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24 Commits

Author SHA1 Message Date
taohe 6a94b58ad1 Fix safe user id digest algorithm 2026-06-10 22:53:07 +08:00
taohe d06643d8a2 Align IM connections with local channels 2026-06-10 22:16:47 +08:00
taohe 92c185b90d Support local IM channel connections 2026-06-10 21:59:33 +08:00
taohe 9effa7be6d Merge remote-tracking branch 'origin/main' into codex/im-channel-connections 2026-06-10 21:42:12 +08:00
taohe 582bfda6f8 Harden dev service daemon startup 2026-06-10 21:41:40 +08:00
Xinmin Zeng 05ae4467ae fix(docker): default Gateway to a single worker to prevent multi-worker breakage (#3475)
The default `make up` started the Gateway with `--workers 4`, but run state
(RunManager and the stream bridge) is held in-process and nginx uses no sticky
sessions. With the default config, same-run requests scatter across workers that
each keep their own run state, breaking run cancellation (409), SSE reconnect
(hangs on heartbeats), multitask de-duplication, and IM channels (duplicate
replies). The shared cross-worker stream bridge does not exist yet.

Default GATEWAY_WORKERS to 1 so the out-of-the-box deployment is correct,
document the single-worker boundary in the README, and add a regression test
pinning the default while keeping it overridable. This is a stop-gap, not a
multi-worker implementation; the full fix (shared run state + stream bridge) is
tracked in #3191.

Refs #3239, #3260
2026-06-10 21:36:25 +08:00
taohe b66152c514 Use async channel connect flow 2026-06-10 21:34:29 +08:00
taohe 78fbc0abdb Fix dev startup and channel connect popup 2026-06-10 21:33:15 +08:00
taohe ec5ed185cd Merge remote-tracking branch 'origin/main' into codex/im-channel-connections
# Conflicts:
#	backend/app/channels/discord.py
#	backend/app/channels/manager.py
#	backend/app/channels/slack.py
#	backend/app/channels/telegram.py
2026-06-10 21:13:02 +08:00
taohe dbe3a3bb0d Add user-owned IM channel connections 2026-06-10 21:07:44 +08:00
DanielWalnut 2b795265e7 fix: align auth-disabled mode and mock history loading (#3471)
* fix: align auth-disabled mode and mock history loading

* fix: address auth-disabled review feedback

* test: cover auth-disabled backend contract

* style: format frontend tests

* fix: address follow-up review comments
2026-06-10 16:11:00 +08:00
Nan Gao a57d05fe0a fix runtime journal run lifecycle events (#3470) 2026-06-10 08:33:29 +08:00
Lucy Shen ae9e8bc0bf fix(sandbox): make missing sandbox.mounts host_path a loud ERROR (#3244) (#3250)
In Docker production deployments, LocalSandboxProvider runs inside the
deer-flow-gateway container, so any `sandbox.mounts[].host_path` from
config.yaml is resolved against the gateway container's filesystem — not
the host machine. When the path isn't also bind-mounted into the gateway
service, the mount was silently dropped with only a WARNING log, leaving
agents reading an empty directory in production while the same config
worked under `make dev`.

Escalate the missing-host_path branch to logger.error with explicit
guidance about Docker bind mounts and docker-compose, so the failure is
hard to miss in default log configurations. Skip behaviour is preserved
to avoid breaking existing deployments.

Also clarify the misleading `VolumeMountConfig.host_path` field
description so it documents reality for both providers:

  - LocalSandboxProvider checks host_path from inside the gateway process
    (host in `make dev`, container in `make up`).
  - AioSandboxProvider (DooD) passes host_path straight to `docker -v`
    for the sandbox container, where the host Docker daemon resolves it
    from the host machine's perspective.

config.example.yaml's `sandbox.mounts` comment gets a Note: block
pointing operators at the docker-compose bind-mount requirement so the
Docker-mode gotcha is discoverable from the canonical template.

Adds a regression test that:
  - confirms missing host_path is still skipped (no behaviour break);
  - asserts an ERROR record is emitted referencing the offending paths;
  - asserts the message contains actionable Docker/gateway/docker-compose
    keywords so future refactors can't quietly downgrade it.

Refs: https://github.com/bytedance/deer-flow/issues/3244
2026-06-09 23:16:14 +08:00
DanielWalnut 16391e35ab fix(skills): harden slash skill activation across chat channels (#3466)
* support slash skill activation

* format slash skill activation

* Preserve slash skill activation with uploads

* Address slash skill review feedback

* Address slash skill follow-up review

* Fix lazy slash skill storage resolution

* Keep slash skill activation out of system prompt

* Address slash skill review issues

* fix: harden slash skill command handling

* feat(frontend): add slash skill autocomplete

* fix: address slash skill review feedback

* fix: preserve slash skill text for IM uploads
2026-06-09 23:07:17 +08:00
tanghang97 18bbb82f07 Fix 'make dev' failure in Windows environment (#3236)
* fix: Solving the problem of "make dev" failing to start in Windows environment

* fix: revert the change to the startup_config and fix the lint errors

* fix: Address Copilot review feedback

- Validate wait-for-port input and avoid PowerShell port interpolation
- Require Python 3 in serve.sh launcher detection
- Keep Windows event loop policy setup in sitecustomize only
- Clarify sitecustomize process-wide backend behavior
2026-06-09 22:37:54 +08:00
ly-wang19 b62c5a7b5b fix(agents): offload blocking filesystem IO in the custom-agent router off the event loop (#3457)
* fix(agents): offload blocking filesystem IO in delete_agent off the event loop

delete_agent is an async route handler but resolved the agent directory (Paths.base_dir -> Path.resolve), probed it (Path.exists), and removed it (shutil.rmtree) directly on the event loop, blocking it for the duration of every delete. Surfaced by 'make detect-blocking-io'.

Move the resolve/exists/rmtree sequence into a sync helper run via asyncio.to_thread, mapping its outcome back to the existing 404/409/500 responses (behavior unchanged). Adds a tests/blocking_io/ regression anchor under the strict Blockbuster gate, mirroring test_skills_load.py (#1917).

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* fix(agents): offload blocking filesystem IO in create_agent_endpoint too

Like delete_agent, the async create_agent_endpoint resolved and created the agent directory and wrote config.yaml + SOUL.md (with rmtree cleanup on failure) directly on the event loop. Move the whole create-or-409 sequence into a sync helper run via asyncio.to_thread; behavior is unchanged (201 / 409 / 500). Extends the blocking_io regression anchor to cover create as well as delete and renames it to test_agents_router.py.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

* Apply suggestions from code review

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>

---------

Co-authored-by: ly-wang19 <ly-wang19@users.noreply.github.com>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
2026-06-09 22:24:53 +08:00
Admire 5b81588b87 fix(frontend): fallback Streamdown clipboard copy (#3397)
* fix(frontend): fallback streamdown clipboard copy

* fix(frontend): address clipboard fallback review

* fix(frontend): normalize clipboard fallback rejection

* fix(frontend): harden clipboard fallback install

* fix(frontend): clarify clipboard fallback errors

* fix(frontend): cover clipboard fallback edge cases

* fix(frontend): tighten clipboard fallback cleanup

* fix(frontend): reduce clipboard fallback copy window

* fix(frontend): guard clipboard item fallback install

* fix(frontend): clean up clipboard fallback on selection errors

* Address clipboard fallback review feedback

* fix(frontend): guard clipboard fallback install during SSR
2026-06-09 22:09:13 +08:00
Nan Gao 63ce88f874 fix(replay-e2e): key fixtures by caller and conversation (#3453)
* add caller identity in replay e2e

* make format

* fix(replay-e2e): stabilize title caller replay

* fix(replay-e2e): use captured caller without run manager

---------

Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
2026-06-09 21:58:31 +08:00
hataa 37337b77f9 feat(models): add StepFun reasoning model adapter (#3461)
Add PatchedChatStepFun adapter for StepFun reasoning models (step-3.7-flash,
step-3.5-flash). Captures reasoning from both streaming and non-streaming
responses and replays it on historical assistant messages for multi-turn
tool-call conversations.

- New: PatchedChatStepFun adapter with streaming/non-streaming reasoning capture
- Support both reasoning and reasoning_content field names
- 17 unit tests covering all response paths
- Updated: config.example.yaml with StepFun configuration example
2026-06-09 18:01:43 +08:00
ly-wang19 8db16bb3d8 fix(config): coerce null config.yaml list sections to empty list (#3434)
Copying config.example.yaml to config.yaml and starting DeerFlow crashed with `pydantic ValidationError: models — Input should be a valid list [input_value=None]`, because the example ships every entry under `models:` commented out, so PyYAML parses the key as null. Reported in #1444.

Add a field_validator(mode="before") on AppConfig that coerces null models/tools/tool_groups to [] (matching their default_factory=list), and emit an actionable warning from from_file when no models are configured (pointing to config.example.yaml / make setup). Adds regression tests.

Closes #1444

Co-authored-by: ly-wang19 <ly-wang19@users.noreply.github.com>
Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
2026-06-09 15:45:28 +08:00
AochenShen99 93e3281cbf fix(dev): create backend/sandbox before uvicorn reload-exclude (#3459) (#3460)
* fix(dev): create backend/sandbox before uvicorn reload-exclude (#3459)

#3426 switched the dev gateway's --reload-exclude patterns to absolute
paths. uvicorn only excludes an absolute path directly when it already
exists as a directory; otherwise it globs the pattern, and Python 3.12's
pathlib raises NotImplementedError("Non-relative patterns are unsupported")
for an absolute glob pattern. serve.sh mkdir'd the .deer-flow excludes but
not backend/sandbox, so `make dev` crashed on startup on a fresh checkout
under Python 3.12 (#3454). docker/dev-entrypoint.sh had the same latent gap.

Create backend/sandbox in both launchers so every absolute exclude stays on
uvicorn's is_dir() short-circuit. Add a regression test that pins the uvicorn
mechanism (crash on missing dir, safe once created) and enforces that every
absolute --reload-exclude is mkdir'd before launch.

Closes #3459

* test(dev): harden reload-exclude invariant parser against false pass/negatives

The launcher invariant test parsed shell with a "mkdir -p" line filter and a
substring membership check. Two latent gaps (sub-threshold for this fix, but
this code guards a user-facing startup path, so close them):

- A `\`-continued multi-line `mkdir` would drop arguments on continuation
  lines, silently weakening coverage.
- Substring membership could false-pass when an exclude is a path-prefix of a
  different created dir (e.g. `/app/backend/sandbox` "found" inside
  `/app/backend/sandbox-other`).

Fold line-continuations, drop comments, and shlex-tokenize each `mkdir`
argument list into an exact set (quotes stripped, `$VAR` literal); assert exact
set membership. Same shlex handling for `--reload-exclude` values. Verified the
parser still flags the pre-fix missing `backend/sandbox` (RED preserved) and no
longer false-passes on a path-prefix.

* fix(dev): gitignore backend/sandbox runtime dir + pin mkdir-before-launch

Address two review findings on the #3459 fix:

- backend/sandbox was described as "gitignored runtime state" but no ignore
  rule actually matched it. Add an anchored `/sandbox/` to backend/.gitignore
  (anchored so it does NOT shadow the source package
  backend/packages/harness/deerflow/sandbox/) so sandbox artifacts created at
  runtime can't pollute the working tree or be committed by accident. New test
  asserts content under backend/sandbox is ignored, making the claim verifiable.

- The launcher invariant test only proved the sandbox mkdir exists somewhere,
  not that it runs before uvicorn starts. Add an order test (sandbox mkdir line
  must precede the `uv run uvicorn` launch) so a future edit can't move the
  mkdir below the launch and silently reintroduce the crash.

* Potential fix for pull request finding

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>

* test(dev): fix reload-exclude parser to handle serve.sh's quoted flag bundle

The previous autofix tokenized each whole line with shlex, but serve.sh packs
every flag into a single double-quoted `GATEWAY_EXTRA_FLAGS="..."` assignment.
shlex collapses that into one token, so no `--reload-exclude` flag is found and
`test_launcher_precreates_every_absolute_reload_exclude[scripts/serve.sh]`
failed CI with "expected at least one absolute reload-exclude".

Parse `--reload-exclude` with a regex that matches a balanced single/double
quoted group or a bare token, so the assignment's surrounding `"` is never
swallowed into the value. This recovers all three serve.sh excludes (the prior
regex also silently dropped the last `$BACKEND_RUNTIME_HOME` because the
adjacent closing quote broke shlex) while still covering dev-entrypoint.sh and
the space-separated `--reload-exclude <value>` form.

---------

Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
2026-06-09 15:29:40 +08:00
AochenShen99 0fb18e368c refactor(lead-agent): make build_middlewares public to drop the last cross-module private import (#3458)
`client.py` imported the private `_build_middlewares` from `agent.py` across a
module boundary and called it as public API. Because the `_` name signals
"module-private, no external callers", any future rename or signature change
silently breaks the embedded `DeerFlowClient` path — and the test suite even
monkeypatched `deerflow.client._build_middlewares`, baking the leak in.

`DeerFlowClient` is a lead-agent variant that genuinely needs the lead agent's
full middleware composition, so make the dependency honest: promote the helper
to a documented public entry point `build_middlewares` and update every in-repo
caller. Found during #3341 review; #3341 already removed one such leak
(`_assemble_deferred` -> public `assemble_deferred_tools`) and left this one out
of scope on purpose.

- agent.py: rename def + both internal call sites; expand the docstring into a
  public-entry-point contract and document the previously-undocumented
  model_name / app_config / deferred_setup params
- client.py: import + call site now use the public name (removes the last
  cross-module private import)
- scripts/tool-error-degradation-detection.sh: update its import + call site
- tests (5 files): update monkeypatch/patch targets and direct calls
- docs (backend/CLAUDE.md, plan_mode_usage.md, middlewares.mdx): sync the live
  references that describe the symbol as current API

Pure mechanical rename, no behavior change. Historical design docs (rfc,
superpowers spec) intentionally keep the old name as point-in-time records.

Closes #3431
2026-06-09 11:56:28 +08:00
Xinmin Zeng 90e23bfd09 fix(ci): consolidate PR/issue labeling and fix reviewing-job crash + label thrash (#3455)
* fix(ci): consolidate PR/issue labeling into one triage.yml; fix reviewing crash & label thrash

- Replace pr-labeler + pr-triage + issue-triage with a single triage.yml; drop actions/labeler.
  Its sync-labels removed labels outside its config (clobbered size/risk/needs-validation and
  could clobber maintainer labels). Area is now computed in-script and reconciled only within
  owned namespaces (area:/size//risk:/needs-validation); first-time/reviewing are add-only.
- reviewing: gate on author_association in {OWNER,MEMBER,COLLABORATOR} + user.type==='User'
  instead of getCollaboratorPermissionLevel, which 404'd on bot reviewers ('Copilot is not a
  user') and crashed the job. Excludes all review bots with no denylist and no API call.
- Read live state (listFiles + listLabelsOnIssue) not the stale event payload, so rapid
  synchronize events converge instead of thrashing. Size churn excludes lockfiles/snapshots.

* fix(ci): read labels live via paginate in reviewing & issue-triage jobs

Address review feedback on #3455:
- reviewing: listLabelsOnIssue now paginates (per_page:100) instead of the
  default 30, matching pr-labels, so a 'reviewing' label is never missed on
  PRs with many labels.
- issue-triage: read live labels via the API instead of the event payload,
  consistent with the live-state reads documented in the header.
2026-06-09 11:14:19 +08:00
Ryker_Feng f92a26d56f fix(web_fetch): support proxy for Jina reader in restricted networks (#3418) (#3430)
* fix(web_fetch): support proxy for Jina reader in restricted networks

The web_fetch tool built a bare httpx.AsyncClient() with no proxy
awareness, so users behind a corporate proxy / in Docker / WSL could
not reach https://r.jina.ai and web_fetch timed out.

- Add optional `proxy` / `trust_env` params to JinaClient.crawl and
  wire them from the `web_fetch` tool config (with type coercion for
  YAML string values).
- Pass internal service hostnames through NO_PROXY in both compose
  files so proxy env inherited via env_file does not break in-cluster
  calls (gateway/provisioner/etc).
- Load proxy vars from .env into the shell in scripts/docker.sh so the
  NO_PROXY interpolation can merge user-provided values on `make` path.
- Document proxy/trust_env options in config.example.yaml.

