_GOLDEN=1 PYTHONPATH=. uv run pytest tests/test_replay_golden.py
```
## Run (no key)
```bash
cd backend && PYTHONPATH=. uv run pytest tests/test_replay_golden.py # Layer 1
cd frontend && pnpm exec playwright test -c playwright.real-backend.config.ts # Layer 2
```
## CI
`.github/workflows/replay-e2e.yml` runs both layers on changes to **either** side
of the contract (`frontend/**`, `backend/app/gateway/**`,
`backend/packages/harness/**`, fixtures). DOM assertions are the gate; the rendered
screenshot + Playwright HTML report are uploaded as a CI artifact.
## Known limitations
- Visual regression baselines are OS-specific, so they are a **local dev gate
only** (gitignored); CI uploads the render as an artifact for human review
instead of hard-asserting a cross-OS baseline.
- Fixtures are coupled to the recording-time prompt; if new
environment-dependent content enters the system prompt, extend the
normalization in `replay_provider.py` (or pin it in `build_config_yaml`).
- Re-record a scenario if the agent graph changes how many model calls it makes
— the replay raises loudly on a hash miss pointing at the divergence.
+4 -4
View File
@@ -127,8 +127,8 @@ complex_agent = create_agent_for_task("high")
## How It Works
1. When `make_lead_agent(config)` is called, it extracts `is_plan_mode` from `config.configurable`
2. The config is passed to `build_middlewares(config)`
3. `build_middlewares()` reads `is_plan_mode` and calls `_create_todo_list_middleware(is_plan_mode)`
2. The config is passed to `_build_middlewares(config)`
3. `_build_middlewares()` reads `is_plan_mode` and calls `_create_todo_list_middleware(is_plan_mode)`
4. If `is_plan_mode=True`, a `TodoListMiddleware` instance is created and added to the middleware chain
5. The middleware automatically adds a `write_todos` tool to the agent's toolset
6. The agent can use this tool to manage tasks during execution
@@ -141,7 +141,7 @@ make_lead_agent(config)
├─> Extracts: is_plan_mode = config.configurable.get("is_plan_mode", False)
└─> build_middlewares(config)
└─> _build_middlewares(config)
├─> ThreadDataMiddleware
├─> SandboxMiddleware
@@ -156,7 +156,7 @@ make_lead_agent(config)
### Agent Module
- **Location**: `packages/harness/deerflow/agents/lead_agent/agent.py`
- **Function**: `_create_todo_list_middleware(is_plan_mode: bool)` - Creates TodoListMiddleware if plan mode is enabled
- **Function**: `build_middlewares(config: RunnableConfig)` - Builds middleware chain based on runtime config
- **Function**: `_build_middlewares(config: RunnableConfig)` - Builds middleware chain based on runtime config
- **Function**: `make_lead_agent(config: RunnableConfig)` - Creates agent with appropriate middlewares
### Runtime Configuration
@@ -21,6 +21,7 @@ middleware, and the async path inside ``TitleMiddleware``. Any new in-graph
from __future__ import annotations
import logging
from typing import TYPE_CHECKING
from langchain.agents import create_agent
from langchain.agents.middleware import AgentMiddleware
@@ -47,9 +48,12 @@ from deerflow.skills.tool_policy import filter_tools_by_skill_allowed_tools
from deerflow.skills.types import Skill
from deerflow.tracing import build_tracing_callbacks
logger = logging.getLogger(__name__)
if TYPE_CHECKING:
from langchain.tools import BaseTool
_BOOTSTRAP_SKILL_NAMES = {"bootstrap"}
from deerflow.tools.builtins.tool_search import DeferredToolSetup
logger = logging.getLogger(__name__)
def _get_runtime_config(config: RunnableConfig) -> dict:
@@ -267,31 +271,21 @@ Being proactive with task management demonstrates thoroughness and ensures all r
# ViewImageMiddleware should be before ClarificationMiddleware to inject image details before LLM
# ToolErrorHandlingMiddleware should be before ClarificationMiddleware to convert tool exceptions to ToolMessages
# ClarificationMiddleware should be last to intercept clarification requests after model calls
def build_middlewares(
def _build_middlewares(
config: RunnableConfig,
model_name: str | None,
agent_name: str | None = None,
custom_middlewares: list[AgentMiddleware] | None = None,
*,
available_skills: set[str] | None = None,
app_config: AppConfig | None = None,
deferred_setup=None,
):
"""Build the lead-agent middleware chain based on runtime configuration.
Public entry point for the lead agent's full middleware composition. Used by
``make_lead_agent`` and by the embedded ``DeerFlowClient`` (a lead-agent variant
that needs the identical chain). Keep this name stable: it is imported across a
module boundary, so renames/signature changes ripple into ``client.py``.
"""Build middleware chain based on runtime configuration.
Args:
config: Runtime configuration containing configurable options like is_plan_mode.
model_name: Resolved runtime model name; gates vision-only middleware.
agent_name: If provided, MemoryMiddleware will use per-agent memory storage.
custom_middlewares: Optional list of custom middlewares to inject into the chain.
app_config: Explicit AppConfig; falls back to ``get_app_config()`` when omitted.
deferred_setup: Optional deferred-MCP-tool setup that attaches
``DeferredToolFilterMiddleware`` when ``tool_search`` is enabled.
Returns:
List of middleware instances.
@@ -305,13 +299,6 @@ def build_middlewares(
middlewares.append(DynamicContextMiddleware(agent_name=agent_name, app_config=resolved_app_config))
# Deterministically load a full SKILL.md when the user starts the turn with
# /skill-name. This keeps the base system prompt metadata-only while giving
# explicit user activation priority over model-side relevance guessing.
from deerflow.agents.middlewares.skill_activation_middleware import SkillActivationMiddleware
middlewares.append(SkillActivationMiddleware(available_skills=available_skills, app_config=resolved_app_config))
# Add summarization middleware if enabled
summarization_middleware = _create_summarization_middleware(app_config=resolved_app_config)
if summarization_middleware is not None:
@@ -377,9 +364,29 @@ def build_middlewares(
return middlewares
def _assemble_deferred(filtered_tools: list[BaseTool], *, enabled: bool) -> tuple[list[BaseTool], DeferredToolSetup]:
"""Build the final tool list + deferred setup from a policy-filtered list.
Call AFTER tool-policy filtering so the deferred catalog never exposes a
tool the agent is not allowed to use. Fail-closed: if tool_search is enabled
and MCP tools survived filtering but no deferred set was recovered, raise
rather than silently binding their full schemas to the model.
"""
from deerflow.tools.builtins.tool_search import build_deferred_tool_setup
from deerflow.tools.mcp_metadata import is_mcp_tool
deferred_setup = build_deferred_tool_setup(filtered_tools, enabled=enabled)
if enabled and not deferred_setup.deferred_names and any(is_mcp_tool(t) for t in filtered_tools):
raise RuntimeError("tool_search enabled and MCP tools survived policy filtering, but no deferred set was recovered — refusing to bind MCP schemas (fail-closed).")
final_tools = list(filtered_tools)
if deferred_setup.tool_search_tool:
final_tools.append(deferred_setup.tool_search_tool)
return final_tools, deferred_setup
def _available_skill_names(agent_config, is_bootstrap: bool) -> set[str] | None:
if is_bootstrap:
return set(_BOOTSTRAP_SKILL_NAMES)
return {"bootstrap"}
if agent_config and agent_config.skills is not None:
return set(agent_config.skills)
return None
@@ -410,7 +417,6 @@ def _make_lead_agent(config: RunnableConfig, *, app_config: AppConfig):
# Lazy import to avoid circular dependency
from deerflow.tools import get_available_tools
from deerflow.tools.builtins import setup_agent, update_agent
from deerflow.tools.builtins.tool_search import assemble_deferred_tools
cfg = _get_runtime_config(config)
resolved_app_config = app_config
@@ -485,25 +491,17 @@ def _make_lead_agent(config: RunnableConfig, *, app_config: AppConfig):
if is_bootstrap:
# Special bootstrap agent with minimal prompt for initial custom agent creation flow
# Keep the bootstrap skill set intentionally narrow so agent creation
# remains deterministic before the custom agent's own config exists.
raw_tools = get_available_tools(model_name=model_name, subagent_enabled=subagent_enabled, app_config=resolved_app_config) + [setup_agent]
filtered = filter_tools_by_skill_allowed_tools(raw_tools, skills_for_tool_policy)
final_tools, setup = assemble_deferred_tools(filtered, enabled=resolved_app_config.tool_search.enabled)
final_tools, setup = _assemble_deferred(filtered, enabled=resolved_app_config.tool_search.enabled)
return create_agent(
model=create_chat_model(name=model_name, thinking_enabled=thinking_enabled, app_config=resolved_app_config, attach_tracing=False),
tools=final_tools,
middleware=build_middlewares(
config,
model_name=model_name,
available_skills=set(_BOOTSTRAP_SKILL_NAMES),
app_config=resolved_app_config,
deferred_setup=setup,
),
middleware=_build_middlewares(config, model_name=model_name, app_config=resolved_app_config, deferred_setup=setup),
system_prompt=apply_prompt_template(
subagent_enabled=subagent_enabled,
max_concurrent_subagents=max_concurrent_subagents,
available_skills=set(_BOOTSTRAP_SKILL_NAMES),
available_skills=set(["bootstrap"]),
app_config=resolved_app_config,
deferred_names=setup.deferred_names,
),
@@ -516,23 +514,16 @@ def _make_lead_agent(config: RunnableConfig, *, app_config: AppConfig):
# Default lead agent (unchanged behavior)
raw_tools = get_available_tools(model_name=model_name, groups=agent_config.tool_groups if agent_config else None, subagent_enabled=subagent_enabled, app_config=resolved_app_config)
filtered = filter_tools_by_skill_allowed_tools(raw_tools + extra_tools, skills_for_tool_policy)
final_tools, setup = assemble_deferred_tools(filtered, enabled=resolved_app_config.tool_search.enabled)
final_tools, setup = _assemble_deferred(filtered, enabled=resolved_app_config.tool_search.enabled)
return create_agent(
model=create_chat_model(name=model_name, thinking_enabled=thinking_enabled, reasoning_effort=reasoning_effort, app_config=resolved_app_config, attach_tracing=False),
tools=final_tools,
middleware=build_middlewares(
config,
model_name=model_name,
agent_name=agent_name,
available_skills=available_skills,
app_config=resolved_app_config,
deferred_setup=setup,
),
middleware=_build_middlewares(config, model_name=model_name, agent_name=agent_name, app_config=resolved_app_config, deferred_setup=setup),
system_prompt=apply_prompt_template(
subagent_enabled=subagent_enabled,
max_concurrent_subagents=max_concurrent_subagents,
agent_name=agent_name,
available_skills=available_skills,
available_skills=set(agent_config.skills) if agent_config and agent_config.skills is not None else None,
app_config=resolved_app_config,
deferred_names=setup.deferred_names,
),
@@ -10,7 +10,6 @@ from deerflow.config.agents_config import load_agent_soul
from deerflow.skills.storage import get_or_new_skill_storage
from deerflow.skills.types import Skill, SkillCategory
from deerflow.subagents import get_available_subagent_names
from deerflow.tools.builtins.tool_search import get_deferred_tools_prompt_section
if TYPE_CHECKING:
from deerflow.config.app_config import AppConfig
@@ -625,11 +624,6 @@ You have access to skills that provide optimized workflows for specific tasks. E
4. Load referenced resources only when needed during execution
5. Follow the skill's instructions precisely
**Explicit Slash Skill Activation:**
- If the user starts a request with `/<skill-name>`, that skill was explicitly requested for the current turn.
- Follow the activated skill before choosing a general workflow.
- The runtime injects the activated skill content for explicit slash activations; do not call `read_file` for that SKILL.md again unless the injected skill references supporting resources you need.
**Skills are located at:** {container_base_path}
{skill_evolution_section}
{skills_list}
@@ -699,6 +693,19 @@ Rules:
"""
def get_deferred_tools_prompt_section(*, deferred_names: frozenset[str] = frozenset()) -> str:
"""Generate <available-deferred-tools> from an explicit deferred-name set.
Lists only names so the agent knows what exists and can use tool_search to
load them. Returns empty string when there are no deferred tools. The set is
computed at agent build time (after tool-policy filtering) and passed in.
"""
if not deferred_names:
return ""
names = "\n".join(sorted(deferred_names))
return f"<available-deferred-tools>\n{names}\n</available-deferred-tools>"
def _build_acp_section(*, app_config: AppConfig | None = None) -> str:
"""Build the ACP agent prompt section, only if ACP agents are configured."""
if app_config is None:
@@ -1,14 +1,9 @@
"""Prompt templates for memory update and injection."""
from __future__ import annotations
import logging
import math
import re
from typing import Any
logger = logging.getLogger(__name__)
try:
import tiktoken
@@ -165,39 +160,6 @@ Rules:
Return ONLY valid JSON."""
# Module-level tiktoken encoding cache. Populated lazily on first use;
# subsequent calls are a dict lookup (no network I/O). Pre-warming at
# startup via :func:`warm_tiktoken_cache` avoids blocking a request on the
# (potentially slow) first ``get_encoding`` call.
_tiktoken_encoding_cache: dict[str, tiktoken.Encoding] = {}
def _get_tiktoken_encoding(encoding_name: str = "cl100k_base") -> tiktoken.Encoding | None:
"""Return a cached tiktoken encoding, or ``None`` on failure / unavailability.
On the very first call for a given *encoding_name*, tiktoken may need to
download the BPE data from ``openaipublic.blob.core.windows.net``. In
network-restricted environments (e.g. deployments behind the GFW) this
download can block for tens of minutes before the OS TCP timeout kicks in.
The caller must therefore be prepared for this to block and should run it
off the event loop (e.g. via ``asyncio.to_thread``).
"""
if not TIKTOKEN_AVAILABLE:
return None
cached = _tiktoken_encoding_cache.get(encoding_name)
if cached is not None:
return cached
try:
encoding = tiktoken.get_encoding(encoding_name)
_tiktoken_encoding_cache[encoding_name] = encoding
return encoding
except Exception:
logger.warning("Failed to load tiktoken encoding %r; falling back to char-based estimation", encoding_name, exc_info=True)
return None
def _count_tokens(text: str, encoding_name: str = "cl100k_base") -> int:
"""Count tokens in text using tiktoken.
@@ -208,30 +170,18 @@ def _count_tokens(text: str, encoding_name: str = "cl100k_base") -> int:
Returns:
The number of tokens in the text.
"""
encoding = _get_tiktoken_encoding(encoding_name)
if encoding is None:
if not TIKTOKEN_AVAILABLE:
# Fallback to character-based estimation if tiktoken is not available
# or the encoding failed to load.
return len(text) // 4
try:
encoding = tiktoken.get_encoding(encoding_name)
return len(encoding.encode(text))
except Exception:
# Fallback to character-based estimation on error
return len(text) // 4
def warm_tiktoken_cache() -> bool:
"""Pre-warm the tiktoken encoding cache.
Call at startup (off the event loop) so the first request never blocks
on the BPE download. Returns ``True`` if the encoding was loaded
successfully (or was already cached), ``False`` if tiktoken is
unavailable or the download failed.
"""
return _get_tiktoken_encoding("cl100k_base") is not None
def _coerce_confidence(value: Any, default: float = 0.0) -> float:
"""Coerce a confidence-like value to a bounded float in [0, 1].
@@ -28,7 +28,6 @@ Date-update format:
from __future__ import annotations
import asyncio
import logging
import re
import uuid
@@ -44,12 +43,6 @@ if TYPE_CHECKING:
logger = logging.getLogger(__name__)
# Upper bound (seconds) for a single _inject() offload. If the warm-up at
# gateway startup failed silently, the first request may still hit a cold
# tiktoken BPE download that blocks until the OS TCP timeout (~26 min).
# This cap ensures the request degrades gracefully instead of hanging.
_INJECT_TIMEOUT_SECONDS = 5.0
_DATE_RE = re.compile(r"<current_date>([^<]+)</current_date>")
_DYNAMIC_CONTEXT_REMINDER_KEY = "dynamic_context_reminder"
_SUMMARY_MESSAGE_NAME = "summary"
@@ -208,25 +201,4 @@ class DynamicContextMiddleware(AgentMiddleware):
@override
async def abefore_agent(self, state, runtime: Runtime) -> dict | None:
# _inject() performs synchronous file I/O (memory JSON loading) and
# potentially blocking network calls (tiktoken encoding download on
# first use). Offload to a thread so the event loop is never blocked
# — a blocking call here starves all concurrent HTTP handlers (auth,
# SSE heartbeats, etc.). See issue #3402.
#
# Bounded timeout: if startup warm-up failed silently (e.g. network
# blip during deploy), the first request's cold tiktoken download can
# block for tens of minutes (OS TCP timeout). Time-box injection so
# the request degrades gracefully (no memory context) rather than
# hanging.
try:
return await asyncio.wait_for(
asyncio.to_thread(self._inject, state),
timeout=_INJECT_TIMEOUT_SECONDS,
)
except TimeoutError:
logger.warning(
"DynamicContextMiddleware: injection timed out (%.1fs); skipping memory/date injection for this turn",
_INJECT_TIMEOUT_SECONDS,
)
return None
return self._inject(state)
@@ -1,289 +0,0 @@
"""Middleware for explicit slash skill activation."""
from __future__ import annotations
import asyncio
import hashlib
import html
import logging
import uuid
from collections.abc import Awaitable, Callable
from dataclasses import dataclass
from pathlib import Path
from typing import TYPE_CHECKING, override
from langchain.agents.middleware import AgentMiddleware
from langchain.agents.middleware.types import ModelRequest, ModelResponse
from langchain_core.messages import AIMessage, HumanMessage
from deerflow.skills.slash import parse_slash_skill_reference, resolve_slash_skill
from deerflow.skills.storage import get_or_new_skill_storage
from deerflow.skills.storage.skill_storage import SkillStorage
from deerflow.skills.types import SKILL_MD_FILE
from deerflow.utils.messages import get_original_user_content_text
if TYPE_CHECKING:
from deerflow.config.app_config import AppConfig
logger = logging.getLogger(__name__)
_SLASH_SKILL_ACTIVATION_KEY = "slash_skill_activation"
_SLASH_SKILL_ACTIVATION_TARGET_ID_KEY = "slash_skill_activation_target_id"
_SUMMARY_MESSAGE_NAME = "summary"
@dataclass(frozen=True, slots=True)
class _Activation:
skill_name: str
category: str
container_file_path: str
skill_content: str
content_hash: str
remaining_text: str
@dataclass(frozen=True, slots=True)
class _ActivationResolution:
activation: _Activation | None = None
failure_message: str | None = None
def is_slash_skill_activation_reminder(message: object) -> bool:
"""Return whether a message is hidden slash-skill activation context."""
return isinstance(message, HumanMessage) and bool(message.additional_kwargs.get(_SLASH_SKILL_ACTIVATION_KEY))
def _is_user_activation_target(message: object) -> bool:
if not isinstance(message, HumanMessage):
return False
if message.name == _SUMMARY_MESSAGE_NAME:
return False
if message.additional_kwargs.get("hide_from_ui"):
return False
return True
class SkillActivationMiddleware(AgentMiddleware):
"""Inject full SKILL.md content when the user explicitly types /skill-name."""
def __init__(
self,
*,
available_skills: set[str] | None = None,
app_config: AppConfig | None = None,
) -> None:
super().__init__()
self._available_skills = set(available_skills) if available_skills is not None else None
self._app_config = app_config
def _storage(self) -> SkillStorage:
if self._app_config is not None:
return get_or_new_skill_storage(app_config=self._app_config)
return get_or_new_skill_storage()
@staticmethod
def _read_skill_content(skill_file: Path, skills_root: Path) -> str:
if skill_file.name != SKILL_MD_FILE:
raise ValueError(f"Expected {SKILL_MD_FILE}, got {skill_file.name}")
resolved_root = skills_root.resolve()
resolved_file = skill_file.resolve()
try:
resolved_file.relative_to(resolved_root)
except ValueError as exc:
raise ValueError("Resolved skill file must stay within the configured skills root.") from exc
if not resolved_file.is_file():
raise FileNotFoundError(resolved_file)
return resolved_file.read_text(encoding="utf-8")
def _resolve_activation(self, text: str) -> _ActivationResolution | None:
reference = parse_slash_skill_reference(text)
if reference is None:
return None
storage = self._storage()
skills = storage.load_skills(enabled_only=False)
skill = next((candidate for candidate in skills if candidate.name == reference.name), None)
if skill is None:
return _ActivationResolution(failure_message=f"Skill `/{reference.name}` is not installed.")
if not skill.enabled:
return _ActivationResolution(failure_message=f"Skill `/{reference.name}` is installed but disabled. Enable it before using slash activation.")
if self._available_skills is not None and reference.name not in self._available_skills:
return _ActivationResolution(failure_message=f"Skill `/{reference.name}` is not available for this agent.")
resolved = resolve_slash_skill(
text,
skills,
available_skills=self._available_skills,
container_base_path=storage.get_container_root(),
)
if resolved is None:
return _ActivationResolution(failure_message=f"Skill `/{reference.name}` could not be resolved.")
try:
skill_content = self._read_skill_content(resolved.skill.skill_file, storage.get_skills_root_path())
except (OSError, ValueError):
logger.exception("Failed to read slash-activated skill %s", resolved.skill.name)
return _ActivationResolution(failure_message=f"Skill `/{reference.name}` could not be loaded safely. Please check the skill installation.")
content_hash = hashlib.sha256(skill_content.encode("utf-8")).hexdigest()
return _ActivationResolution(
activation=_Activation(
skill_name=resolved.skill.name,
category=str(resolved.skill.category),
container_file_path=resolved.container_file_path,
skill_content=skill_content,
content_hash=content_hash,
remaining_text=resolved.remaining_text,
)
)
@staticmethod
def _build_activation_reminder(activation: _Activation) -> str:
user_request = activation.remaining_text or ("No additional task text was provided after the slash skill command. Ask the user what they want to do with this skill if the next step is unclear.")
escaped_user_request = html.escape(user_request, quote=False)
escaped_skill_content = html.escape(activation.skill_content, quote=False)
escaped_skill_name = html.escape(activation.skill_name, quote=True)
escaped_category = html.escape(activation.category, quote=True)
escaped_path = html.escape(activation.container_file_path, quote=True)
escaped_content_hash = html.escape(activation.content_hash, quote=True)
return f"""<slash_skill_activation>
The user explicitly activated the `{activation.skill_name}` skill for this turn.
Treat the task text as:
<user_request>
{escaped_user_request}
</user_request>
Follow this skill before choosing a general workflow. Load supporting resources from the same skill directory only when needed.
<skill name="{escaped_skill_name}" category="{escaped_category}" path="{escaped_path}" sha256="{escaped_content_hash}">
<skill_content encoding="xml-escaped">
{escaped_skill_content}
</skill_content>
</skill>
</slash_skill_activation>"""
@staticmethod
def _has_existing_activation_for_target(messages: list, target_index: int, target: HumanMessage) -> bool:
if target_index <= 0:
return False
if target.id:
for previous in messages[:target_index]:
if not is_slash_skill_activation_reminder(previous):
continue
target_id = previous.additional_kwargs.get(_SLASH_SKILL_ACTIVATION_TARGET_ID_KEY)
if target_id == target.id or previous.id == f"{target.id}__slash_activation":
return True
previous = messages[target_index - 1]
return is_slash_skill_activation_reminder(previous)
def _find_activation_target(self, messages: list) -> tuple[int, HumanMessage, _ActivationResolution] | None:
if not messages:
return None
target_index = next((idx for idx in range(len(messages) - 1, -1, -1) if _is_user_activation_target(messages[idx])), None)
if target_index is None:
return None
target = messages[target_index]
if target is None:
return None
if self._has_existing_activation_for_target(messages, target_index, target):
return None
content = get_original_user_content_text(target.content, target.additional_kwargs)
resolution = self._resolve_activation(content)
if resolution is None:
return None
return target_index, target, resolution
@staticmethod
def _record_activation(request: ModelRequest, activation: _Activation, *, hook: str) -> None:
runtime = getattr(request, "runtime", None)
context = getattr(runtime, "context", None)
journal = context.get("__run_journal") if isinstance(context, dict) else None
if journal is None:
return
try:
journal.record_middleware(
"skill_activation",
name="SkillActivationMiddleware",
hook=hook,
action="activate",
changes={
"skill_name": activation.skill_name,
"category": activation.category,
"path": activation.container_file_path,
"content_hash": activation.content_hash,
},
)
except Exception:
logger.debug("Failed to record slash skill activation audit event", exc_info=True)
def _prepare_model_request(self, request: ModelRequest, *, hook: str) -> ModelRequest | AIMessage | None:
target_and_resolution = self._find_activation_target(list(request.messages))
if target_and_resolution is None:
return None
target_index, target, resolution = target_and_resolution
if resolution.failure_message:
return AIMessage(content=resolution.failure_message)
activation = resolution.activation
if activation is None:
return None
logger.info(
"SkillActivationMiddleware: activating slash skill %s category=%s path=%s hash=%s",
activation.skill_name,
activation.category,
activation.container_file_path,
activation.content_hash,
)
self._record_activation(request, activation, hook=hook)
activation_msg = self._make_activation_message(target, self._build_activation_reminder(activation))
messages = list(request.messages)
messages.insert(target_index, activation_msg)
return request.override(messages=messages)
@staticmethod
def _make_activation_message(target: HumanMessage, activation_content: str) -> HumanMessage:
stable_id = target.id or str(uuid.uuid4())
additional_kwargs = {
"hide_from_ui": True,
_SLASH_SKILL_ACTIVATION_KEY: True,
}
if target.id:
additional_kwargs[_SLASH_SKILL_ACTIVATION_TARGET_ID_KEY] = target.id
return HumanMessage(
content=activation_content,
id=f"{stable_id}__slash_activation",
additional_kwargs=additional_kwargs,
)
@override
def wrap_model_call(
self,
request: ModelRequest,
handler: Callable[[ModelRequest], ModelResponse],
) -> ModelResponse | AIMessage:
prepared = self._prepare_model_request(request, hook="wrap_model_call")
if prepared is None:
return handler(request)
if isinstance(prepared, AIMessage):
return prepared
return handler(prepared)
@override
async def awrap_model_call(
self,
request: ModelRequest,
handler: Callable[[ModelRequest], Awaitable[ModelResponse]],
) -> ModelResponse | AIMessage:
prepared = await asyncio.to_thread(self._prepare_model_request, request, hook="awrap_model_call")
if prepared is None:
return await handler(request)
if isinstance(prepared, AIMessage):
return prepared
return await handler(prepared)
@@ -2,7 +2,7 @@
import logging
from collections.abc import Awaitable, Callable
from typing import TYPE_CHECKING, override
from typing import override
from langchain.agents import AgentState
from langchain.agents.middleware import AgentMiddleware
@@ -12,48 +12,10 @@ from langgraph.prebuilt.tool_node import ToolCallRequest
from langgraph.types import Command
from deerflow.config.app_config import AppConfig
from deerflow.subagents.status_contract import (
extract_subagent_status,
make_subagent_additional_kwargs,
)
if TYPE_CHECKING:
from deerflow.tools.builtins.tool_search import DeferredToolSetup
logger = logging.getLogger(__name__)
_MISSING_TOOL_CALL_ID = "missing_tool_call_id"
_TASK_TOOL_NAME = "task"
def _stamp_task_subagent_status(message: ToolMessage, *, tool_name: str, error: str | None = None) -> ToolMessage:
"""Centralised stamping of ``additional_kwargs.subagent_status``.