Closes #3418

* Potential fix for pull request finding

Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>

---------

Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
Co-authored-by: Copilot Autofix powered by AI <175728472+Copilot@users.noreply.github.com>
2026-06-08 23:25:29 +08:00
138 changed files with 9774 additions and 665 deletions
+1
View File
@@ -21,6 +21,7 @@ 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
View File
@@ -1,72 +0,0 @@
# 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
View File
@@ -1,44 +0,0 @@
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 #${issue_number}.`);
-28
View File
@@ -1,28 +0,0 @@
name: PR Labeler
# Applies area:* labels based on which files a PR changes (see .github/labeler.yml).
# Uses pull_request_target so it also works on fork PRs. SAFE: actions/labeler
# only reads the changed-file list via the API — it never checks out or runs PR code.
on:
pull_request_target:
types: [opened, synchronize, reopened, ready_for_review]
permissions:
contents: read
pull-requests: write
concurrency:
group: pr-labeler-${{ 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
View File
@@ -1,164 +0,0 @@
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 ${reviewer}).`);
} catch (e) {
// 403 is expected for review events on some fork PR contexts.
if (e.status === 403) core.info('No permission to label (expected on some fork PRs).');
else throw e;
}
+223
View File
@@ -0,0 +1,223 @@
name: Triage
# One workflow for all event-driven PR/issue labeling. Replaces the former
# pr-labeler / pr-triage / issue-triage workflows (and drops actions/labeler).
#
# Design notes:
# * All jobs are pure-metadata: they read changed-file lists / PR fields / the
# review payload via the API and write labels. PR code is NEVER checked out
# or executed, so pull_request_target is safe here.
# * Each job only reconciles labels in namespaces IT owns
# (area:* / size/* / risk:* / needs-validation). It never touches labels
# applied by maintainers or other tools (bug, priority, etc.). first-time-
# contributor and reviewing are add-only.
# * State is read LIVE (listFiles + listLabelsOnIssue) at run time, not from
# the (stale) event payload, so rapid synchronize events converge instead
# of thrashing.
on:
pull_request_target:
types: [opened, synchronize, reopened, ready_for_review]
pull_request_review:
types: [submitted]
issues:
types: [opened]
permissions:
contents: read
pull-requests: write
issues: write
jobs:
# ── PR: area / size / risk / needs-validation / first-time ─────────────────
pr-labels:
if: github.event_name == 'pull_request_target' && github.event.pull_request.draft == false
runs-on: ubuntu-latest
concurrency:
group: triage-pr-${{ 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
View File
@@ -247,6 +247,9 @@ 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
@@ -340,6 +343,8 @@ 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 |
@@ -585,6 +590,8 @@ 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
@@ -24,5 +24,10 @@ 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
+36 -22
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
@@ -202,16 +202,17 @@ 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. **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)
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)
### Configuration System
@@ -348,6 +349,7 @@ 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`)
@@ -367,8 +369,7 @@ Proxied through nginx: `/api/langgraph/*` → Gateway LangGraph-compatible runti
### IM Channels System (`app/channels/`)
Bridges external messaging platforms (Feishu, Slack, Telegram, DingTalk) to the DeerFlow agent via Gateway's LangGraph-compatible API.
Bridges external messaging platforms (Feishu, Slack, Telegram, Discord, 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.
@@ -378,18 +379,21 @@ Bridges external messaging platforms (Feishu, Slack, Telegram, DingTalk) to the
- `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` / `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)
- `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
**Message Flow**:
1. External platform -> Channel impl -> `MessageBus.publish_inbound()`
2. `ChannelManager._dispatch_loop()` consumes from queue
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
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
**Configuration** (`config.yaml` -> `channels`):
- `langgraph_url` - LangGraph-compatible Gateway API base URL (default: `http://localhost:8001/api`)
@@ -397,6 +401,16 @@ Bridges external messaging platforms (Feishu, Slack, Telegram, DingTalk) to the
- 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/`)
@@ -493,7 +507,7 @@ 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
@@ -18,3 +18,10 @@ 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
+2 -4
View File
@@ -14,7 +14,7 @@ from typing import Any
import httpx
from app.channels.base import Channel
from app.channels.commands import KNOWN_CHANNEL_COMMANDS
from app.channels.commands import is_known_channel_command
from app.channels.message_bus import InboundMessage, InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
logger = logging.getLogger(__name__)
@@ -59,9 +59,7 @@ def _normalize_allowed_users(allowed_users: Any) -> set[str]:
def _is_dingtalk_command(text: str) -> bool:
if not text.startswith("/"):
return False
return text.split(maxsplit=1)[0].lower() in KNOWN_CHANNEL_COMMANDS
return is_known_channel_command(text)
def _extract_text_from_rich_text(rich_text_list: list) -> str:
+91 -3
View File
@@ -10,13 +10,24 @@ from pathlib import Path
from typing import Any
from app.channels.base import Channel
from app.channels.message_bus import InboundMessageType, MessageBus, OutboundMessage, ResolvedAttachment
from app.channels.commands import is_known_channel_command
from app.channels.message_bus import InboundMessage, 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.
@@ -69,6 +80,7 @@ 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:
@@ -286,6 +298,10 @@ 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
@@ -300,7 +316,7 @@ 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 text.startswith("/") else InboundMessageType.CHAT
msg_type = InboundMessageType.COMMAND if is_known_channel_command(text) else InboundMessageType.CHAT
inbound = self._make_inbound(
chat_id=chat_id,
user_id=str(message.author.id),
@@ -314,6 +330,7 @@ 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:
@@ -407,7 +424,7 @@ class DiscordChannel(Channel):
chat_id = channel_id
typing_target = message.channel # Type into the channel
msg_type = InboundMessageType.COMMAND if text.startswith("/") else InboundMessageType.CHAT
msg_type = InboundMessageType.COMMAND if is_known_channel_command(text) else InboundMessageType.CHAT
inbound = self._make_inbound(
chat_id=chat_id,
user_id=str(message.author.id),
@@ -421,6 +438,7 @@ 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:
@@ -435,6 +453,76 @@ 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)
+2 -4
View File
@@ -11,7 +11,7 @@ import time
from typing import Any, Literal
from app.channels.base import Channel
from app.channels.commands import KNOWN_CHANNEL_COMMANDS
from app.channels.commands import is_known_channel_command
from app.channels.message_bus import (
PENDING_CLARIFICATION_METADATA_KEY,
RESOLVED_FROM_PENDING_CLARIFICATION_METADATA_KEY,
@@ -30,9 +30,7 @@ PENDING_CLARIFICATION_TTL_SECONDS = 30 * 60
def _is_feishu_command(text: str) -> bool:
if not text.startswith("/"):
return False
return text.split(maxsplit=1)[0].lower() in KNOWN_CHANNEL_COMMANDS
return is_known_channel_command(text)
class FeishuChannel(Channel):
+179 -32
View File
@@ -8,6 +8,7 @@ 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
@@ -26,8 +27,13 @@ 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__)
@@ -124,6 +130,16 @@ 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
@@ -410,6 +426,46 @@ 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.
@@ -614,6 +670,7 @@ 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
@@ -623,7 +680,9 @@ 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
@@ -671,12 +730,16 @@ class ChannelManager:
configurable["checkpoint_ns"] = ""
configurable["thread_id"] = thread_id
# ``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.
# ``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.
run_context_identity: dict[str, Any] = {"thread_id": thread_id}
if msg.user_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["channel_user_id"] = msg.user_id
run_context = _merge_dicts(
@@ -696,6 +759,21 @@ 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):
@@ -713,6 +791,11 @@ 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:
@@ -782,6 +865,14 @@ 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)",
@@ -792,10 +883,27 @@ class ChannelManager:
# -- chat handling -----------------------------------------------------
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"]
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
self.store.set_thread_id(
msg.channel_name,
msg.chat_id,
@@ -803,6 +911,12 @@ 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
@@ -812,7 +926,7 @@ 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 = self.store.get_thread_id(msg.channel_name, msg.chat_id, topic_id=msg.topic_id)
thread_id = await self._lookup_thread_id(msg)
if thread_id:
logger.info("[Manager] reusing thread: thread_id=%s for topic_id=%s", thread_id, msg.topic_id)
@@ -836,9 +950,11 @@ 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(
@@ -848,6 +964,7 @@ class ChannelManager:
assistant_id,
run_config,
run_context,
human_message,
)
return
@@ -856,7 +973,7 @@ class ChannelManager:
result = await client.runs.wait(
thread_id,
assistant_id,
input={"messages": [{"role": "human", "content": msg.text}]},
input={"messages": [human_message]},
config=run_config,
context=run_context,
multitask_strategy="reject",
@@ -896,6 +1013,8 @@ 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)
@@ -909,6 +1028,7 @@ 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])
@@ -924,7 +1044,7 @@ class ChannelManager:
async for chunk in client.runs.stream(
thread_id,
assistant_id,
input={"messages": [{"role": "human", "content": msg.text}]},
input={"messages": [human_message]},
config=run_config,
context=run_context,
stream_mode=["messages-tuple", "values"],
@@ -958,6 +1078,8 @@ 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),
)
)
@@ -1004,6 +1126,8 @@ 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),
)
)
@@ -1011,11 +1135,20 @@ class ChannelManager:
# -- command handling --------------------------------------------------
async def _handle_command(self, msg: InboundMessage) -> None:
text = msg.text.strip()
raw_text = msg.text
text = raw_text.strip()
parts = text.split(maxsplit=1)
command = parts[0].lower().lstrip("/")
reply: str | None = None
if not parts:
command = None
reply = _unknown_command_reply()
else:
command = parts[0].lower().removeprefix("/")
if command == "bootstrap":
if reply is None and not raw_text.startswith("/"):
reply = _unknown_command_reply(command)
if reply is None and command == "bootstrap":
from dataclasses import replace as _dc_replace
chat_text = parts[1] if len(parts) > 1 else "Initialize workspace"
@@ -1023,27 +1156,21 @@ class ChannelManager:
await self._handle_chat(chat_msg, extra_context={"is_bootstrap": True})
return
if command == "new":
if reply is None and command == "new":
# Create a new thread through Gateway
client = self._get_client()
thread = await client.threads.create()
new_thread_id = thread["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,
)
await self._store_thread_id(msg, new_thread_id)
reply = "New conversation started."
elif command == "status":
thread_id = self.store.get_thread_id(msg.channel_name, msg.chat_id, topic_id=msg.topic_id)
elif reply is None and command == "status":
thread_id = await self._lookup_thread_id(msg)
reply = f"Active thread: {thread_id}" if thread_id else "No active conversation."
elif command == "models":
elif reply is None and command == "models":
reply = await self._fetch_gateway("/api/models", "models")
elif command == "memory":
elif reply is None and command == "memory":
reply = await self._fetch_gateway("/api/memory", "memory")
elif command == "help":
elif reply is None and command == "help":
reply = (
"Available commands:\n"
"/bootstrap — Start a bootstrap session (enables agent setup)\n"
@@ -1051,18 +1178,36 @@ 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"
)
else:
available = " | ".join(sorted(KNOWN_CHANNEL_COMMANDS))
reply = f"Unknown command: /{command}. Available commands: {available}"
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)
outbound = OutboundMessage(
channel_name=msg.channel_name,
chat_id=msg.chat_id,
thread_id=self.store.get_thread_id(msg.channel_name, msg.chat_id) or "",
thread_id=await self._lookup_thread_id(msg) 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)
@@ -1098,9 +1243,11 @@ class ChannelManager:
outbound = OutboundMessage(
channel_name=msg.channel_name,
chat_id=msg.chat_id,
thread_id=self.store.get_thread_id(msg.channel_name, msg.chat_id) or "",
thread_id=await self._lookup_thread_id(msg) 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
@@ -44,6 +44,12 @@ 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.
@@ -56,6 +62,9 @@ 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)
@@ -95,6 +104,9 @@ 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.
"""
@@ -106,6 +118,8 @@ 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)
+33 -3
View File
@@ -52,6 +52,31 @@ 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.
@@ -59,9 +84,10 @@ class ChannelService:
instantiates enabled channels, and starts the ChannelManager dispatcher.
"""
def __init__(self, channels_config: dict[str, Any] | None = None) -> None:
def __init__(self, channels_config: dict[str, Any] | None = None, *, connection_repo: 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)
@@ -74,6 +100,7 @@ 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
@@ -90,8 +117,9 @@ class ChannelService:
# extra fields are allowed by AppConfig (extra="allow")
extra = app_config.model_extra or {}
if "channels" in extra:
channels_config = extra["channels"]
return cls(channels_config=channels_config)
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))
async def start(self) -> None:
"""Start the manager and all enabled channels."""
@@ -169,6 +197,8 @@ 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()
+179 -16
View File
@@ -9,6 +9,7 @@ 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__)
@@ -32,6 +33,30 @@ 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).
@@ -49,6 +74,10 @@ 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:
@@ -63,15 +92,35 @@ 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 = WebClient(token=bot_token)
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._socket_client = SocketModeClient(
app_token=app_token,
web_client=self._web_client,
@@ -96,7 +145,8 @@ class SlackChannel(Channel):
logger.info("Slack channel stopped")
async def send(self, msg: OutboundMessage, *, _max_retries: int = 3) -> None:
if not self._web_client:
web_client = await self._get_web_client_for_message(msg)
if not web_client:
return
kwargs: dict[str, Any] = {
@@ -109,11 +159,12 @@ class SlackChannel(Channel):
last_exc: Exception | None = None
for attempt in range(_max_retries):
try:
await asyncio.to_thread(self._web_client.chat_postMessage, **kwargs)
await asyncio.to_thread(web_client.chat_postMessage, **kwargs)
# Add a completion reaction to the thread root
if msg.thread_ts:
await asyncio.to_thread(
self._add_reaction,
self._add_reaction_with_client,
web_client,
msg.chat_id,
msg.thread_ts,
"white_check_mark",
@@ -137,7 +188,8 @@ class SlackChannel(Channel):
if msg.thread_ts:
try:
await asyncio.to_thread(
self._add_reaction,
self._add_reaction_with_client,
web_client,
msg.chat_id,
msg.thread_ts,
"x",
@@ -149,7 +201,8 @@ class SlackChannel(Channel):
raise last_exc
async def send_file(self, msg: OutboundMessage, attachment: ResolvedAttachment) -> bool:
if not self._web_client:
web_client = await self._get_web_client_for_message(msg)
if not web_client:
return False
try:
@@ -162,7 +215,7 @@ class SlackChannel(Channel):
if msg.thread_ts:
kwargs["thread_ts"] = msg.thread_ts
await asyncio.to_thread(self._web_client.files_upload_v2, **kwargs)
await asyncio.to_thread(web_client.files_upload_v2, **kwargs)
logger.info("[Slack] file uploaded: %s to channel=%s", attachment.filename, msg.chat_id)
return True
except Exception:
@@ -171,12 +224,23 @@ class SlackChannel(Channel):
# -- internal ----------------------------------------------------------
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
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:
try:
self._web_client.reactions_add(
web_client.reactions_add(
channel=channel_id,
timestamp=timestamp,
name=emoji,
@@ -185,6 +249,12 @@ 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:
@@ -210,17 +280,26 @@ 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)
self._handle_message_event(
event,
team_id=req.payload.get("team_id") or req.payload.get("team") or event.get("team"),
)
except Exception:
logger.exception("Error processing Slack event")
def _handle_message_event(self, event: dict) -> None:
def _handle_message_event(self, event: dict, *, team_id: str | None = None) -> None:
# Ignore bot messages
if event.get("bot_id") or event.get("subtype"):
return
@@ -233,13 +312,28 @@ 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 text.startswith("/"):
if is_known_channel_command(text):
msg_type = InboundMessageType.COMMAND
else:
msg_type = InboundMessageType.CHAT
@@ -261,4 +355,73 @@ 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)
asyncio.run_coroutine_threadsafe(self.bus.publish_inbound(inbound), self._loop)
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)
+119 -2
View File
@@ -35,6 +35,7 @@ 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:
@@ -60,12 +61,17 @@ 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))
@@ -171,6 +177,26 @@ 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:
@@ -228,10 +254,99 @@ 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:
@@ -243,7 +358,7 @@ class TelegramChannel(Channel):
if not self._check_user(update.effective_user.id):
return
text = update.message.text
text = self._strip_bot_username_from_leading_command(update.message.text.strip(), self._get_bot_username(context))
chat_id = str(update.effective_chat.id)
user_id = str(update.effective_user.id)
msg_id = str(update.message.message_id)
@@ -267,6 +382,7 @@ 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)
@@ -279,7 +395,7 @@ class TelegramChannel(Channel):
if not self._check_user(update.effective_user.id):
return
text = update.message.text.strip()
text = self._strip_bot_username_from_leading_command(update.message.text.strip(), self._get_bot_username(context))
if not text:
return
@@ -309,6 +425,7 @@ 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)
+2 -1
View File
@@ -22,6 +22,7 @@ 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__)
@@ -620,7 +621,7 @@ class WechatChannel(Channel):
chat_id=chat_id,
user_id=chat_id,
text=text,
msg_type=InboundMessageType.COMMAND if text.startswith("/") else InboundMessageType.CHAT,
msg_type=InboundMessageType.COMMAND if is_known_channel_command(text) else InboundMessageType.CHAT,
thread_ts=thread_ts,
files=files,
metadata={
+2 -1
View File
@@ -8,6 +8,7 @@ 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,
@@ -270,7 +271,7 @@ class WeComChannel(Channel):
user_id = (body.get("from") or {}).get("userid")
inbound_type = InboundMessageType.COMMAND if text.startswith("/") else InboundMessageType.CHAT
inbound_type = InboundMessageType.COMMAND if is_known_channel_command(text) else InboundMessageType.CHAT
inbound = self._make_inbound(
chat_id=user_id, # keep user's conversation in memory
user_id=user_id,
+6
View File
@@ -6,6 +6,7 @@ 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
@@ -15,6 +16,7 @@ from app.gateway.routers import (
artifacts,
assistants_compat,
auth,
channel_connections,
channels,
feedback,
mcp,
@@ -172,6 +174,7 @@ 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)
@@ -376,6 +379,9 @@ 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
@@ -0,0 +1,54 @@
"""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,
)
+39 -22
View File
@@ -17,6 +17,13 @@ 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
@@ -80,8 +87,38 @@ 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 None and not request.cookies.get("access_token"):
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:
return JSONResponse(
status_code=401,
content={
@@ -92,32 +129,12 @@ 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
@@ -14,6 +14,8 @@ 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
@@ -38,6 +40,9 @@ 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
@@ -331,6 +331,17 @@ 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
@@ -20,6 +20,7 @@ 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()
@@ -38,6 +39,9 @@ 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")
@@ -66,6 +70,9 @@ 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(
+70 -45
View File
@@ -1,5 +1,6 @@
"""CRUD API for custom agents."""
import asyncio
import logging
import re
import shutil
@@ -213,48 +214,61 @@ async def create_agent_endpoint(request: AgentCreateRequest) -> AgentResponse:
user_id = get_effective_user_id()
paths = get_paths()
agent_dir = paths.user_agent_dir(user_id, normalized_name)
legacy_dir = paths.agent_dir(normalized_name)
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)
if agent_dir.exists() or legacy_dir.exists():
raise HTTPException(status_code=409, detail=f"Agent '{normalized_name}' already exists")
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:
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
response = await asyncio.to_thread(_create_agent)
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)}")
if response is None:
raise HTTPException(status_code=409, detail=f"Agent '{normalized_name}' already exists")
return response
@router.put(
"/agents/{name}",
@@ -428,19 +442,30 @@ 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)
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")
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)
try:
shutil.rmtree(agent_dir)
logger.info(f"Deleted agent '{name}' from {agent_dir}")
outcome, agent_dir = await asyncio.to_thread(_remove_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
@@ -341,9 +341,19 @@ 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())
@@ -0,0 +1,294 @@
"""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,
)
+84
View File
@@ -0,0 +1,84 @@
# 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.
+10 -6
View File
@@ -50,18 +50,22 @@ gateway's own run/event stores using the request's auth context, so the real
## How replay works
`tests/replay_provider.py::ReplayChatModel` returns recorded assistant turns keyed
by a **normalized hash of the conversation** (human / ai / tool messages — role,
text, tool-call name+args; with `<system-reminder>`, dates, UUIDs, tmp paths
stripped). A miss raises loudly rather than passing silently.
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. (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
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**.
+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
@@ -49,6 +49,8 @@ from deerflow.tracing import build_tracing_callbacks
logger = logging.getLogger(__name__)
_BOOTSTRAP_SKILL_NAMES = {"bootstrap"}
def _get_runtime_config(config: RunnableConfig) -> dict:
"""Merge legacy configurable options with LangGraph runtime context."""
@@ -265,21 +267,31 @@ 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 middleware chain based on runtime configuration.
"""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``.
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.
@@ -293,6 +305,13 @@ 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:
@@ -360,7 +379,7 @@ def _build_middlewares(
def _available_skill_names(agent_config, is_bootstrap: bool) -> set[str] | None:
if is_bootstrap:
return {"bootstrap"}
return set(_BOOTSTRAP_SKILL_NAMES)
if agent_config and agent_config.skills is not None:
return set(agent_config.skills)
return None
@@ -466,17 +485,25 @@ 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)
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, app_config=resolved_app_config, deferred_setup=setup),
middleware=build_middlewares(
config,
model_name=model_name,
available_skills=set(_BOOTSTRAP_SKILL_NAMES),
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"]),
available_skills=set(_BOOTSTRAP_SKILL_NAMES),
app_config=resolved_app_config,
deferred_names=setup.deferred_names,
),
@@ -493,12 +520,19 @@ def _make_lead_agent(config: RunnableConfig, *, app_config: AppConfig):
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, app_config=resolved_app_config, deferred_setup=setup),
middleware=build_middlewares(
config,
model_name=model_name,
agent_name=agent_name,
available_skills=available_skills,
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=set(agent_config.skills) if agent_config and agent_config.skills is not None else None,
available_skills=available_skills,
app_config=resolved_app_config,
deferred_names=setup.deferred_names,
),
@@ -625,6 +625,11 @@ 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}
@@ -0,0 +1,289 @@
"""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)
@@ -13,6 +13,7 @@ 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__)
@@ -265,6 +266,8 @@ 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}"
@@ -285,7 +288,7 @@ class UploadsMiddleware(AgentMiddleware[UploadsMiddlewareState]):
content=updated_content,
id=last_message.id,
name=last_message.name,
additional_kwargs=last_message.additional_kwargs,
additional_kwargs=additional_kwargs,
)
messages[last_message_index] = updated_message
+10 -2
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 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
@@ -247,7 +247,15 @@ 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, custom_middlewares=self._middlewares, deferred_setup=deferred_setup),
"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,
),
"system_prompt": apply_prompt_template(
subagent_enabled=subagent_enabled,
max_concurrent_subagents=max_concurrent_subagents,
@@ -9,7 +9,7 @@ _api_key_warned = False
class JinaClient:
async def crawl(self, url: str, return_format: str = "html", timeout: int = 10) -> str:
async def crawl(self, url: str, return_format: str = "html", timeout: int = 10, proxy: str | None = None, trust_env: bool = True) -> str:
global _api_key_warned
headers = {
"Content-Type": "application/json",
@@ -23,7 +23,10 @@ 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:
async with httpx.AsyncClient() as client:
client_kwargs: dict[str, object] = {"trust_env": trust_env}
if proxy:
client_kwargs["proxy"] = proxy
async with httpx.AsyncClient(**client_kwargs) as client:
response = await client.post("https://r.jina.ai/", headers=headers, json=data, timeout=timeout)
if response.status_code != 200:
@@ -9,6 +9,38 @@ 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.
@@ -22,10 +54,14 @@ 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 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 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 isinstance(html_content, str) and html_content.startswith("Error:"):
return html_content
article = await asyncio.to_thread(readability_extractor.extract_article, html_content)
@@ -7,10 +7,11 @@ from typing import Any, Self
import yaml
from dotenv import load_dotenv
from pydantic import BaseModel, ConfigDict, Field
from pydantic import BaseModel, ConfigDict, Field, field_validator
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
@@ -116,6 +117,7 @@ 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")
@@ -148,6 +150,21 @@ 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.
@@ -209,6 +226,11 @@ 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
@@ -0,0 +1,49 @@
"""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),
}
@@ -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.sha1(raw.encode("utf-8")).hexdigest()[:_SAFE_USER_ID_DIGEST_HEX_LEN]
digest = hashlib.sha256(raw.encode("utf-8")).hexdigest()[:_SAFE_USER_ID_DIGEST_HEX_LEN]
return f"{sanitized}-{digest}"
@@ -4,7 +4,20 @@ from pydantic import BaseModel, ConfigDict, Field
class VolumeMountConfig(BaseModel):
"""Configuration for a volume mount."""
host_path: str = Field(..., description="Path on the host machine")
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."
),
)
container_path: str = Field(..., description="Path inside the container")
read_only: bool = Field(default=False, description="Whether the mount is read-only")
@@ -0,0 +1,175 @@
"""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,
)
@@ -0,0 +1,21 @@
"""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",
]
@@ -0,0 +1,111 @@
"""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",
),
)
@@ -0,0 +1,346 @@
"""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()
@@ -14,10 +14,26 @@ 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__ = ["FeedbackRow", "RunEventRow", "RunRow", "ThreadMetaRow", "UserRow"]
__all__ = [
"ChannelConnectionRow",
"ChannelConversationRow",
"ChannelCredentialRow",
"ChannelOAuthStateRow",
"FeedbackRow",
"RunEventRow",
"RunRow",
"ThreadMetaRow",
"UserRow",
]
@@ -164,7 +164,18 @@ class RunJournal(BaseCallbackHandler):
metadata={"caller": caller, **(metadata or {})},
)
def on_chain_end(self, outputs: Any, *, run_id: UUID, **kwargs: Any) -> None:
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
self._put(event_type="run.end", category="outputs", content=outputs, metadata={"status": "success"})
self._flush_sync()
@@ -147,7 +147,17 @@ class LocalSandboxProvider(SandboxProvider):
mount.container_path,
)
continue
# Ensure the host path exists before adding mapping
# 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.
if host_path.exists():
mappings.append(
PathMapping(
@@ -157,10 +167,16 @@ class LocalSandboxProvider(SandboxProvider):
)
)
else:
logger.warning(
"Mount host_path does not exist, skipping: %s -> %s",
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.",
mount.host_path,
mount.container_path,
mount.host_path,
)
except Exception as e:
# Log but don't fail if config loading fails
@@ -0,0 +1,65 @@
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),
)
@@ -0,0 +1,31 @@
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
@@ -36,6 +36,7 @@ dependencies = [
"sqlalchemy[asyncio]>=2.0,<3.0",
"aiosqlite>=0.19",
"alembic>=1.13",
"cryptography>=43.0.0",
]
[project.optional-dependencies]
+2 -1
View File
@@ -36,7 +36,8 @@ def main() -> int:
for index, turn in enumerate(turns):
data = turn["output"].get("data", {})
tool_calls = [tc.get("name") for tc in (data.get("tool_calls") or [])]
print(f" turn {index}: hash={turn['input_hash'][:12]} tool_calls={tool_calls} content={str(data.get('content'))[:50]!r}")
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
+25 -7
View File
@@ -28,27 +28,45 @@ 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 hash_messages
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, list] = {}
self.inputs: dict[str, tuple[list, str]] = {}
def on_chat_model_start(self, serialized, messages, *, run_id=None, **kwargs): # noqa: ANN001
self.inputs[str(run_id)] = messages[0] if messages else []
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
inp = self.inputs.pop(str(run_id), None)
if inp is None:
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 = {"input_hash": hash_messages(inp), "output": messages_to_dict([message])[0]}
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()
+26
View File
@@ -0,0 +1,26 @@
"""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()
+2 -1
View File
@@ -32,7 +32,8 @@ REPLAY_MODEL_BLOCK = """\
- name: scenario-model
display_name: Scenario Model
use: replay_provider:ReplayChatModel
model: replay"""
model: replay
supports_thinking: true"""
def real_model_block(model: str) -> str:
@@ -0,0 +1,64 @@
"""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({})
+16 -6
View File
@@ -12,7 +12,9 @@
},
"turns": [
{
"input_hash": "9c50eda6ab7e8593dabccbdeadc70a4a7bf778b2c0c3f275f1f96cf2c8ab58db",
"caller": "lead_agent",
"conversation_hash": "9c50eda6ab7e8593dabccbdeadc70a4a7bf778b2c0c3f275f1f96cf2c8ab58db",
"input_hash": "27aeb4c11bff2c3ebc182fe52a06556823c21928620a400c7f26be9733c31f3f",
"output": {
"type": "ai",
"data": {
@@ -56,7 +58,9 @@
}
},
{
"input_hash": "3598aeb87e221ca8f554e4d61ce6d5e8801754606fa5c95a89c38bd6cb623045",
"caller": "middleware:title",
"conversation_hash": "3598aeb87e221ca8f554e4d61ce6d5e8801754606fa5c95a89c38bd6cb623045",
"input_hash": "75101f9faa453b1a35deff920b1e3c1a9f0b013a7627fbbaa03436752776b953",
"output": {
"type": "ai",
"data": {
@@ -89,7 +93,9 @@
}
},
{
"input_hash": "6af134379b2a9efa01b4f63032f88211d5f38f459f8bed621eb6c65e8e05c1f9",
"caller": "lead_agent",
"conversation_hash": "6af134379b2a9efa01b4f63032f88211d5f38f459f8bed621eb6c65e8e05c1f9",
"input_hash": "f7468603a43d301fcc0167c2f7cd10e53137bfc584f1b3d776614b7a612ed7a6",
"output": {
"type": "ai",
"data": {
@@ -132,7 +138,9 @@
}
},
{
"input_hash": "04751c4f7b0107b78b5c97d417063883fd586f5ebcbc4acf79be6cb3c0cdaec1",
"caller": "lead_agent",
"conversation_hash": "04751c4f7b0107b78b5c97d417063883fd586f5ebcbc4acf79be6cb3c0cdaec1",
"input_hash": "218645dabc6926a1dbdf45dd20fba8a41e1e690cef78d7752566db3acf5a36ce",
"output": {
"type": "ai",
"data": {
@@ -165,7 +173,9 @@
}
},
{