Bytedance/deer-flow issue #3146: the frontend now reads the subagent
status from a structured field instead of parsing the leading text of
the task tool's return string. That contract is enforced here, in the
one place every task tool result flows through, rather than at the 5
normal-return + 3 ``Error:`` pre-execution branches inside
``task_tool.py``. Centralisation prevents the "added a new return
path, forgot the stamp" drift mode.
For non-``task`` tools this is a no-op so other tools' additional_kwargs
conventions are untouched.
"""
if tool_name != _TASK_TOOL_NAME:
return message
content = message.content if isinstance(message.content, str) else ""
status = extract_subagent_status(content)
if status is None:
# Non-terminal streaming chunks or unrecognised shapes leave the
# field unset so the frontend can keep the card on its in-progress
# placeholder until a real terminal frame arrives.
return message
stamp = make_subagent_additional_kwargs(status, error=error)
existing = dict(message.additional_kwargs or {})
existing.update(stamp)
message.additional_kwargs = existing
return message
class ToolErrorHandlingMiddleware(AgentMiddleware[AgentState]):
@@ -67,31 +29,12 @@ class ToolErrorHandlingMiddleware(AgentMiddleware[AgentState]):
detail = detail[:497] + "..."
content = f"Error: Tool '{tool_name}' failed with {exc.__class__.__name__}: {detail}. Continue with available context, or choose an alternative tool."
message = ToolMessage(
return ToolMessage(
content=content,
tool_call_id=tool_call_id,
name=tool_name,
status="error",
)
# Stamp the structured subagent status on the wrapper too: the
# frontend would otherwise have to fall back to prefix-matching
# ``Error: Tool 'task' failed ...`` on the wire. The ``subagent_error``
# carries the same ``ExcClass: detail`` shape the wrapper string
# uses so debugging artifacts stay aligned.
structured_error = f"{exc.__class__.__name__}: {detail}"
return _stamp_task_subagent_status(message, tool_name=tool_name, error=structured_error)
@staticmethod
def _maybe_stamp(result: ToolMessage | Command, request: ToolCallRequest) -> ToolMessage | Command:
"""Apply the subagent stamp to successful task tool returns.
``Command`` results bypass the stamp they encode LangGraph
control flow rather than user-facing tool output.
"""
if not isinstance(result, ToolMessage):
return result
tool_name = str(request.tool_call.get("name") or "")
return _stamp_task_subagent_status(result, tool_name=tool_name)
@override
def wrap_tool_call(
@@ -100,14 +43,13 @@ class ToolErrorHandlingMiddleware(AgentMiddleware[AgentState]):
handler: Callable[[ToolCallRequest], ToolMessage | Command],
) -> ToolMessage | Command:
try:
result = handler(request)
return handler(request)
except GraphBubbleUp:
# Preserve LangGraph control-flow signals (interrupt/pause/resume).
raise
except Exception as exc:
logger.exception("Tool execution failed (sync): name=%s id=%s", request.tool_call.get("name"), request.tool_call.get("id"))
return self._build_error_message(request, exc)
return self._maybe_stamp(result, request)
@override
async def awrap_tool_call(
@@ -116,14 +58,13 @@ class ToolErrorHandlingMiddleware(AgentMiddleware[AgentState]):
handler: Callable[[ToolCallRequest], Awaitable[ToolMessage | Command]],
) -> ToolMessage | Command:
try:
result = await handler(request)
return await handler(request)
except GraphBubbleUp:
# Preserve LangGraph control-flow signals (interrupt/pause/resume).
raise
except Exception as exc:
logger.exception("Tool execution failed (async): name=%s id=%s", request.tool_call.get("name"), request.tool_call.get("id"))
return self._build_error_message(request, exc)
return self._maybe_stamp(result, request)
def _build_runtime_middlewares(
@@ -202,7 +143,6 @@ def build_subagent_runtime_middlewares(
app_config: AppConfig | None = None,
model_name: str | None = None,
lazy_init: bool = True,
deferred_setup: "DeferredToolSetup | None" = None,
) -> list[AgentMiddleware]:
"""Middlewares shared by subagent runtime before subagent-only middlewares."""
if app_config is None:
@@ -226,16 +166,6 @@ def build_subagent_runtime_middlewares(
middlewares.append(ViewImageMiddleware())
# Hide deferred (MCP) tool schemas from the subagent's model binding until
# tool_search promotes them. This is the same wiring the lead agent gets. The deferred
# set + catalog hash come from the build-time setup (assembled after
# tool-policy filtering); promotion is read from graph state. Empty/None
# setup (deferral disabled or no MCP tool survived) is a pure no-op.
if deferred_setup is not None and deferred_setup.deferred_names:
from deerflow.agents.middlewares.deferred_tool_filter_middleware import DeferredToolFilterMiddleware
middlewares.append(DeferredToolFilterMiddleware(deferred_setup.deferred_names, deferred_setup.catalog_hash))
# Same provider safety-termination guard the lead agent uses — subagents
# are equally exposed to truncated tool_calls returned with
# finish_reason=content_filter (and friends), and the bad call would then
@@ -11,11 +11,10 @@ from __future__ import annotations
import asyncio
import logging
import os
import shlex
import uuid
from collections.abc import Awaitable, Callable
from dataclasses import replace as dc_replace
from typing import TYPE_CHECKING, Any, override
from typing import Any, override
from langchain.agents import AgentState
from langchain.agents.middleware import AgentMiddleware
@@ -25,19 +24,9 @@ from langgraph.prebuilt.tool_node import ToolCallRequest
from langgraph.types import Command
from deerflow.config.tool_output_config import ToolOutputConfig
from deerflow.sandbox.sandbox_provider import get_sandbox_provider
if TYPE_CHECKING:
from deerflow.sandbox.sandbox import Sandbox
logger = logging.getLogger(__name__)
# Virtual outputs root inside the sandbox. Host-mounted sandboxes map this to
# the thread outputs dir on the host; for non-mounted (remote) sandboxes the
# same path is written directly into the sandbox filesystem so the model's
# ``read_file`` tool can read it back (issue #3416).
_VIRTUAL_OUTPUTS_BASE = "/mnt/user-data/outputs"
def _default_config() -> ToolOutputConfig:
return ToolOutputConfig()
@@ -105,18 +94,6 @@ def _sanitize_tool_name(name: str) -> str:
return safe or "unknown"
def _build_externalized_filename(*, tool_name: str, tool_call_id: str) -> str:
"""Build the on-disk filename for an externalized tool output.
Shared by the host-disk and sandbox externalization paths so both
produce the identical naming scheme.
"""
safe_name = _sanitize_tool_name(tool_name)
ext = _EXT_MAP.get(tool_name, "txt")
short_id = uuid.uuid4().hex[:12]
return f"{safe_name}-{short_id}.{ext}"
def _externalize(
content: str,
*,
@@ -134,7 +111,10 @@ def _externalize(
except OSError:
return None
filename = _build_externalized_filename(tool_name=tool_name, tool_call_id=tool_call_id)
safe_name = _sanitize_tool_name(tool_name)
ext = _EXT_MAP.get(tool_name, "txt")
short_id = uuid.uuid4().hex[:12]
filename = f"{safe_name}-{short_id}.{ext}"
filepath = os.path.join(storage_dir, filename)
if not os.path.abspath(filepath).startswith(os.path.abspath(storage_dir)):
@@ -146,56 +126,8 @@ def _externalize(
except OSError:
return None
return f"{_VIRTUAL_OUTPUTS_BASE}/{storage_subdir}/{filename}"
def _externalize_to_sandbox(
content: str,
*,
tool_name: str,
tool_call_id: str,
storage_subdir: str,
sandbox: Sandbox,
) -> str | None:
"""Write *content* into the sandbox filesystem and return the virtual path.
Used when the sandbox does not use thread-data mounts (e.g. a remote AIO
sandbox): the host-side :func:`_externalize` virtual path would not exist
inside the sandbox, so the model's ``read_file`` tool could not read it
back (issue #3416). Returns the same virtual-path contract on success, or
``None`` to signal the caller to fall back to inline truncation.
"""
if os.path.isabs(storage_subdir) or ".." in storage_subdir:
return None
filename = _build_externalized_filename(tool_name=tool_name, tool_call_id=tool_call_id)
virtual_dir = f"{_VIRTUAL_OUTPUTS_BASE}/{storage_subdir}"
virtual_path = f"{virtual_dir}/{filename}"
try:
# AIO sandbox write_file does NOT create parent directories, so create
# them explicitly before writing. execute_command returns its stdout
# verbatim (including an "Error: ..." string on failure) rather than
# raising, so we cannot rely on exception propagation here.
sandbox.execute_command(f"mkdir -p {shlex.quote(virtual_dir)}")
sandbox.write_file(virtual_path, content)
# Validate the file landed: execute_command may have silently failed
# to create the directory, and write_file backends differ. Refuse to
# hand the model an unreadable read_file path.
check = sandbox.execute_command(f"test -s {shlex.quote(virtual_path)} && echo OK || echo MISSING")
if not isinstance(check, str) or check.strip() != "OK":
logger.warning(
"Sandbox externalize validation failed: path=%s, check=%r",
virtual_path,
check,
)
return None
except Exception:
logger.exception(
"Failed to externalize %s output to sandbox (call_id=%s)",
tool_name,
tool_call_id,
)
return None
return virtual_path
virtual_base = "/mnt/user-data/outputs"
return f"{virtual_base}/{storage_subdir}/{filename}"
# ---------------------------------------------------------------------------
@@ -295,33 +227,6 @@ def _resolve_outputs_path(request: ToolCallRequest) -> str | None:
return outputs_path if isinstance(outputs_path, str) else None
def _resolve_sandbox(request: ToolCallRequest) -> Sandbox | None:
"""Resolve the active sandbox for the current tool call, or ``None``.
Reads the sandbox_id that ``SandboxMiddleware`` (and the sandbox tools
themselves) write into ``runtime.state["sandbox"]``. We intentionally do
NOT call ``provider.acquire`` here: acquiring a sandbox can trigger
blocking remote I/O, and this resolver runs on every tool call. Tools
that do not use a sandbox (``web_search``, MCP, ...) will return ``None``
here, which is fine -- the caller falls back to inline truncation.
"""
runtime = getattr(request, "runtime", None)
state = getattr(runtime, "state", None)
if not isinstance(state, dict):
return None
sandbox_state = state.get("sandbox")
if not isinstance(sandbox_state, dict):
return None
sandbox_id = sandbox_state.get("sandbox_id")
if not sandbox_id:
return None
try:
return get_sandbox_provider().get(sandbox_id)
except Exception:
logger.exception("Failed to look up sandbox %s for tool-output externalization", sandbox_id)
return None
def _budget_content(
content: str,
*,
@@ -329,7 +234,6 @@ def _budget_content(
tool_call_id: str,
outputs_path: str | None,
config: ToolOutputConfig,
sandbox: Sandbox | None = None,
) -> str | None:
"""Apply budget to *content*. Returns ``None`` if no change needed."""
threshold = config.tool_overrides.get(tool_name, config.externalize_min_chars)
@@ -338,50 +242,14 @@ def _budget_content(
if len(content) <= threshold and len(content) <= config.fallback_max_chars:
return None
if threshold > 0 and len(content) > threshold:
virtual_path: str | None = None
# Decide persistence target based on what's available, without touching
# the sandbox provider unless a sandbox was actually resolved for this
# call. This keeps the legacy host-disk path provider-free, so callers
# without a configured sandbox (and CI environments without a
# config.yaml) continue to externalize to the host as before.
if sandbox is not None:
provider = None
try:
provider = get_sandbox_provider()
except Exception:
logger.exception("Failed to get sandbox provider for tool-output externalization; falling back to inline truncation")
if provider is not None and getattr(provider, "uses_thread_data_mounts", False):
# Host-mounted sandbox: host outputs path is bind-mounted into
# the sandbox at the same virtual path, so writing host-side is
# equivalent. Preserve the original behavior to avoid extra
# sandbox round-trips.
if outputs_path:
virtual_path = _externalize(
content,
tool_name=tool_name,
tool_call_id=tool_call_id,
outputs_path=outputs_path,
storage_subdir=config.storage_subdir,
)
else:
virtual_path = _externalize_to_sandbox(
content,
tool_name=tool_name,
tool_call_id=tool_call_id,
storage_subdir=config.storage_subdir,
sandbox=sandbox,
)
elif outputs_path:
# No sandbox in this call (legacy / non-sandbox tools): write to
# host outputs path directly, no provider needed.
virtual_path = _externalize(
content,
tool_name=tool_name,
tool_call_id=tool_call_id,
outputs_path=outputs_path,
storage_subdir=config.storage_subdir,
)
if threshold > 0 and len(content) > threshold and outputs_path:
virtual_path = _externalize(
content,
tool_name=tool_name,
tool_call_id=tool_call_id,
outputs_path=outputs_path,
storage_subdir=config.storage_subdir,
)
if virtual_path is not None:
logger.info(
"Externalized %s output (%d chars) to %s",
@@ -420,12 +288,7 @@ def _budget_content(
# ---------------------------------------------------------------------------
def _patch_tool_message(
msg: ToolMessage,
config: ToolOutputConfig,
outputs_path: str | None,
sandbox: Sandbox | None = None,
) -> ToolMessage:
def _patch_tool_message(msg: ToolMessage, config: ToolOutputConfig, outputs_path: str | None) -> ToolMessage:
"""Apply budget to a single ToolMessage. Returns the original if unchanged."""
tool_name = msg.name or "unknown"
if tool_name in config.exempt_tools:
@@ -441,7 +304,6 @@ def _patch_tool_message(
tool_call_id=msg.tool_call_id or "",
outputs_path=outputs_path,
config=config,
sandbox=sandbox,
)
if replacement is None:
return msg
@@ -493,15 +355,10 @@ def _needs_budget(result: ToolMessage | Command, config: ToolOutputConfig) -> bo
return False
def _patch_result(
result: ToolMessage | Command,
config: ToolOutputConfig,
outputs_path: str | None,
sandbox: Sandbox | None = None,
) -> ToolMessage | Command:
def _patch_result(result: ToolMessage | Command, config: ToolOutputConfig, outputs_path: str | None) -> ToolMessage | Command:
"""Apply budget to a tool call result (ToolMessage or Command)."""
if isinstance(result, ToolMessage):
return _patch_tool_message(result, config, outputs_path, sandbox)
return _patch_tool_message(result, config, outputs_path)
update = getattr(result, "update", None)
if not isinstance(update, dict):
@@ -515,7 +372,7 @@ def _patch_result(
changed = False
for msg in messages:
if isinstance(msg, ToolMessage):
patched = _patch_tool_message(msg, config, outputs_path, sandbox)
patched = _patch_tool_message(msg, config, outputs_path)
if patched is not msg:
changed = True
new_messages.append(patched)
@@ -535,11 +392,6 @@ def _patch_model_messages(messages: list[Any], config: ToolOutputConfig) -> list
ToolMessage exceeds the budget the common case once every result has
already been budgeted at tool-call time, so a long history is not rebuilt
on every model call.
Historical messages do not get a ``sandbox`` argument: any oversized tool
message in history was already budgeted (and possibly externalized) at
tool-call time, so the only thing left for the history path to do is
inline fallback truncation, which needs no sandbox.
"""
if not any(isinstance(msg, ToolMessage) and _tool_message_over_budget(msg, config) for msg in messages):
return None
@@ -590,8 +442,7 @@ class ToolOutputBudgetMiddleware(AgentMiddleware[AgentState]):
if not _needs_budget(result, self._config):
return result
outputs_path = _resolve_outputs_path(request)
sandbox = _resolve_sandbox(request)
return _patch_result(result, self._config, outputs_path, sandbox)
return _patch_result(result, self._config, outputs_path)
@override
async def awrap_tool_call(
@@ -605,12 +456,7 @@ class ToolOutputBudgetMiddleware(AgentMiddleware[AgentState]):
if not _needs_budget(result, self._config):
return result
outputs_path = _resolve_outputs_path(request)
# _resolve_sandbox only touches runtime.state and the provider's
# in-memory sandbox registry, so it is safe to call on the event
# loop. The actual sandbox I/O (mkdir/write/test) happens inside
# _patch_result, which is offloaded to a worker thread below.
sandbox = _resolve_sandbox(request)
return await asyncio.to_thread(_patch_result, result, self._config, outputs_path, sandbox)
return await asyncio.to_thread(_patch_result, result, self._config, outputs_path)
# -- model call hooks (historical message truncation) ------------------
@@ -13,7 +13,6 @@ from langgraph.runtime import Runtime
from deerflow.config.paths import Paths, get_paths
from deerflow.runtime.user_context import get_effective_user_id
from deerflow.utils.file_conversion import extract_outline
from deerflow.utils.messages import ORIGINAL_USER_CONTENT_KEY, message_content_to_text
logger = logging.getLogger(__name__)
@@ -266,8 +265,6 @@ class UploadsMiddleware(AgentMiddleware[UploadsMiddlewareState]):
# Extract original content - handle both string and list formats
original_content = last_message.content
additional_kwargs = dict(last_message.additional_kwargs or {})
additional_kwargs.setdefault(ORIGINAL_USER_CONTENT_KEY, message_content_to_text(original_content))
if isinstance(original_content, str):
# Simple case: string content, just prepend files message
updated_content = f"{files_message}\n\n{original_content}"
@@ -288,7 +285,7 @@ class UploadsMiddleware(AgentMiddleware[UploadsMiddlewareState]):
content=updated_content,
id=last_message.id,
name=last_message.name,
additional_kwargs=additional_kwargs,
additional_kwargs=last_message.additional_kwargs,
)
messages[last_message_index] = updated_message
@@ -179,10 +179,8 @@ class ViewImageMiddleware(AgentMiddleware[ViewImageMiddlewareState]):
# Create the image details message with text and image content
image_content = self._create_image_details_message(state)
# Create a new human message with mixed content (text + images). This is
# internal context for the model only, so hide it from the chat UI and IM
# channels (matches the other middleware-injected context messages).
human_msg = HumanMessage(content=image_content, additional_kwargs={"hide_from_ui": True})
# Create a new human message with mixed content (text + images)
human_msg = HumanMessage(content=image_content)
logger.debug("Injecting image details message with images before LLM call")
+3 -12
View File
@@ -33,7 +33,7 @@ from langchain.agents.middleware import AgentMiddleware
from langchain_core.messages import AIMessage, HumanMessage, SystemMessage, ToolMessage
from langchain_core.runnables import RunnableConfig
from deerflow.agents.lead_agent.agent import build_middlewares
from deerflow.agents.lead_agent.agent import _assemble_deferred, _build_middlewares
from deerflow.agents.lead_agent.prompt import apply_prompt_template
from deerflow.agents.thread_state import ThreadState
from deerflow.config.agents_config import AGENT_NAME_PATTERN
@@ -43,7 +43,6 @@ from deerflow.config.paths import get_paths
from deerflow.models import create_chat_model
from deerflow.runtime.user_context import get_effective_user_id
from deerflow.skills.storage import get_or_new_skill_storage
from deerflow.tools.builtins.tool_search import assemble_deferred_tools
from deerflow.tracing import build_tracing_callbacks, inject_langfuse_metadata
from deerflow.uploads.manager import (
claim_unique_filename,
@@ -239,7 +238,7 @@ class DeerFlowClient:
max_concurrent_subagents = cfg.get("max_concurrent_subagents", 3)
tools = self._get_tools(model_name=model_name, subagent_enabled=subagent_enabled)
final_tools, deferred_setup = assemble_deferred_tools(tools, enabled=self._app_config.tool_search.enabled)
final_tools, deferred_setup = _assemble_deferred(tools, enabled=self._app_config.tool_search.enabled)
kwargs: dict[str, Any] = {
# attach_tracing=False because ``stream()`` injects tracing
# callbacks at the graph invocation root so a single embedded run
@@ -247,15 +246,7 @@ class DeerFlowClient:
# Attaching them again on the model would emit duplicate spans.
"model": create_chat_model(name=model_name, thinking_enabled=thinking_enabled, attach_tracing=False),
"tools": final_tools,
"middleware": build_middlewares(
config,
model_name=model_name,
agent_name=self._agent_name,
available_skills=self._available_skills,
custom_middlewares=self._middlewares,
app_config=self._app_config,
deferred_setup=deferred_setup,
),
"middleware": _build_middlewares(config, model_name=model_name, agent_name=self._agent_name, custom_middlewares=self._middlewares, deferred_setup=deferred_setup),
"system_prompt": apply_prompt_template(
subagent_enabled=subagent_enabled,
max_concurrent_subagents=max_concurrent_subagents,
@@ -11,85 +11,12 @@ from deerflow.config import get_app_config
logger = logging.getLogger(__name__)
DEFAULT_BACKEND = "auto"
DEFAULT_REGION = "wt-wt"
DEFAULT_SAFESEARCH = "moderate"
DEFAULT_WIKIPEDIA_REGION = "us-en"
WIKIPEDIA_BACKENDS = {"auto", "all", "wikipedia"}
WIKIPEDIA_LANGUAGE_ALIASES = {
"jp": "ja",
"kr": "ko",
"tzh": "zh",
"wt": "en",
}
def _normalize_backend(backend: str | list[str] | tuple[str, ...] | None) -> str:
if backend is None:
return DEFAULT_BACKEND
if isinstance(backend, (list, tuple)):
return ",".join(str(part).strip() for part in backend if str(part).strip()) or DEFAULT_BACKEND
return str(backend).strip() or DEFAULT_BACKEND
def _normalize_setting(value: str | None, default: str) -> str:
return str(value).strip() if value else default
def _backend_includes_wikipedia(backend: str | list[str] | tuple[str, ...] | None) -> bool:
backend = _normalize_backend(backend)
return any(part.strip().lower() in WIKIPEDIA_BACKENDS for part in backend.split(","))
def _contains_codepoint(query: str, ranges: tuple[tuple[int, int], ...]) -> bool:
return any(start <= ord(char) <= end for char in query for start, end in ranges)
def _infer_wikipedia_region(query: str) -> str:
"""Pick a valid Wikipedia language region when DDGS' worldwide region is used."""
if _contains_codepoint(query, ((0x3040, 0x30FF), (0x31F0, 0x31FF))):
return "jp-ja"
if _contains_codepoint(query, ((0xAC00, 0xD7AF), (0x1100, 0x11FF), (0x3130, 0x318F))):
return "kr-ko"
if _contains_codepoint(query, ((0x3400, 0x9FFF),)):
return "cn-zh"
if _contains_codepoint(query, ((0x0400, 0x04FF),)):
return "ru-ru"
if _contains_codepoint(query, ((0x0370, 0x03FF),)):
return "gr-el"
if _contains_codepoint(query, ((0x0590, 0x05FF),)):
return "il-he"
if _contains_codepoint(query, ((0x0600, 0x06FF),)):
return "xa-ar"
return DEFAULT_WIKIPEDIA_REGION
def _resolve_ddgs_region(query: str, region: str | None, backend: str | list[str] | tuple[str, ...] | None) -> str:
"""
DDGS' wikipedia engine treats the second part of region as a Wikipedia
subdomain. Its default worldwide region, wt-wt, becomes wt.wikipedia.org.
"""
normalized_region = _normalize_setting(region, DEFAULT_REGION).lower()
if not _backend_includes_wikipedia(backend):
return normalized_region
if normalized_region == DEFAULT_REGION:
return _infer_wikipedia_region(query)
if "-" not in normalized_region:
return DEFAULT_WIKIPEDIA_REGION
country, language = normalized_region.split("-", 1)
return f"{country}-{WIKIPEDIA_LANGUAGE_ALIASES.get(language, language)}"
def _search_text(
query: str,
max_results: int = 5,
region: str | None = DEFAULT_REGION,
safesearch: str | None = DEFAULT_SAFESEARCH,
backend: str | list[str] | tuple[str, ...] | None = DEFAULT_BACKEND,
region: str = "wt-wt",
safesearch: str = "moderate",
) -> list[dict]:
"""
Execute text search using DuckDuckGo.
@@ -99,7 +26,6 @@ def _search_text(
max_results: Maximum number of results
region: Search region
safesearch: Safe search level
backend: DDGS backend(s), e.g. "auto", "duckduckgo", or "duckduckgo,brave"
Returns:
List of search results
@@ -113,15 +39,11 @@ def _search_text(
ddgs = DDGS(timeout=30)
try:
backend = _normalize_backend(backend)
safesearch = _normalize_setting(safesearch, DEFAULT_SAFESEARCH)
effective_region = _resolve_ddgs_region(query, region, backend)
results = ddgs.text(
query,
region=effective_region,
region=region,
safesearch=safesearch,
max_results=max_results,
backend=backend,
)
return list(results) if results else []
@@ -142,23 +64,14 @@ def web_search_tool(
max_results: Maximum number of results to return. Default is 5.