"input_hash": "8b98ebdbb53e88f000556c4753adede8eaa076ff6fd7b8a1285bfd18aee8144d",
"caller": "suggest_agent",
"conversation_hash": "8b98ebdbb53e88f000556c4753adede8eaa076ff6fd7b8a1285bfd18aee8144d",
"input_hash": "dcd855d389d7179a1e4bc7074fa9ba7ce697570af8947225d6bacb538f14a0cb",
"output": {
"type": "ai",
"data": {
@@ -230,4 +240,4 @@
}
}
]
}
}
+137 -13
View File
@@ -2,14 +2,19 @@
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 **input** each call received::
keyed by a normalized hash of the **caller + input** each call received::
{
"scenario": "write_read_file",
"mode": "ultra",
"model": "gpt-5.5",
"turns": [
{"input_hash": "<sha256>", "input_preview": "...", "output": <message dict>},
{
"caller": "lead_agent",
"conversation_hash": "<sha256>",
"input_hash": "<sha256>",
"output": <message dict>,
},
...
]
}
@@ -21,8 +26,11 @@ A real run makes model calls from several callers — the lead agent's own turns
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. That keeps the in-graph, deterministic title call part of the
recording; memory/summarization, by contrast, are disabled in the replay config
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.
@@ -67,7 +75,7 @@ from collections import deque
from collections.abc import Iterator
from typing import Any
from langchain_core.callbacks import CallbackManagerForLLMRun
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
@@ -75,6 +83,14 @@ 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
@@ -94,6 +110,30 @@ 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.
@@ -172,10 +212,30 @@ def _canonical_messages(messages: list[BaseMessage]) -> str:
def hash_messages(messages: list[BaseMessage]) -> str:
"""Stable hash of a model call's input. Shared by recorder and replayer."""
"""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)
@@ -199,24 +259,54 @@ class ReplayChatModel(BaseChatModel):
_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)
super().__init__()
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 _match(self, messages: list[BaseMessage]) -> AIMessage:
key = hash_messages(messages)
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)
@@ -224,6 +314,7 @@ class ReplayChatModel(BaseChatModel):
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}"
)
@@ -236,7 +327,7 @@ class ReplayChatModel(BaseChatModel):
run_manager: CallbackManagerForLLMRun | None = None,
**kwargs: Any,
) -> ChatResult:
return ChatResult(generations=[ChatGeneration(message=self._match(messages))])
return ChatResult(generations=[ChatGeneration(message=self._match(messages, run_manager))])
def _stream(
self,
@@ -245,9 +336,16 @@ class ReplayChatModel(BaseChatModel):
run_manager: CallbackManagerForLLMRun | None = None,
**kwargs: Any,
) -> Iterator[ChatGenerationChunk]:
turn = self._match(messages)
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))
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
@@ -256,5 +354,31 @@ class ReplayChatModel(BaseChatModel):
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", "hash_messages", "replay_misses", "reset_replay_misses"]
__all__ = [
"ReplayChatModel",
"caller_identity",
"hash_input_key",
"hash_messages",
"hash_replay_input",
"replay_misses",
"reset_replay_misses",
]
+51
View File
@@ -140,6 +140,57 @@ 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"
+189 -4
View File
@@ -4,6 +4,7 @@ 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 ─────────────────────────────────────────────────
@@ -38,6 +39,8 @@ 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",
@@ -88,7 +91,9 @@ def test_unknown_api_path_is_protected():
def _make_app():
"""Create a minimal FastAPI app with AuthMiddleware for testing."""
from fastapi import FastAPI
from fastapi import FastAPI, Request
from deerflow.runtime.user_context import get_effective_user_id
app = FastAPI()
app.add_middleware(AuthMiddleware)
@@ -98,8 +103,16 @@ def _make_app():
return {"status": "ok"}
@app.get("/api/v1/auth/me")
async def auth_me():
return {"id": "1", "email": "test@test.com"}
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,
}
@app.get("/api/v1/auth/setup-status")
async def setup_status():
@@ -109,6 +122,29 @@ 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}
@@ -132,8 +168,24 @@ 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():
def client(monkeypatch):
monkeypatch.delenv("DEER_FLOW_AUTH_DISABLED", raising=False)
return TestClient(_make_app())
@@ -161,6 +213,139 @@ 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
@@ -0,0 +1,40 @@
"""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}
@@ -0,0 +1,202 @@
"""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"
@@ -0,0 +1,287 @@
"""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
+2 -2
View File
@@ -747,7 +747,7 @@ 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 +781,7 @@ 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}
@@ -0,0 +1,45 @@
"""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 ${{GATEWAY_WORKERS:-1}} so operators can override it; got: {command}"
+12
View File
@@ -233,3 +233,15 @@ def test_non_auth_mutation_rejects_mismatched_double_submit_token():
assert response.status_code == 403
assert response.json()["detail"] == "CSRF token mismatch."
def test_channel_posts_require_double_submit_csrf():
client = TestClient(_make_app(), base_url="https://deerflow.example")
response = client.post(
"/api/channels/slack/connect",
headers={"Origin": "https://deerflow.example"},
)
assert response.status_code == 403
assert response.json()["detail"] == "CSRF token missing. Include X-CSRF-Token header."
+2 -1
View File
@@ -44,7 +44,8 @@ def test_entrypoint_excludes_runtime_state_from_uvicorn_reload():
content = ENTRYPOINT.read_text(encoding="utf-8")
assert ': "${DEER_FLOW_HOME:=/app/backend/.deer-flow}"' in content
assert 'mkdir -p "$DEER_FLOW_HOME" /app/backend/.deer-flow' in content
# sandbox must be created too, not just .deer-flow (#3459 / #3454).
assert 'mkdir -p "$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
+66 -1
View File
@@ -2,9 +2,13 @@
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 MessageBus
from app.channels.message_bus import InboundMessageType, MessageBus
from app.channels.service import _CHANNEL_REGISTRY
@@ -21,3 +25,64 @@ 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"
@@ -0,0 +1,88 @@
"""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()
@@ -49,7 +49,9 @@ def test_local_dev_gateway_reload_excludes_runtime_state_with_absolute_dirs():
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="$BACKEND_RUNTIME_HOME"' in serve_sh
assert 'mkdir -p "$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
+170 -1
View File
@@ -8,7 +8,12 @@ import pytest
import deerflow.community.jina_ai.jina_client as jina_client_module
from deerflow.community.jina_ai.jina_client import JinaClient
from deerflow.community.jina_ai.tools import web_fetch_tool
from deerflow.community.jina_ai.tools import (
_coerce_bool,
_coerce_proxy,
_coerce_timeout,
web_fetch_tool,
)
@pytest.fixture
@@ -117,6 +122,59 @@ async def test_crawl_passes_headers(jina_client, monkeypatch):
assert captured_headers["X-Timeout"] == "30"
@pytest.mark.anyio
async def test_crawl_passes_proxy_to_httpx_client(jina_client, monkeypatch):
"""Explicit proxy config should be passed to httpx.AsyncClient."""
captured_client_kwargs = {}
class MockAsyncClient:
def __init__(self, **kwargs):
captured_client_kwargs.update(kwargs)
async def __aenter__(self):
return self
async def __aexit__(self, exc_type, exc, tb):
return None
async def post(self, url, **kwargs):
return httpx.Response(200, text="ok", request=httpx.Request("POST", url))
monkeypatch.setattr(httpx, "AsyncClient", MockAsyncClient)
result = await jina_client.crawl("https://example.com", proxy="http://127.0.0.1:7890")
assert result == "ok"
assert captured_client_kwargs["proxy"] == "http://127.0.0.1:7890"
assert captured_client_kwargs["trust_env"] is True
@pytest.mark.anyio
async def test_crawl_can_disable_trust_env(jina_client, monkeypatch):
"""Callers can disable environment proxy lookup for deterministic networking."""
captured_client_kwargs = {}
class MockAsyncClient:
def __init__(self, **kwargs):
captured_client_kwargs.update(kwargs)
async def __aenter__(self):
return self
async def __aexit__(self, exc_type, exc, tb):
return None
async def post(self, url, **kwargs):
return httpx.Response(200, text="ok", request=httpx.Request("POST", url))
monkeypatch.setattr(httpx, "AsyncClient", MockAsyncClient)
result = await jina_client.crawl("https://example.com", trust_env=False)
assert result == "ok"
assert captured_client_kwargs == {"trust_env": False}
@pytest.mark.anyio
async def test_crawl_includes_api_key_when_set(jina_client, monkeypatch):
"""Test that Authorization header is set when JINA_API_KEY is available."""
@@ -199,6 +257,60 @@ async def test_web_fetch_tool_returns_markdown_on_success(monkeypatch):
assert not result.startswith("Error:")
@pytest.mark.anyio
async def test_web_fetch_tool_forwards_proxy_and_trust_env(monkeypatch):
"""web_fetch tool config should be forwarded to JinaClient.crawl."""
captured_crawl_kwargs = {}
async def mock_crawl(self, url, **kwargs):
captured_crawl_kwargs.update(kwargs)
return "<html><body><p>Hello world</p></body></html>"
mock_config = MagicMock()
mock_tool_config = MagicMock()
mock_tool_config.model_extra = {
"timeout": "20",
"proxy": "http://host.docker.internal:7890",
"trust_env": "false",
}
mock_config.get_tool_config.return_value = mock_tool_config
monkeypatch.setattr("deerflow.community.jina_ai.tools.get_app_config", lambda: mock_config)
monkeypatch.setattr(JinaClient, "crawl", mock_crawl)
result = await web_fetch_tool.ainvoke("https://example.com")
assert "Hello world" in result
assert captured_crawl_kwargs == {
"return_format": "html",
"timeout": 20,
"proxy": "http://host.docker.internal:7890",
"trust_env": False,
}
@pytest.mark.anyio
async def test_web_fetch_tool_ignores_empty_proxy(monkeypatch):
"""Empty proxy values from unresolved env vars should not be passed to httpx."""
captured_crawl_kwargs = {}
async def mock_crawl(self, url, **kwargs):
captured_crawl_kwargs.update(kwargs)
return "<html><body><p>Hello world</p></body></html>"
mock_config = MagicMock()
mock_tool_config = MagicMock()
mock_tool_config.model_extra = {"proxy": " ", "trust_env": True}
mock_config.get_tool_config.return_value = mock_tool_config
monkeypatch.setattr("deerflow.community.jina_ai.tools.get_app_config", lambda: mock_config)
monkeypatch.setattr(JinaClient, "crawl", mock_crawl)
result = await web_fetch_tool.ainvoke("https://example.com")
assert "Hello world" in result
assert captured_crawl_kwargs["proxy"] is None
assert captured_crawl_kwargs["trust_env"] is True
@pytest.mark.anyio
async def test_web_fetch_tool_offloads_extraction_to_thread(monkeypatch):
"""Test that readability extraction is offloaded via asyncio.to_thread to avoid blocking the event loop."""
@@ -224,3 +336,60 @@ async def test_web_fetch_tool_offloads_extraction_to_thread(monkeypatch):
result = await web_fetch_tool.ainvoke("https://example.com")
assert to_thread_called, "extract_article must be called via asyncio.to_thread to avoid blocking the event loop"
assert "threaded" in result
@pytest.mark.parametrize(
("value", "default", "expected"),
[
(True, False, True),
(False, True, False),
("true", False, True),
("YES", False, True),
(" on ", False, True),
("1", False, True),
("false", True, False),
("No", True, False),
("off", True, False),
("0", True, False),
("maybe", True, True),
("maybe", False, False),
(None, True, True),
(123, False, False),
],
)
def test_coerce_bool(value, default, expected):
"""_coerce_bool normalizes booleans, known strings, and falls back to the default."""
assert _coerce_bool(value, default) is expected
@pytest.mark.parametrize(
("value", "default", "expected"),
[
(30, 10, 30),
("45", 10, 45),
("not-a-number", 10, 10),
(True, 10, 10),
(False, 10, 10),
(None, 10, 10),
(1.5, 10, 10),
],
)
def test_coerce_timeout(value, default, expected):
"""_coerce_timeout accepts ints and numeric strings, rejecting bools and junk."""
assert _coerce_timeout(value, default) == expected
@pytest.mark.parametrize(
("value", "expected"),
[
("http://127.0.0.1:7890", "http://127.0.0.1:7890"),
(" http://proxy:8080 ", "http://proxy:8080"),
("", None),
(" ", None),
(None, None),
(123, None),
],
)
def test_coerce_proxy(value, expected):
"""_coerce_proxy trims strings and treats empty/non-string values as None."""
assert _coerce_proxy(value) == expected
+9
View File
@@ -21,6 +21,7 @@ from langgraph_sdk import Auth
from app.gateway.auth.config import AuthConfig, set_auth_config
from app.gateway.auth.jwt import create_access_token, decode_token
from app.gateway.auth.models import User
from app.gateway.auth_disabled import AUTH_DISABLED_USER_ID
from app.gateway.langgraph_auth import add_owner_filter, authenticate
# ── Helpers ───────────────────────────────────────────────────────────────
@@ -59,6 +60,14 @@ def test_no_cookie_raises_401():
assert "Not authenticated" in str(exc.value.detail)
def test_auth_disabled_skips_csrf_and_authenticates_e2e_user(monkeypatch):
monkeypatch.setenv("DEER_FLOW_AUTH_DISABLED", "1")
identity = asyncio.run(authenticate(_req(method="POST")))
assert identity == AUTH_DISABLED_USER_ID
def test_invalid_jwt_raises_401():
with pytest.raises(Auth.exceptions.HTTPException) as exc:
asyncio.run(authenticate(_req({"access_token": "garbage"})))
@@ -56,7 +56,7 @@ def test_make_lead_agent_attaches_tracing_callbacks_at_graph_root(monkeypatch):
monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
monkeypatch.setattr(tools_module, "get_available_tools", lambda **kwargs: [])
monkeypatch.setattr(lead_agent_module, "_build_middlewares", lambda config, model_name, agent_name=None, **kwargs: [])
monkeypatch.setattr(lead_agent_module, "build_middlewares", lambda config, model_name, agent_name=None, **kwargs: [])
sentinel_handler = object()
monkeypatch.setattr(lead_agent_module, "build_tracing_callbacks", lambda: [sentinel_handler])
@@ -94,7 +94,7 @@ def test_internal_make_lead_agent_uses_explicit_app_config(monkeypatch):
monkeypatch.setattr(lead_agent_module, "get_app_config", _raise_get_app_config)
monkeypatch.setattr(tools_module, "get_available_tools", lambda **kwargs: [])
monkeypatch.setattr(lead_agent_module, "_build_middlewares", lambda config, model_name, agent_name=None, **kwargs: [])
monkeypatch.setattr(lead_agent_module, "build_middlewares", lambda config, model_name, agent_name=None, **kwargs: [])
captured: dict[str, object] = {}
@@ -128,7 +128,7 @@ def test_make_lead_agent_uses_runtime_app_config_from_context_without_global_rea
monkeypatch.setattr(lead_agent_module, "get_app_config", _raise_get_app_config)
monkeypatch.setattr(tools_module, "get_available_tools", lambda **kwargs: [])
monkeypatch.setattr(lead_agent_module, "_build_middlewares", lambda config, model_name, agent_name=None, **kwargs: [])
monkeypatch.setattr(lead_agent_module, "build_middlewares", lambda config, model_name, agent_name=None, **kwargs: [])
captured: dict[str, object] = {}
@@ -207,7 +207,7 @@ def test_make_lead_agent_disables_thinking_when_model_does_not_support_it(monkey
monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
monkeypatch.setattr(tools_module, "get_available_tools", lambda **kwargs: [])
monkeypatch.setattr(lead_agent_module, "_build_middlewares", lambda config, model_name, agent_name=None, **kwargs: [])
monkeypatch.setattr(lead_agent_module, "build_middlewares", lambda config, model_name, agent_name=None, **kwargs: [])
captured: dict[str, object] = {}
@@ -251,7 +251,7 @@ def test_make_lead_agent_reads_runtime_options_from_context(monkeypatch):
get_available_tools = MagicMock(return_value=[])
monkeypatch.setattr(lead_agent_module, "get_app_config", lambda: app_config)
monkeypatch.setattr(tools_module, "get_available_tools", get_available_tools)
monkeypatch.setattr(lead_agent_module, "_build_middlewares", lambda config, model_name, agent_name=None, **kwargs: [])
monkeypatch.setattr(lead_agent_module, "build_middlewares", lambda config, model_name, agent_name=None, **kwargs: [])
captured: dict[str, object] = {}
@@ -328,7 +328,7 @@ def test_build_middlewares_uses_resolved_model_name_for_vision(monkeypatch):
monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda **kwargs: None)
monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
middlewares = lead_agent_module._build_middlewares(
middlewares = lead_agent_module.build_middlewares(
{"configurable": {"model_name": "stale-model", "is_plan_mode": False, "subagent_enabled": False}},
model_name="vision-model",
custom_middlewares=[MagicMock()],
@@ -374,7 +374,7 @@ def test_build_middlewares_passes_explicit_app_config_to_shared_factory(monkeypa
lambda agent_name=None, *, memory_config: captured.setdefault("memory_config", memory_config) or "memory-middleware",
)