"""
config = get_app_config().get_tool_config("web_search")
region = DEFAULT_REGION
safesearch = DEFAULT_SAFESEARCH
backend = DEFAULT_BACKEND
if config is not None:
# Override tool call defaults from config if set.
# Override max_results from config if set
if config is not None and "max_results" in config.model_extra:
max_results = config.model_extra.get("max_results", max_results)
region = config.model_extra.get("region", region)
safesearch = config.model_extra.get("safesearch", safesearch)
backend = config.model_extra.get("backend", backend)
results = _search_text(
query=query,
max_results=max_results,
region=region,
safesearch=safesearch,
backend=backend,
)
if not results:
@@ -9,7 +9,7 @@ _api_key_warned = False
class JinaClient:
async def crawl(self, url: str, return_format: str = "html", timeout: int = 10, proxy: str | None = None, trust_env: bool = True) -> str:
async def crawl(self, url: str, return_format: str = "html", timeout: int = 10) -> str:
global _api_key_warned
headers = {
"Content-Type": "application/json",
@@ -23,10 +23,7 @@ class JinaClient:
logger.warning("Jina API key is not set. Provide your own key to access a higher rate limit. See https://jina.ai/reader for more information.")
data = {"url": url}
try:
client_kwargs: dict[str, object] = {"trust_env": trust_env}
if proxy:
client_kwargs["proxy"] = proxy
async with httpx.AsyncClient(**client_kwargs) as client:
async with httpx.AsyncClient() as client:
response = await client.post("https://r.jina.ai/", headers=headers, json=data, timeout=timeout)
if response.status_code != 200:
@@ -9,38 +9,6 @@ from deerflow.utils.readability import ReadabilityExtractor
readability_extractor = ReadabilityExtractor()
def _coerce_bool(value: object, default: bool) -> bool:
if isinstance(value, bool):
return value
if isinstance(value, str):
normalized = value.strip().lower()
if normalized in {"1", "true", "yes", "on"}:
return True
if normalized in {"0", "false", "no", "off"}:
return False
return default
def _coerce_timeout(value: object, default: int) -> int:
if isinstance(value, bool):
return default
if isinstance(value, int):
return value
if isinstance(value, str):
try:
return int(value)
except ValueError:
return default
return default
def _coerce_proxy(value: object) -> str | None:
if not isinstance(value, str):
return None
proxy = value.strip()
return proxy or None
@tool("web_fetch", parse_docstring=True)
async def web_fetch_tool(url: str) -> str:
"""Fetch the contents of a web page at a given URL.
@@ -54,14 +22,10 @@ async def web_fetch_tool(url: str) -> str:
"""
jina_client = JinaClient()
timeout = 10
proxy = None
trust_env = True
config = get_app_config().get_tool_config("web_fetch")
if config is not None:
timeout = _coerce_timeout(config.model_extra.get("timeout"), timeout)
proxy = _coerce_proxy(config.model_extra.get("proxy"))
trust_env = _coerce_bool(config.model_extra.get("trust_env"), trust_env)
html_content = await jina_client.crawl(url, return_format="html", timeout=timeout, proxy=proxy, trust_env=trust_env)
if config is not None and "timeout" in config.model_extra:
timeout = config.model_extra.get("timeout")
html_content = await jina_client.crawl(url, return_format="html", timeout=timeout)
if isinstance(html_content, str) and html_content.startswith("Error:"):
return html_content
article = await asyncio.to_thread(readability_extractor.extract_article, html_content)
@@ -7,11 +7,10 @@ from typing import Any, Self
import yaml
from dotenv import load_dotenv
from pydantic import BaseModel, ConfigDict, Field, field_validator
from pydantic import BaseModel, ConfigDict, Field
from deerflow.config.acp_config import ACPAgentConfig, load_acp_config_from_dict
from deerflow.config.agents_api_config import AgentsApiConfig, load_agents_api_config_from_dict
from deerflow.config.channel_connections_config import ChannelConnectionsConfig
from deerflow.config.checkpointer_config import CheckpointerConfig, load_checkpointer_config_from_dict
from deerflow.config.database_config import DatabaseConfig
from deerflow.config.extensions_config import ExtensionsConfig
@@ -117,7 +116,6 @@ class AppConfig(BaseModel):
subagents: SubagentsAppConfig = Field(default_factory=SubagentsAppConfig, description="Subagent runtime configuration")
guardrails: GuardrailsConfig = Field(default_factory=GuardrailsConfig, description="Guardrail middleware configuration")
circuit_breaker: CircuitBreakerConfig = Field(default_factory=CircuitBreakerConfig, description="LLM circuit breaker configuration")
channel_connections: ChannelConnectionsConfig = Field(default_factory=ChannelConnectionsConfig, description="User-facing IM channel connection configuration")
loop_detection: LoopDetectionConfig = Field(default_factory=LoopDetectionConfig, description="Loop detection middleware configuration")
safety_finish_reason: SafetyFinishReasonConfig = Field(default_factory=SafetyFinishReasonConfig, description="Provider safety-filter finish_reason interception middleware configuration")
model_config = ConfigDict(extra="allow")
@@ -150,21 +148,6 @@ class AppConfig(BaseModel):
),
)
@field_validator("models", "tools", "tool_groups", mode="before")
@classmethod
def _coerce_null_list_sections(cls, value: Any) -> Any:
"""Treat a present-but-empty config section as an empty list.
Commenting out every entry under a top-level YAML key e.g. ``models:``
with only comments beneath it, exactly as shipped in
``config.example.yaml`` makes PyYAML parse the value as ``None``.
Without this, the documented ``cp config.example.yaml config.yaml``
first-run flow crashes with an opaque ``Input should be a valid list``
pydantic error. Coercing ``None`` to ``[]`` keeps that flow working and
matches the field's own ``default_factory=list``.
"""
return [] if value is None else value
@classmethod
def resolve_config_path(cls, config_path: str | None = None) -> Path:
"""Resolve the config file path.
@@ -226,11 +209,6 @@ class AppConfig(BaseModel):
config_data["extensions"] = extensions_config.model_dump()
result = cls.model_validate(config_data)
if not result.models:
logger.warning(
"No models are configured in %s. Add at least one entry under `models:` (see the commented examples in config.example.yaml) or run `make setup`.",
resolved_path,
)
acp_agents = cls._validate_acp_agents(config_data.get("acp_agents", {}))
cls._apply_singleton_configs(result, acp_agents)
return result
@@ -1,49 +0,0 @@
"""Configuration for user-owned IM channel connections."""
from __future__ import annotations
from pydantic import BaseModel, Field
class SlackChannelConnectionConfig(BaseModel):
enabled: bool = False
@property
def configured(self) -> bool:
return True
class TelegramChannelConnectionConfig(BaseModel):
enabled: bool = False
bot_username: str = ""
@property
def configured(self) -> bool:
return bool(self.bot_username)
class DiscordChannelConnectionConfig(BaseModel):
enabled: bool = False
@property
def configured(self) -> bool:
return True
class ChannelConnectionsConfig(BaseModel):
"""Top-level config for browser-connectable IM channels."""
enabled: bool = False
slack: SlackChannelConnectionConfig = Field(default_factory=SlackChannelConnectionConfig)
telegram: TelegramChannelConnectionConfig = Field(default_factory=TelegramChannelConnectionConfig)
discord: DiscordChannelConnectionConfig = Field(default_factory=DiscordChannelConnectionConfig)
def provider_status(self, provider: str) -> dict[str, bool]:
config = getattr(self, provider, None)
if config is None:
return {"enabled": False, "configured": False}
enabled = bool(config.enabled)
return {
"enabled": enabled,
"configured": enabled and bool(config.configured),
}
@@ -41,20 +41,6 @@ def set_checkpointer_config(config: CheckpointerConfig | None) -> None:
_checkpointer_config = config
def ensure_config_loaded() -> None:
"""Lazily load app config when checkpointer config has not been initialized."""
from deerflow.config.app_config import _app_config, get_app_config
config = get_checkpointer_config()
if config is not None or _app_config is not None:
return
try:
get_app_config()
except FileNotFoundError:
pass
def load_checkpointer_config_from_dict(config_dict: dict | None) -> None:
"""Load checkpointer configuration from a dictionary."""
global _checkpointer_config
@@ -47,7 +47,7 @@ def make_safe_user_id(raw: str) -> str:
sanitized = _UNSAFE_USER_ID_CHAR_RE.sub("-", raw)
if sanitized == raw:
return raw
digest = hashlib.sha256(raw.encode("utf-8")).hexdigest()[:_SAFE_USER_ID_DIGEST_HEX_LEN]
digest = hashlib.sha1(raw.encode("utf-8")).hexdigest()[:_SAFE_USER_ID_DIGEST_HEX_LEN]
return f"{sanitized}-{digest}"
@@ -4,20 +4,7 @@ from pydantic import BaseModel, ConfigDict, Field
class VolumeMountConfig(BaseModel):
"""Configuration for a volume mount."""
host_path: str = Field(
...,
description=(
"Source path for the mount. Resolution depends on the active provider: "
"``LocalSandboxProvider`` checks this path from the gateway process — in "
"``make dev`` that is the host machine, but in Docker deployments "
"(``make up`` / docker-compose) it is the path *inside* the "
"``deer-flow-gateway`` container, so the host directory must also be "
"bind-mounted into the gateway service for the mount to take effect. "
"``AioSandboxProvider`` (DooD) passes this value straight to ``docker -v`` "
"for the sandbox container, where it is resolved by the host Docker daemon "
"from the host machine's perspective."
),
)
host_path: str = Field(..., description="Path on the host machine")
container_path: str = Field(..., description="Path inside the container")
read_only: bool = Field(default=False, description="Whether the mount is read-only")
@@ -114,27 +114,8 @@ class PatchedChatMiniMax(ChatOpenAI):
}
else:
payload["extra_body"] = {"reasoning_split": True}
self._strip_user_message_names(payload)
return payload
@staticmethod
def _strip_user_message_names(payload: dict) -> None:
"""Drop the per-message ``name`` field from user-role messages.
DeerFlow middlewares tag user messages with internal provenance names
(``user-input``, ``summary``, ``loop_warning``, ...). ``langchain_openai``
serializes those into the OpenAI-compatible request, but MiniMax requires
every user-role ``name`` to be identical and otherwise rejects the request
with ``invalid params, user name must be consistent (2013)``. MiniMax does
not use the per-message author name, so strip it.
"""
messages = payload.get("messages")
if not isinstance(messages, list):
return
for message in messages:
if isinstance(message, dict) and message.get("role") == "user":
message.pop("name", None)
def _convert_chunk_to_generation_chunk(
self,
chunk: dict,
@@ -1,175 +0,0 @@
"""Patched ChatOpenAI adapter for StepFun reasoning models.
StepFun returns ``reasoning`` (or ``reasoning_content`` with deepseek-style) in
both streaming deltas and non-streaming responses. Standard ``ChatOpenAI``
ignores these non-standard fields, so reasoning content is silently dropped.
This adapter captures reasoning from all response paths and replays it on
historical assistant messages for multi-turn tool-call conversations.
"""
from __future__ import annotations
from collections.abc import Mapping
from typing import Any
from langchain_core.language_models import LanguageModelInput
from langchain_core.messages import AIMessage, AIMessageChunk
from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
from langchain_openai import ChatOpenAI
from deerflow.models.assistant_payload_replay import (
restore_assistant_payloads,
restore_reasoning_content,
)
_MISSING = object()
def _extract_reasoning(value: Any) -> str | object:
"""Return reasoning content from a dict/Pydantic object.
StepFun may return reasoning via ``reasoning`` (default) or
``reasoning_content`` (deepseek-style). Check both fields.
"""
if isinstance(value, Mapping):
# Check reasoning_content first (deepseek-style), then reasoning (default)
for field in ("reasoning_content", "reasoning"):
if field in value and value[field] is not None:
return value[field]
return _MISSING
# Pydantic / SDK object attributes
for field in ("reasoning_content", "reasoning"):
attr = getattr(value, field, _MISSING)
if attr is not _MISSING and attr is not None:
return attr
# Some SDK versions store extra fields in model_extra
model_extra = getattr(value, "model_extra", None)
if isinstance(model_extra, Mapping):
for field in ("reasoning_content", "reasoning"):
if field in model_extra and model_extra[field] is not None:
return model_extra[field]
return _MISSING
def _with_reasoning_content(message: AIMessage | AIMessageChunk, reasoning: str) -> AIMessage | AIMessageChunk:
"""Return a copy of *message* with reasoning_content stored in additional_kwargs."""
additional_kwargs = dict(message.additional_kwargs)
if additional_kwargs.get("reasoning_content") != reasoning:
additional_kwargs["reasoning_content"] = reasoning
return message.model_copy(update={"additional_kwargs": additional_kwargs})
def _get_typed_choice_message(response: Any, index: int) -> Any:
"""Extract the SDK-typed choice message at *index*, if available."""
choices = getattr(response, "choices", None)
if choices is None:
return None
try:
return choices[index].message
except (AttributeError, IndexError, TypeError):
return None
class PatchedChatStepFun(ChatOpenAI):
"""ChatOpenAI with full reasoning support for StepFun models.
Captures ``reasoning`` / ``reasoning_content`` from both streaming and
non-streaming responses and replays it on historical assistant messages in
multi-turn tool-call conversations.
"""
@classmethod
def is_lc_serializable(cls) -> bool:
return True
@property
def lc_secrets(self) -> dict[str, str]:
return {"api_key": "STEPFUN_API_KEY", "openai_api_key": "STEPFUN_API_KEY"}
# --- Request payload replay ---
def _get_request_payload(
self,
input_: LanguageModelInput,
*,
stop: list[str] | None = None,
**kwargs: Any,
) -> dict:
"""Restore ``reasoning_content`` on historical assistant messages."""
original_messages = self._convert_input(input_).to_messages()
payload = super()._get_request_payload(input_, stop=stop, **kwargs)
restore_assistant_payloads(
payload.get("messages", []),
original_messages,
restore_reasoning_content,
)
return payload
# --- Streaming reasoning capture ---
def _convert_chunk_to_generation_chunk(
self,
chunk: dict,
default_chunk_class: type,
base_generation_info: dict | None,
) -> ChatGenerationChunk | None:
"""Capture ``reasoning`` / ``reasoning_content`` from streaming deltas."""
generation_chunk = super()._convert_chunk_to_generation_chunk(
chunk,
default_chunk_class,
base_generation_info,
)
if generation_chunk is None:
return None
choices = chunk.get("choices", [])
if choices:
delta = choices[0].get("delta") or {}
reasoning = _extract_reasoning(delta)
if reasoning is not _MISSING and isinstance(generation_chunk.message, AIMessageChunk):
generation_chunk = ChatGenerationChunk(
message=_with_reasoning_content(generation_chunk.message, reasoning),
generation_info=generation_chunk.generation_info,
)
return generation_chunk
# --- Non-streaming reasoning capture ---
def _create_chat_result(
self,
response: dict | Any,
generation_info: dict | None = None,
) -> ChatResult:
"""Extract ``reasoning`` / ``reasoning_content`` from non-streaming responses."""
result = super()._create_chat_result(response, generation_info)
response_dict = response if isinstance(response, dict) else response.model_dump()
choices = response_dict.get("choices", [])
patched_generations: list[ChatGeneration] | None = None
for index, generation in enumerate(result.generations):
choice = choices[index] if index < len(choices) else {}
choice_message = choice.get("message", {}) if isinstance(choice, Mapping) else {}
reasoning = _extract_reasoning(choice_message)
if reasoning is _MISSING and not isinstance(response, dict):
reasoning = _extract_reasoning(_get_typed_choice_message(response, index))
message = generation.message
if reasoning is not _MISSING and isinstance(message, AIMessage):
if patched_generations is None:
patched_generations = list(result.generations)
patched_generations[index] = ChatGeneration(
message=_with_reasoning_content(message, reasoning),
generation_info=generation.generation_info,
)
return ChatResult(
generations=patched_generations or result.generations,
llm_output=result.llm_output,
)
@@ -1,21 +0,0 @@
"""User-owned IM channel connection persistence."""
from deerflow.persistence.channel_connections.model import (
ChannelConnectionRow,
ChannelConversationRow,
ChannelCredentialRow,
ChannelOAuthStateRow,
)
from deerflow.persistence.channel_connections.sql import (
ChannelConnectionRepository,
ChannelCredentialCipher,
)
__all__ = [
"ChannelConnectionRepository",
"ChannelConnectionRow",
"ChannelConversationRow",
"ChannelCredentialCipher",
"ChannelCredentialRow",
"ChannelOAuthStateRow",
]
@@ -1,111 +0,0 @@
"""ORM models for user-owned IM channel connections."""
from __future__ import annotations
from datetime import UTC, datetime
from sqlalchemy import JSON, DateTime, ForeignKey, Index, Integer, String, Text, UniqueConstraint
from sqlalchemy.orm import Mapped, mapped_column
from deerflow.persistence.base import Base
def _utc_now() -> datetime:
return datetime.now(UTC)
class ChannelConnectionRow(Base):
__tablename__ = "channel_connections"
id: Mapped[str] = mapped_column(String(64), primary_key=True)
owner_user_id: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
provider: Mapped[str] = mapped_column(String(32), nullable=False, index=True)
status: Mapped[str] = mapped_column(String(32), nullable=False, default="connected")
external_account_id: Mapped[str] = mapped_column(String(128), nullable=False, default="")
external_account_name: Mapped[str | None] = mapped_column(String(256), nullable=True)
workspace_id: Mapped[str] = mapped_column(String(128), nullable=False, default="")
workspace_name: Mapped[str | None] = mapped_column(String(256), nullable=True)
bot_user_id: Mapped[str | None] = mapped_column(String(128), nullable=True)
scopes_json: Mapped[list] = mapped_column(JSON, default=list)
capabilities_json: Mapped[dict] = mapped_column(JSON, default=dict)
metadata_json: Mapped[dict] = mapped_column(JSON, default=dict)
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False, default=_utc_now)
updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False, default=_utc_now, onupdate=_utc_now)
last_seen_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
last_error_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
__table_args__ = (
UniqueConstraint(
"owner_user_id",
"provider",
"external_account_id",
"workspace_id",
name="uq_channel_connection_owner_provider_identity",
),
Index("idx_channel_connections_event_lookup", "provider", "workspace_id", "bot_user_id"),
)
class ChannelCredentialRow(Base):
__tablename__ = "channel_credentials"
connection_id: Mapped[str] = mapped_column(
String(64),
ForeignKey("channel_connections.id", ondelete="CASCADE"),
primary_key=True,
)
encrypted_access_token: Mapped[str | None] = mapped_column(Text, nullable=True)
encrypted_refresh_token: Mapped[str | None] = mapped_column(Text, nullable=True)
token_type: Mapped[str | None] = mapped_column(String(32), nullable=True)
expires_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
refresh_expires_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
encrypted_extra_json: Mapped[str | None] = mapped_column(Text, nullable=True)
version: Mapped[int] = mapped_column(Integer, nullable=False, default=1)
updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False, default=_utc_now, onupdate=_utc_now)
class ChannelOAuthStateRow(Base):
__tablename__ = "channel_oauth_states"
state_hash: Mapped[str] = mapped_column(String(128), primary_key=True)
owner_user_id: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
provider: Mapped[str] = mapped_column(String(32), nullable=False, index=True)
code_verifier_encrypted: Mapped[str | None] = mapped_column(Text, nullable=True)
nonce_hash: Mapped[str | None] = mapped_column(String(128), nullable=True)
redirect_after: Mapped[str | None] = mapped_column(Text, nullable=True)
requested_scopes_json: Mapped[list] = mapped_column(JSON, default=list)
metadata_json: Mapped[dict] = mapped_column(JSON, default=dict)
expires_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False)
consumed_at: Mapped[datetime | None] = mapped_column(DateTime(timezone=True), nullable=True)
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False, default=_utc_now)
class ChannelConversationRow(Base):
__tablename__ = "channel_conversations"
id: Mapped[str] = mapped_column(String(64), primary_key=True)
connection_id: Mapped[str] = mapped_column(
String(64),
ForeignKey("channel_connections.id", ondelete="CASCADE"),
nullable=False,
index=True,
)
owner_user_id: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
provider: Mapped[str] = mapped_column(String(32), nullable=False, index=True)
external_conversation_id: Mapped[str] = mapped_column(String(128), nullable=False)
external_topic_id: Mapped[str] = mapped_column(String(128), nullable=False, default="")
thread_id: Mapped[str] = mapped_column(String(64), nullable=False, index=True)
created_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False, default=_utc_now)
updated_at: Mapped[datetime] = mapped_column(DateTime(timezone=True), nullable=False, default=_utc_now, onupdate=_utc_now)
__table_args__ = (
UniqueConstraint(
"connection_id",
"external_conversation_id",
"external_topic_id",
name="uq_channel_conversation_connection_external",
),
)
@@ -1,346 +0,0 @@
"""SQL repository for user-owned IM channel connections."""
from __future__ import annotations
import base64
import hashlib
import json
import uuid
from datetime import UTC, datetime
from typing import Any
from cryptography.fernet import Fernet
from sqlalchemy import select
from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker
from deerflow.persistence.channel_connections.model import (
ChannelConnectionRow,
ChannelConversationRow,
ChannelCredentialRow,
ChannelOAuthStateRow,
)
from deerflow.utils.time import coerce_iso
class ChannelCredentialCipher:
"""Encrypts provider credentials before they are persisted."""
def __init__(self, fernet: Fernet) -> None:
self._fernet = fernet
@classmethod
def from_key(cls, key: str) -> ChannelCredentialCipher:
digest = hashlib.sha256(key.encode("utf-8")).digest()
return cls(Fernet(base64.urlsafe_b64encode(digest)))
def encrypt_text(self, value: str | None) -> str | None:
if value is None:
return None
return "fernet:v1:" + self._fernet.encrypt(value.encode("utf-8")).decode("ascii")
def decrypt_text(self, value: str | None) -> str | None:
if value is None:
return None
token = value.removeprefix("fernet:v1:")
return self._fernet.decrypt(token.encode("ascii")).decode("utf-8")
class ChannelConnectionRepository:
"""Persistence facade for channel connections, credentials, and conversations."""
def __init__(
self,
session_factory: async_sessionmaker[AsyncSession],
*,
cipher: ChannelCredentialCipher | None = None,
) -> None:
self.session_factory = session_factory
self._cipher = cipher
async def close(self) -> None:
from deerflow.persistence.engine import close_engine
await close_engine()
@staticmethod
def _new_id() -> str:
return uuid.uuid4().hex
@staticmethod
def _normalize_optional_identity(value: str | None) -> str:
return value or ""
@staticmethod
def _coerce_datetime(value: datetime | None) -> datetime | None:
if value is None or value.tzinfo is not None:
return value
return value.replace(tzinfo=UTC)
def _encrypt_optional_secret(self, value: str | None) -> str | None:
if value is None:
return None
if self._cipher is None:
raise RuntimeError("channel connection encryption key is required")
return self._cipher.encrypt_text(value)
@staticmethod
def _connection_to_dict(row: ChannelConnectionRow) -> dict[str, Any]:
data = row.to_dict()
data["external_account_id"] = data["external_account_id"] or None
data["workspace_id"] = data["workspace_id"] or None
data["scopes"] = data.pop("scopes_json") or []
data["capabilities"] = data.pop("capabilities_json") or {}
data["metadata"] = data.pop("metadata_json") or {}
for key in ("created_at", "updated_at", "last_seen_at", "last_error_at"):
value = data.get(key)
if isinstance(value, datetime):
data[key] = coerce_iso(value)
return data
async def upsert_connection(
self,
*,
owner_user_id: str,
provider: str,
external_account_id: str | None = None,
external_account_name: str | None = None,
workspace_id: str | None = None,
workspace_name: str | None = None,
bot_user_id: str | None = None,
scopes: list[str] | None = None,
capabilities: dict[str, Any] | None = None,
metadata: dict[str, Any] | None = None,
status: str = "connected",
) -> dict[str, Any]:
external_account_id_value = self._normalize_optional_identity(external_account_id)
workspace_id_value = self._normalize_optional_identity(workspace_id)
async with self.session_factory() as session:
stmt = select(ChannelConnectionRow).where(
ChannelConnectionRow.owner_user_id == owner_user_id,
ChannelConnectionRow.provider == provider,
ChannelConnectionRow.external_account_id == external_account_id_value,
ChannelConnectionRow.workspace_id == workspace_id_value,
)
row = (await session.execute(stmt)).scalar_one_or_none()
if row is None:
row = ChannelConnectionRow(
id=self._new_id(),
owner_user_id=owner_user_id,
provider=provider,
external_account_id=external_account_id_value,
workspace_id=workspace_id_value,
)
session.add(row)
row.status = status
row.external_account_name = external_account_name
row.workspace_name = workspace_name
row.bot_user_id = bot_user_id
row.scopes_json = list(scopes or [])
row.capabilities_json = dict(capabilities or {})
row.metadata_json = dict(metadata or {})
await session.commit()
await session.refresh(row)
return self._connection_to_dict(row)
async def list_connections(self, owner_user_id: str) -> list[dict[str, Any]]:
async with self.session_factory() as session:
result = await session.execute(select(ChannelConnectionRow).where(ChannelConnectionRow.owner_user_id == owner_user_id).order_by(ChannelConnectionRow.updated_at.desc(), ChannelConnectionRow.id.desc()))
return [self._connection_to_dict(row) for row in result.scalars()]
async def disconnect_connection(self, *, connection_id: str, owner_user_id: str) -> bool:
async with self.session_factory() as session:
row = await session.get(ChannelConnectionRow, connection_id)
if row is None or row.owner_user_id != owner_user_id:
return False
row.status = "revoked"
credential = await session.get(ChannelCredentialRow, connection_id)
if credential is not None:
await session.delete(credential)
await session.commit()
return True
async def store_credentials(
self,
connection_id: str,
*,
access_token: str | None,
refresh_token: str | None = None,
token_type: str | None = None,
expires_at: datetime | None = None,
refresh_expires_at: datetime | None = None,
extra: dict[str, Any] | None = None,
) -> None:
if self._cipher is None:
raise RuntimeError("channel connection encryption key is required")
async with self.session_factory() as session:
row = await session.get(ChannelCredentialRow, connection_id)
if row is None:
row = ChannelCredentialRow(connection_id=connection_id)
session.add(row)
row.encrypted_access_token = self._cipher.encrypt_text(access_token)
row.encrypted_refresh_token = self._cipher.encrypt_text(refresh_token)
row.token_type = token_type
row.expires_at = expires_at
row.refresh_expires_at = refresh_expires_at
row.encrypted_extra_json = self._cipher.encrypt_text(json.dumps(extra or {}, ensure_ascii=False))
row.version = (row.version or 0) + 1
await session.commit()
async def get_credentials(self, connection_id: str) -> dict[str, Any] | None:
if self._cipher is None:
return None
async with self.session_factory() as session:
row = await session.get(ChannelCredentialRow, connection_id)
if row is None:
return None
extra_raw = self._cipher.decrypt_text(row.encrypted_extra_json)
return {
"connection_id": row.connection_id,
"access_token": self._cipher.decrypt_text(row.encrypted_access_token),
"refresh_token": self._cipher.decrypt_text(row.encrypted_refresh_token),
"token_type": row.token_type,
"expires_at": self._coerce_datetime(row.expires_at),
"refresh_expires_at": self._coerce_datetime(row.refresh_expires_at),
"extra": json.loads(extra_raw) if extra_raw else {},
}
@staticmethod
def hash_state(state: str) -> str:
return hashlib.sha256(state.encode("utf-8")).hexdigest()
async def create_oauth_state(
self,
*,
owner_user_id: str,
provider: str,
state: str,
expires_at: datetime,
code_verifier: str | None = None,
nonce_hash: str | None = None,
redirect_after: str | None = None,
requested_scopes: list[str] | None = None,
metadata: dict[str, Any] | None = None,
) -> None:
row = ChannelOAuthStateRow(
state_hash=self.hash_state(state),
owner_user_id=owner_user_id,
provider=provider,
code_verifier_encrypted=self._encrypt_optional_secret(code_verifier),
nonce_hash=nonce_hash,
redirect_after=redirect_after,
requested_scopes_json=list(requested_scopes or []),
metadata_json=dict(metadata or {}),
expires_at=expires_at,
)
async with self.session_factory() as session:
session.add(row)
await session.commit()
async def count_oauth_states(self, *, owner_user_id: str, provider: str) -> int:
async with self.session_factory() as session:
result = await session.execute(
select(ChannelOAuthStateRow).where(
ChannelOAuthStateRow.owner_user_id == owner_user_id,
ChannelOAuthStateRow.provider == provider,
)
)
return len(list(result.scalars()))
async def consume_oauth_state(
self,
*,
provider: str,
state: str,
now: datetime | None = None,
) -> dict[str, Any] | None:
current_time = now or datetime.now(UTC)
async with self.session_factory() as session:
row = await session.get(ChannelOAuthStateRow, self.hash_state(state))
if row is None or row.provider != provider or row.consumed_at is not None:
return None
expires_at = self._coerce_datetime(row.expires_at)
if expires_at is not None and expires_at < current_time:
return None
row.consumed_at = current_time
await session.commit()
return {
"owner_user_id": row.owner_user_id,
"provider": row.provider,
"requested_scopes": row.requested_scopes_json or [],
"metadata": row.metadata_json or {},
"redirect_after": row.redirect_after,
}
async def find_connection_by_external_identity(
self,
*,
provider: str,
external_account_id: str,
workspace_id: str | None = None,
) -> dict[str, Any] | None:
async with self.session_factory() as session:
result = await session.execute(
select(ChannelConnectionRow)
.where(
ChannelConnectionRow.provider == provider,
ChannelConnectionRow.external_account_id == self._normalize_optional_identity(external_account_id),
ChannelConnectionRow.workspace_id == self._normalize_optional_identity(workspace_id),
ChannelConnectionRow.status == "connected",
)
.order_by(ChannelConnectionRow.updated_at.desc(), ChannelConnectionRow.id.desc())
.limit(1)
)
row = result.scalar_one_or_none()
return self._connection_to_dict(row) if row is not None else None
async def set_thread_id(
self,
*,
connection_id: str,
owner_user_id: str,
provider: str,
external_conversation_id: str,
thread_id: str,
external_topic_id: str | None = None,
) -> None:
topic_id = external_topic_id or ""
async with self.session_factory() as session:
stmt = select(ChannelConversationRow).where(
ChannelConversationRow.connection_id == connection_id,
ChannelConversationRow.external_conversation_id == external_conversation_id,
ChannelConversationRow.external_topic_id == topic_id,
)
row = (await session.execute(stmt)).scalar_one_or_none()
if row is None:
row = ChannelConversationRow(
id=self._new_id(),
connection_id=connection_id,
owner_user_id=owner_user_id,
provider=provider,
external_conversation_id=external_conversation_id,
external_topic_id=topic_id,
thread_id=thread_id,
)
session.add(row)
else:
row.thread_id = thread_id
row.owner_user_id = owner_user_id
row.provider = provider
await session.commit()
async def get_thread_id(
self,
connection_id: str,
external_conversation_id: str,
external_topic_id: str | None = None,
) -> str | None:
async with self.session_factory() as session:
stmt = select(ChannelConversationRow.thread_id).where(
ChannelConversationRow.connection_id == connection_id,
ChannelConversationRow.external_conversation_id == external_conversation_id,
ChannelConversationRow.external_topic_id == (external_topic_id or ""),
)
return (await session.execute(stmt)).scalar_one_or_none()
@@ -14,26 +14,10 @@ its storage implementation lives in ``deerflow.runtime.events.store.db`` and
there is no matching entity directory.
"""
from deerflow.persistence.channel_connections.model import (
ChannelConnectionRow,
ChannelConversationRow,
ChannelCredentialRow,
ChannelOAuthStateRow,
)
from deerflow.persistence.feedback.model import FeedbackRow
from deerflow.persistence.models.run_event import RunEventRow
from deerflow.persistence.run.model import RunRow
from deerflow.persistence.thread_meta.model import ThreadMetaRow
from deerflow.persistence.user.model import UserRow
__all__ = [
"ChannelConnectionRow",
"ChannelConversationRow",
"ChannelCredentialRow",
"ChannelOAuthStateRow",
"FeedbackRow",
"RunEventRow",
"RunRow",
"ThreadMetaRow",
"UserRow",
]
__all__ = ["FeedbackRow", "RunEventRow", "RunRow", "ThreadMetaRow", "UserRow"]
@@ -21,13 +21,12 @@ from __future__ import annotations
import contextlib
import logging
import threading
from collections.abc import Iterator
from langgraph.types import Checkpointer
from deerflow.config.app_config import get_app_config
from deerflow.config.checkpointer_config import CheckpointerConfig, ensure_config_loaded
from deerflow.config.checkpointer_config import CheckpointerConfig
from deerflow.runtime.store._sqlite_utils import ensure_sqlite_parent_dir, resolve_sqlite_conn_str
logger = logging.getLogger(__name__)
@@ -101,7 +100,6 @@ def _sync_checkpointer_cm(config: CheckpointerConfig) -> Iterator[Checkpointer]:
_checkpointer: Checkpointer | None = None
_checkpointer_ctx = None # open context manager keeping the connection alive
_checkpointer_lock = threading.Lock()
def get_checkpointer() -> Checkpointer:
@@ -118,29 +116,34 @@ def get_checkpointer() -> Checkpointer:
if _checkpointer is not None:
return _checkpointer
# Config loading can reset both persistence singletons. Keep it outside
# this provider lock to avoid cross-provider lock-order inversion.
ensure_config_loaded()
# Ensure app config is loaded before checking checkpointer config
# This prevents returning InMemorySaver when config.yaml actually has a checkpointer section
# but hasn't been loaded yet
from deerflow.config.app_config import _app_config
from deerflow.config.checkpointer_config import get_checkpointer_config
with _checkpointer_lock:
if _checkpointer is not None:
return _checkpointer
from deerflow.config.checkpointer_config import get_checkpointer_config
config = get_checkpointer_config()
if config is None and _app_config is None:
# Only load app config lazily when neither the app config nor an explicit
# checkpointer config has been initialized yet. This keeps tests that
# intentionally set the global checkpointer config isolated from any
# ambient config.yaml on disk.
try:
get_app_config()
except FileNotFoundError:
# In test environments without config.yaml, this is expected.
pass
config = get_checkpointer_config()
if config is None:
from langgraph.checkpoint.memory import InMemorySaver
if config is None:
from langgraph.checkpoint.memory import InMemorySaver
logger.info("Checkpointer: using InMemorySaver (in-process, not persistent)")
_checkpointer = InMemorySaver()
return _checkpointer
logger.info("Checkpointer: using InMemorySaver (in-process, not persistent)")
_checkpointer = InMemorySaver()
return _checkpointer
checkpointer_ctx = _sync_checkpointer_cm(config)
checkpointer = checkpointer_ctx.__enter__()
_checkpointer_ctx = checkpointer_ctx
_checkpointer = checkpointer
_checkpointer_ctx = _sync_checkpointer_cm(config)
_checkpointer = _checkpointer_ctx.__enter__()
return _checkpointer
@@ -152,14 +155,13 @@ def reset_checkpointer() -> None:
Useful in tests or after a configuration change.
"""
global _checkpointer, _checkpointer_ctx
with _checkpointer_lock:
if _checkpointer_ctx is not None:
try:
_checkpointer_ctx.__exit__(None, None, None)
except Exception:
logger.warning("Error during checkpointer cleanup", exc_info=True)
_checkpointer_ctx = None
_checkpointer = None
if _checkpointer_ctx is not None:
try:
_checkpointer_ctx.__exit__(None, None, None)
except Exception:
logger.warning("Error during checkpointer cleanup", exc_info=True)
_checkpointer_ctx = None
_checkpointer = None
# ---------------------------------------------------------------------------
@@ -164,18 +164,7 @@ class RunJournal(BaseCallbackHandler):
metadata={"caller": caller, **(metadata or {})},
)
def on_chain_end(
self,
outputs: Any,
*,
run_id: UUID,
parent_run_id: UUID | None = None,
**kwargs: Any,
) -> None:
# Nested chain ends fire for internal graph nodes; only the root chain
# represents the user-visible run lifecycle.
if parent_run_id is not None:
return
def on_chain_end(self, outputs: Any, *, run_id: UUID, **kwargs: Any) -> None:
self._put(event_type="run.end", category="outputs", content=outputs, metadata={"status": "success"})
self._flush_sync()
@@ -22,13 +22,11 @@ from __future__ import annotations
import contextlib
import logging
import threading
from collections.abc import Iterator
from langgraph.store.base import BaseStore
from deerflow.config.app_config import get_app_config
from deerflow.config.checkpointer_config import ensure_config_loaded
from deerflow.runtime.store._sqlite_utils import ensure_sqlite_parent_dir, resolve_sqlite_conn_str
logger = logging.getLogger(__name__)
@@ -102,7 +100,6 @@ def _sync_store_cm(config) -> Iterator[BaseStore]:
_store: BaseStore | None = None
_store_ctx = None # open context manager keeping the connection alive
_store_lock = threading.Lock()
def get_store() -> BaseStore:
@@ -120,29 +117,29 @@ def get_store() -> BaseStore:
if _store is not None:
return _store
# Config loading can reset both persistence singletons. Keep it outside
# this provider lock to avoid cross-provider lock-order inversion.
ensure_config_loaded()
# Lazily load app config, mirroring the checkpointer singleton pattern so
# that tests that set the global checkpointer config explicitly remain isolated.
from deerflow.config.app_config import _app_config
from deerflow.config.checkpointer_config import get_checkpointer_config
with _store_lock:
if _store is not None:
return _store
from deerflow.config.checkpointer_config import get_checkpointer_config
config = get_checkpointer_config()
if config is None and _app_config is None:
try:
get_app_config()
except FileNotFoundError:
pass
config = get_checkpointer_config()
if config is None:
from langgraph.store.memory import InMemoryStore
if config is None:
from langgraph.store.memory import InMemoryStore
logger.warning("No 'checkpointer' section in config.yaml — using InMemoryStore for the store. Thread list will be lost on server restart. Configure a sqlite or postgres backend for persistence.")
_store = InMemoryStore()
return _store
logger.warning("No 'checkpointer' section in config.yaml — using InMemoryStore for the store. Thread list will be lost on server restart. Configure a sqlite or postgres backend for persistence.")
_store = InMemoryStore()
return _store
store_ctx = _sync_store_cm(config)
store = store_ctx.__enter__()
_store_ctx = store_ctx
_store = store
_store_ctx = _sync_store_cm(config)
_store = _store_ctx.__enter__()
return _store
@@ -153,14 +150,13 @@ def reset_store() -> None:
Useful in tests or after a configuration change.
"""
global _store, _store_ctx
with _store_lock:
if _store_ctx is not None:
try:
_store_ctx.__exit__(None, None, None)
except Exception:
logger.warning("Error during store cleanup", exc_info=True)
_store_ctx = None
_store = None
if _store_ctx is not None:
try:
_store_ctx.__exit__(None, None, None)
except Exception:
logger.warning("Error during store cleanup", exc_info=True)
_store_ctx = None
_store = None
# ---------------------------------------------------------------------------
@@ -147,17 +147,7 @@ class LocalSandboxProvider(SandboxProvider):
mount.container_path,
)
continue
# Ensure the host path exists before adding mapping.
#
# ``host_path`` is resolved against the filesystem of the
# process running this provider — for ``make dev`` that is
# the host machine, but for ``make up`` it is the
# ``deer-flow-gateway`` container, so any host path that
# isn't bind-mounted into the gateway image will be missing
# here. Skipping silently makes this a high-cost-to-debug
# silent failure (sandbox skill / tool reads an empty dir
# instead of the configured mount), so escalate to ERROR
# and include actionable guidance. See #3244.
# Ensure the host path exists before adding mapping
if host_path.exists():
mappings.append(
PathMapping(
@@ -167,16 +157,10 @@ class LocalSandboxProvider(SandboxProvider):
)
)
else:
logger.error(
"sandbox.mounts entry %s -> %s ignored: host_path %s does not exist from the "
"perspective of the gateway process. In Docker deployments (make up / docker-compose), "
"this path must also be bind-mounted into the gateway container — add a matching "
"volume entry under services.gateway.volumes in docker/docker-compose.yaml (and use "
"the in-container path here), or run in local mode (make dev) where the gateway sees "
"the host filesystem directly.",
logger.warning(
"Mount host_path does not exist, skipping: %s -> %s",
mount.host_path,
mount.container_path,
mount.host_path,
)
except Exception as e:
# Log but don't fail if config loading fails
@@ -1,65 +0,0 @@
from __future__ import annotations
import re
from dataclasses import dataclass
from deerflow.skills.types import Skill
RESERVED_SLASH_SKILL_NAMES = frozenset({"bootstrap", "help", "memory", "models", "new", "status"})
_SLASH_SKILL_RE = re.compile(r"^/([a-z0-9]+(?:-[a-z0-9]+)*)(?:\s+|$)")
@dataclass(frozen=True, slots=True)
class SlashSkillReference:
"""Parsed slash-skill command with the skill name and remaining task text."""
name: str
remaining_text: str
@dataclass(frozen=True, slots=True)
class ResolvedSlashSkill:
"""Slash-skill activation resolved against enabled runtime-visible skills."""
skill: Skill
remaining_text: str
container_file_path: str
def parse_slash_skill_reference(text: str) -> SlashSkillReference | None:
"""Parse strict `/skill-name task` syntax, ignoring reserved control commands."""
match = _SLASH_SKILL_RE.match(text)
if not match:
return None
name = match.group(1)
if name in RESERVED_SLASH_SKILL_NAMES:
return None
return SlashSkillReference(
name=name,
remaining_text=text[match.end() :].lstrip(),
)
def resolve_slash_skill(
text: str,
skills: list[Skill],
*,
available_skills: set[str] | None = None,
container_base_path: str = "/mnt/skills",
) -> ResolvedSlashSkill | None:
"""Resolve text into an enabled, whitelisted skill activation if possible."""
reference = parse_slash_skill_reference(text)
if reference is None:
return None
if available_skills is not None and reference.name not in available_skills:
return None
skill = next((candidate for candidate in skills if candidate.name == reference.name and candidate.enabled), None)
if skill is None:
return None
return ResolvedSlashSkill(
skill=skill,
remaining_text=reference.remaining_text,
container_file_path=skill.get_container_file_path(container_base_path),
)
@@ -12,7 +12,7 @@ from contextvars import Context, copy_context
from dataclasses import dataclass, field
from datetime import datetime
from enum import Enum
from typing import TYPE_CHECKING, Any
from typing import Any
from langchain.agents import create_agent
from langchain.tools import BaseTool
@@ -28,13 +28,6 @@ from deerflow.skills.types import Skill
from deerflow.subagents.config import SubagentConfig, resolve_subagent_model_name
from deerflow.subagents.token_collector import SubagentTokenCollector
if TYPE_CHECKING:
# Imported lazily at runtime inside _build_initial_state: importing
# tool_search eagerly would run tools/builtins/__init__ -> task_tool ->
# `from deerflow.subagents import SubagentExecutor`, which re-enters this
# still-initializing package. Type-only here keeps the annotation precise.
from deerflow.tools.builtins.tool_search import DeferredToolSetup
logger = logging.getLogger(__name__)
@@ -326,13 +319,8 @@ class SubagentExecutor:
logger.info(f"[trace={self.trace_id}] SubagentExecutor initialized: {config.name} with {len(self.tools)} tools")
def _create_agent(self, tools: list[BaseTool] | None = None, *, deferred_setup: "DeferredToolSetup | None" = None):
"""Create the agent instance.
``deferred_setup`` (assembled in ``_build_initial_state``) carries the
deferred MCP tool names + catalog hash so the subagent gets the same
DeferredToolFilterMiddleware the lead agent has. ``None`` is a no-op.
"""
def _create_agent(self, tools: list[BaseTool] | None = None):
"""Create the agent instance."""
app_config = self.app_config or get_app_config()
if self.model_name is None:
self.model_name = resolve_subagent_model_name(self.config, self.parent_model, app_config=app_config)
@@ -341,7 +329,7 @@ class SubagentExecutor:
from deerflow.agents.middlewares.tool_error_handling_middleware import build_subagent_runtime_middlewares
# Reuse shared middleware composition with lead agent.
middlewares = build_subagent_runtime_middlewares(app_config=app_config, model_name=self.model_name, lazy_init=True, deferred_setup=deferred_setup)
middlewares = build_subagent_runtime_middlewares(app_config=app_config, model_name=self.model_name, lazy_init=True)
# system_prompt is included in initial state messages (see _build_initial_state)
# to avoid multiple SystemMessages which some LLM APIs don't support.
@@ -415,35 +403,19 @@ class SubagentExecutor:
return messages
async def _build_initial_state(self, task: str) -> tuple[dict[str, Any], list[BaseTool], "DeferredToolSetup"]:
async def _build_initial_state(self, task: str) -> tuple[dict[str, Any], list[BaseTool]]:
"""Build the initial state for agent execution.
Args:
task: The task description.
Returns:
``(state, final_tools, deferred_setup)``. ``final_tools`` is the
policy-filtered tool list with the ``tool_search`` tool appended when
deferral applies; ``deferred_setup`` is consumed by ``_create_agent``
so the agent build and the injected ``<available-deferred-tools>``
section share one catalog/hash.
Initial state dictionary and tools filtered by loaded skill metadata.
"""
# Lazy import: see the TYPE_CHECKING note at the top of this module -
# importing tool_search runs tools/builtins/__init__, which would
# re-enter this package during its own initialization.
from deerflow.tools.builtins.tool_search import assemble_deferred_tools, get_deferred_tools_prompt_section
# Load skills as conversation items (Codex pattern)
skills = await self._load_skills()
filtered_tools = self._apply_skill_allowed_tools(skills)
# Assemble deferred tool_search AFTER policy filtering (fail-closed),
# mirroring the lead path so subagents stop binding full MCP schemas.
# The generated tool_search helper is intentionally not subject to the
# subagent's name-level allow/deny (config.tools / disallowed_tools):
# its catalog is built from the already-filtered list, so it can never
# surface a tool the policy denied. This matches the lead agent.
enabled = (self.app_config or get_app_config()).tool_search.enabled
final_tools, deferred_setup = assemble_deferred_tools(filtered_tools, enabled=enabled)
skill_messages = await self._load_skill_messages(skills)
# Combine system_prompt and skills into a single SystemMessage.
@@ -454,11 +426,6 @@ class SubagentExecutor:
system_parts.append(self.config.system_prompt)
for skill_msg in skill_messages:
system_parts.append(skill_msg.content)
# Name the deferred MCP tools in the prompt; their schemas stay withheld
# until tool_search promotes them. Empty set -> "" -> appends nothing.
deferred_section = get_deferred_tools_prompt_section(deferred_names=deferred_setup.deferred_names)
if deferred_section:
system_parts.append(deferred_section)
messages: list[Any] = []
if system_parts:
@@ -477,7 +444,7 @@ class SubagentExecutor:
if self.thread_data is not None:
state["thread_data"] = self.thread_data
return state, final_tools, deferred_setup
return state, filtered_tools
async def _aexecute(self, task: str, result_holder: SubagentResult | None = None) -> SubagentResult:
"""Execute a task asynchronously.
@@ -508,8 +475,8 @@ class SubagentExecutor:
collector: SubagentTokenCollector | None = None
try:
state, final_tools, deferred_setup = await self._build_initial_state(task)
agent = self._create_agent(final_tools, deferred_setup=deferred_setup)
state, filtered_tools = await self._build_initial_state(task)
agent = self._create_agent(filtered_tools)
# Token collector for subagent LLM calls
collector_caller = f"subagent:{self.config.name}"
@@ -1,102 +0,0 @@
"""Backend↔frontend contract for the structured subagent status.
Bytedance/deer-flow issue #3146: the frontend used to derive the
subtask card state by string-matching the leading text of the
``task`` tool's result. That contract was fragile — any rewording on
the backend silently broke the card lifecycle, and the issue history
of #3107 BUG-007 / #3131 review showed it repeatedly.
This module replaces the text-shaped contract with a small structured
one carried inside ``ToolMessage.additional_kwargs``:
- ``subagent_status``: one of ``SUBAGENT_STATUS_VALUES``.
- ``subagent_error`` (optional): the human-readable error blob the
backend recorded.
The mapping from "task tool result text" to status is the one piece
the backend stamper (``ToolErrorHandlingMiddleware``) and the
frontend fallback parser must agree on. The shared fixture at
``contracts/subagent_status_contract.json`` is the single source of
truth both sides' tests load it and assert behaviour.
"""
from __future__ import annotations
from typing import Literal
SUBAGENT_STATUS_KEY = "subagent_status"
SUBAGENT_ERROR_KEY = "subagent_error"
SubagentStatusValue = Literal[
"completed",
"failed",
"cancelled",
"timed_out",
"polling_timed_out",
]
#: Enumeration of every value ``subagent_status`` may take. Mirrors the
#: ``valid_status_values`` array in the shared fixture; the contract test
#: pins them against each other.
SUBAGENT_STATUS_VALUES: tuple[SubagentStatusValue, ...] = (
"completed",
"failed",
"cancelled",
"timed_out",
"polling_timed_out",
)
# Prefix table — ordered most-specific-first because some prefixes are
# substrings of others ("Task timed out" vs "Task polling timed out", "Task
# failed" vs "Task failed. Error: ..."). The "Task " prefixes come from
# ``task_tool.py``'s 5 normal-return strings; the bare ``Error:`` prefix
# catches both the 3 ``Error:`` pre-execution returns and the wrapper
# produced by ``ToolErrorHandlingMiddleware`` for any task tool exception.
_PREFIX_TO_STATUS: tuple[tuple[str, SubagentStatusValue], ...] = (
("Task Succeeded. Result:", "completed"),
("Task polling timed out", "polling_timed_out"),
("Task timed out", "timed_out"),
("Task cancelled by user", "cancelled"),
("Task failed.", "failed"),
("Error", "failed"),
)
def extract_subagent_status(content: str) -> SubagentStatusValue | None:
"""Infer the structured status for a ``task`` tool result string.
Returns ``None`` when the content does not match any known terminal
prefix. Non-terminal streaming chunks fall into this branch by
design the middleware then leaves ``subagent_status`` unset so
the frontend keeps the card on its in-progress placeholder until
the real terminal frame arrives.
"""
trimmed = content.strip()
for prefix, status in _PREFIX_TO_STATUS:
if trimmed.startswith(prefix):
return status
return None
def make_subagent_additional_kwargs(
status: SubagentStatusValue,
*,
error: str | None = None,
) -> dict[str, str]:
"""Build the ``additional_kwargs`` payload the middleware stamps.
Drops the error field when blank so the JSON wire format never carries
a misleading empty ``subagent_error: ""``.
Raises:
ValueError: when ``status`` is not in :data:`SUBAGENT_STATUS_VALUES`.
We do not accept arbitrary strings: a typo would silently leak
through to the frontend and degrade to the legacy prefix
fallback rather than failing loudly.
"""
if status not in SUBAGENT_STATUS_VALUES:
raise ValueError(f"invalid subagent status {status!r}; expected one of {SUBAGENT_STATUS_VALUES}")
payload: dict[str, str] = {SUBAGENT_STATUS_KEY: status}
if error and error.strip():
payload[SUBAGENT_ERROR_KEY] = error.strip()
return payload
@@ -179,43 +179,3 @@ def build_deferred_tool_setup(filtered_tools: list[BaseTool], *, enabled: bool)
return DeferredToolSetup(None, frozenset(), None)
catalog = DeferredToolCatalog(tuple(deferred))
return DeferredToolSetup(build_tool_search_tool(catalog), catalog.names, catalog.hash)
def assemble_deferred_tools(filtered_tools: list[BaseTool], *, enabled: bool) -> tuple[list[BaseTool], DeferredToolSetup]:
"""Build the final tool list + deferred setup from a POLICY-FILTERED list.
Call AFTER tool-policy filtering so the deferred catalog never exposes a tool
the agent is not allowed to use. Fail-closed: if tool_search is enabled and
MCP tools survived filtering but no deferred set was recovered, raise rather
than silently binding their full schemas to the model.
Shared by every agent-build path (lead, embedded client, subagent) so they
all get the same fail-closed guarantee from one place.
"""
deferred_setup = build_deferred_tool_setup(filtered_tools, enabled=enabled)
if enabled and not deferred_setup.deferred_names and any(is_mcp_tool(t) for t in filtered_tools):
raise RuntimeError("tool_search enabled and MCP tools survived policy filtering, but no deferred set was recovered - refusing to bind MCP schemas (fail-closed).")
final_tools = list(filtered_tools)
if deferred_setup.tool_search_tool:
final_tools.append(deferred_setup.tool_search_tool)
return final_tools, deferred_setup
# Prompt rendering
def get_deferred_tools_prompt_section(*, deferred_names: frozenset[str] = frozenset()) -> str:
"""Generate <available-deferred-tools> from an explicit deferred-name set.