middlewares = lead_agent_module._build_middlewares(
middlewares = lead_agent_module.build_middlewares(
{"configurable": {"is_plan_mode": False, "subagent_enabled": False}},
model_name="safe-model",
app_config=app_config,
@@ -407,7 +407,7 @@ def test_build_middlewares_uses_loop_detection_config(monkeypatch):
monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda *, app_config=None: None)
monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
middlewares = lead_agent_module._build_middlewares(
middlewares = lead_agent_module.build_middlewares(
{"configurable": {"is_plan_mode": False, "subagent_enabled": False}},
model_name="safe-model",
app_config=app_config,
@@ -433,7 +433,7 @@ def test_build_middlewares_omits_loop_detection_when_disabled(monkeypatch):
monkeypatch.setattr(lead_agent_module, "_create_summarization_middleware", lambda *, app_config=None: None)
monkeypatch.setattr(lead_agent_module, "_create_todo_list_middleware", lambda is_plan_mode: None)
middlewares = lead_agent_module._build_middlewares(
middlewares = lead_agent_module.build_middlewares(
{"configurable": {"is_plan_mode": False, "subagent_enabled": False}},
model_name="safe-model",
app_config=app_config,
+15 -4
View File
@@ -60,6 +60,17 @@ def test_get_skills_prompt_section_returns_all_when_available_skills_is_none(mon
assert "skill2" in result
def test_get_skills_prompt_section_includes_slash_activation_guidance(monkeypatch):
skills = [_make_skill("data-analysis")]
monkeypatch.setattr("deerflow.agents.lead_agent.prompt._get_enabled_skills", lambda: skills)
result = get_skills_prompt_section(available_skills={"data-analysis"})
assert "Explicit Slash Skill Activation" in result
assert "The runtime injects the activated skill content" in result
assert "do not call `read_file` for that SKILL.md again" in result
def test_get_skills_prompt_section_includes_self_evolution_rules(monkeypatch):
skills = [_make_skill("skill1")]
monkeypatch.setattr("deerflow.agents.lead_agent.prompt._get_enabled_skills", lambda: skills)
@@ -139,7 +150,7 @@ def test_make_lead_agent_empty_skills_passed_correctly(monkeypatch):
monkeypatch.setattr(lead_agent_module, "create_chat_model", lambda **kwargs: "model")
monkeypatch.setattr("deerflow.tools.get_available_tools", lambda **kwargs: [])
monkeypatch.setattr(lead_agent_module, "_load_enabled_skills_for_tool_policy", lambda available_skills, *, app_config: [])
monkeypatch.setattr(lead_agent_module, "_build_middlewares", lambda *args, **kwargs: [])
monkeypatch.setattr(lead_agent_module, "build_middlewares", lambda *args, **kwargs: [])
monkeypatch.setattr(lead_agent_module, "create_agent", lambda **kwargs: kwargs)
class MockModelConfig:
@@ -180,7 +191,7 @@ def test_make_lead_agent_filters_tools_from_available_skills(monkeypatch):
monkeypatch.setattr(lead_agent_module, "_resolve_model_name", lambda x=None, **kwargs: "default-model")
monkeypatch.setattr(lead_agent_module, "create_chat_model", lambda **kwargs: "model")
monkeypatch.setattr(lead_agent_module, "_build_middlewares", lambda *args, **kwargs: [])
monkeypatch.setattr(lead_agent_module, "build_middlewares", lambda *args, **kwargs: [])
monkeypatch.setattr(lead_agent_module, "apply_prompt_template", lambda **kwargs: "mock_prompt")
monkeypatch.setattr(lead_agent_module, "create_agent", lambda **kwargs: kwargs)
monkeypatch.setattr(lead_agent_module, "load_agent_config", lambda x: AgentConfig(name="test", skills=["restricted", "legacy"]))
@@ -203,7 +214,7 @@ def test_make_lead_agent_all_legacy_skills_preserve_all_tools(monkeypatch):
monkeypatch.setattr(lead_agent_module, "_resolve_model_name", lambda x=None, **kwargs: "default-model")
monkeypatch.setattr(lead_agent_module, "create_chat_model", lambda **kwargs: "model")
monkeypatch.setattr(lead_agent_module, "_build_middlewares", lambda *args, **kwargs: [])
monkeypatch.setattr(lead_agent_module, "build_middlewares", lambda *args, **kwargs: [])
monkeypatch.setattr(lead_agent_module, "apply_prompt_template", lambda **kwargs: "mock_prompt")
monkeypatch.setattr(lead_agent_module, "create_agent", lambda **kwargs: kwargs)
monkeypatch.setattr(lead_agent_module, "load_agent_config", lambda x: AgentConfig(name="test", skills=None))
@@ -227,7 +238,7 @@ def test_make_lead_agent_enforces_allowed_tools_when_skill_cache_is_cold(monkeyp
monkeypatch.setattr(lead_agent_module, "_resolve_model_name", lambda x=None, **kwargs: "default-model")
monkeypatch.setattr(lead_agent_module, "create_chat_model", lambda **kwargs: "model")
monkeypatch.setattr(lead_agent_module, "_build_middlewares", lambda *args, **kwargs: [])
monkeypatch.setattr(lead_agent_module, "build_middlewares", lambda *args, **kwargs: [])
monkeypatch.setattr(lead_agent_module, "apply_prompt_template", lambda **kwargs: "mock_prompt")
monkeypatch.setattr(lead_agent_module, "create_agent", lambda **kwargs: kwargs)
monkeypatch.setattr(lead_agent_module, "load_agent_config", lambda x: AgentConfig(name="test", skills=["restricted"]))
@@ -612,6 +612,54 @@ class TestLocalSandboxProviderMounts:
assert [m.container_path for m in provider._path_mappings] == ["/mnt/skills"]
def test_setup_path_mappings_logs_actionable_error_for_missing_host_path(self, tmp_path, caplog):
"""Regression for #3244.
When ``sandbox.mounts[].host_path`` is absent from the gateway process's
filesystem (the typical symptom in Docker production mode: host_path is a
host machine path that is not bind-mounted into the gateway container),
the mount is still skipped but the failure must be a hard-to-miss ERROR
log with explicit, actionable guidance about Docker bind mounts, not the
old DEBUG/WARNING that buried the silent failure.
"""
skills_dir = tmp_path / "skills"
skills_dir.mkdir()
missing_host_path = tmp_path / "does-not-exist"
from deerflow.config.sandbox_config import SandboxConfig, VolumeMountConfig
sandbox_config = SandboxConfig(
use="deerflow.sandbox.local:LocalSandboxProvider",
mounts=[
VolumeMountConfig(host_path=str(missing_host_path), container_path="/mnt/knowledge", read_only=True),
],
)
config = SimpleNamespace(
skills=SimpleNamespace(container_path="/mnt/skills", get_skills_path=lambda: skills_dir, use="deerflow.skills.storage.local_skill_storage:LocalSkillStorage"),
sandbox=sandbox_config,
)
with caplog.at_level("ERROR", logger="deerflow.sandbox.local.local_sandbox_provider"):
with patch("deerflow.config.get_app_config", return_value=config):
provider = LocalSandboxProvider()
# Silent-skip behaviour is preserved (no breaking change for existing deployments).
assert [m.container_path for m in provider._path_mappings] == ["/mnt/skills"]
# The failure must be observable at ERROR level and reference the offending paths.
error_records = [r for r in caplog.records if r.levelname == "ERROR"]
assert error_records, "expected an ERROR log when host_path is missing"
message = "\n".join(r.getMessage() for r in error_records)
assert str(missing_host_path) in message
assert "/mnt/knowledge" in message
# And it must include actionable Docker guidance so users don't lose hours
# to a silent empty-mount failure in production.
lowered = message.lower()
assert "docker" in lowered
assert "gateway" in lowered
assert "docker-compose" in lowered
def test_write_file_resolves_container_paths_in_content(self, tmp_path):
"""write_file should replace container paths in file content with local paths."""
data_dir = tmp_path / "data"
+305
View File
@@ -0,0 +1,305 @@
"""Tests for deerflow.models.patched_stepfun.PatchedChatStepFun."""
from __future__ import annotations
from unittest.mock import MagicMock, patch
from langchain_core.messages import AIMessage, AIMessageChunk, HumanMessage
def _make_model(**kwargs):
from deerflow.models.patched_stepfun import PatchedChatStepFun
return PatchedChatStepFun(
model="step-3.7-flash",
api_key="test-key",
base_url="https://api.stepfun.com/v1",
**kwargs,
)
# ---------------------------------------------------------------------------
# Basic properties
# ---------------------------------------------------------------------------
def test_is_lc_serializable_returns_true():
from deerflow.models.patched_stepfun import PatchedChatStepFun
assert PatchedChatStepFun.is_lc_serializable() is True
def test_lc_secrets_contains_stepfun_api_key_mapping():
model = _make_model()
assert model.lc_secrets["api_key"] == "STEPFUN_API_KEY"
assert model.lc_secrets["openai_api_key"] == "STEPFUN_API_KEY"
# ---------------------------------------------------------------------------
# _extract_reasoning helper
# ---------------------------------------------------------------------------
def test_extract_reasoning_from_dict_with_reasoning():
from deerflow.models.patched_stepfun import _extract_reasoning
assert _extract_reasoning({"reasoning": "thinking..."}) == "thinking..."
def test_extract_reasoning_from_dict_with_reasoning_content():
from deerflow.models.patched_stepfun import _extract_reasoning
assert _extract_reasoning({"reasoning_content": "thinking..."}) == "thinking..."
def test_extract_reasoning_prefers_reasoning_content_over_reasoning():
from deerflow.models.patched_stepfun import _extract_reasoning
result = _extract_reasoning({"reasoning_content": "deepseek", "reasoning": "native"})
assert result == "deepseek"
def test_extract_reasoning_missing_returns_sentinel():
from deerflow.models.patched_stepfun import _MISSING, _extract_reasoning
assert _extract_reasoning({}) is _MISSING
assert _extract_reasoning({"reasoning": None}) is _MISSING
# ---------------------------------------------------------------------------
# Request payload replay (_get_request_payload)
# ---------------------------------------------------------------------------
def test_reasoning_content_injected_into_assistant_tool_call_message():
model = _make_model()
human = HumanMessage(content="Check Beijing weather.")
ai = AIMessage(
content="",
additional_kwargs={"reasoning_content": "I need to call the weather tool."},
)
payload_message = {
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": "call_weather",
"type": "function",
"function": {"name": "get_weather", "arguments": '{"location":"Beijing"}'},
}
],
}
base_payload = {
"messages": [
{"role": "user", "content": "Check Beijing weather."},
payload_message,
]
}
with patch.object(type(model).__bases__[0], "_get_request_payload", return_value=base_payload):
with patch.object(model, "_convert_input") as mock_convert:
mock_convert.return_value = MagicMock(to_messages=lambda: [human, ai])
payload = model._get_request_payload([human, ai])
assert payload["messages"][1]["reasoning_content"] == "I need to call the weather tool."
def test_reasoning_content_is_noop_when_missing():
model = _make_model()
human = HumanMessage(content="hello")
ai = AIMessage(content="hi", additional_kwargs={})
base_payload = {
"messages": [
{"role": "user", "content": "hello"},
{"role": "assistant", "content": "hi"},
]
}
with patch.object(type(model).__bases__[0], "_get_request_payload", return_value=base_payload):
with patch.object(model, "_convert_input") as mock_convert:
mock_convert.return_value = MagicMock(to_messages=lambda: [human, ai])
payload = model._get_request_payload([human, ai])
assert "reasoning_content" not in payload["messages"][1]
# ---------------------------------------------------------------------------
# Streaming reasoning capture (_convert_chunk_to_generation_chunk)
# ---------------------------------------------------------------------------
def test_convert_chunk_captures_reasoning_field():
"""StepFun default format: delta.reasoning."""
model = _make_model()
chunk = model._convert_chunk_to_generation_chunk(
{"choices": [{"delta": {"role": "assistant", "reasoning": "I need "}}]},
AIMessageChunk,
{},
)
assert chunk is not None
assert chunk.message.additional_kwargs["reasoning_content"] == "I need "
def test_convert_chunk_captures_reasoning_content_field():
"""StepFun deepseek-style format: delta.reasoning_content."""
model = _make_model()
chunk = model._convert_chunk_to_generation_chunk(
{"choices": [{"delta": {"role": "assistant", "reasoning_content": "I need "}}]},
AIMessageChunk,
{},
)
assert chunk is not None
assert chunk.message.additional_kwargs["reasoning_content"] == "I need "
def test_convert_chunk_streams_reasoning_then_content():
"""Full streaming flow: reasoning deltas followed by content."""
model = _make_model()
first = model._convert_chunk_to_generation_chunk(
{"choices": [{"delta": {"role": "assistant", "reasoning": "I need "}}]},
AIMessageChunk,
{},
)
second = model._convert_chunk_to_generation_chunk(
{"choices": [{"delta": {"reasoning": "a tool."}}]},
AIMessageChunk,
{},
)
answer = model._convert_chunk_to_generation_chunk(
{"choices": [{"delta": {"content": "Done."}, "finish_reason": "stop"}], "model": "step-3.7-flash"},
AIMessageChunk,
{},
)
assert first is not None
assert second is not None
assert answer is not None
combined = first.message + second.message + answer.message
assert combined.additional_kwargs["reasoning_content"] == "I need a tool."
assert combined.content == "Done."
def test_convert_chunk_noop_when_no_reasoning():
model = _make_model()
chunk = model._convert_chunk_to_generation_chunk(
{"choices": [{"delta": {"content": "Hello."}, "finish_reason": "stop"}], "model": "step-3.7-flash"},
AIMessageChunk,
{},
)
assert chunk is not None
assert "reasoning_content" not in chunk.message.additional_kwargs
# ---------------------------------------------------------------------------
# Non-streaming reasoning capture (_create_chat_result)
# ---------------------------------------------------------------------------
def test_create_chat_result_extracts_reasoning_field():
"""StepFun default format: message.reasoning."""
model = _make_model()
response = {
"choices": [
{
"message": {
"role": "assistant",
"content": "The weather is sunny.",
"reasoning": "The tool returned sunny weather.",
},
"finish_reason": "stop",
}
],
"model": "step-3.7-flash",
}
result = model._create_chat_result(response)
message = result.generations[0].message
assert message.content == "The weather is sunny."
assert message.additional_kwargs["reasoning_content"] == "The tool returned sunny weather."
def test_create_chat_result_extracts_reasoning_content_field():
"""StepFun deepseek-style format: message.reasoning_content."""
model = _make_model()
response = {
"choices": [
{
"message": {
"role": "assistant",
"content": "The weather is sunny.",
"reasoning_content": "The tool returned sunny weather.",
},
"finish_reason": "stop",
}
],
"model": "step-3.7-flash",
}
result = model._create_chat_result(response)
message = result.generations[0].message
assert message.content == "The weather is sunny."
assert message.additional_kwargs["reasoning_content"] == "The tool returned sunny weather."
def test_create_chat_result_reads_reasoning_from_sdk_object():
"""When the response is a Pydantic model, reasoning is an attribute."""
model = _make_model()
class FakeMessage:
reasoning = "Reasoning stored on the SDK message object."
reasoning_content = None
model_extra = None
class FakeChoice:
message = FakeMessage()
class FakeResponse:
choices = [FakeChoice()]
def model_dump(self, **kwargs):
return {
"choices": [
{
"message": {
"role": "assistant",
"content": "Answer.",
},
"finish_reason": "stop",
}
],
"model": "step-3.7-flash",
}
result = model._create_chat_result(FakeResponse())
assert result.generations[0].message.additional_kwargs["reasoning_content"] == "Reasoning stored on the SDK message object."
def test_create_chat_result_noop_when_no_reasoning():
model = _make_model()
response = {
"choices": [
{
"message": {
"role": "assistant",
"content": "Hello!",
},
"finish_reason": "stop",
}
],
"model": "step-3.7-flash",
}
result = model._create_chat_result(response)
assert "reasoning_content" not in result.generations[0].message.additional_kwargs
+116
View File
@@ -0,0 +1,116 @@
from __future__ import annotations
import json
from pathlib import Path
from langchain_core.messages import AIMessage, HumanMessage, messages_to_dict
from replay_provider import ReplayChatModel, caller_identity, hash_messages, hash_replay_input
def _write_fixture(path: Path, turns: list[dict]) -> None:
path.write_text(
json.dumps(
{
"scenario": "unit",
"mode": "unit",
"model": "replay",
"prompt": "unit",
"context": {},
"turns": turns,
}
),
encoding="utf-8",
)
def test_replay_key_includes_caller_identity(tmp_path: Path):
messages = [HumanMessage(content="same conversation")]
lead_output = AIMessage(content="lead")
suggest_output = AIMessage(content="suggest")
fixture_path = tmp_path / "fixture.json"
_write_fixture(
fixture_path,
[
{
"caller": "lead_agent",
"conversation_hash": hash_messages(messages),
"input_hash": hash_replay_input(messages, caller="lead_agent"),
"output": messages_to_dict([lead_output])[0],
},
{
"caller": "suggest_agent",
"conversation_hash": hash_messages(messages),
"input_hash": hash_replay_input(messages, caller="suggest_agent"),