Lists only names so the agent knows what exists and can use tool_search to
load them. Returns empty string when there are no deferred tools. The set is
computed at agent build time (after tool-policy filtering) and passed in.
Lives here, next to the assembly that produces ``deferred_names``, so every
agent-build path (lead, embedded client, subagent) renders the section the
same way without coupling back to ``lead_agent.prompt``.
"""
if not deferred_names:
return ""
names = "\n".join(sorted(deferred_names))
return f"<available-deferred-tools>\n{names}\n</available-deferred-tools>"
@@ -1,31 +0,0 @@
from __future__ import annotations
from collections.abc import Mapping
from typing import Any
ORIGINAL_USER_CONTENT_KEY = "original_user_content"
def message_content_to_text(content: Any) -> str:
"""Extract text from LangChain message content shapes."""
if isinstance(content, str):
return content
if isinstance(content, list):
parts: list[str] = []
for item in content:
if isinstance(item, str):
parts.append(item)
elif isinstance(item, dict):
text = item.get("text")
if isinstance(text, str):
parts.append(text)
return "\n".join(part for part in parts if part)
return str(content)
def get_original_user_content_text(content: Any, additional_kwargs: Mapping[str, Any] | None) -> str:
"""Return pre-middleware user text when available, otherwise content text."""
original_content = (additional_kwargs or {}).get(ORIGINAL_USER_CONTENT_KEY)
if isinstance(original_content, str):
return original_content
return message_content_to_text(content)
-1
View File
@@ -36,7 +36,6 @@ dependencies = [
"sqlalchemy[asyncio]>=2.0,<3.0",
"aiosqlite>=0.19",
"alembic>=1.13",
"cryptography>=43.0.0",
]
[project.optional-dependencies]
@@ -1,45 +0,0 @@
"""Turn a record-through-browser JSONL capture into a replay fixture.
The recording gateway (``record_gateway.py``) appends ``{input_hash, output}``
lines as the frontend drives a real run; the record spec writes a ``.meta.json``
sidecar with ``{scenario, mode, prompt}``. This stitches them into the fixture
the replay provider + tests consume.
"""
from __future__ import annotations
import argparse
import json
from pathlib import Path
def main() -> int:
parser = argparse.ArgumentParser()
parser.add_argument("--jsonl", required=True)
parser.add_argument("--meta", required=True)
parser.add_argument("--out", required=True)
parser.add_argument("--model", default="gpt-5.5")
args = parser.parse_args()
turns = [json.loads(line) for line in Path(args.jsonl).read_text(encoding="utf-8").splitlines() if line.strip()]
meta = json.loads(Path(args.meta).read_text(encoding="utf-8"))
fixture = {
"scenario": meta["scenario"],
"mode": meta["mode"],
"model": args.model,
"prompt": meta["prompt"],
"context": meta.get("context", {}),
"turns": turns,
}
Path(args.out).write_text(json.dumps(fixture, ensure_ascii=False, indent=2), encoding="utf-8")
print(f"wrote {len(turns)} turn(s) -> {args.out}")
for index, turn in enumerate(turns):
data = turn["output"].get("data", {})
tool_calls = [tc.get("name") for tc in (data.get("tool_calls") or [])]
caller = turn.get("caller", "legacy")
print(f" turn {index}: caller={caller} hash={turn['input_hash'][:12]} tool_calls={tool_calls} content={str(data.get('content'))[:50]!r}")
return 0
if __name__ == "__main__":
raise SystemExit(main())
-127
View File
@@ -1,127 +0,0 @@
"""Recording gateway for *record-through-browser* (Plan A).
Runs the gateway with a REAL model and a callback that appends every model
call's ``(input_hash, output)`` to a JSONL file. Because the run is driven by
the real frontend (Playwright), the captured inputs are EXACTLY what the
frontend produces (date system-reminder, suggestions/title calls, ...), so the
resulting fixture replays cleanly against the browser.
Used by ``frontend/playwright.record.config.ts``. Env:
OPENAI_API_KEY / OPENAI_API_BASE - the real upstream (never committed)
DEERFLOW_RECORD_OUT - JSONL path to append captured turns to
RECORD_PORT (default 8012), RECORD_MODEL (default gpt-5.5)
"""
from __future__ import annotations
import json
import os
import sys
import tempfile
from pathlib import Path
_BACKEND = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(_BACKEND))
sys.path.insert(0, str(_BACKEND / "tests"))
def _install_capture(out_path: Path) -> None:
from langchain_core.callbacks import BaseCallbackHandler
from langchain_core.messages import messages_to_dict
from replay_provider import caller_identity, hash_messages, hash_replay_input
import deerflow.models.factory as factory_mod
class Capture(BaseCallbackHandler):
def __init__(self) -> None:
self.inputs: dict[str, tuple[list, str]] = {}
def on_chat_model_start( # noqa: ANN001
self,
serialized,
messages,
*,
run_id=None,
tags=None,
name=None,
**kwargs,
):
self.inputs[str(run_id)] = (
messages[0] if messages else [],
caller_identity(name=name, tags=tags),
)
def on_llm_end(self, response, *, run_id=None, **kwargs): # noqa: ANN001
captured = self.inputs.pop(str(run_id), None)
if captured is None:
return
inp, caller = captured
for batch in response.generations:
for gen in batch:
message = getattr(gen, "message", None)
if message is None:
continue
record = {
"caller": caller,
"conversation_hash": hash_messages(inp),
"input_hash": hash_replay_input(inp, caller=caller),
"output": messages_to_dict([message])[0],
}
with open(out_path, "a", encoding="utf-8") as handle:
handle.write(json.dumps(record, ensure_ascii=False) + "\n")
handle.flush()
cb = Capture()
original = factory_mod.create_chat_model
def wrapped(*args, **kwargs):
model = original(*args, **kwargs)
model.callbacks = (model.callbacks or []) + [cb]
return model
factory_mod.create_chat_model = wrapped
for module in list(sys.modules.values()):
if getattr(module, "create_chat_model", None) is original:
module.create_chat_model = wrapped
def main() -> int:
if not os.environ.get("OPENAI_API_KEY") or not os.environ.get("OPENAI_API_BASE"):
print("ERROR: set OPENAI_API_KEY and OPENAI_API_BASE (an OpenAI-compatible /v1 endpoint)", file=sys.stderr)
return 2
record_out = os.environ.get("DEERFLOW_RECORD_OUT")
if not record_out:
print("ERROR: set DEERFLOW_RECORD_OUT to the JSONL path to append captured turns to", file=sys.stderr)
return 2
port = int(os.environ.get("RECORD_PORT", "8012"))
model = os.environ.get("RECORD_MODEL", "gpt-5.5")
out = Path(record_out)
out.parent.mkdir(parents=True, exist_ok=True)
out.write_text("", encoding="utf-8") # fresh capture per recording run
from _replay_fixture import build_config_yaml, prepare_hermetic_extras, real_model_block
home = Path(tempfile.mkdtemp(prefix="record-gw-"))
cfg = home / "config.yaml"
cfg.write_text(build_config_yaml(model_block=real_model_block(model), home=home), encoding="utf-8")
# Override (not setdefault): the recorder must be hermetic, so an outer
# DEER_FLOW_HOME can't leak in and shift prompt-affecting paths/skills.
os.environ["DEER_FLOW_HOME"] = str(home)
os.environ["DEER_FLOW_CONFIG_PATH"] = str(cfg)
os.environ["DEER_FLOW_EXTENSIONS_CONFIG_PATH"] = str(prepare_hermetic_extras(home))
os.environ.setdefault("AUTH_JWT_SECRET", "record-secret")
os.environ["PYTHONPATH"] = os.pathsep.join(p for p in (str(_BACKEND), str(_BACKEND / "tests"), os.environ.get("PYTHONPATH", "")) if p)
_install_capture(out)
import uvicorn
print(f"[record-gw] model={model} out={out} port={port}", flush=True)
uvicorn.run("app.gateway.app:app", host="127.0.0.1", port=port, log_level="warning")
return 0
if __name__ == "__main__":
raise SystemExit(main())
-73
View File
@@ -1,73 +0,0 @@
"""Start a hermetic *replay* gateway for the full-stack (Layer 2) e2e.
Builds an ephemeral config that points the model at ``ReplayChatModel`` + a
recorded fixture, then runs uvicorn no API key, deterministic. Used as a
Playwright ``webServer`` (see ``frontend/playwright.real-backend.config.ts``) and
runnable standalone for debugging::
uv run python scripts/run_replay_gateway.py --port 8011
``tests/`` is put on the path so the config ``use: replay_provider:ReplayChatModel``
resolves; ``GATEWAY_CORS_ORIGINS`` is set so the frontend on :3000 can talk to it.
"""
from __future__ import annotations
import argparse
import os
import sys
import tempfile
from pathlib import Path
_BACKEND = Path(__file__).resolve().parents[1]
sys.path.insert(0, str(_BACKEND))
sys.path.insert(0, str(_BACKEND / "tests")) # replay_provider + build_config_yaml live here
def main() -> int:
parser = argparse.ArgumentParser()
parser.add_argument("--port", type=int, default=8011)
parser.add_argument("--fixture", default=str(_BACKEND / "tests" / "fixtures" / "replay" / "write_read_file.ultra.json"))
parser.add_argument("--cors", default="http://localhost:3000")
args = parser.parse_args()
from _replay_fixture import REPLAY_MODEL_BLOCK, build_config_yaml, prepare_hermetic_extras
home = Path(tempfile.mkdtemp(prefix="replay-gw-"))
cfg = home / "config.yaml"
cfg.write_text(build_config_yaml(model_block=REPLAY_MODEL_BLOCK, home=home), encoding="utf-8")
# Override (not setdefault): the replay gateway must be hermetic, so an outer
# DEER_FLOW_HOME can't leak in and shift prompt-affecting paths/skills.
os.environ["DEER_FLOW_HOME"] = str(home)
os.environ["DEER_FLOW_CONFIG_PATH"] = str(cfg)
os.environ["DEER_FLOW_EXTENSIONS_CONFIG_PATH"] = str(prepare_hermetic_extras(home))
os.environ["DEERFLOW_REPLAY_FIXTURE"] = args.fixture
os.environ.setdefault("AUTH_JWT_SECRET", "ci-replay-secret")
os.environ["GATEWAY_CORS_ORIGINS"] = args.cors
# Child / dynamic imports (resolve_class) search PYTHONPATH too.
os.environ["PYTHONPATH"] = os.pathsep.join(p for p in (str(_BACKEND), str(_BACKEND / "tests"), os.environ.get("PYTHONPATH", "")) if p)
import uvicorn
target: str | object = "app.gateway.app:app"
# Test-only: attach the run/message seeder used by the multi-run render-order
# e2e (#3352). Imported from tests/ and mounted here only — never in the
# production app. Pass the app object (not the import string) so the extra
# router is registered before uvicorn serves it.
if os.environ.get("DEERFLOW_ENABLE_TEST_SEED") == "1":
from seed_runs_router import router as seed_router
from app.gateway.app import app as gateway_app
gateway_app.include_router(seed_router)
target = gateway_app
print("[replay-gw] test-only seed router mounted at /api/test-only/seed-runs", flush=True)
print(f"[replay-gw] config={cfg} fixture={args.fixture} cors={args.cors} port={args.port}", flush=True)
uvicorn.run(target, host="127.0.0.1", port=args.port, log_level="warning")
return 0
if __name__ == "__main__":
raise SystemExit(main())
-26
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@@ -1,26 +0,0 @@
"""Process-wide Python startup customizations for backend entrypoints.
When ``backend/`` is on ``sys.path``, Python imports this module during
interpreter startup. Keep changes here suitable for all gateway, script,
migration, and test entrypoints that run in that environment.
"""
from __future__ import annotations
import asyncio
import sys
def _configure_windows_event_loop_policy() -> None:
if sys.platform != "win32":
return
selector_policy = getattr(asyncio, "WindowsSelectorEventLoopPolicy", None)
if selector_policy is None:
return
if not isinstance(asyncio.get_event_loop_policy(), selector_policy):
asyncio.set_event_loop_policy(selector_policy())
_configure_windows_event_loop_policy()
-164
View File
@@ -1,164 +0,0 @@
"""Shared config + gateway-drive helpers for the record/replay e2e.
Record (``scripts/record_gateway.py`` + ``scripts/build_fixture_from_jsonl.py``)
and replay (``tests/test_replay_golden.py``)
MUST drive the gateway through an identical, prompt-affecting config otherwise
the system prompt differs and the recorded input hashes never match on replay.
Centralising the config builder + drive loop here makes that identity hold by
construction; only the ``models[].use`` block differs (real model vs
``ReplayChatModel``).
"""
from __future__ import annotations
import json
import uuid
from pathlib import Path
# mode -> (thinking_enabled, is_plan_mode, subagent_enabled). Mirrors the
# frontend mapping in core/threads/hooks.ts.
MODE_CONTEXT: dict[str, tuple[bool, bool, bool]] = {
"flash": (False, False, False),
"thinking": (True, False, False),
"pro": (True, True, False),
# thinking_enabled mirrors the frontend `context.mode !== "flash"` (hooks.ts),
# so ultra is thinking-enabled too.
"ultra": (True, True, True),
}
# The replay model block: same model NAME as recording (so nothing in the prompt
# shifts), only ``use`` swapped to the deterministic replay provider.
REPLAY_MODEL_BLOCK = """\
- name: scenario-model
display_name: Scenario Model
use: replay_provider:ReplayChatModel
model: replay
supports_thinking: true"""
def real_model_block(model: str) -> str:
return f"""\
- name: scenario-model
display_name: Scenario Model
use: langchain_openai:ChatOpenAI
model: {model}
api_key: $OPENAI_API_KEY
base_url: $OPENAI_API_BASE"""
def build_config_yaml(*, model_block: str, home: Path) -> str:
"""Full gateway config. Only ``model_block`` varies between record/replay.
Everything that shapes the system prompt is pinned so record, replay, and CI
produce byte-identical prompts regardless of the machine:
- sandbox / tool_groups / tools fixed here
- skills pointed at an empty ``<home>/skills`` so filesystem skills (incl.
gitignored custom skills present only on a dev box) never leak into the
prompt. Pair with an empty ``extensions_config.json`` (no MCP) via
:func:`prepare_hermetic_extras`.
- memory / summarization disabled (background, non-deterministic timing)
"""
return f"""\
log_level: warning
models:
{model_block}
sandbox:
use: deerflow.sandbox.local:LocalSandboxProvider
skills:
path: {home / "skills"}
container_path: /mnt/skills
tool_groups:
- name: file:read
- name: file:write
tools:
- name: ls
group: file:read
use: deerflow.sandbox.tools:ls_tool
- name: read_file
group: file:read
use: deerflow.sandbox.tools:read_file_tool
- name: write_file
group: file:write
use: deerflow.sandbox.tools:write_file_tool
# Memory + summarization make background / debounced model calls whose timing is
# non-deterministic; disable them so record and replay see the same model-call
# set. (Title stays — it is an in-graph, deterministic call we record.)
memory:
enabled: false
injection_enabled: false
summarization:
enabled: false
agents_api:
enabled: true
database:
backend: sqlite
sqlite_dir: {home / "db"}
"""
def prepare_hermetic_extras(home: Path) -> Path:
"""Create the empty skills tree + an empty extensions_config.json so the
system prompt has no environment-dependent skills/MCP content.
Returns the extensions-config path; the caller must point
``DEER_FLOW_EXTENSIONS_CONFIG_PATH`` at it. Call before starting the gateway.
"""
(home / "skills" / "public").mkdir(parents=True, exist_ok=True)
(home / "skills" / "custom").mkdir(parents=True, exist_ok=True)
extensions = home / "extensions_config.json"
extensions.write_text(json.dumps({"mcpServers": {}, "skills": {}}), encoding="utf-8")
return extensions
def sse_event_shapes(resp) -> list[dict]:
"""Reduce an SSE stream to (event name, sorted top-level data keys).
Snapshots the *shape* of the stream, not volatile values, so the golden is
stable across runs while still catching event-sequence / payload-shape drift.
"""
events: list[dict] = []
current: str | None = None
for line in resp.iter_lines():
if line.startswith("event:"):
current = line[len("event:") :].strip()
elif line.startswith("data:"):
raw = line[len("data:") :].strip()
try:
data = json.loads(raw) if raw else {}
except json.JSONDecodeError:
data = {"_raw": raw[:200]}
events.append({"event": current, "keys": sorted(data.keys()) if isinstance(data, dict) else None})
return events
def drive_gateway(app, *, prompt: str, context: dict) -> list[dict]:
"""Register -> create thread -> POST /runs/stream; return SSE event shapes.
This is the exact wire path the React frontend uses (LangGraph SDK), driven
in-process via Starlette's TestClient with the real auth flow.
"""
from starlette.testclient import TestClient
with TestClient(app) as client:
reg = client.post(
"/api/v1/auth/register",
json={"email": f"e2e-{uuid.uuid4().hex[:8]}@example.com", "password": "very-strong-password-123"},
)
assert reg.status_code == 201, reg.text
csrf = client.cookies.get("csrf_token")
assert csrf, "register must set csrf_token cookie"
thread_id = str(uuid.uuid4())
created = client.post("/api/threads", json={"thread_id": thread_id, "metadata": {}}, headers={"X-CSRF-Token": csrf})
assert created.status_code == 200, created.text
body = {
"assistant_id": "lead_agent",
"input": {"messages": [{"role": "user", "content": prompt}]},
"config": {"recursion_limit": 50},
"context": context,
"stream_mode": ["values"],
}
with client.stream("POST", f"/api/threads/{thread_id}/runs/stream", json=body, headers={"X-CSRF-Token": csrf}) as resp:
assert resp.status_code == 200, resp.read().decode()
return sse_event_shapes(resp)
@@ -1,64 +0,0 @@
"""Regression anchors: the custom-agent router must not block the event loop.
``app.gateway.routers.agents.create_agent_endpoint`` and ``delete_agent`` are
async route handlers that resolve the agent directory (``Paths.base_dir`` calls
``Path.resolve``), probe it (``Path.exists``), and create/remove it (``mkdir``,
config/SOUL writes, ``shutil.rmtree``) all blocking IO. Both offload that work
via ``asyncio.to_thread``; if any of it regresses back onto the event loop, the
strict Blockbuster gate raises ``BlockingError`` and these tests fail.
Imports live at module scope so the one-time FastAPI app construction (which
reads files while building OpenAPI schemas) happens at collection time, not on
the event loop under test. Test-side path resolution is itself offloaded with
``asyncio.to_thread`` (matching ``test_uploads_middleware``) so only the
handlers' own filesystem access is exercised on the loop.
"""
from __future__ import annotations
import asyncio
from pathlib import Path
import pytest
from app.gateway.routers.agents import AgentCreateRequest, create_agent_endpoint, delete_agent
from deerflow.config.agents_api_config import load_agents_api_config_from_dict
from deerflow.config.paths import get_paths
from deerflow.runtime.user_context import get_effective_user_id
pytestmark = pytest.mark.asyncio
async def test_create_agent_does_not_block_event_loop(tmp_path: Path, monkeypatch) -> None:
monkeypatch.setenv("DEER_FLOW_HOME", str(tmp_path))
monkeypatch.setattr("deerflow.config.paths._paths", None)
load_agents_api_config_from_dict({"enabled": True})
try:
response = await create_agent_endpoint(AgentCreateRequest(name="loop-make-agent", soul="You are a test agent."))
assert response is not None
user_id = get_effective_user_id()
# test-side check (resolution offloaded; not exercised on the loop)
agent_dir = await asyncio.to_thread(get_paths().user_agent_dir, user_id, "loop-make-agent")
assert await asyncio.to_thread((agent_dir / "config.yaml").exists)
finally:
load_agents_api_config_from_dict({})
async def test_delete_agent_does_not_block_event_loop(tmp_path: Path, monkeypatch) -> None:
monkeypatch.setenv("DEER_FLOW_HOME", str(tmp_path))
monkeypatch.setattr("deerflow.config.paths._paths", None)
load_agents_api_config_from_dict({"enabled": True})
try:
user_id = get_effective_user_id()
user_id = get_effective_user_id()
# test-side seeding (resolution offloaded; not exercised on the loop)
agent_dir = await asyncio.to_thread(get_paths().user_agent_dir, user_id, "loop-test-agent")
await asyncio.to_thread(agent_dir.mkdir, parents=True, exist_ok=True)
await asyncio.to_thread((agent_dir / "config.yaml").write_text, "name: loop-test-agent\n", encoding="utf-8")
await delete_agent("loop-test-agent")
assert not await asyncio.to_thread(agent_dir.exists)
finally:
load_agents_api_config_from_dict({})
@@ -1,124 +0,0 @@
"""Regression anchor: DynamicContextMiddleware must not block the event loop.
``_inject`` performs synchronous file I/O (memory JSON loading) and
potentially blocking network calls (tiktoken encoding download on first
use see issue #3402). ``abefore_agent`` offloads the call via
``asyncio.to_thread`` so the event loop stays responsive.
This anchor drives the real ``create_agent`` graph via ``ainvoke`` under
the strict Blockbuster gate. If the offload regresses and the blocking
I/O runs on the event loop, Blockbuster raises ``BlockingError`` and
this test fails.
"""
from __future__ import annotations
import asyncio
from types import SimpleNamespace
from unittest import mock
import pytest
from langchain.agents import create_agent
from langchain_core.language_models.fake_chat_models import FakeMessagesListChatModel
from langchain_core.messages import AIMessage, HumanMessage
from deerflow.agents.middlewares.dynamic_context_middleware import DynamicContextMiddleware
pytestmark = pytest.mark.asyncio
class _FakeModel(FakeMessagesListChatModel):
"""FakeMessagesListChatModel with a no-op ``bind_tools`` for create_agent."""
def bind_tools(self, tools, **kwargs): # type: ignore[override]
return self
async def test_abefore_agent_does_not_block_event_loop() -> None:
"""``abefore_agent`` must offload _inject() to a thread pool."""
mw = DynamicContextMiddleware()
# Mock _build_full_reminder to simulate a slow synchronous operation
# (file I/O + tiktoken download). The mock sleeps briefly to make any
# event-loop blocking visible to the Blockbuster gate.
original_build = mw._build_full_reminder
def slow_build_reminder():
import time
time.sleep(0.05) # 50ms sync sleep — blocks the thread it runs on
return original_build()
with (
mock.patch.object(mw, "_build_full_reminder", slow_build_reminder),
mock.patch("deerflow.agents.lead_agent.prompt._get_memory_context", return_value=""),
):
agent = await asyncio.to_thread(
lambda: create_agent(
model=_FakeModel(responses=[AIMessage(content="ok")]),
tools=[],
middleware=[mw],
)
)
result = await agent.ainvoke(
{"messages": [HumanMessage(content="hi")]},
{"configurable": {"thread_id": "test-thread"}},
)
assert result["messages"]
async def test_abefore_agent_returns_same_result_as_before_agent() -> None:
"""``abefore_agent`` (async, offloaded) must produce the same result as
``before_agent`` (sync, for backward compatibility)."""
mw = DynamicContextMiddleware()
state = {"messages": [HumanMessage(content="Hello", id="msg-1")]}
runtime = SimpleNamespace(context={})
with (
mock.patch("deerflow.agents.lead_agent.prompt._get_memory_context", return_value=""),
mock.patch("deerflow.agents.middlewares.dynamic_context_middleware.datetime") as mock_dt,
):
mock_dt.now.return_value.strftime.return_value = "2026-06-05, Friday"
# Sync path
sync_result = mw.before_agent(state, runtime)
# Async path (offloaded to thread)
async_result = await mw.abefore_agent(state, runtime)
assert sync_result is not None
assert async_result is not None
assert sync_result.keys() == async_result.keys()
# Both return 2 messages: reminder + user content
assert len(sync_result["messages"]) == 2
assert len(async_result["messages"]) == 2
# IDs match
assert sync_result["messages"][0].id == async_result["messages"][0].id
assert sync_result["messages"][1].id == async_result["messages"][1].id
async def test_abefore_agent_returns_none_on_timeout() -> None:
"""If _inject() exceeds the timeout, abefore_agent returns None gracefully."""
import time
mw = DynamicContextMiddleware()
def blocking_inject(state):
time.sleep(10) # Simulate a blocking call that far exceeds the timeout
return {"messages": [HumanMessage(content="should not reach")]}
with (
mock.patch.object(mw, "_inject", blocking_inject),
mock.patch(
"deerflow.agents.middlewares.dynamic_context_middleware._INJECT_TIMEOUT_SECONDS",
0.1,
),
):
state = {"messages": [HumanMessage(content="Hello", id="msg-1")]}
runtime = SimpleNamespace(context={})
result = await mw.abefore_agent(state, runtime)
assert result is None
@@ -1,132 +0,0 @@
{
"scenario": "write_read_file",
"mode": "ultra",
"events": [
{
"event": "metadata",
"keys": [
"run_id",
"thread_id"
]
},
{
"event": "values",
"keys": [
"artifacts",
"messages",
"viewed_images"
]
},
{
"event": "values",
"keys": [
"artifacts",
"messages",
"thread_data",
"viewed_images"
]
},
{
"event": "values",
"keys": [
"artifacts",
"messages",
"thread_data",
"viewed_images"
]
},
{
"event": "values",
"keys": [
"artifacts",
"messages",
"thread_data",
"viewed_images"
]
},
{
"event": "values",
"keys": [
"artifacts",
"messages",
"thread_data",
"title",
"viewed_images"
]
},
{
"event": "values",
"keys": [
"artifacts",
"messages",
"thread_data",
"title",
"viewed_images"
]
},
{
"event": "values",
"keys": [
"artifacts",
"messages",
"thread_data",
"title",
"viewed_images"
]
},
{
"event": "values",
"keys": [
"artifacts",
"messages",
"thread_data",
"title",
"viewed_images"
]
},
{
"event": "values",
"keys": [
"artifacts",
"messages",
"thread_data",
"title",
"viewed_images"
]
},
{
"event": "values",
"keys": [
"artifacts",
"messages",
"thread_data",
"title",
"viewed_images"
]
},
{
"event": "values",
"keys": [
"artifacts",
"messages",
"thread_data",
"title",
"viewed_images"
]
},
{
"event": "values",
"keys": [
"artifacts",
"messages",
"thread_data",
"title",
"viewed_images"
]
},
{
"event": "end",
"keys": null
}
]
}
-243
View File
@@ -1,243 +0,0 @@
{
"scenario": "write_read_file",
"mode": "ultra",
"model": "sre/gpt-5",
"prompt": "Using your own file tools directly, create the file /mnt/user-data/outputs/note.txt with exactly this content: hi from replay. Then read that same file back and reply with its exact contents. Do NOT delegate to a subagent and do NOT use the task tool — do it yourself. Do not ask any clarifying questions.",
"context": {
"is_bootstrap": false,
"mode": "ultra",
"thinking_enabled": true,
"is_plan_mode": true,
"subagent_enabled": true
},
"turns": [
{
"caller": "lead_agent",
"conversation_hash": "9c50eda6ab7e8593dabccbdeadc70a4a7bf778b2c0c3f275f1f96cf2c8ab58db",
"input_hash": "27aeb4c11bff2c3ebc182fe52a06556823c21928620a400c7f26be9733c31f3f",
"output": {
"type": "ai",
"data": {
"content": "",
"additional_kwargs": {},
"response_metadata": {
"finish_reason": "tool_calls",
"model_name": "sre/gpt-5",
"model_provider": "openai"
},
"type": "ai",
"name": null,
"id": "lc_run--019ea641-acda-7423-9a9f-79725057bc20",
"tool_calls": [
{
"name": "write_file",
"args": {
"description": "Create the requested output file with exact content",
"path": "/mnt/user-data/outputs/note.txt",
"content": "hi from replay."