"output": messages_to_dict([suggest_output])[0],
},
],
)
model = ReplayChatModel(fixture=str(fixture_path))
assert model.invoke(messages, config={"run_name": "suggest_agent"}).content == "suggest"
assert model.invoke(messages, config={"run_name": "lead_agent"}).content == "lead"
def test_replay_supports_legacy_conversation_only_fixture(tmp_path: Path):
messages = [HumanMessage(content="legacy conversation")]
fixture_path = tmp_path / "legacy.json"
_write_fixture(
fixture_path,
[
{
"input_hash": hash_messages(messages),
"output": messages_to_dict([AIMessage(content="legacy")])[0],
}
],
)
model = ReplayChatModel(fixture=str(fixture_path))
assert model.invoke(messages, config={"run_name": "suggest_agent"}).content == "legacy"
def test_title_run_name_uses_middleware_caller_namespace(tmp_path: Path):
messages = [HumanMessage(content="title prompt")]
fixture_path = tmp_path / "fixture.json"
_write_fixture(
fixture_path,
[
{
"caller": "middleware:title",
"conversation_hash": hash_messages(messages),
"input_hash": hash_replay_input(messages, caller="middleware:title"),
"output": messages_to_dict([AIMessage(content="generated title")])[0],
}
],
)
model = ReplayChatModel(fixture=str(fixture_path))
assert caller_identity(name="title_agent") == "middleware:title"
assert model.invoke(messages, config={"run_name": "title_agent"}).content == "generated title"
def test_replay_uses_single_pending_capture_when_run_manager_is_missing(tmp_path: Path):
messages = [HumanMessage(content="title prompt")]
fixture_path = tmp_path / "fixture.json"
_write_fixture(
fixture_path,
[
{
"caller": "middleware:title",
"conversation_hash": hash_messages(messages),
"input_hash": hash_replay_input(messages, caller="middleware:title"),
"output": messages_to_dict([AIMessage(content="generated title")])[0],
}
],
)
model = ReplayChatModel(fixture=str(fixture_path))
model._run_callers["captured-run"] = caller_identity(name="title_agent", tags=["middleware:title"])
assert model._match(messages, run_manager=None).content == "generated title"
+4 -3
View File
@@ -179,15 +179,16 @@ class TestLifecycleCallbacks:
assert "run.end" in types
@pytest.mark.anyio
async def test_nested_chain_no_run_start(self, journal_setup):
"""Nested chains (parent_run_id set) should NOT produce run.start."""
async def test_nested_chain_no_run_lifecycle_events(self, journal_setup):
"""Nested chains (parent_run_id set) should NOT produce root run lifecycle events."""
j, store = journal_setup
parent_id = uuid4()
j.on_chain_start({}, {}, run_id=uuid4(), parent_run_id=parent_id)
j.on_chain_end({}, run_id=uuid4())
j.on_chain_end({}, run_id=uuid4(), parent_run_id=parent_id)
await j.flush()
events = await store.list_events("t1", "r1")
assert not any(e["event_type"] == "run.start" for e in events)
assert not any(e["event_type"] == "run.end" for e in events)
class TestToolCallbacks:
@@ -0,0 +1,96 @@
"""Slack connection tests for user-owned channel bindings."""
from __future__ import annotations
from datetime import UTC, datetime, timedelta
from unittest.mock import AsyncMock, MagicMock
from app.channels.message_bus import MessageBus, OutboundMessage
async def _make_repo(tmp_path):
from deerflow.persistence.channel_connections import ChannelConnectionRepository, ChannelCredentialCipher
from deerflow.persistence.engine import get_session_factory, init_engine
await init_engine("sqlite", url=f"sqlite+aiosqlite:///{tmp_path / 'slack.db'}", sqlite_dir=str(tmp_path))
return ChannelConnectionRepository(
get_session_factory(),
cipher=ChannelCredentialCipher.from_key("slack-secret"),
)
def test_slack_connect_command_binds_socket_mode_identity(tmp_path):
import anyio
from app.channels.slack import SlackChannel
async def go():
repo = await _make_repo(tmp_path)
state = "slack-bind-code"
await repo.create_oauth_state(
owner_user_id="deerflow-user-1",
provider="slack",
state=state,
expires_at=datetime.now(UTC) + timedelta(minutes=5),
)
channel = SlackChannel(
bus=MessageBus(),
config={"bot_token": "xoxb-operator", "app_token": "xapp-operator", "connection_repo": repo},
)
channel._web_client = MagicMock()
handled = await channel._bind_connection_from_connect_code(
event={
"user": "U123",
"channel": "C123",
"ts": "1710000000.000100",
},
team_id="T123",
code=state,
)
connections = await repo.list_connections("deerflow-user-1")
assert handled is True
assert len(connections) == 1
assert connections[0]["provider"] == "slack"
assert connections[0]["external_account_id"] == "U123"
assert connections[0]["workspace_id"] == "T123"
assert connections[0]["metadata"]["channel_id"] == "C123"
channel._web_client.chat_postMessage.assert_called_once()
await repo.close()
anyio.run(go)
def test_slack_send_uses_connection_bot_token_when_connection_id_is_present():
import anyio
from app.channels.slack import SlackChannel
async def go():
repo = AsyncMock()
repo.get_credentials.return_value = {"access_token": "xoxb-connection-token"}
web_client = MagicMock()
web_client_factory = MagicMock(return_value=web_client)
channel = SlackChannel(
bus=MessageBus(),
config={
"connection_repo": repo,
"web_client_factory": web_client_factory,
},
)
msg = OutboundMessage(
channel_name="slack",
chat_id="C123",
thread_id="thread-1",
text="hello",
connection_id="connection-1",
)
await channel.send(msg)
repo.get_credentials.assert_awaited_once_with("connection-1")
web_client_factory.assert_called_once_with(token="xoxb-connection-token")
web_client.chat_postMessage.assert_called_once()
anyio.run(go)
+557
View File
@@ -0,0 +1,557 @@
import asyncio
import hashlib
from pathlib import Path
from types import SimpleNamespace
from langchain.agents.middleware.types import ModelRequest
from langchain_core.messages import AIMessage, HumanMessage
from app.channels.commands import KNOWN_CHANNEL_COMMANDS
from deerflow.agents.middlewares import skill_activation_middleware as middleware_module
from deerflow.agents.middlewares.skill_activation_middleware import SkillActivationMiddleware, is_slash_skill_activation_reminder
from deerflow.skills.slash import RESERVED_SLASH_SKILL_NAMES, parse_slash_skill_reference, resolve_slash_skill
from deerflow.skills.types import Skill, SkillCategory
from deerflow.utils.messages import ORIGINAL_USER_CONTENT_KEY
def _make_skill(tmp_path: Path, name: str, content: str = "skill body") -> Skill:
skill_dir = tmp_path / name
skill_dir.mkdir()
skill_file = skill_dir / "SKILL.md"
skill_file.write_text(content, encoding="utf-8")
return Skill(
name=name,
description=f"Description for {name}",
license="MIT",
skill_dir=skill_dir,
skill_file=skill_file,
relative_path=Path(name),
category=SkillCategory.CUSTOM,
enabled=True,
)
def _make_storage(tmp_path: Path, skills: list[Skill]):
return SimpleNamespace(
load_skills=lambda *, enabled_only: [skill for skill in skills if skill.enabled] if enabled_only else skills,
get_container_root=lambda: "/mnt/skills",
get_skills_root_path=lambda: tmp_path,
)
def _make_model_request(messages: list[HumanMessage], *, runtime=None) -> ModelRequest:
return ModelRequest(
model=object(),
messages=messages,
state={"messages": list(messages)},
runtime=runtime,
)
def test_parse_slash_skill_reference_extracts_name_and_remaining_text():
parsed = parse_slash_skill_reference("/data-analysis analyze uploads/foo.csv")
assert parsed is not None
assert parsed.name == "data-analysis"
assert parsed.remaining_text == "analyze uploads/foo.csv"
def test_parse_slash_skill_reference_accepts_skill_name_without_task():
parsed = parse_slash_skill_reference("/data-analysis")
assert parsed is not None
assert parsed.name == "data-analysis"
assert parsed.remaining_text == ""
def test_parse_slash_skill_reference_rejects_invalid_names():
assert parse_slash_skill_reference("/DataAnalysis run") is None
assert parse_slash_skill_reference("/data_analysis run") is None
assert parse_slash_skill_reference("please use /data-analysis") is None
assert parse_slash_skill_reference(" /data-analysis run") is None
assert parse_slash_skill_reference("/data-analysis分析这个文档") is None
def test_resolve_slash_skill_ignores_reserved_control_commands(tmp_path):
for command in ["bootstrap", "help", "memory", "models", "new", "status"]:
skill = _make_skill(tmp_path, command)
assert resolve_slash_skill(f"/{command} create an agent", [skill]) is None
def test_reserved_slash_skill_names_match_channel_commands():
assert RESERVED_SLASH_SKILL_NAMES == {command.removeprefix("/") for command in KNOWN_CHANNEL_COMMANDS}
def test_resolve_slash_skill_respects_available_skill_whitelist(tmp_path):
skill = _make_skill(tmp_path, "data-analysis")
assert resolve_slash_skill("/data-analysis run", [skill], available_skills=set()) is None
resolved = resolve_slash_skill("/data-analysis run", [skill], available_skills={"data-analysis"})
assert resolved is not None
assert resolved.skill.name == "data-analysis"
assert resolved.remaining_text == "run"
assert resolved.container_file_path == "/mnt/skills/custom/data-analysis/SKILL.md"
def test_resolve_slash_skill_rejects_disabled_skills(tmp_path):
skill = _make_skill(tmp_path, "data-analysis")
skill.enabled = False
assert resolve_slash_skill("/data-analysis run", [skill]) is None
def test_skill_activation_middleware_injects_hidden_human_context_for_model_call(monkeypatch, tmp_path):
skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
middleware = SkillActivationMiddleware()
original = HumanMessage(content="/data-analysis analyze uploads/foo.csv", id="msg-1")
request = _make_model_request([original])
captured = {}
def handler(model_request: ModelRequest):
captured["messages"] = model_request.messages
return AIMessage(content="ok")
result = middleware.wrap_model_call(request, handler)
assert isinstance(result, AIMessage)
assert result.content == "ok"
activation_msg, user_msg = captured["messages"]
assert is_slash_skill_activation_reminder(activation_msg)
assert activation_msg.additional_kwargs["hide_from_ui"] is True
assert "Use pandas." in activation_msg.content
assert "<user_request>\nanalyze uploads/foo.csv\n</user_request>" in activation_msg.content
assert user_msg.content == original.content
assert request.state["messages"] == [original]
def test_skill_activation_middleware_does_not_duplicate_existing_activation(monkeypatch, tmp_path):
skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
middleware = SkillActivationMiddleware()
original = HumanMessage(content="/data-analysis analyze uploads/foo.csv", id="msg-1")
first_capture = {}
def first_handler(model_request: ModelRequest):
first_capture["messages"] = model_request.messages
return AIMessage(content="ok")
first_result = middleware.wrap_model_call(_make_model_request([original]), first_handler)
assert isinstance(first_result, AIMessage)
activation_msg, user_msg = first_capture["messages"]
assert is_slash_skill_activation_reminder(activation_msg)
second_capture = {}
def second_handler(model_request: ModelRequest):
second_capture["messages"] = model_request.messages
return AIMessage(content="ok")
second_result = middleware.wrap_model_call(_make_model_request([activation_msg, user_msg]), second_handler)
assert isinstance(second_result, AIMessage)
assert second_capture["messages"] == [activation_msg, user_msg]
assert sum(is_slash_skill_activation_reminder(message) for message in second_capture["messages"]) == 1
def test_skill_activation_middleware_does_not_duplicate_activation_separated_by_hidden_context(monkeypatch, tmp_path):
skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
middleware = SkillActivationMiddleware()
original = HumanMessage(content="/data-analysis analyze uploads/foo.csv", id="msg-1")
first_capture = {}
def first_handler(model_request: ModelRequest):
first_capture["messages"] = model_request.messages
return AIMessage(content="ok")
middleware.wrap_model_call(_make_model_request([original]), first_handler)
activation_msg, user_msg = first_capture["messages"]
hidden_context = HumanMessage(content="dynamic context", additional_kwargs={"hide_from_ui": True})
second_capture = {}
def second_handler(model_request: ModelRequest):
second_capture["messages"] = model_request.messages
return AIMessage(content="ok")
second_result = middleware.wrap_model_call(_make_model_request([activation_msg, hidden_context, user_msg]), second_handler)
assert isinstance(second_result, AIMessage)
assert second_capture["messages"] == [activation_msg, hidden_context, user_msg]
assert sum(is_slash_skill_activation_reminder(message) for message in second_capture["messages"]) == 1
def test_skill_activation_middleware_dedupes_immediately_previous_activation_without_target_id(monkeypatch, tmp_path):
skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
middleware = SkillActivationMiddleware()
legacy_activation_msg = SkillActivationMiddleware._make_activation_message(
HumanMessage(content="/data-analysis analyze uploads/foo.csv"),
"existing activation context",
)
target = HumanMessage(content="/data-analysis analyze uploads/foo.csv", id="msg-1")
captured = {}
def handler(model_request: ModelRequest):
captured["messages"] = model_request.messages
return AIMessage(content="ok")
result = middleware.wrap_model_call(_make_model_request([legacy_activation_msg, target]), handler)
assert isinstance(result, AIMessage)
assert captured["messages"] == [legacy_activation_msg, target]
assert sum(is_slash_skill_activation_reminder(message) for message in captured["messages"]) == 1
def test_skill_activation_middleware_async_injects_hidden_human_context_for_model_call(monkeypatch, tmp_path):
skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
middleware = SkillActivationMiddleware()
original = HumanMessage(content="/data-analysis analyze uploads/foo.csv", id="msg-1")
request = _make_model_request([original])
captured = {}
async def handler(model_request: ModelRequest):
captured["messages"] = model_request.messages
return AIMessage(content="ok")
result = asyncio.run(middleware.awrap_model_call(request, handler))
assert isinstance(result, AIMessage)
assert result.content == "ok"
activation_msg, user_msg = captured["messages"]
assert is_slash_skill_activation_reminder(activation_msg)
assert activation_msg.additional_kwargs["hide_from_ui"] is True
assert "Use pandas." in activation_msg.content
assert "<user_request>\nanalyze uploads/foo.csv\n</user_request>" in activation_msg.content
assert user_msg.content == original.content
assert request.state["messages"] == [original]
def test_skill_activation_middleware_uses_fallback_when_task_text_is_empty(monkeypatch, tmp_path):
skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
middleware = SkillActivationMiddleware()
original = HumanMessage(content="/data-analysis", id="msg-1")
captured = {}
def handler(model_request: ModelRequest):
captured["messages"] = model_request.messages
return AIMessage(content="ok")
result = middleware.wrap_model_call(_make_model_request([original]), handler)
assert isinstance(result, AIMessage)
activation_msg = captured["messages"][0]
assert "No additional task text was provided after the slash skill command." in activation_msg.content
def test_skill_activation_middleware_uses_original_user_content_when_uploads_are_injected(monkeypatch, tmp_path):
skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
middleware = SkillActivationMiddleware()
original = HumanMessage(
content="<uploaded_files>\n- report.pdf\n</uploaded_files>\n\n/data-analysis 分析这个文档",
id="msg-1",
additional_kwargs={ORIGINAL_USER_CONTENT_KEY: "/data-analysis 分析这个文档"},
)
captured = {}
def handler(model_request: ModelRequest):
captured["messages"] = model_request.messages
return AIMessage(content="ok")
result = middleware.wrap_model_call(_make_model_request([original]), handler)
assert isinstance(result, AIMessage)
assert result.content == "ok"
activation_msg, user_msg = captured["messages"]
assert is_slash_skill_activation_reminder(activation_msg)
assert "Use pandas." in activation_msg.content
assert "<user_request>\n分析这个文档\n</user_request>" in activation_msg.content
assert user_msg.content == original.content
assert user_msg.additional_kwargs[ORIGINAL_USER_CONTENT_KEY] == "/data-analysis 分析这个文档"
def test_skill_activation_middleware_activates_from_list_content(monkeypatch, tmp_path):
skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
middleware = SkillActivationMiddleware()
original = HumanMessage(content=[{"type": "text", "text": "/data-analysis analyze uploads/foo.csv"}], id="msg-1")
captured = {}
def handler(model_request: ModelRequest):
captured["messages"] = model_request.messages
return AIMessage(content="ok")
result = middleware.wrap_model_call(_make_model_request([original]), handler)
assert isinstance(result, AIMessage)
activation_msg, user_msg = captured["messages"]
assert is_slash_skill_activation_reminder(activation_msg)
assert "<user_request>\nanalyze uploads/foo.csv\n</user_request>" in activation_msg.content
assert user_msg.content == original.content
def test_skill_activation_middleware_records_activation_audit_event(monkeypatch, tmp_path):
skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
recorded = []
journal = SimpleNamespace(record_middleware=lambda *args, **kwargs: recorded.append((args, kwargs)))
runtime = SimpleNamespace(context={"__run_journal": journal})
middleware = SkillActivationMiddleware()
original = HumanMessage(content="/data-analysis analyze uploads/foo.csv", id="msg-1")
def handler(model_request: ModelRequest):
return AIMessage(content="ok")
result = middleware.wrap_model_call(_make_model_request([original], runtime=runtime), handler)
assert isinstance(result, AIMessage)
assert len(recorded) == 1
args, kwargs = recorded[0]
assert args == ("skill_activation",)
assert kwargs["name"] == "SkillActivationMiddleware"
assert kwargs["hook"] == "wrap_model_call"
assert kwargs["action"] == "activate"
assert kwargs["changes"] == {
"skill_name": "data-analysis",
"category": "custom",
"path": "/mnt/skills/custom/data-analysis/SKILL.md",
"content_hash": hashlib.sha256(b"# Data Analysis\nUse pandas.").hexdigest(),
}
def test_skill_activation_middleware_async_records_activation_audit_event(monkeypatch, tmp_path):
skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
recorded = []
journal = SimpleNamespace(record_middleware=lambda *args, **kwargs: recorded.append((args, kwargs)))
runtime = SimpleNamespace(context={"__run_journal": journal})
middleware = SkillActivationMiddleware()
original = HumanMessage(content="/data-analysis analyze uploads/foo.csv", id="msg-1")
async def handler(model_request: ModelRequest):
return AIMessage(content="ok")
result = asyncio.run(middleware.awrap_model_call(_make_model_request([original], runtime=runtime), handler))
assert isinstance(result, AIMessage)
assert len(recorded) == 1
args, kwargs = recorded[0]
assert args == ("skill_activation",)
assert kwargs["hook"] == "awrap_model_call"
assert kwargs["changes"]["skill_name"] == "data-analysis"
assert kwargs["changes"]["content_hash"] == hashlib.sha256(b"# Data Analysis\nUse pandas.").hexdigest()
def test_skill_activation_middleware_ignores_activation_audit_errors(monkeypatch, tmp_path):
skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
journal = SimpleNamespace(record_middleware=lambda *args, **kwargs: (_ for _ in ()).throw(RuntimeError("db down")))
runtime = SimpleNamespace(context={"__run_journal": journal})
middleware = SkillActivationMiddleware()
original = HumanMessage(content="/data-analysis analyze uploads/foo.csv", id="msg-1")
def handler(model_request: ModelRequest):
return AIMessage(content="ok")
result = middleware.wrap_model_call(_make_model_request([original], runtime=runtime), handler)
assert isinstance(result, AIMessage)
assert result.content == "ok"
def test_skill_activation_middleware_activates_only_latest_real_user_message(monkeypatch, tmp_path):
skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
middleware = SkillActivationMiddleware()
old_slash = HumanMessage(content="/data-analysis old request", id="msg-1")
latest_user = HumanMessage(content="continue normally", id="msg-2")
request = _make_model_request([old_slash, AIMessage(content="done"), latest_user])
captured = {}
def handler(model_request: ModelRequest):
captured["messages"] = model_request.messages
return AIMessage(content="ok")
result = middleware.wrap_model_call(request, handler)
assert isinstance(result, AIMessage)
assert captured["messages"] == request.messages
assert not any(is_slash_skill_activation_reminder(message) for message in captured["messages"])
def test_skill_activation_middleware_ignores_hidden_and_summary_user_messages(monkeypatch, tmp_path):
skill = _make_skill(tmp_path, "data-analysis", content="# Data Analysis\nUse pandas.")
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
middleware = SkillActivationMiddleware()
real_user = HumanMessage(content="continue normally", id="msg-1")
hidden_slash = HumanMessage(content="/data-analysis hidden request", id="msg-2", additional_kwargs={"hide_from_ui": True})
summary_slash = HumanMessage(content="/data-analysis summary request", id="msg-3", name="summary")
request = _make_model_request([real_user, hidden_slash, summary_slash])
captured = {}
def handler(model_request: ModelRequest):
captured["messages"] = model_request.messages
return AIMessage(content="ok")
result = middleware.wrap_model_call(request, handler)
assert isinstance(result, AIMessage)
assert captured["messages"] == request.messages
assert not any(is_slash_skill_activation_reminder(message) for message in captured["messages"])
def test_skill_activation_middleware_returns_clear_error_for_disallowed_skill(monkeypatch, tmp_path):
skill = _make_skill(tmp_path, "data-analysis")
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
middleware = SkillActivationMiddleware(available_skills={"frontend-design"})
original = HumanMessage(content="/data-analysis run")
def handler(model_request: ModelRequest):
raise AssertionError("handler should not be called for invalid slash skills")
result = middleware.wrap_model_call(_make_model_request([original]), handler)
assert isinstance(result, AIMessage)
assert "not available for this agent" in result.content
def test_skill_activation_middleware_returns_clear_error_for_missing_skill(monkeypatch, tmp_path):
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, []))
middleware = SkillActivationMiddleware()
original = HumanMessage(content="/data-analysis run")
def handler(model_request: ModelRequest):
raise AssertionError("handler should not be called for missing slash skills")
result = middleware.wrap_model_call(_make_model_request([original]), handler)
assert isinstance(result, AIMessage)
assert "not installed" in result.content
def test_skill_activation_middleware_returns_clear_error_for_disabled_skill(monkeypatch, tmp_path):
skill = _make_skill(tmp_path, "data-analysis")
skill.enabled = False
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
middleware = SkillActivationMiddleware()
original = HumanMessage(content="/data-analysis run")
def handler(model_request: ModelRequest):
raise AssertionError("handler should not be called for disabled slash skills")
result = middleware.wrap_model_call(_make_model_request([original]), handler)
assert isinstance(result, AIMessage)
assert "installed but disabled" in result.content
def test_skill_activation_middleware_escapes_activation_content(monkeypatch, tmp_path):
skill = _make_skill(
tmp_path,
"data-analysis",
content="# Data Analysis\nUse <xml> & avoid </skill> collisions.\n----- END SKILL.md -----",
)
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
middleware = SkillActivationMiddleware()
original = HumanMessage(content="/data-analysis analyze </user_request>")
captured = {}
def handler(model_request: ModelRequest):
captured["messages"] = model_request.messages
return AIMessage(content="ok")
result = middleware.wrap_model_call(_make_model_request([original]), handler)
assert isinstance(result, AIMessage)
activation_msg = captured["messages"][0]
assert '<skill_content encoding="xml-escaped">' in activation_msg.content
assert "analyze &lt;/user_request&gt;" in activation_msg.content
assert "Use &lt;xml&gt; &amp; avoid &lt;/skill&gt; collisions." in activation_msg.content
assert "----- BEGIN SKILL.md -----" not in activation_msg.content
def test_skill_activation_middleware_rejects_skill_file_outside_skills_root(monkeypatch, tmp_path):
skills_root = tmp_path / "skills"
skill_dir = skills_root / "custom" / "data-analysis"
skill_dir.mkdir(parents=True)
outside_dir = tmp_path / "outside"
outside_dir.mkdir()
outside_file = outside_dir / "SKILL.md"
outside_file.write_text("# Leaked\nDo not read me.", encoding="utf-8")
(skill_dir / "SKILL.md").symlink_to(outside_file)
skill = Skill(
name="data-analysis",
description="Description for data-analysis",
license="MIT",
skill_dir=skill_dir,
skill_file=skill_dir / "SKILL.md",
relative_path=Path("data-analysis"),
category=SkillCategory.CUSTOM,
enabled=True,
)
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(skills_root, [skill]))
middleware = SkillActivationMiddleware()
def handler(model_request: ModelRequest):
raise AssertionError("handler should not be called when SKILL.md fails safety checks")
result = middleware.wrap_model_call(_make_model_request([HumanMessage(content="/data-analysis run")]), handler)
assert isinstance(result, AIMessage)
assert "could not be loaded safely" in result.content
def test_skill_activation_middleware_reports_missing_skill_file_safely(monkeypatch, tmp_path):
skill = _make_skill(tmp_path, "data-analysis")
skill.skill_file.unlink()
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
middleware = SkillActivationMiddleware()
def handler(model_request: ModelRequest):
raise AssertionError("handler should not be called when SKILL.md is missing")
result = middleware.wrap_model_call(_make_model_request([HumanMessage(content="/data-analysis run")]), handler)
assert isinstance(result, AIMessage)
assert "could not be loaded safely" in result.content
def test_skill_activation_middleware_reports_invalid_utf8_skill_file_safely(monkeypatch, tmp_path):
skill = _make_skill(tmp_path, "data-analysis")
skill.skill_file.write_bytes(b"\xff\xfe\x00")
monkeypatch.setattr(middleware_module, "get_or_new_skill_storage", lambda **kwargs: _make_storage(tmp_path, [skill]))
middleware = SkillActivationMiddleware()
def handler(model_request: ModelRequest):
raise AssertionError("handler should not be called when SKILL.md is not valid UTF-8")
result = middleware.wrap_model_call(_make_model_request([HumanMessage(content="/data-analysis run")]), handler)
assert isinstance(result, AIMessage)
assert "could not be loaded safely" in result.content
@@ -0,0 +1,100 @@
"""Tests for Telegram deep-link channel connections."""
from __future__ import annotations
from datetime import UTC, datetime, timedelta
from pathlib import Path
from unittest.mock import AsyncMock, MagicMock
import pytest
from app.channels.message_bus import MessageBus
from app.channels.telegram import TelegramChannel
@pytest.fixture
async def repo(tmp_path: 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 / 'telegram.db'}", sqlite_dir=str(tmp_path))
try:
yield ChannelConnectionRepository(
get_session_factory(),
cipher=ChannelCredentialCipher.from_key("telegram-secret"),
)
finally:
await close_engine()
def _telegram_update(*, text: str = "/start", user_id: int = 42, chat_id: int = 100, chat_type: str = "private"):
update = MagicMock()
update.effective_user.id = user_id
update.effective_user.username = "alice"
update.effective_user.full_name = "Alice Example"
update.effective_chat.id = chat_id
update.effective_chat.type = chat_type
update.message.text = text
update.message.message_id = 55
update.message.reply_to_message = None
update.message.reply_text = AsyncMock()
return update
@pytest.mark.anyio
async def test_start_with_deep_link_state_binds_telegram_chat(repo):
state = "telegram-bind-state"
await repo.create_oauth_state(
owner_user_id="deerflow-user-1",
provider="telegram",
state=state,
expires_at=datetime.now(UTC) + timedelta(minutes=5),
)
channel = TelegramChannel(
bus=MessageBus(),
config={"bot_token": "test-token", "connection_repo": repo},
)
update = _telegram_update(text=f"/start {state}")
context = MagicMock()
context.args = [state]
await channel._cmd_start(update, context)
connections = await repo.list_connections("deerflow-user-1")
assert len(connections) == 1
assert connections[0]["provider"] == "telegram"
assert connections[0]["external_account_id"] == "42"
assert connections[0]["external_account_name"] == "Alice Example"
assert connections[0]["workspace_id"] == "100"
assert connections[0]["metadata"]["chat_type"] == "private"
update.message.reply_text.assert_awaited_once()
assert "connected" in update.message.reply_text.await_args.args[0].lower()
@pytest.mark.anyio
async def test_bound_telegram_message_publishes_connection_identity(repo):
connection = await repo.upsert_connection(
owner_user_id="deerflow-user-1",
provider="telegram",
external_account_id="42",
external_account_name="Alice Example",
workspace_id="100",
metadata={"chat_type": "private"},
)
bus = MessageBus()
channel = TelegramChannel(
bus=bus,
config={"bot_token": "test-token", "connection_repo": repo},
)
channel._main_loop = __import__("asyncio").get_event_loop()
channel._send_running_reply = AsyncMock()
await channel._on_text(_telegram_update(text="hello"), None)
inbound = await bus.get_inbound()
assert inbound.connection_id == connection["id"]
assert inbound.owner_user_id == "deerflow-user-1"
assert inbound.workspace_id == "100"
assert inbound.user_id == "42"
assert inbound.chat_id == "100"
assert inbound.text == "hello"
@@ -14,6 +14,7 @@ from langchain_core.messages import AIMessage, HumanMessage
from deerflow.agents.middlewares.uploads_middleware import UploadsMiddleware
from deerflow.config.paths import Paths
from deerflow.utils.messages import ORIGINAL_USER_CONTENT_KEY
THREAD_ID = "thread-abc123"
@@ -263,6 +264,22 @@ class TestBeforeAgent:
assert "<uploaded_files>" in combined_text
assert "analyse this" in combined_text
def test_list_content_preserves_original_slash_skill_text(self, tmp_path):
mw = _middleware(tmp_path)
uploads_dir = _uploads_dir(tmp_path)
(uploads_dir / "data.csv").write_bytes(b"a,b")
msg = _human(
[{"type": "text", "text": "/data-analysis analyze data.csv"}],
files=[{"filename": "data.csv", "size": 3, "path": "/mnt/user-data/uploads/data.csv"}],
)
result = mw.before_agent(self._state(msg), _runtime())
assert result is not None
updated_msg = result["messages"][-1]
assert isinstance(updated_msg.content, list)
assert updated_msg.additional_kwargs[ORIGINAL_USER_CONTENT_KEY] == "/data-analysis analyze data.csv"
def test_preserves_additional_kwargs_on_updated_message(self, tmp_path):
mw = _middleware(tmp_path)
uploads_dir = _uploads_dir(tmp_path)
@@ -278,6 +295,37 @@ class TestBeforeAgent:
assert updated_kwargs.get("files") == files_meta
assert updated_kwargs.get("element") == "task"
def test_preserves_original_user_content_before_upload_context(self, tmp_path):
mw = _middleware(tmp_path)
uploads_dir = _uploads_dir(tmp_path)
(uploads_dir / "report.pdf").write_bytes(b"pdf")
msg = _human(
"/data-analysis 分析这个文档",
files=[{"filename": "report.pdf", "size": 3, "path": "/mnt/user-data/uploads/report.pdf"}],
)
result = mw.before_agent(self._state(msg), _runtime())
assert result is not None
updated_msg = result["messages"][-1]
assert updated_msg.content.startswith("<uploaded_files>")
assert updated_msg.additional_kwargs[ORIGINAL_USER_CONTENT_KEY] == "/data-analysis 分析这个文档"
def test_preserves_existing_original_user_content_marker(self, tmp_path):
mw = _middleware(tmp_path)
uploads_dir = _uploads_dir(tmp_path)
(uploads_dir / "report.pdf").write_bytes(b"pdf")
msg = _human(
"<uploaded_files>\nold\n</uploaded_files>\n\n/data-analysis run",
files=[{"filename": "report.pdf", "size": 3, "path": "/mnt/user-data/uploads/report.pdf"}],
**{ORIGINAL_USER_CONTENT_KEY: "/data-analysis run"},
)
result = mw.before_agent(self._state(msg), _runtime())
assert result is not None
assert result["messages"][-1].additional_kwargs[ORIGINAL_USER_CONTENT_KEY] == "/data-analysis run"
def test_uploaded_files_returned_in_state_update(self, tmp_path):
mw = _middleware(tmp_path)
uploads_dir = _uploads_dir(tmp_path)
@@ -0,0 +1,185 @@
"""Regression for #3459 / #3454 — dev gateway reload-exclude must not crash.
#3426 switched the dev gateway's ``--reload-exclude`` patterns from relative
(``sandbox/``) to absolute (``$REPO_ROOT/backend/sandbox``). uvicorn only
excludes such a path directly when it already exists as a directory; otherwise
it falls back to ``Path.cwd().glob(pattern)``, and on **Python 3.12**
``pathlib.Path.glob()`` raises ``NotImplementedError: Non-relative patterns are
unsupported`` for an absolute pattern. ``serve.sh`` created the ``.deer-flow``
excludes but not ``backend/sandbox``, so a fresh checkout crashed ``make dev``
on startup.
Two layers of coverage:
* ``test_*_resolve_*`` exercises uvicorn's real ``resolve_reload_patterns`` to
pin the failure mode and the fix's mechanism.
* ``test_launcher_precreates_every_absolute_reload_exclude`` enforces the actual
invariant on both launchers: every absolute exclude dir is ``mkdir -p``'d
before uvicorn starts. This encodes the root cause, so any future absolute
exclude that forgets its ``mkdir`` fails here.
"""
from __future__ import annotations
import re
import shlex
import subprocess
import sys
from pathlib import Path
import pytest
from uvicorn.config import resolve_reload_patterns
REPO_ROOT = Path(__file__).resolve().parents[2]
LAUNCHERS = {
"scripts/serve.sh": REPO_ROOT / "scripts" / "serve.sh",
"docker/dev-entrypoint.sh": REPO_ROOT / "docker" / "dev-entrypoint.sh",