},
"id": "call_FV7zhKonjx5CAa1RwIcKihpi",
"type": "tool_call"
}
],
"invalid_tool_calls": [],
"usage_metadata": {
"input_tokens": 3664,
"output_tokens": 434,
"total_tokens": 4098,
"input_token_details": {
"audio": 0,
"cache_read": 3584
},
"output_token_details": {
"audio": 0,
"reasoning": 384
}
}
}
}
},
{
"caller": "middleware:title",
"conversation_hash": "3598aeb87e221ca8f554e4d61ce6d5e8801754606fa5c95a89c38bd6cb623045",
"input_hash": "75101f9faa453b1a35deff920b1e3c1a9f0b013a7627fbbaa03436752776b953",
"output": {
"type": "ai",
"data": {
"content": "Direct File Creation and Readback",
"additional_kwargs": {},
"response_metadata": {
"finish_reason": "stop",
"model_name": "sre/gpt-5",
"model_provider": "openai"
},
"type": "ai",
"name": null,
"id": "lc_run--019ea641-cf52-7793-900e-15ad4f032c0e",
"tool_calls": [],
"invalid_tool_calls": [],
"usage_metadata": {
"input_tokens": 104,
"output_tokens": 656,
"total_tokens": 760,
"input_token_details": {
"audio": 0,
"cache_read": 0
},
"output_token_details": {
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"reasoning": 640
}
}
}
}
},
{
"caller": "lead_agent",
"conversation_hash": "6af134379b2a9efa01b4f63032f88211d5f38f459f8bed621eb6c65e8e05c1f9",
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},
"type": "ai",
"name": null,
"id": "lc_run--019ea641-f523-7d60-a416-b051fba469a2",
"tool_calls": [
{
"name": "read_file",
"args": {
"description": "Verify contents to echo back exactly",
"path": "/mnt/user-data/outputs/note.txt"
},
"id": "call_YevFCnLcjWfWHaZm8wwMpEk8",
"type": "tool_call"
}
],
"invalid_tool_calls": [],
"usage_metadata": {
"input_tokens": 3719,
"output_tokens": 35,
"total_tokens": 3754,
"input_token_details": {
"audio": 0,
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},
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}
},
{
"caller": "lead_agent",
"conversation_hash": "04751c4f7b0107b78b5c97d417063883fd586f5ebcbc4acf79be6cb3c0cdaec1",
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"output": {
"type": "ai",
"data": {
"content": "hi from replay.",
"additional_kwargs": {},
"response_metadata": {
"finish_reason": "stop",
"model_name": "sre/gpt-5",
"model_provider": "openai"
},
"type": "ai",
"name": null,
"id": "lc_run--019ea641-ff38-7751-9c2b-cc648811883b",
"tool_calls": [],
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"usage_metadata": {
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"total_tokens": 3776,
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},
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}
},
{
"caller": "suggest_agent",
"conversation_hash": "8b98ebdbb53e88f000556c4753adede8eaa076ff6fd7b8a1285bfd18aee8144d",
"input_hash": "dcd855d389d7179a1e4bc7074fa9ba7ce697570af8947225d6bacb538f14a0cb",
"output": {
"type": "ai",
"data": {
"content": "[\n \"Can you show the file size and last modified time of /mnt/user-data/outputs/note.txt?\",\n \"List the contents of /mnt/user-data/outputs/ to confirm the file exists.\",\n \"Append 'second line' to /mnt/user-data/outputs/note.txt and print its new contents.\"\n]",
"additional_kwargs": {
"refusal": null
},
"response_metadata": {
"token_usage": {
"completion_tokens": 909,
"prompt_tokens": 224,
"total_tokens": 1133,
"completion_tokens_details": {
"accepted_prediction_tokens": 0,
"audio_tokens": 0,
"reasoning_tokens": 832,
"rejected_prediction_tokens": 0
},
"prompt_tokens_details": {
"audio_tokens": 0,
"cached_tokens": 0
},
"latency_checkpoint": {
"engine_tbt_ms": 12,
"engine_ttft_ms": 324,
"engine_ttlt_ms": 10965,
"pre_inference_ms": 153,
"service_tbt_ms": 12,
"service_ttft_ms": 849,
"service_ttlt_ms": 11491,
"total_duration_ms": 11351,
"user_visible_ttft_ms": 696
}
},
"model_provider": "openai",
"model_name": "sre/gpt-5",
"system_fingerprint": null,
"id": "chatcmpl-DoPFALdwiyEDYOIN7wFYhqBrr6eTA",
"service_tier": "default",
"finish_reason": "stop",
"logprobs": null
},
"type": "ai",
"name": null,
"id": "lc_run--019ea642-0eac-78f1-a506-931e343184f1-0",
"tool_calls": [],
"invalid_tool_calls": [],
"usage_metadata": {
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"reasoning": 832
}
}
}
}
}
]
}
-384
View File
@@ -1,384 +0,0 @@
"""Replay a recorded LLM trace deterministically — the "replay" half of
record/replay e2e (mirrors open-design's ``mocks/`` golden traces).
A fixture is a JSON file capturing the *real* model calls of one scenario,
keyed by a normalized hash of the **caller + input** each call received::
{
"scenario": "write_read_file",
"mode": "ultra",
"model": "gpt-5.5",
"turns": [
{
"caller": "lead_agent",
"conversation_hash": "<sha256>",
"input_hash": "<sha256>",
"output": <message dict>,
},
...
]
}
Why hash-by-input (not turn index)
----------------------------------
A real run makes model calls from several callers the lead agent's own turns,
``TitleMiddleware`` (auto-title), memory, and possibly subagents. They interleave
and their count/order is not something we want a replay to depend on. Matching by
a normalized hash of the *input messages* means each call gets back exactly the
output that was recorded for that input, regardless of order or which middleware
issued it. The caller name (``lead_agent``, ``middleware:title``,
``suggest_agent``, ``subagent:*``, ...) is included so two different model
callers with the same conversation text do not compete for the same replay
bucket. That keeps the in-graph, deterministic title call part of the recording;
memory/summarization, by contrast, are disabled in the replay config
(``_replay_fixture.py``) because their background, debounced timing is not
reproducible across runs.
Volatile fields (UUID thread/run/user ids, timestamps, dates, tmp/home paths)
are normalized out before hashing so a recording replays across processes with
different temp dirs. The same ``hash_messages`` is used by the recorder
(``scripts/record_gateway.py``) and here, so record and replay agree by
construction.
This lives in ``tests/`` (not in the publishable ``deerflow-harness`` package),
matching the repo convention for test-only fakes (cf. ``FakeToolCallingModel`` in
``_agent_e2e_helpers.py``). In-process tests get ``tests/`` on ``sys.path`` for
free via pytest; a standalone replay gateway just needs ``PYTHONPATH`` to include
``backend/tests`` so the config ``use:`` below resolves.
Point a config model's ``use`` at this class and set the fixture via env::
models:
- name: replay-model
use: replay_provider:ReplayChatModel
model: gpt-5.5 # placeholder; ignored
DEERFLOW_REPLAY_FIXTURE=/path/to/write_read_file.ultra.json
A cache miss raises loudly with a diagnostic that is the signal that the
replayed run diverged from the recording (graph changed, a new volatile field
slipped through normalization, or a non-deterministic tool result changed a
downstream input). Re-record or extend normalization; never pass silently.
Recording lives outside production code too (``scripts/record_gateway.py`` +
``scripts/build_fixture_from_jsonl.py``); CI consumes the fixtures through this
replay side with no API key.
"""
from __future__ import annotations
import hashlib
import json
import os
import re
from collections import deque
from collections.abc import Iterator
from typing import Any
from langchain_core.callbacks import BaseCallbackHandler, CallbackManagerForLLMRun
from langchain_core.language_models.chat_models import BaseChatModel
from langchain_core.messages import AIMessage, AIMessageChunk, BaseMessage, messages_from_dict
from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
from langchain_core.runnables import Runnable
from pydantic import PrivateAttr
_FIXTURE_ENV = "DEERFLOW_REPLAY_FIXTURE"
_DEFAULT_CALLER = "lead_agent"
_CALLER_TAG_PREFIXES = ("middleware:", "subagent:")
_CALLER_NAME_ALIASES = {
# TitleMiddleware uses this run_name and tags the call as middleware:title.
# Some execution paths do not preserve the tag down to the model callback,
# so keep the run_name and tag in the same replay namespace.
"title_agent": "middleware:title",
}
# Process-wide record of replay misses. A miss raises inside the model, but the
# gateway's LLMErrorHandlingMiddleware swallows it into a normal assistant error
# message — so the SSE *event shapes* are unchanged and a shape-only golden stays
# green on a stale fixture. The in-process Layer-1 test inspects this list to fail
# loud on a miss instead. (Layer-2 already fails on a miss: the recorded turns
# never render.)
_replay_misses: list[str] = []
def replay_misses() -> list[str]:
"""Hashes that missed the fixture since the last reset (see ``_replay_misses``)."""
return list(_replay_misses)
def reset_replay_misses() -> None:
_replay_misses.clear()
def _normalize_caller(caller: str | None) -> str:
value = _normalize_text(str(caller or "").strip())
if not value:
return _DEFAULT_CALLER
return _CALLER_NAME_ALIASES.get(value, value)
def _caller_from_tags(tags: list[str] | None) -> str | None:
for tag in tags or []:
if isinstance(tag, str) and (tag == _DEFAULT_CALLER or tag.startswith(_CALLER_TAG_PREFIXES)):
return tag
return None
def caller_identity(*, name: str | None = None, tags: list[str] | None = None) -> str:
"""Stable model-caller identity shared by record and replay.
Tags win because graph middleware and subagents already use them as the
explicit caller marker. ``run_name`` is exposed to callbacks as ``name`` and
covers route-level callers such as ``suggest_agent``.
"""
return _normalize_caller(_caller_from_tags(tags) or name)
# Volatile substrings that differ between a recording run and a replay run but
# carry no semantic weight for matching. Normalized to stable placeholders
# before hashing so the same logical input hashes identically across processes.
# The frontend injects a per-request ``<system-reminder>`` (current date, weekday,
# dynamic context) that the backend-direct path does not — and its date/weekday
# change every day. Strip the whole block before hashing so a fixture replays
# (a) across days and (b) from both the browser and direct-POST paths.
_SYSTEM_REMINDER_RE = re.compile(r"<system-reminder>.*?</system-reminder>", re.DOTALL)
_UUID_RE = re.compile(r"[0-9a-fA-F]{8}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{4}-[0-9a-fA-F]{12}")
_ISO_TS_RE = re.compile(r"\d{4}-\d{2}-\d{2}[T ]\d{2}:\d{2}:\d{2}(?:\.\d+)?(?:Z|[+-]\d{2}:?\d{2})?")
_DATE_RE = re.compile(r"\d{4}-\d{2}-\d{2}")
# Absolute temp/home roots used for per-run isolation (macOS + Linux + DEER_FLOW_HOME tmp).
_PATH_RE = re.compile(r"(?:/private)?/(?:var/folders|tmp)/[^\s\"']*")
def _normalize_text(text: str) -> str:
text = _SYSTEM_REMINDER_RE.sub("", text)
text = _UUID_RE.sub("<UUID>", text)
text = _ISO_TS_RE.sub("<TS>", text)
text = _DATE_RE.sub("<DATE>", text)
text = _PATH_RE.sub("<PATH>", text)
return text
def _content_to_text(content: Any) -> str:
if isinstance(content, str):
return content
if isinstance(content, list):
parts: list[str] = []
for block in content:
if isinstance(block, dict):
parts.append(block.get("text", "") or json.dumps(block, sort_keys=True, ensure_ascii=False))
else:
parts.append(str(block))
return "".join(parts)
return str(content)
def _canonical_messages(messages: list[BaseMessage]) -> str:
"""Project messages to a stable shape that excludes volatile metadata/ids.
Keeps only what determines which recorded turn to replay: the conversation
(human / ai / tool messages role, text content, tool-call name+args). Drops
``id``, ``response_metadata``, ``usage_metadata``, ``tool_call_id`` (all
volatile), then normalizes embedded volatile substrings.
**The system message is excluded entirely.** The lead-agent system prompt is
a living, frequently-edited implementation detail (its wording changes across
PRs), not part of the front-back contract this harness verifies. Hashing it
would make every fixture go stale and red-fail on unrelated PRs the moment
anyone edits the prompt. The conversation flow (user input -> tool calls ->
results -> answer) is the stable key that identifies a recorded turn.
"""
projected: list[dict[str, Any]] = []
for message in messages:
# Exclude the system prompt from the match key — see docstring. It is the
# most-edited part of the prompt and not part of the contract under test.
if message.type == "system":
continue
content = _normalize_text(_content_to_text(message.content))
tool_calls = getattr(message, "tool_calls", None)
# Drop messages that are empty after normalization — e.g. a turn that was
# nothing but a frontend-injected <system-reminder>. They carry no
# decision-relevant content and differ between client paths.
if not content.strip() and not tool_calls:
continue
entry: dict[str, Any] = {"type": message.type, "content": content}
if tool_calls:
entry["tool_calls"] = [{"name": tc.get("name"), "args": tc.get("args")} for tc in tool_calls]
name = getattr(message, "name", None)
if name:
entry["name"] = name
projected.append(entry)
raw = json.dumps(projected, sort_keys=True, ensure_ascii=False)
return _normalize_text(raw)
def hash_messages(messages: list[BaseMessage]) -> str:
"""Legacy stable hash of only a model call's conversation input."""
return hashlib.sha256(_canonical_messages(messages).encode("utf-8")).hexdigest()
def hash_replay_input(messages: list[BaseMessage], *, caller: str | None) -> str:
"""Stable replay key for a caller-specific model input."""
return hash_input_key(hash_messages(messages), caller=caller)
def hash_input_key(conversation_hash: str, *, caller: str | None) -> str:
"""Namespace a conversation hash by caller identity.
Keeping this as ``hash(caller + legacy_conversation_hash)`` lets existing
fixtures migrate without a live-model re-record: their old ``input_hash`` is
exactly the conversation hash.
"""
payload = json.dumps(
{"caller": _normalize_caller(caller), "conversation_hash": conversation_hash},
sort_keys=True,
ensure_ascii=False,
)
return hashlib.sha256(payload.encode("utf-8")).hexdigest()
def _load_fixture(fixture_path: str) -> dict[str, deque[AIMessage]]:
with open(fixture_path, encoding="utf-8") as handle:
payload = json.load(handle)
table: dict[str, deque[AIMessage]] = {}
for index, turn in enumerate(payload.get("turns", [])):
input_hash = turn["input_hash"]
(message,) = messages_from_dict([turn["output"]])
if not isinstance(message, AIMessage):
raise ValueError(f"replay fixture {fixture_path!r} turn {index} output is {type(message).__name__}, expected AIMessage")
table.setdefault(input_hash, deque()).append(message)
return table
class ReplayChatModel(BaseChatModel):
"""Returns the recorded assistant output whose input matches this call.
``bind_tools`` is a no-op returning ``self`` recorded turns already carry
the real ``tool_calls``, so the agent dispatches them as if a live model had
produced them.
"""
_table: dict[str, deque] = PrivateAttr(default_factory=dict)
_fixture_path: str = PrivateAttr(default="")
_run_callers: dict[str, str] = PrivateAttr(default_factory=dict)
def __init__(self, **kwargs: Any) -> None:
# Ignore provider noise the factory forwards from config (model, api_key,
# base_url, ...). Fixture path comes from the ``fixture`` kwarg or env.
fixture_path = kwargs.pop("fixture", None) or os.environ.get(_FIXTURE_ENV)
callbacks = kwargs.pop("callbacks", None)
super().__init__(callbacks=callbacks)
if not fixture_path:
raise ValueError(f"ReplayChatModel needs a fixture path via the ``fixture`` kwarg or ${_FIXTURE_ENV}")
self._fixture_path = fixture_path
self._table = _load_fixture(fixture_path)
self.callbacks = [*(self.callbacks or []), _ReplayCallerCapture(self._run_callers)]
@property
def _llm_type(self) -> str:
return "deerflow-replay"
def _caller_from_run_manager(self, run_manager: CallbackManagerForLLMRun | None) -> str:
if run_manager is None:
if len(self._run_callers) == 1:
# Some async LangGraph paths fire on_chat_model_start with the
# caller metadata but invoke the model implementation without a
# run_manager. When there is only one pending start event, it is
# the current call; use it so record/replay share the same
# caller key.
return self._run_callers.pop(next(iter(self._run_callers)))
return _DEFAULT_CALLER
run_id = str(getattr(run_manager, "run_id", ""))
caller = self._run_callers.pop(run_id, None)
if caller:
return caller
return caller_identity(
name=getattr(run_manager, "run_name", None) or getattr(run_manager, "name", None),
tags=getattr(run_manager, "tags", None),
)
def _match(self, messages: list[BaseMessage], run_manager: CallbackManagerForLLMRun | None = None) -> AIMessage:
caller = self._caller_from_run_manager(run_manager)
key = hash_replay_input(messages, caller=caller)
bucket = self._table.get(key)
if not bucket:
# Backward compatibility for fixtures recorded before caller-aware
# keys. New recordings write caller-aware ``input_hash`` values.
legacy_key = hash_messages(messages)
bucket = self._table.get(legacy_key)
if bucket:
key = legacy_key
if not bucket:
_replay_misses.append(key)
preview = _canonical_messages(messages)
raise KeyError(
f"replay miss: no recorded output for input hash {key} in {self._fixture_path!r}. "
"The replayed run diverged from the recording (graph changed, a non-deterministic tool result "
"altered a downstream input, or a volatile field slipped past normalization). "
f"Caller: {caller!r}. "
f"Known hashes: {sorted(self._table)}. "
f"Normalized input (first 800 chars): {preview[:800]!r}"
)
return bucket.popleft()
def _generate(
self,
messages: list[BaseMessage],
stop: list[str] | None = None,
run_manager: CallbackManagerForLLMRun | None = None,
**kwargs: Any,
) -> ChatResult:
return ChatResult(generations=[ChatGeneration(message=self._match(messages, run_manager))])
def _stream(
self,
messages: list[BaseMessage],
stop: list[str] | None = None,
run_manager: CallbackManagerForLLMRun | None = None,
**kwargs: Any,
) -> Iterator[ChatGenerationChunk]:
turn = self._match(messages, run_manager)
text = turn.content if isinstance(turn.content, str) else ""
chunk = ChatGenerationChunk(
message=AIMessageChunk(
content=turn.content,
tool_calls=turn.tool_calls,
additional_kwargs=turn.additional_kwargs,
id=turn.id,
)
)
if run_manager is not None and text:
run_manager.on_llm_new_token(text, chunk=chunk)
yield chunk
def bind_tools(self, tools: Any, **kwargs: Any) -> Runnable: # type: ignore[override]
return self
class _ReplayCallerCapture(BaseCallbackHandler):
def __init__(self, run_callers: dict[str, str]) -> None:
self._run_callers = run_callers
def on_chat_model_start(
self,
serialized: dict,
messages: list[list[BaseMessage]],
*,
run_id: Any = None,
tags: list[str] | None = None,
name: str | None = None,
**kwargs: Any,
) -> None:
if run_id is not None:
self._run_callers[str(run_id)] = caller_identity(name=name, tags=tags)
# Re-export so the recorder shares the exact hashing logic.
__all__ = [
"ReplayChatModel",
"caller_identity",
"hash_input_key",
"hash_messages",
"hash_replay_input",
"replay_misses",
"reset_replay_misses",
]
-100
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@@ -1,100 +0,0 @@
"""Test-only run/message seeder for the multi-run render-order e2e (issue #3352).
Mounted **only** by ``scripts/run_replay_gateway.py`` (the replay e2e gateway)
and never by the production app, so it cannot ship. It lets a Playwright spec
stand up a thread with >=2 runs whose per-run messages exercise the frontend's
reload / history-rebuild ordering path with no real model, no recording, and
no API key.
Why a seeder instead of recording a conversation: issue #3352 only reproduces
when the checkpoint no longer holds the older messages (post-compression), so
the frontend rebuilds them from the per-run history endpoints. A seeder lets us
create exactly that precondition deterministically runs in the run store +
per-run ``category="message"`` events, and **no checkpoint** so on reload the
buggy ``findLatestUnloadedRunIndex`` + prepend in ``core/threads/hooks.ts`` is
the sole source of truth and its reversed order becomes observable.
It writes through the gateway's OWN ``app.state.run_store`` +
``app.state.run_event_store`` using the request's auth context, so the seeded
``user_id`` matches the browser session that reads it back. The event shape
mirrors exactly what ``runtime/journal.py`` writes for real runs
(``event_type`` ``llm.human.input`` / ``llm.ai.response``, ``category``
``"message"``, ``content`` = ``message.model_dump()``, ``metadata.caller`` =
``"lead_agent"``).
"""
from __future__ import annotations
from typing import Literal
from fastapi import APIRouter, Request
from pydantic import BaseModel
router = APIRouter(prefix="/api/test-only", tags=["test-only"])
# Mirror runtime/journal.py: human prompts are recorded as ``llm.human.input``
# and assistant turns as ``llm.ai.response``; both land in ``category="message"``.
_EVENT_TYPE = {"human": "llm.human.input", "ai": "llm.ai.response"}
class SeedMessage(BaseModel):
role: Literal["human", "ai"]
content: str
id: str
class SeedRun(BaseModel):
run_id: str
# ISO timestamp; RunManager.list_by_thread sorts newest-first by created_at,
# so a later created_at must mean a later run for the ordering to be faithful.
created_at: str
messages: list[SeedMessage]
class SeedRunsBody(BaseModel):
thread_id: str
runs: list[SeedRun]
@router.post("/seed-runs")
async def seed_runs(body: SeedRunsBody, request: Request) -> dict:
"""Seed runs + per-run message events for the authenticated user.
No checkpoint is written: that is the whole point it forces the frontend's
reload path to rebuild history from the per-run endpoints (the #3352 bug
site) instead of the (correctly ordered) checkpoint snapshot.
"""
from langchain_core.messages import AIMessage, HumanMessage
run_store = request.app.state.run_store
event_store = request.app.state.run_event_store
for run in body.runs:
# user_id defaults (AUTO) to the request's auth context, matching the
# browser session that will read these runs back via GET /runs.
await run_store.put(
run.run_id,
thread_id=body.thread_id,
assistant_id="lead_agent",
status="success",
created_at=run.created_at,
)
events = []
for m in run.messages:
msg = (HumanMessage if m.role == "human" else AIMessage)(content=m.content, id=m.id)
events.append(
{
"thread_id": body.thread_id,
"run_id": run.run_id,
"event_type": _EVENT_TYPE[m.role],
"category": "message",
"content": msg.model_dump(),
"metadata": {"caller": "lead_agent"},
"created_at": run.created_at,
}
)
# One batch per run so seq is monotonic and run1's messages precede
# run2's; the gateway reads them back per-run anyway.
await event_store.put_batch(events)
return {"ok": True, "thread_id": body.thread_id, "runs": len(body.runs)}
-51
View File
@@ -140,57 +140,6 @@ def test_app_config_defaults_empty_database_to_sqlite(tmp_path, monkeypatch):
assert config.database.sqlite_dir == ".deer-flow/data"
def test_app_config_coerces_commented_out_list_sections(tmp_path, monkeypatch):
"""Commenting out every entry under a list key makes PyYAML parse it as None.
Regression for the documented ``cp config.example.yaml config.yaml`` flow
(issue #1444): such a config must load with empty lists instead of raising
``Input should be a valid list``.
"""
config_path = tmp_path / "config.yaml"
extensions_path = tmp_path / "extensions_config.json"
_write_extensions_config(extensions_path)
config_path.write_text(
yaml.safe_dump(
{
"sandbox": {"use": "deerflow.sandbox.local:LocalSandboxProvider"},
"models": None,
"tools": None,
"tool_groups": None,
}
),
encoding="utf-8",
)
monkeypatch.setenv("DEER_FLOW_EXTENSIONS_CONFIG_PATH", str(extensions_path))
config = AppConfig.from_file(str(config_path))
assert config.models == []
assert config.tools == []
assert config.tool_groups == []
def test_app_config_warns_when_no_models_configured(tmp_path, monkeypatch, caplog):
config_path = tmp_path / "config.yaml"
extensions_path = tmp_path / "extensions_config.json"
_write_extensions_config(extensions_path)
config_path.write_text(
yaml.safe_dump(
{
"sandbox": {"use": "deerflow.sandbox.local:LocalSandboxProvider"},
"models": None,
}
),
encoding="utf-8",
)
monkeypatch.setenv("DEER_FLOW_EXTENSIONS_CONFIG_PATH", str(extensions_path))
with caplog.at_level("WARNING", logger="deerflow.config.app_config"):
AppConfig.from_file(str(config_path))
assert "No models are configured" in caplog.text
def test_get_app_config_reloads_when_file_changes(tmp_path, monkeypatch):
config_path = tmp_path / "config.yaml"
extensions_path = tmp_path / "extensions_config.json"
+4 -189
View File
@@ -4,7 +4,6 @@ import pytest
from starlette.testclient import TestClient
from app.gateway.auth_middleware import AuthMiddleware, _is_public
from app.gateway.csrf_middleware import CSRFMiddleware
# ── _is_public unit tests ─────────────────────────────────────────────────
@@ -39,8 +38,6 @@ def test_public_paths(path: str):
"/api/threads/123/uploads",
"/api/agents",
"/api/channels",
"/api/channels/providers",
"/api/channels/slack/connect",
"/api/runs/stream",
"/api/threads/123/runs",
"/api/v1/auth/me",
@@ -91,9 +88,7 @@ def test_unknown_api_path_is_protected():
def _make_app():
"""Create a minimal FastAPI app with AuthMiddleware for testing."""
from fastapi import FastAPI, Request
from deerflow.runtime.user_context import get_effective_user_id
from fastapi import FastAPI
app = FastAPI()
app.add_middleware(AuthMiddleware)
@@ -103,16 +98,8 @@ def _make_app():
return {"status": "ok"}
@app.get("/api/v1/auth/me")
async def auth_me(request: Request):
from app.gateway.deps import get_current_user_from_request
user = await get_current_user_from_request(request)
return {
"id": str(user.id),
"email": user.email,
"system_role": user.system_role,
"needs_setup": user.needs_setup,
}
async def auth_me():
return {"id": "1", "email": "test@test.com"}
@app.get("/api/v1/auth/setup-status")
async def setup_status():
@@ -122,29 +109,6 @@ def _make_app():
async def models_get():
return {"models": []}
@app.get("/api/whoami")
async def whoami(request: Request):
user = request.state.user
return {
"id": str(user.id),
"email": getattr(user, "email", None),
"system_role": getattr(user, "system_role", None),
"context_user_id": get_effective_user_id(),
}
@app.get("/api/current-user-from-dep")
async def current_user_from_dep(request: Request):
from app.gateway.deps import get_current_user_from_request
user = await get_current_user_from_request(request)
state_user = request.state.user
return {
"id": str(user.id),
"state_id": str(state_user.id),
"auth_source": request.state.auth_source,
"context_user_id": get_effective_user_id(),
}
@app.put("/api/mcp/config")
async def mcp_put():
return {"ok": True}
@@ -168,24 +132,8 @@ def _make_app():
return app
def _make_auth_csrf_app():
"""Create a minimal app with production middleware ordering."""
from fastapi import FastAPI
app = FastAPI()
app.add_middleware(AuthMiddleware)
app.add_middleware(CSRFMiddleware)
@app.post("/api/threads/abc/runs/stream")
async def protected_mutation():
return {"ok": True}
return app
@pytest.fixture
def client(monkeypatch):
monkeypatch.delenv("DEER_FLOW_AUTH_DISABLED", raising=False)
def client():
return TestClient(_make_app())
@@ -213,139 +161,6 @@ def test_protected_path_no_cookie_returns_401(client):
assert body["detail"]["code"] == "not_authenticated"
def test_auth_disabled_allows_protected_path_without_cookie(monkeypatch):
monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
client = TestClient(_make_app())
res = client.get("/api/models")
assert res.status_code == 200
assert res.json() == {"models": []}
def test_auth_disabled_stamps_e2e_admin_user_without_cookie(monkeypatch):
monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
client = TestClient(_make_app())
res = client.get("/api/whoami")
assert res.status_code == 200
assert res.json() == {
"id": "e2e-user",
"email": "e2e@test.local",
"system_role": "admin",
"context_user_id": "e2e-user",
}
def test_auth_disabled_auth_me_reuses_middleware_user_without_cookie(monkeypatch):
monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
client = TestClient(_make_app())
res = client.get("/api/v1/auth/me")
assert res.status_code == 200
assert res.json() == {
"id": "e2e-user",
"email": "e2e@test.local",
"system_role": "admin",
"needs_setup": False,
}
def test_auth_disabled_does_not_clobber_valid_session_cookie(monkeypatch):
from types import SimpleNamespace
async def fake_current_user(request):
return SimpleNamespace(
id="session-user",
email="session@test.local",
system_role="user",
needs_setup=False,
)
monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
monkeypatch.setattr("app.gateway.deps.get_current_user_from_request", fake_current_user)
client = TestClient(_make_app())
res = client.get("/api/whoami", cookies={"access_token": "valid-session"})
assert res.status_code == 200
assert res.json() == {
"id": "session-user",
"email": "session@test.local",
"system_role": "user",
"context_user_id": "session-user",
}
def test_auth_disabled_does_not_clobber_internal_auth_identity(monkeypatch):
from app.gateway.internal_auth import create_internal_auth_headers
from deerflow.runtime.user_context import DEFAULT_USER_ID
monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
client = TestClient(_make_app())
res = client.get(
"/api/current-user-from-dep",
headers=create_internal_auth_headers(),
)
assert res.status_code == 200
assert res.json() == {
"id": DEFAULT_USER_ID,
"state_id": DEFAULT_USER_ID,
"auth_source": "internal",
"context_user_id": DEFAULT_USER_ID,
}
def test_auth_disabled_skips_csrf_for_state_changing_requests(monkeypatch):
monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
client = TestClient(_make_auth_csrf_app())
res = client.post("/api/threads/abc/runs/stream")
assert res.status_code == 200
assert res.json() == {"ok": True}
def test_auth_disabled_is_ignored_in_explicit_production_env(monkeypatch):
monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
monkeypatch.setenv("DEER_FLOW_ENV", "production")
client = TestClient(_make_app())
res = client.get("/api/models")
assert res.status_code == 401
def test_auth_disabled_startup_warning_when_effective(monkeypatch, caplog):
from app.gateway.auth_disabled import warn_if_auth_disabled_enabled
monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
monkeypatch.delenv("DEER_FLOW_ENV", raising=False)
monkeypatch.delenv("ENVIRONMENT", raising=False)
with caplog.at_level("WARNING", logger="app.gateway.auth_disabled"):
warn_if_auth_disabled_enabled()
assert "authentication is bypassed" in caplog.text
assert "e2e-user" in caplog.text
def test_auth_disabled_startup_warning_suppressed_in_explicit_production_env(monkeypatch, caplog):
from app.gateway.auth_disabled import warn_if_auth_disabled_enabled
monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
monkeypatch.setenv("ENVIRONMENT", "production")
with caplog.at_level("WARNING", logger="app.gateway.auth_disabled"):
warn_if_auth_disabled_enabled()
assert "authentication is bypassed" not in caplog.text
def test_protected_path_with_junk_cookie_rejected(client):
"""Junk cookie → 401. Middleware strictly validates the JWT now
(AUTH_TEST_PLAN test 7.5.8); it no longer silently passes bad
@@ -1,40 +0,0 @@
"""Tests for user-facing IM channel connection configuration."""
from deerflow.config.channel_connections_config import ChannelConnectionsConfig
def test_channel_connections_disabled_by_default():
config = ChannelConnectionsConfig()
assert config.enabled is False
assert config.slack.enabled is False
assert config.telegram.enabled is False
assert config.discord.enabled is False
def test_enabled_channel_connections_do_not_require_public_url_or_encryption_key():
config = ChannelConnectionsConfig.model_validate(
{
"enabled": True,
"telegram": {
"enabled": True,
"bot_username": "deerflow_bot",
},
"slack": {"enabled": True},
"discord": {"enabled": True},
}
)
assert config.enabled is True
assert config.provider_status("telegram") == {"enabled": True, "configured": True}
assert config.provider_status("slack") == {"enabled": True, "configured": True}
assert config.provider_status("discord") == {"enabled": True, "configured": True}
def test_provider_status_reports_disabled_and_unknown_providers():
config = ChannelConnectionsConfig.model_validate({"enabled": True})
assert config.provider_status("slack") == {"enabled": False, "configured": False}
assert config.provider_status("telegram") == {"enabled": False, "configured": False}
assert config.provider_status("discord") == {"enabled": False, "configured": False}
assert config.provider_status("unknown") == {"enabled": False, "configured": False}
@@ -1,202 +0,0 @@
"""Tests for per-user IM channel connection persistence."""
from __future__ import annotations
from datetime import UTC, datetime, timedelta
import pytest
from sqlalchemy import select
from deerflow.persistence.channel_connections import (
ChannelConnectionRepository,
ChannelConnectionRow,
ChannelCredentialCipher,
ChannelCredentialRow,
)
@pytest.fixture
async def repo(tmp_path):
from deerflow.persistence.engine import close_engine, get_session_factory, init_engine
url = f"sqlite+aiosqlite:///{tmp_path / 'channels.db'}"
await init_engine("sqlite", url=url, sqlite_dir=str(tmp_path))
try:
yield ChannelConnectionRepository(
get_session_factory(),
cipher=ChannelCredentialCipher.from_key("test-encryption-key"),
)
finally:
await close_engine()
class TestChannelConnectionRepository:
@pytest.mark.anyio
async def test_connections_are_listed_per_owner(self, repo):
alice = await repo.upsert_connection(
owner_user_id="alice",
provider="slack",
external_account_id="U-alice",
external_account_name="Alice",
workspace_id="T1",
workspace_name="Team One",
scopes=["chat:write"],
)
await repo.upsert_connection(
owner_user_id="bob",
provider="slack",
external_account_id="U-bob",
external_account_name="Bob",
workspace_id="T1",
workspace_name="Team One",
scopes=["chat:write"],
)
results = await repo.list_connections("alice")
assert [item["id"] for item in results] == [alice["id"]]
assert results[0]["owner_user_id"] == "alice"
assert results[0]["provider"] == "slack"
assert results[0]["scopes"] == ["chat:write"]
assert "encrypted_access_token" not in results[0]
@pytest.mark.anyio
async def test_upsert_connection_updates_existing_provider_identity(self, repo):
first = await repo.upsert_connection(
owner_user_id="alice",
provider="telegram",
external_account_id="42",
external_account_name="Alice",
workspace_id=None,
workspace_name=None,
status="pending",
)
second = await repo.upsert_connection(
owner_user_id="alice",
provider="telegram",
external_account_id="42",
external_account_name="Alice Telegram",
workspace_id=None,
workspace_name=None,
status="connected",
)
assert second["id"] == first["id"]
assert second["status"] == "connected"
assert second["external_account_name"] == "Alice Telegram"
assert len(await repo.list_connections("alice")) == 1
@pytest.mark.anyio
async def test_credentials_are_encrypted_at_rest_and_decrypted_by_repository(self, repo):
connection = await repo.upsert_connection(
owner_user_id="alice",
provider="slack",
external_account_id="U-alice",
workspace_id="T1",
)
expires_at = datetime.now(UTC) + timedelta(hours=1)
await repo.store_credentials(
connection["id"],
access_token="xoxb-secret-access-token",
refresh_token="secret-refresh-token",
token_type="Bearer",
expires_at=expires_at,
extra={"bot_user_id": "B123"},
)
async with repo.session_factory() as session:
row = (await session.execute(select(ChannelCredentialRow))).scalar_one()
assert row.encrypted_access_token is not None
assert "xoxb-secret-access-token" not in row.encrypted_access_token
assert "secret-refresh-token" not in (row.encrypted_refresh_token or "")
assert "B123" not in (row.encrypted_extra_json or "")
credentials = await repo.get_credentials(connection["id"])
assert credentials is not None
assert credentials["access_token"] == "xoxb-secret-access-token"
assert credentials["refresh_token"] == "secret-refresh-token"
assert credentials["token_type"] == "Bearer"
assert credentials["expires_at"] == expires_at
assert credentials["extra"] == {"bot_user_id": "B123"}
@pytest.mark.anyio
async def test_conversations_are_scoped_by_connection(self, repo):
alice = await repo.upsert_connection(
owner_user_id="alice",
provider="slack",
external_account_id="U-alice",
workspace_id="T1",
)
bob = await repo.upsert_connection(
owner_user_id="bob",
provider="slack",
external_account_id="U-bob",
workspace_id="T1",
)
await repo.set_thread_id(
connection_id=alice["id"],
owner_user_id="alice",
provider="slack",
external_conversation_id="C-shared",
external_topic_id="1710000000.000100",
thread_id="thread-alice",
)
await repo.set_thread_id(
connection_id=bob["id"],
owner_user_id="bob",
provider="slack",
external_conversation_id="C-shared",
external_topic_id="1710000000.000100",
thread_id="thread-bob",
)
assert await repo.get_thread_id(alice["id"], "C-shared", "1710000000.000100") == "thread-alice"
assert await repo.get_thread_id(bob["id"], "C-shared", "1710000000.000100") == "thread-bob"
@pytest.mark.anyio
async def test_disconnect_connection_revokes_owner_connection_and_removes_credentials(self, repo):
connection = await repo.upsert_connection(
owner_user_id="alice",
provider="telegram",
external_account_id="42",
)
await repo.store_credentials(connection["id"], access_token="secret-token")
disconnected = await repo.disconnect_connection(
connection_id=connection["id"],
owner_user_id="alice",
)
assert disconnected is True
async with repo.session_factory() as session:
connection_row = await session.get(ChannelConnectionRow, connection["id"])
credential_row = await session.get(ChannelCredentialRow, connection["id"])
assert connection_row is not None
assert connection_row.status == "revoked"
assert credential_row is None
assert (
await repo.find_connection_by_external_identity(
provider="telegram",
external_account_id="42",
)
is None
)
@pytest.mark.anyio
async def test_disconnect_connection_is_owner_scoped(self, repo):
connection = await repo.upsert_connection(
owner_user_id="alice",
provider="telegram",
external_account_id="42",
)
disconnected = await repo.disconnect_connection(
connection_id=connection["id"],
owner_user_id="bob",
)
assert disconnected is False
assert (await repo.list_connections("alice"))[0]["status"] == "connected"
@@ -1,287 +0,0 @@
"""Router tests for browser-connectable IM channels."""
from __future__ import annotations
from uuid import UUID
from _router_auth_helpers import make_authed_test_app
from fastapi.testclient import TestClient
from app.gateway.auth.models import User
from app.gateway.routers import channel_connections
from deerflow.config.channel_connections_config import ChannelConnectionsConfig
def _user() -> User:
return User(
id=UUID("11111111-2222-3333-4444-555555555555"),
email="alice@example.com",
password_hash="x",
system_role="user",
)
async def _make_repo(tmp_path):
from deerflow.persistence.channel_connections import ChannelConnectionRepository
from deerflow.persistence.engine import get_session_factory, init_engine
await init_engine("sqlite", url=f"sqlite+aiosqlite:///{tmp_path / 'router.db'}", sqlite_dir=str(tmp_path))
return ChannelConnectionRepository(get_session_factory())
def _make_app(config: ChannelConnectionsConfig, repo, channels_config: dict | None = None):
app = make_authed_test_app(user_factory=_user)
app.state.channel_connections_config = config
app.state.channel_connection_repo = repo
app.state.channels_config = channels_config or {}
app.include_router(channel_connections.router)
return app
def _enabled_connections_config() -> ChannelConnectionsConfig:
return ChannelConnectionsConfig.model_validate(
{
"enabled": True,
"telegram": {"enabled": True, "bot_username": "deerflow_bot"},
"slack": {"enabled": True},
"discord": {"enabled": True},
}
)
def _channels_config() -> dict:
return {
"telegram": {"enabled": True, "bot_token": "telegram-token"},
"slack": {"enabled": True, "bot_token": "xoxb-operator", "app_token": "xapp-operator"},
"discord": {"enabled": True, "bot_token": "discord-bot"},
}
def test_get_providers_uses_existing_channels_config(tmp_path):
import anyio
repo = anyio.run(_make_repo, tmp_path)
app = _make_app(_enabled_connections_config(), repo, _channels_config())
with TestClient(app) as client:
response = client.get("/api/channels/providers")
assert response.status_code == 200
body = response.json()
assert body["enabled"] is True
by_provider = {item["provider"]: item for item in body["providers"]}
assert by_provider["telegram"]["configured"] is True
assert by_provider["telegram"]["auth_mode"] == "deep_link"
assert by_provider["slack"]["configured"] is True
assert by_provider["slack"]["auth_mode"] == "binding_code"
assert by_provider["discord"]["configured"] is True
assert by_provider["discord"]["auth_mode"] == "binding_code"
anyio.run(repo.close)
def test_get_providers_reports_unconfigured_when_runtime_channel_is_missing(tmp_path):
import anyio
repo = anyio.run(_make_repo, tmp_path)
app = _make_app(_enabled_connections_config(), repo, {"telegram": {"enabled": True, "bot_token": "telegram-token"}})
with TestClient(app) as client:
response = client.get("/api/channels/providers")
assert response.status_code == 200
by_provider = {item["provider"]: item for item in response.json()["providers"]}
assert by_provider["telegram"]["configured"] is True
assert by_provider["slack"]["configured"] is False
assert by_provider["slack"]["connectable"] is False
assert "channels.slack" in by_provider["slack"]["unavailable_reason"]
assert by_provider["discord"]["configured"] is False
assert "channels.discord" in by_provider["discord"]["unavailable_reason"]
anyio.run(repo.close)
def test_get_connections_returns_current_user_connections_only(tmp_path):
import anyio
repo = anyio.run(_make_repo, tmp_path)
async def seed_connections():
await repo.upsert_connection(
owner_user_id=str(_user().id),
provider="telegram",
external_account_id="42",
external_account_name="Alice",
status="connected",
)
await repo.upsert_connection(
owner_user_id="other-user",
provider="telegram",
external_account_id="99",
external_account_name="Bob",
status="connected",
)
anyio.run(seed_connections)
app = _make_app(_enabled_connections_config(), repo, _channels_config())
with TestClient(app) as client:
response = client.get("/api/channels/connections")
assert response.status_code == 200
body = response.json()
assert len(body["connections"]) == 1
assert body["connections"][0]["provider"] == "telegram"
assert body["connections"][0]["external_account_id"] == "42"
anyio.run(repo.close)
def test_connect_telegram_returns_deep_link_and_persists_state(tmp_path):
import anyio
repo = anyio.run(_make_repo, tmp_path)
app = _make_app(_enabled_connections_config(), repo, _channels_config())
with TestClient(app) as client:
response = client.post("/api/channels/telegram/connect")
assert response.status_code == 200
body = response.json()
assert body["provider"] == "telegram"
assert body["mode"] == "deep_link"
assert body["url"].startswith("https://t.me/deerflow_bot?start=")
assert body["code"]
assert "/start" in body["instruction"]
async def count_states():
return await repo.count_oauth_states(owner_user_id=str(_user().id), provider="telegram")
assert anyio.run(count_states) == 1
anyio.run(repo.close)
def test_connect_slack_returns_binding_command_and_persists_state(tmp_path):
import anyio
repo = anyio.run(_make_repo, tmp_path)
app = _make_app(_enabled_connections_config(), repo, _channels_config())
with TestClient(app) as client:
response = client.post("/api/channels/slack/connect")
assert response.status_code == 200
body = response.json()
assert body["provider"] == "slack"
assert body["mode"] == "binding_code"
assert body["url"] is None
assert body["code"]
assert body["instruction"] == f"Send /connect {body['code']} to the DeerFlow Slack bot."
async def count_states():
return await repo.count_oauth_states(owner_user_id=str(_user().id), provider="slack")
assert anyio.run(count_states) == 1
anyio.run(repo.close)
def test_connect_discord_returns_binding_command_and_persists_state(tmp_path):
import anyio
repo = anyio.run(_make_repo, tmp_path)
app = _make_app(_enabled_connections_config(), repo, _channels_config())
with TestClient(app) as client:
response = client.post("/api/channels/discord/connect")
assert response.status_code == 200
body = response.json()
assert body["provider"] == "discord"
assert body["mode"] == "binding_code"
assert body["url"] is None
assert body["code"]
assert body["instruction"] == f"Send /connect {body['code']} to the DeerFlow Discord bot."
async def count_states():
return await repo.count_oauth_states(owner_user_id=str(_user().id), provider="discord")
assert anyio.run(count_states) == 1
anyio.run(repo.close)
def test_connect_unconfigured_runtime_channel_returns_400(tmp_path):
import anyio
repo = anyio.run(_make_repo, tmp_path)
app = _make_app(_enabled_connections_config(), repo, {})
with TestClient(app) as client:
response = client.post("/api/channels/slack/connect")
assert response.status_code == 400
assert "channels.slack" in response.json()["detail"]
anyio.run(repo.close)
def test_disconnect_connection_revokes_current_user_connection(tmp_path):
import anyio
repo = anyio.run(_make_repo, tmp_path)
async def seed_connection():
connection = await repo.upsert_connection(
owner_user_id=str(_user().id),
provider="telegram",
external_account_id="42",
status="connected",
)
return connection["id"]
connection_id = anyio.run(seed_connection)
app = _make_app(_enabled_connections_config(), repo, _channels_config())
with TestClient(app) as client:
response = client.delete(f"/api/channels/connections/{connection_id}")
assert response.status_code == 204
async def get_connection_status():
return (await repo.list_connections(str(_user().id)))[0]["status"]
assert anyio.run(get_connection_status) == "revoked"
anyio.run(repo.close)
def test_disconnect_connection_is_current_user_scoped(tmp_path):
import anyio
repo = anyio.run(_make_repo, tmp_path)
async def seed_connection():
connection = await repo.upsert_connection(
owner_user_id="other-user",
provider="telegram",
external_account_id="42",
status="connected",
)
return connection["id"]
connection_id = anyio.run(seed_connection)
app = _make_app(_enabled_connections_config(), repo, _channels_config())
with TestClient(app) as client:
response = client.delete(f"/api/channels/connections/{connection_id}")
assert response.status_code == 404
async def get_connection_status():
return (await repo.list_connections("other-user"))[0]["status"]
assert anyio.run(get_connection_status) == "connected"
anyio.run(repo.close)
File diff suppressed because it is too large Load Diff
+3 -244
View File
@@ -2,9 +2,7 @@
import sys
import tomllib
from concurrent.futures import ThreadPoolExecutor
from pathlib import Path
from threading import Barrier, Event, Lock
from unittest.mock import AsyncMock, MagicMock, patch
import pytest
@@ -12,14 +10,12 @@ import pytest
import deerflow.config.app_config as app_config_module
from deerflow.config.checkpointer_config import (
CheckpointerConfig,
ensure_config_loaded,
get_checkpointer_config,
load_checkpointer_config_from_dict,
set_checkpointer_config,
)
from deerflow.runtime.checkpointer import get_checkpointer, reset_checkpointer
from deerflow.runtime.checkpointer.provider import POSTGRES_INSTALL
from deerflow.runtime.store import get_store, reset_store
from deerflow.runtime.store.provider import POSTGRES_STORE_INSTALL
@@ -29,90 +25,10 @@ def reset_state():
app_config_module._app_config = None
set_checkpointer_config(None)
reset_checkpointer()
reset_store()
yield
app_config_module._app_config = None
set_checkpointer_config(None)
reset_checkpointer()
reset_store()
class _BlockingSingletonContext:
def __init__(self, value: object, entered: Event, release: Event, stats: dict[str, object]):
self._value = value
self._entered = entered
self._release = release
self._stats = stats
def __enter__(self):
with self._stats["lock"]:
self._stats["enters"] += 1
self._entered.set()
assert self._release.wait(timeout=3), "timed out waiting to release singleton initialization"
return self._value
def __exit__(self, exc_type, exc, tb):
with self._stats["lock"]:
self._stats["exits"] += 1
return False
class _BlockingSingletonFactory:
def __init__(self):
self.value = object()
self.entered = Event()
self.release = Event()
self.stats = {"enters": 0, "exits": 0, "lock": Lock()}
def context_manager(self, _config):
return _BlockingSingletonContext(self.value, self.entered, self.release, self.stats)
def enter_count(self) -> int:
with self.stats["lock"]:
return self.stats["enters"]
def exit_count(self) -> int:
with self.stats["lock"]:
return self.stats["exits"]
class _TrackingLock:
def __init__(self):
self._lock = Lock()
self.acquired = Event()
def acquire(self, *args, **kwargs):
acquired = self._lock.acquire(*args, **kwargs)
if acquired:
self.acquired.set()
return acquired
def release(self):
self._lock.release()
def __enter__(self):
self.acquire()
return self
def __exit__(self, exc_type, exc, tb):
self.release()
return False
def locked(self) -> bool:
return self._lock.locked()
def _call_getter_concurrently(getter, workers: int = 8) -> list[object]:
ready = Barrier(workers + 1)
def worker():
ready.wait(timeout=3)
return getter()
with ThreadPoolExecutor(max_workers=workers) as executor:
futures = [executor.submit(worker) for _ in range(workers)]
ready.wait(timeout=3)
return [future.result(timeout=3) for future in futures]
# ---------------------------------------------------------------------------
@@ -151,26 +67,6 @@ class TestCheckpointerConfig:
set_checkpointer_config(None)
assert get_checkpointer_config() is None
def test_ensure_config_loaded_loads_app_config_when_uninitialized(self):
def fake_get_app_config():
load_checkpointer_config_from_dict({"type": "memory"})
with patch("deerflow.config.app_config.get_app_config", side_effect=fake_get_app_config) as mock_get_app_config:
ensure_config_loaded()
mock_get_app_config.assert_called_once()
config = get_checkpointer_config()
assert config is not None
assert config.type == "memory"
def test_ensure_config_loaded_skips_explicit_config(self):
load_checkpointer_config_from_dict({"type": "memory"})
with patch("deerflow.config.app_config.get_app_config") as mock_get_app_config:
ensure_config_loaded()
mock_get_app_config.assert_not_called()
def test_invalid_type_raises(self):
with pytest.raises(Exception):
load_checkpointer_config_from_dict({"type": "unknown"})
@@ -222,7 +118,7 @@ class TestGetCheckpointer:
"""get_checkpointer should return InMemorySaver when not configured."""
from langgraph.checkpoint.memory import InMemorySaver
with patch("deerflow.config.app_config.get_app_config", side_effect=FileNotFoundError):
with patch("deerflow.runtime.checkpointer.provider.get_app_config", side_effect=FileNotFoundError):
cp = get_checkpointer()
assert cp is not None
assert isinstance(cp, InMemorySaver)
@@ -391,143 +287,6 @@ class TestGetCheckpointer:
mock_saver_instance.setup.assert_called_once()
class TestSyncSingletonThreadSafety:
def test_store_reset_clears_singleton(self):
load_checkpointer_config_from_dict({"type": "memory"})
store1 = get_store()
reset_store()
store2 = get_store()
assert store1 is not store2
def test_concurrent_checkpointer_getter_creates_one_instance(self):
load_checkpointer_config_from_dict({"type": "memory"})
factory = _BlockingSingletonFactory()
with patch("deerflow.runtime.checkpointer.provider._sync_checkpointer_cm", side_effect=factory.context_manager):
futures_started = ThreadPoolExecutor(max_workers=1)
try:
result_future = futures_started.submit(_call_getter_concurrently, get_checkpointer)
assert factory.entered.wait(timeout=3)
factory.release.wait(timeout=0.05)
factory.release.set()
results = result_future.result(timeout=3)
finally:
futures_started.shutdown(wait=True)
assert all(result is factory.value for result in results)
assert factory.enter_count() == 1
def test_concurrent_store_getter_creates_one_instance(self):
load_checkpointer_config_from_dict({"type": "memory"})
factory = _BlockingSingletonFactory()
with patch("deerflow.runtime.store.provider._sync_store_cm", side_effect=factory.context_manager):
futures_started = ThreadPoolExecutor(max_workers=1)
try:
result_future = futures_started.submit(_call_getter_concurrently, get_store)
assert factory.entered.wait(timeout=3)
factory.release.wait(timeout=0.05)
factory.release.set()
results = result_future.result(timeout=3)
finally:
futures_started.shutdown(wait=True)
assert all(result is factory.value for result in results)
assert factory.enter_count() == 1
def test_checkpointer_loads_config_outside_singleton_lock(self):
tracking_lock = _TrackingLock()
def fake_ensure_config_loaded():
assert not tracking_lock.locked()
load_checkpointer_config_from_dict({"type": "memory"})
with (
patch("deerflow.runtime.checkpointer.provider._checkpointer_lock", tracking_lock),
patch("deerflow.runtime.checkpointer.provider.ensure_config_loaded", side_effect=fake_ensure_config_loaded),
):
checkpointer = get_checkpointer()
assert checkpointer is not None
assert tracking_lock.acquired.is_set()
def test_store_loads_config_outside_singleton_lock(self):
tracking_lock = _TrackingLock()
def fake_ensure_config_loaded():
assert not tracking_lock.locked()
load_checkpointer_config_from_dict({"type": "memory"})
with (
patch("deerflow.runtime.store.provider._store_lock", tracking_lock),
patch("deerflow.runtime.store.provider.ensure_config_loaded", side_effect=fake_ensure_config_loaded),
):
store = get_store()
assert store is not None
assert tracking_lock.acquired.is_set()
def test_checkpointer_reset_waits_for_initialization(self):
load_checkpointer_config_from_dict({"type": "memory"})
factory = _BlockingSingletonFactory()
with (
patch("deerflow.runtime.checkpointer.provider._sync_checkpointer_cm", side_effect=factory.context_manager),
ThreadPoolExecutor(max_workers=2) as executor,
):
get_future = executor.submit(get_checkpointer)
assert factory.entered.wait(timeout=3)
reset_started = Event()
def reset_worker():
reset_started.set()
reset_checkpointer()
reset_future = executor.submit(reset_worker)
assert reset_started.wait(timeout=3)
factory.release.wait(timeout=0.05)
assert not reset_future.done()
assert factory.exit_count() == 0
factory.release.set()
assert get_future.result(timeout=3) is factory.value
reset_future.result(timeout=3)
assert factory.exit_count() == 1
def test_store_reset_waits_for_initialization(self):
load_checkpointer_config_from_dict({"type": "memory"})
factory = _BlockingSingletonFactory()
with (
patch("deerflow.runtime.store.provider._sync_store_cm", side_effect=factory.context_manager),
ThreadPoolExecutor(max_workers=2) as executor,
):
get_future = executor.submit(get_store)
assert factory.entered.wait(timeout=3)
reset_started = Event()
def reset_worker():
reset_started.set()
reset_store()
reset_future = executor.submit(reset_worker)
assert reset_started.wait(timeout=3)
factory.release.wait(timeout=0.05)
assert not reset_future.done()
assert factory.exit_count() == 0
factory.release.set()
assert get_future.result(timeout=3) is factory.value
reset_future.result(timeout=3)
assert factory.exit_count() == 1
class TestAsyncCheckpointer:
@pytest.mark.anyio
async def test_sqlite_creates_parent_dir_via_to_thread(self):
@@ -747,7 +506,7 @@ class TestClientCheckpointerFallback:
patch("deerflow.client.get_app_config", return_value=config_mock),
patch("deerflow.client.create_agent", side_effect=fake_create_agent),
patch("deerflow.client.create_chat_model", return_value=MagicMock()),
patch("deerflow.client.build_middlewares", return_value=[]),
patch("deerflow.client._build_middlewares", return_value=[]),
patch("deerflow.client.apply_prompt_template", return_value=""),
patch("deerflow.client.DeerFlowClient._get_tools", return_value=[]),
):
@@ -781,7 +540,7 @@ class TestClientCheckpointerFallback:
patch("deerflow.client.get_app_config", return_value=config_mock),
patch("deerflow.client.create_agent", side_effect=fake_create_agent),
patch("deerflow.client.create_chat_model", return_value=MagicMock()),
patch("deerflow.client.build_middlewares", return_value=[]),
patch("deerflow.client._build_middlewares", return_value=[]),
patch("deerflow.client.apply_prompt_template", return_value=""),
patch("deerflow.client.DeerFlowClient._get_tools", return_value=[]),
):
+7 -7
View File
@@ -910,7 +910,7 @@ class TestEnsureAgent:
with (
patch("deerflow.client.create_chat_model"),
patch("deerflow.client.create_agent", return_value=mock_agent),
patch("deerflow.client.build_middlewares", return_value=[]) as mock_build_middlewares,
patch("deerflow.client._build_middlewares", return_value=[]) as mock_build_middlewares,
patch("deerflow.client.apply_prompt_template", return_value="prompt") as mock_apply_prompt,
patch.object(client, "_get_tools", return_value=[]),
patch("deerflow.runtime.checkpointer.get_checkpointer", return_value=MagicMock()),
@@ -935,7 +935,7 @@ class TestEnsureAgent:
with (
patch("deerflow.client.create_chat_model"),
patch("deerflow.client.create_agent", return_value=mock_agent) as mock_create_agent,
patch("deerflow.client.build_middlewares", return_value=[]),
patch("deerflow.client._build_middlewares", return_value=[]),
patch("deerflow.client.apply_prompt_template", return_value="prompt"),
patch.object(client, "_get_tools", return_value=[]),
patch("deerflow.runtime.checkpointer.get_checkpointer", return_value=mock_checkpointer),
@@ -960,7 +960,7 @@ class TestEnsureAgent:
with (
patch("deerflow.client.create_chat_model"),
patch("deerflow.client.create_agent", return_value=mock_agent) as mock_create_agent,
patch("deerflow.client.build_middlewares", side_effect=fake_build_middlewares),
patch("deerflow.client._build_middlewares", side_effect=fake_build_middlewares),
patch("deerflow.client.apply_prompt_template", return_value="prompt"),
patch.object(client, "_get_tools", return_value=[]),
patch("deerflow.runtime.checkpointer.get_checkpointer", return_value=MagicMock()),
@@ -979,7 +979,7 @@ class TestEnsureAgent:
with (
patch("deerflow.client.create_chat_model"),
patch("deerflow.client.create_agent", return_value=mock_agent) as mock_create_agent,
patch("deerflow.client.build_middlewares", return_value=[]),
patch("deerflow.client._build_middlewares", return_value=[]),
patch("deerflow.client.apply_prompt_template", return_value="prompt"),
patch.object(client, "_get_tools", return_value=[]),
patch("deerflow.runtime.checkpointer.get_checkpointer", return_value=None),
@@ -1957,7 +1957,7 @@ class TestScenarioAgentRecreation:
with (
patch("deerflow.client.create_chat_model"),
patch("deerflow.client.create_agent", side_effect=fake_create_agent),
patch("deerflow.client.build_middlewares", return_value=[]),
patch("deerflow.client._build_middlewares", return_value=[]),
patch("deerflow.client.apply_prompt_template", return_value="prompt"),
patch.object(client, "_get_tools", return_value=[]),
patch("deerflow.runtime.checkpointer.get_checkpointer", return_value=MagicMock()),
@@ -1985,7 +1985,7 @@ class TestScenarioAgentRecreation:
with (
patch("deerflow.client.create_chat_model"),
patch("deerflow.client.create_agent", side_effect=fake_create_agent),
patch("deerflow.client.build_middlewares", return_value=[]),
patch("deerflow.client._build_middlewares", return_value=[]),
patch("deerflow.client.apply_prompt_template", return_value="prompt"),
patch.object(client, "_get_tools", return_value=[]),
patch("deerflow.runtime.checkpointer.get_checkpointer", return_value=MagicMock()),
@@ -2010,7 +2010,7 @@ class TestScenarioAgentRecreation:
with (
patch("deerflow.client.create_chat_model"),
patch("deerflow.client.create_agent", side_effect=fake_create_agent),
patch("deerflow.client.build_middlewares", return_value=[]),
patch("deerflow.client._build_middlewares", return_value=[]),
patch("deerflow.client.apply_prompt_template", return_value="prompt"),
patch.object(client, "_get_tools", return_value=[]),
patch("deerflow.runtime.checkpointer.get_checkpointer", return_value=MagicMock()),
+2 -2
View File
@@ -144,14 +144,14 @@ def e2e_env(tmp_path, monkeypatch):
# non-determinism and cost to E2E tests (title generation is already
# disabled via TitleConfig above, but the middleware still participates
# in the chain and can interfere with event ordering).
from deerflow.agents.lead_agent.agent import build_middlewares as _original_build_middlewares
from deerflow.agents.lead_agent.agent import _build_middlewares as _original_build_middlewares
from deerflow.agents.middlewares.title_middleware import TitleMiddleware
def _sync_safe_build_middlewares(*args, **kwargs):
mws = _original_build_middlewares(*args, **kwargs)
return [m for m in mws if not isinstance(m, TitleMiddleware)]
monkeypatch.setattr("deerflow.client.build_middlewares", _sync_safe_build_middlewares)
monkeypatch.setattr("deerflow.client._build_middlewares", _sync_safe_build_middlewares)
return {"tmp_path": tmp_path}
@@ -1,45 +0,0 @@
"""Regression test for the Docker Compose default Gateway worker count.
The Gateway holds run state (RunManager and the stream bridge) in process, so
the default deployment must run a single Uvicorn worker. Running more than one
worker without a shared cross-worker stream bridge breaks run cancellation, SSE
reconnects, request de-duplication, and IM channels (nginx has no sticky
sessions, so requests scatter across workers that each keep their own run
state). This test pins the safe default so it cannot silently regress to a
multi-worker default, while still allowing operators to override it once a
shared stream bridge exists.
"""
from __future__ import annotations
import re
from pathlib import Path
import yaml
REPO_ROOT = Path(__file__).resolve().parents[2]
COMPOSE_PATH = REPO_ROOT / "docker" / "docker-compose.yaml"
def _gateway_command() -> str:
"""Return the gateway service command as a single string."""
compose = yaml.safe_load(COMPOSE_PATH.read_text(encoding="utf-8"))
command = compose["services"]["gateway"]["command"]
# ``command`` may load as a scalar string or a list depending on YAML style.
if isinstance(command, list):
command = " ".join(str(part) for part in command)
return command
def test_gateway_defaults_to_single_worker():
"""With GATEWAY_WORKERS unset, the worker count must default to 1."""
command = _gateway_command()
match = re.search(r"GATEWAY_WORKERS:-(\d+)", command)
assert match is not None, f"gateway command must set a GATEWAY_WORKERS default; got: {command}"
assert match.group(1) == "1", f"default Gateway worker count must be 1, got {match.group(1)}"
def test_gateway_worker_count_remains_overridable():
"""The worker count must stay configurable, not hard-coded to 1."""
command = _gateway_command()
assert "${GATEWAY_WORKERS:-1}" in command, f"worker count must use ${{GATEWAY_WORKERS:-1}} so operators can override it; got: {command}"
-12
View File
@@ -233,15 +233,3 @@ def test_non_auth_mutation_rejects_mismatched_double_submit_token():
assert response.status_code == 403
assert response.json()["detail"] == "CSRF token mismatch."
def test_channel_posts_require_double_submit_csrf():
client = TestClient(_make_app(), base_url="https://deerflow.example")
response = client.post(
"/api/channels/slack/connect",
headers={"Origin": "https://deerflow.example"},
)
assert response.status_code == 403
assert response.json()["detail"] == "CSRF token missing. Include X-CSRF-Token header."
-75
View File
@@ -1,75 +0,0 @@
"""Unit tests for the DDGS community web search tool."""
import json
import sys
from types import SimpleNamespace
from unittest.mock import MagicMock, patch
from deerflow.community.ddg_search import tools
def test_resolve_ddgs_region_maps_worldwide_chinese_query_for_wikipedia() -> None:
assert tools._resolve_ddgs_region("\u4e16\u754c\u676f\u65b0\u95fb 2026", "wt-wt", "auto") == "cn-zh"
def test_resolve_ddgs_region_uses_english_fallback_for_worldwide_query() -> None:
assert tools._resolve_ddgs_region("latest world cup news", "wt-wt", "auto") == "us-en"
def test_resolve_ddgs_region_preserves_worldwide_for_non_wikipedia_backend() -> None:
assert tools._resolve_ddgs_region("latest world cup news", "wt-wt", "duckduckgo") == "wt-wt"
def test_resolve_ddgs_region_maps_common_ddg_locale_aliases() -> None:
assert tools._resolve_ddgs_region("\u65e5\u672c \u30cb\u30e5\u30fc\u30b9", "jp-jp", "auto") == "jp-ja"
assert tools._resolve_ddgs_region("\ud55c\uad6d \ub274\uc2a4", "kr-kr", "auto") == "kr-ko"
assert tools._resolve_ddgs_region("\u53f0\u7063\u65b0\u805e", "tw-tzh", "auto") == "tw-zh"
def test_search_text_passes_wikipedia_safe_region_to_ddgs(monkeypatch) -> None:
calls = {}
class FakeDDGS:
def __init__(self, timeout: int) -> None:
calls["timeout"] = timeout
def text(self, query: str, **kwargs):
calls["query"] = query
calls.update(kwargs)
return [{"title": "Result", "href": "https://example.com", "body": "Snippet"}]
monkeypatch.setitem(sys.modules, "ddgs", SimpleNamespace(DDGS=FakeDDGS))
results = tools._search_text("\u4e16\u754c\u676f\u65b0\u95fb 2026", backend="auto")
assert results == [{"title": "Result", "href": "https://example.com", "body": "Snippet"}]
assert calls["timeout"] == 30
assert calls["region"] == "cn-zh"
assert calls["backend"] == "auto"
def test_web_search_tool_reads_ddgs_options_from_config() -> None:
with patch("deerflow.community.ddg_search.tools.get_app_config") as mock_config:
tool_config = MagicMock()
tool_config.model_extra = {
"max_results": 3,
"region": "us-en",
"safesearch": "off",
"backend": "auto",
}
mock_config.return_value.get_tool_config.return_value = tool_config
with patch("deerflow.community.ddg_search.tools._search_text") as mock_search:
mock_search.return_value = [{"title": "Result", "href": "https://example.com", "body": "Snippet"}]
result = tools.web_search_tool.invoke({"query": "latest news", "max_results": 8})
parsed = json.loads(result)
assert parsed["total_results"] == 1
mock_search.assert_called_once_with(
query="latest news",
max_results=3,
region="us-en",
safesearch="off",
backend="auto",
)
@@ -22,7 +22,7 @@ from langchain_core.tools import tool as as_tool
from deerflow.agents.middlewares.deferred_tool_filter_middleware import DeferredToolFilterMiddleware
from deerflow.skills.tool_policy import filter_tools_by_skill_allowed_tools
from deerflow.skills.types import Skill
from deerflow.tools.builtins.tool_search import DeferredToolSetup, assemble_deferred_tools, build_deferred_tool_setup
from deerflow.tools.builtins.tool_search import DeferredToolSetup, build_deferred_tool_setup
from deerflow.tools.mcp_metadata import tag_mcp_tool
@@ -93,15 +93,17 @@ def test_policy_excluded_mcp_tool_not_in_catalog():
def test_fail_closed_when_mcp_survives_without_setup(monkeypatch):
"""Finding 2: simulate a wiring regression and assert it fails loudly.
``assemble_deferred_tools`` references ``build_deferred_tool_setup`` as a
module global, so patch it in ``tool_search`` (its home module).
``_assemble_deferred`` lazy-imports ``build_deferred_tool_setup`` from the
source module, so patch it there (not on the agent module).
"""
from deerflow.agents.lead_agent import agent as agentmod
monkeypatch.setattr(
"deerflow.tools.builtins.tool_search.build_deferred_tool_setup",
lambda tools, *, enabled: DeferredToolSetup(None, frozenset(), None),
)
with pytest.raises(RuntimeError, match="fail-closed"):
assemble_deferred_tools([tag_mcp_tool(mcp_secret)], enabled=True)
agentmod._assemble_deferred([tag_mcp_tool(mcp_secret)], enabled=True)
def test_subagent_reentry_does_not_touch_lead_state():
@@ -144,10 +146,12 @@ def _make_skill(allowed_tools):
def test_policy_denied_mcp_yields_no_tool_search_end_to_end():
"""An allowlist that denies the MCP tool gates it end-to-end: after the real
policy filter no MCP tool survives, so ``assemble_deferred_tools`` adds no
policy filter no MCP tool survives, so ``_assemble_deferred`` adds no
tool_search (and does not fail-closed, because no MCP tool leaked through)."""
from deerflow.agents.lead_agent import agent as agentmod
filtered = filter_tools_by_skill_allowed_tools([active_tool, tag_mcp_tool(mcp_secret)], [_make_skill(["active_tool"])])
final_tools, setup = assemble_deferred_tools(filtered, enabled=True)
final_tools, setup = agentmod._assemble_deferred(filtered, enabled=True)
assert [t.name for t in final_tools] == ["active_tool"]
assert "tool_search" not in {t.name for t in final_tools}
@@ -163,9 +167,11 @@ def test_tool_search_appended_after_policy_but_never_exposes_denied_tool():
is derived from the already policy-filtered list so it can never expose a
tool the allowlist denied. Locks that contract so the ordering cannot regress.
"""
from deerflow.agents.lead_agent import agent as agentmod
allowed = ["active_tool", "mcp_secret"] # permits the MCP tool, does NOT list tool_search
filtered = filter_tools_by_skill_allowed_tools([active_tool, tag_mcp_tool(mcp_secret)], [_make_skill(allowed)])
final_tools, setup = assemble_deferred_tools(filtered, enabled=True)
final_tools, setup = agentmod._assemble_deferred(filtered, enabled=True)
names = {t.name for t in final_tools}
assert "tool_search" in names # appended despite not being in the allowlist
-14
View File
@@ -40,20 +40,6 @@ def test_entrypoint_script_exists_and_is_posix_sh():
assert proc.returncode == 0, proc.stderr
def test_entrypoint_excludes_runtime_state_from_uvicorn_reload():
content = ENTRYPOINT.read_text(encoding="utf-8")
assert ': "${DEER_FLOW_HOME:=/app/backend/.deer-flow}"' in content
# sandbox must be created too, not just .deer-flow (#3459 / #3454).
assert 'mkdir -p "$DEER_FLOW_HOME" /app/backend/.deer-flow /app/backend/sandbox' in content
assert "--reload-include='*.yaml .env'" not in content
assert "--reload-include='*.yaml'" in content
assert "--reload-include='.env'" in content
assert "--reload-exclude=/app/backend/sandbox" in content
assert '--reload-exclude="$DEER_FLOW_HOME"' in content
assert "--reload-exclude=/app/backend/.deer-flow" in content
def test_no_uv_extras_yields_empty_flags():
proc = _run(None)
assert proc.returncode == 0
+1 -66
View File
@@ -2,13 +2,9 @@
from __future__ import annotations
from types import SimpleNamespace
import pytest
from app.channels.discord import DiscordChannel
from app.channels.manager import CHANNEL_CAPABILITIES
from app.channels.message_bus import InboundMessageType, MessageBus
from app.channels.message_bus import MessageBus
from app.channels.service import _CHANNEL_REGISTRY
@@ -25,64 +21,3 @@ def test_discord_channel_init() -> None:
channel = DiscordChannel(bus=bus, config={"bot_token": "token"})
assert channel.name == "discord"
def _make_discord_message(text: str):
return SimpleNamespace(
id=111,
content=text,
author=SimpleNamespace(id=123, bot=False, display_name="alice"),
guild=SimpleNamespace(id=321),
channel=SimpleNamespace(id=456),
add_reaction=lambda _emoji: None,
)
@pytest.mark.asyncio
async def test_discord_bot_mention_slash_skill_routes_as_chat() -> None:
bus = MessageBus()
channel = DiscordChannel(bus=bus, config={"bot_token": "token"})
captured = []
channel._running = True
channel._client = SimpleNamespace(user=SimpleNamespace(id=999, mention="<@999>"))
channel._discord_module = SimpleNamespace(Thread=type("FakeThread", (), {}))
channel._publish = captured.append
async def noop(*_args, **_kwargs):
return None
channel._start_typing = noop
channel._add_reaction = noop
await channel._on_message(_make_discord_message("<@999> /data-analysis analyze uploads/foo.csv"))
assert len(captured) == 1
inbound = captured[0]
assert inbound.text == "/data-analysis analyze uploads/foo.csv"
assert inbound.msg_type == InboundMessageType.CHAT
assert inbound.topic_id == "456"
@pytest.mark.asyncio
async def test_discord_bot_mention_known_command_routes_as_command() -> None:
bus = MessageBus()
channel = DiscordChannel(bus=bus, config={"bot_token": "token"})
captured = []
channel._running = True
channel._client = SimpleNamespace(user=SimpleNamespace(id=999, mention="<@999>"))
channel._discord_module = SimpleNamespace(Thread=type("FakeThread", (), {}))
channel._publish = captured.append
async def noop(*_args, **_kwargs):
return None
channel._start_typing = noop
channel._add_reaction = noop
await channel._on_message(_make_discord_message("<@999> /help"))
assert len(captured) == 1
inbound = captured[0]
assert inbound.text == "/help"
assert inbound.msg_type == InboundMessageType.COMMAND
assert inbound.topic_id == "456"
@@ -1,88 +0,0 @@
"""Discord connection routing tests."""
from __future__ import annotations
from datetime import UTC, datetime, timedelta
from unittest.mock import AsyncMock, MagicMock
import pytest
from app.channels.discord import DiscordChannel
from app.channels.message_bus import InboundMessage, MessageBus
@pytest.fixture
async def repo(tmp_path):
from deerflow.persistence.channel_connections import ChannelConnectionRepository, ChannelCredentialCipher
from deerflow.persistence.engine import close_engine, get_session_factory, init_engine
await init_engine("sqlite", url=f"sqlite+aiosqlite:///{tmp_path / 'discord.db'}", sqlite_dir=str(tmp_path))
try:
yield ChannelConnectionRepository(
get_session_factory(),
cipher=ChannelCredentialCipher.from_key("discord-secret"),
)
finally:
await close_engine()
@pytest.mark.anyio
async def test_discord_inbound_attaches_owner_identity_from_user_level_connection(repo):
connection = await repo.upsert_connection(
owner_user_id="alice",
provider="discord",
external_account_id="987",
external_account_name="Alice",
status="connected",
)
channel = DiscordChannel(
bus=MessageBus(),
config={"bot_token": "discord-bot", "connection_repo": repo},
)
inbound = InboundMessage(
channel_name="discord",
chat_id="C123",
user_id="987",
text="hello",
)
attached = await channel._attach_connection_identity(inbound, guild_id="G123")
assert attached.connection_id == connection["id"]
assert attached.owner_user_id == "alice"
assert attached.workspace_id is None
@pytest.mark.anyio
async def test_discord_connect_command_binds_gateway_identity(repo):
state = "discord-bind-code"
await repo.create_oauth_state(
owner_user_id="deerflow-user-1",
provider="discord",
state=state,
expires_at=datetime.now(UTC) + timedelta(minutes=5),
)
channel = DiscordChannel(
bus=MessageBus(),
config={"bot_token": "discord-bot", "connection_repo": repo},
)
message = MagicMock()
message.author.id = 987
message.author.display_name = "Alice"
message.guild.id = 123
message.guild.name = "Deer Guild"
message.channel.id = 456
message.channel.send = AsyncMock()
handled = await channel._bind_connection_from_connect_code(message, state)
connections = await repo.list_connections("deerflow-user-1")
assert handled is True
assert len(connections) == 1
assert connections[0]["provider"] == "discord"
assert connections[0]["external_account_id"] == "987"
assert connections[0]["external_account_name"] == "Alice"
assert connections[0]["workspace_id"] == "123"
assert connections[0]["workspace_name"] == "Deer Guild"
assert connections[0]["metadata"]["channel_id"] == "456"
message.channel.send.assert_awaited_once()
@@ -43,21 +43,6 @@ def test_service_launchers_always_use_gateway_runtime():
assert "LANGGRAPH_REWRITE" not in content, path
def test_local_dev_gateway_reload_excludes_runtime_state_with_absolute_dirs():
serve_sh = _read("scripts/serve.sh")
assert 'export DEER_FLOW_PROJECT_ROOT="$REPO_ROOT"' in serve_sh
assert 'BACKEND_RUNTIME_HOME="$REPO_ROOT/backend/.deer-flow"' in serve_sh
assert 'export DEER_FLOW_HOME="$BACKEND_RUNTIME_HOME"' in serve_sh
# Every absolute reload-exclude must be pre-created, including backend/sandbox
# (#3459 / #3454) — see test_uvicorn_reload_exclude.py for the mechanism.
assert 'mkdir -p "$DEER_FLOW_HOME" "$BACKEND_RUNTIME_HOME" "$REPO_ROOT/backend/sandbox"' in serve_sh
assert "--reload-exclude='$DEER_FLOW_HOME'" in serve_sh
assert "--reload-exclude='$BACKEND_RUNTIME_HOME'" in serve_sh
assert "--reload-exclude='sandbox/'" not in serve_sh
assert "--reload-exclude='.deer-flow/'" not in serve_sh
def test_backend_container_only_exposes_gateway_port():
dockerfile = _read("backend/Dockerfile")

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