}
# Shell terminators / redirects that end a simple command's argument list.
_CMD_BOUNDARY = re.compile(r"[;&|<>]")
def _logical_lines(script: str) -> list[str]:
"""Fold ``\\``-continuations and drop comment lines, yielding logical lines.
A ``mkdir`` or ``--reload-exclude`` list split across lines with a trailing
backslash becomes one line here, so an argument on a continuation line can't
be silently dropped by per-line scanning.
"""
folded = script.replace("\\\n", " ")
return [line for line in folded.splitlines() if not line.lstrip().startswith("#")]
def _shlex(fragment: str) -> list[str]:
"""Tokenize a shell fragment (quotes stripped, ``$VAR`` kept literal,
trailing ``# comment`` honored); tolerate pathological quoting."""
try:
return shlex.split(fragment, comments=True)
except ValueError:
return fragment.split()
# ``--reload-exclude`` followed by ``=`` or whitespace, then a value that is a
# single-quoted group, a double-quoted group, or a bare token. The quoted
# alternatives match a *balanced* pair first, so serve.sh's surrounding
# ``GATEWAY_EXTRA_FLAGS="..."`` closing quote is never swallowed into the value.
_RELOAD_EXCLUDE = re.compile(r"""--reload-exclude[=\s]+('[^']*'|"[^"]*"|[^\s'"]+)""")
def _reload_exclude_values(script: str) -> list[str]:
"""Every ``--reload-exclude`` value, with surrounding quotes removed.
Handles both CLI forms (``--reload-exclude=<value>`` and the space form
``--reload-exclude <value>``) and both shell quotings the launchers use:
* ``docker/dev-entrypoint.sh`` puts each flag on its own line.
* ``scripts/serve.sh`` packs every flag into a single double-quoted
``GATEWAY_EXTRA_FLAGS="... --reload-exclude='$X' ..."`` assignment. A
whole-line ``shlex`` would collapse that assignment into one token and
find no flags (this is what regressed serve.sh in CI); matching balanced
inner quotes here keeps the assignment's closing ``"`` out of the value,
so every exclude including the last ``$BACKEND_RUNTIME_HOME`` is seen.
"""
values: list[str] = []
for line in _logical_lines(script):
for raw in _RELOAD_EXCLUDE.findall(line):
values.append(raw.strip("\"'"))
return values
def _mkdir_dirs(script: str) -> set[str]:
"""Exact set of directories created by every ``mkdir`` command.
Tokenizes each ``mkdir`` argument list rather than substring-matching, so
``/app/backend/sandbox`` is not falsely considered created by, say,
``mkdir -p /app/backend/sandbox-other``.
"""
dirs: set[str] = set()
for line in _logical_lines(script):
match = re.search(r"\bmkdir\b(.*)", line)
if not match:
continue
args = _CMD_BOUNDARY.split(match.group(1), maxsplit=1)[0]
for token in _shlex(args):
if token.startswith("-"): # skip flags such as -p
continue
dirs.add(token)
return dirs
@pytest.mark.skipif(
sys.version_info >= (3, 13),
reason="pathlib accepts absolute glob patterns on 3.13+, so the crash is 3.12-only",
)
def test_resolve_reload_patterns_crashes_on_missing_absolute_dir(tmp_path):
"""The exact #3454 failure: absolute exclude + missing dir on Python 3.12."""
missing = tmp_path / "sandbox" # absolute path that does not exist yet
assert not missing.exists()
with pytest.raises(NotImplementedError):
resolve_reload_patterns([str(missing)], [])
def test_resolve_reload_patterns_is_safe_once_dir_exists(tmp_path):
"""The fix's mechanism: a pre-created dir takes uvicorn's is_dir() path."""
sandbox = tmp_path / "sandbox"
sandbox.mkdir()
_patterns, directories = resolve_reload_patterns([str(sandbox)], [])
resolved = {d.resolve() for d in directories}
assert sandbox.resolve() in resolved
@pytest.mark.parametrize("name", list(LAUNCHERS))
def test_launcher_precreates_every_absolute_reload_exclude(name):
"""Every absolute ``--reload-exclude`` dir must be created by ``mkdir`` first.
Relative glob patterns (``*.pyc``, ``__pycache__``) are safe and skipped;
anything anchored at ``/`` or a shell variable is an absolute path that
uvicorn would glob and crash on unless it already exists. Membership is
an exact match against the parsed ``mkdir`` argument set (not a substring
test), so a path-prefix can't produce a false pass.
"""
script = LAUNCHERS[name].read_text(encoding="utf-8")
created = _mkdir_dirs(script)
absolute_excludes = [v for v in _reload_exclude_values(script) if v.startswith(("/", "$"))]
assert absolute_excludes, f"{name}: expected at least one absolute reload-exclude"
for value in absolute_excludes:
assert value in created, f"{name}: absolute reload-exclude {value!r} is never created via mkdir (created dirs: {sorted(created)})"
@pytest.mark.parametrize("name", list(LAUNCHERS))
def test_sandbox_mkdir_precedes_uvicorn_launch(name):
"""The sandbox mkdir must come before the uvicorn launch, not just exist.
``_mkdir_dirs`` only proves the mkdir is present somewhere; this pins script
order so a future edit can't move (or guard) the mkdir below the launch and
silently reintroduce the #3454 crash on a fresh checkout. ``uv run uvicorn``
matches the launch but not serve.sh's ``stop_all`` kill line.
"""
lines = LAUNCHERS[name].read_text(encoding="utf-8").splitlines()
launch_idx = next((i for i, ln in enumerate(lines) if "uv run uvicorn" in ln), None)
mkdir_idx = next((i for i, ln in enumerate(lines) if re.search(r"\bmkdir\b", ln) and "sandbox" in ln), None)
assert launch_idx is not None, f"{name}: could not locate the 'uv run uvicorn' launch line"
assert mkdir_idx is not None, f"{name}: could not locate the sandbox mkdir line"
assert mkdir_idx < launch_idx, f"{name}: sandbox mkdir (line {mkdir_idx + 1}) must precede uvicorn launch (line {launch_idx + 1})"
def test_precreated_sandbox_artifacts_are_gitignored():
"""backend/sandbox is runtime state — its contents must stay out of git so
sandbox artifacts can't be accidentally committed (matches the reload-exclude
intent). A content path is existence-independent, unlike the bare dir path.
Guards against the inaccurate "gitignored" claim by making it verifiable.
"""
probe = "backend/sandbox/__artifact_probe__"
result = subprocess.run(
["git", "-C", str(REPO_ROOT), "check-ignore", "-q", probe],
capture_output=True,
)
if result.returncode == 128: # not a git checkout (e.g. packaged install)
pytest.skip("not inside a git working tree")
assert result.returncode == 0, "backend/sandbox/* should be gitignored (see backend/.gitignore '/sandbox/')"
+2
View File
@@ -820,6 +820,7 @@ dependencies = [
{ name = "agent-sandbox" },
{ name = "aiosqlite" },
{ name = "alembic" },
{ name = "cryptography" },
{ name = "ddgs" },
{ name = "dotenv" },
{ name = "duckdb" },
@@ -871,6 +872,7 @@ requires-dist = [
{ name = "aiosqlite", specifier = ">=0.19" },
{ name = "alembic", specifier = ">=1.13" },
{ name = "asyncpg", marker = "extra == 'postgres'", specifier = ">=0.29" },
{ name = "cryptography", specifier = ">=43.0.0" },
{ name = "ddgs", specifier = ">=9.10.0" },
{ name = "dotenv", specifier = ">=0.9.9" },
{ name = "duckdb", specifier = ">=1.4.4" },
+63 -2
View File
@@ -15,7 +15,7 @@
# ============================================================================
# Bump this number when the config schema changes.
# Run `make config-upgrade` to merge new fields into your local config.yaml.
config_version: 11
config_version: 12
# ============================================================================
# Logging
@@ -274,6 +274,32 @@ models:
# thinking:
# type: disabled
# Example: StepFun (阶跃星辰) reasoning models
# StepFun provides OpenAI-compatible API with reasoning models.
# With reasoning_format: deepseek-style, the API returns reasoning_content
# (same field as DeepSeek), which must be replayed on historical assistant
# messages in multi-turn tool-call conversations.
# Use PatchedChatStepFun instead of plain ChatOpenAI.
# Docs: https://platform.stepfun.com/docs/api-reference/chat-completions
# - name: step-3.7-flash
# display_name: Step 3.7 Flash
# use: deerflow.models.patched_stepfun:PatchedChatStepFun
# model: step-3.7-flash
# api_key: $STEPFUN_API_KEY
# base_url: https://api.stepfun.com/v1
# request_timeout: 600.0
# max_retries: 2
# max_tokens: 4096
# supports_thinking: true
# supports_reasoning_effort: true
# supports_vision: true
# when_thinking_enabled:
# extra_body:
# reasoning_format: deepseek-style
# when_thinking_disabled:
# extra_body:
# reasoning_format: deepseek-style
# Example: MiniMax (OpenAI-compatible) - International Edition
# MiniMax provides high-performance models with 512K context window and 128K max output
# Docs: https://platform.minimax.io/docs/api-reference/text-openai-api
@@ -537,6 +563,10 @@ tools:
group: web
use: deerflow.community.jina_ai.tools:web_fetch_tool
timeout: 10
# Optional proxy for restricted networks / Docker / WSL.
# Use host.docker.internal instead of 127.0.0.1 when the proxy runs on the host.
# proxy: $HTTPS_PROXY
# trust_env: true
# Web fetch tool (uses InfoQuest)
# - name: web_fetch
@@ -738,8 +768,12 @@ sandbox:
allow_host_bash: false
# Optional: Mount additional host directories into the sandbox.
# Each mount maps a host path to a virtual container path accessible by the agent.
# Note: with LocalSandboxProvider under `make up` (docker-compose), host_path is
# checked from inside the deer-flow-gateway container — you must also bind-mount
# the same directory into services.gateway.volumes in docker/docker-compose.yaml
# for this mount to take effect (see issue #3244).
# mounts:
# - host_path: /home/user/my-project # Absolute path on the host machine
# - host_path: /home/user/my-project # Absolute path; see note above for Docker mode
# container_path: /mnt/my-project # Virtual path inside the sandbox
# read_only: true # Whether the mount is read-only (default: false)
@@ -1097,6 +1131,33 @@ run_events:
max_trace_content: 10240
track_token_usage: true
# ============================================================================
# User-Owned IM Channel Connections
# ============================================================================
# Lets logged-in users connect their own Telegram, Slack, and Discord accounts
# from the DeerFlow frontend while reusing the existing `channels` runtime
# configuration below.
#
# Security notes:
# - No public IP, OAuth callback URL, or provider webhook is required.
# - Provider bot/app credentials stay under `channels.*`.
# - `channel_connections` stores per-user bindings and one-time connect codes.
# - Telegram uses a deep link when `bot_username` is configured.
# - Slack and Discord use `/connect <code>` through the already-running bot.
#
# channel_connections:
# enabled: false
#
# telegram:
# enabled: false
# bot_username: $TELEGRAM_BOT_USERNAME
#
# slack:
# enabled: false
#
# discord:
# enabled: false
# ============================================================================
# IM Channels Configuration
# ============================================================================
+6 -4
View File
@@ -64,12 +64,14 @@ if [ -n "$EXTRAS_FLAGS" ]; then
echo "[startup] uv extras:$EXTRAS_FLAGS"
fi
# Keep runtime-owned files out of uvicorn's reload watcher. The directory must
# exist before uvicorn starts so watchfiles treats it as an excluded directory,
# not as a plain glob pattern.
# Keep runtime-owned files out of uvicorn's reload watcher. Each excluded path
# must exist before uvicorn starts so watchfiles treats it as an excluded
# directory, not as a plain glob pattern — on Python 3.12, globbing an absolute
# pattern raises NotImplementedError and crashes startup (#3459 / #3454). That
# means `sandbox` must be created here too, not just `.deer-flow`.
: "${DEER_FLOW_HOME:=/app/backend/.deer-flow}"
export DEER_FLOW_HOME
mkdir -p "$DEER_FLOW_HOME" /app/backend/.deer-flow
mkdir -p "$DEER_FLOW_HOME" /app/backend/.deer-flow /app/backend/sandbox
# ── Sync dependencies (with self-heal) ──────────────────────────────────────
+4
View File
@@ -172,6 +172,10 @@ services:
- DEER_FLOW_HOST_BASE_DIR=${DEER_FLOW_ROOT}/backend/.deer-flow
- DEER_FLOW_HOST_SKILLS_PATH=${DEER_FLOW_ROOT}/skills
- DEER_FLOW_SANDBOX_HOST=host.docker.internal
# Proxy values (HTTP_PROXY/HTTPS_PROXY/ALL_PROXY) are inherited from ../.env via env_file.
# Only NO_PROXY is declared here so internal service hostnames are always exempt from the proxy.
- NO_PROXY=${NO_PROXY:-}${NO_PROXY:+,}localhost,127.0.0.1,::1,gateway,frontend,nginx,provisioner,host.docker.internal
- no_proxy=${no_proxy:-}${no_proxy:+,}localhost,127.0.0.1,::1,gateway,frontend,nginx,provisioner,host.docker.internal
env_file:
- ../.env
extra_hosts:
+11 -1
View File
@@ -72,7 +72,13 @@ services:
UV_INDEX_URL: ${UV_INDEX_URL:-https://pypi.org/simple}
UV_EXTRAS: ${UV_EXTRAS:-}
container_name: deer-flow-gateway
command: sh -c "cd backend && PYTHONPATH=. uv run uvicorn app.gateway.app:app --host 0.0.0.0 --port 8001 --workers ${GATEWAY_WORKERS:-4}"
# Gateway hosts the agent runtime with in-process RunManager + StreamBridge
# singletons -- run state lives in this worker's memory. Default to a single
# worker: with >1 worker and no nginx sticky sessions, run cancel, SSE
# reconnect, request dedup, and per-worker IM channel services all break
# across workers until a shared (e.g. redis) stream bridge lands, which is
# not yet implemented. Override GATEWAY_WORKERS only once that is in place.
command: sh -c "cd backend && PYTHONPATH=. uv run uvicorn app.gateway.app:app --host 0.0.0.0 --port 8001 --workers ${GATEWAY_WORKERS:-1}"
volumes:
- ${DEER_FLOW_CONFIG_PATH}:/app/backend/config.yaml:ro
- ${DEER_FLOW_EXTENSIONS_CONFIG_PATH}:/app/backend/extensions_config.json:ro
@@ -107,6 +113,10 @@ services:
- DEER_FLOW_HOST_BASE_DIR=${DEER_FLOW_HOME}
- DEER_FLOW_HOST_SKILLS_PATH=${DEER_FLOW_REPO_ROOT}/skills
- DEER_FLOW_SANDBOX_HOST=host.docker.internal
# Proxy values (HTTP_PROXY/HTTPS_PROXY/ALL_PROXY) are inherited from ../.env via env_file.
# Only NO_PROXY is declared here so internal service hostnames are always exempt from the proxy.
- NO_PROXY=${NO_PROXY:-}${NO_PROXY:+,}localhost,127.0.0.1,::1,gateway,frontend,nginx,provisioner,host.docker.internal
- no_proxy=${no_proxy:-}${no_proxy:+,}localhost,127.0.0.1,::1,gateway,frontend,nginx,provisioner,host.docker.internal
env_file:
- ../.env
extra_hosts:
+2
View File
@@ -9,6 +9,8 @@ export default tseslint.config(
{
ignores: [
".next",
"playwright-report",
"test-results",
"src/components/ui/**",
"src/components/ai-elements/**",
"*.js",
+7 -3
View File
@@ -7,8 +7,9 @@ import { defineConfig, devices } from "@playwright/test";
* so the mock-based suite is untouched.
*
* Two webServers are started: the replay gateway (:8011) and the frontend
* (:3000, pointed at the gateway). Auth uses a throwaway test account the spec
* registers at runtime no secrets.
* (:3000, pointed at the gateway). Auth-disabled mode is enabled on both
* servers so the no-cookie e2e contract is covered; specs that need session
* cookies still register a throwaway test account at runtime.
*/
export default defineConfig({
testDir: "./tests/e2e-real-backend",
@@ -38,7 +39,10 @@ export default defineConfig({
// Mount the test-only run/message seeder used by multi-run-order.spec.ts
// (#3352). The endpoint exists only on this replay gateway, never in the
// production app.
env: { DEERFLOW_ENABLE_TEST_SEED: "1" },
env: {
DEERFLOW_ENABLE_TEST_SEED: "1",
DEER_FLOW_AUTH_DISABLED: "1",
},
},
{
command: "pnpm build && pnpm start",
@@ -18,7 +18,8 @@ import {
} from "lucide-react";
import type { ComponentProps, HTMLAttributes, ReactElement } from "react";
import { createContext, memo, useContext, useEffect, useState } from "react";
import { Streamdown } from "streamdown";
import { ClipboardSafeStreamdown } from "./streamdown";
export type MessageProps = HTMLAttributes<HTMLDivElement> & {
from: UIMessage["role"];
@@ -302,11 +303,13 @@ export const MessageBranchPage = ({
);
};
export type MessageResponseProps = ComponentProps<typeof Streamdown>;
export type MessageResponseProps = ComponentProps<
typeof ClipboardSafeStreamdown
>;
export const MessageResponse = memo(
({ className, ...props }: MessageResponseProps) => (
<Streamdown
<ClipboardSafeStreamdown
className={cn(
"size-full [&>*:first-child]:mt-0 [&>*:last-child]:mb-0",
className,
@@ -881,6 +881,7 @@ export type PromptInputTextareaProps = ComponentProps<
export const PromptInputTextarea = ({
onChange,
onKeyDown,
className,
placeholder = "What would you like to know?",
...props
@@ -891,6 +892,10 @@ export const PromptInputTextarea = ({
const [isComposing, setIsComposing] = useState(false);
const handleKeyDown: KeyboardEventHandler<HTMLTextAreaElement> = (e) => {
onKeyDown?.(e);
if (e.defaultPrevented) {
return;
}
if (e.key === "Enter") {
if (isIMEComposing(e, isComposing)) {
return;
@@ -10,9 +10,9 @@ import { cn } from "@/lib/utils";
import { BrainIcon, ChevronDownIcon } from "lucide-react";
import type { ComponentProps, ReactNode } from "react";
import { createContext, memo, useContext, useEffect, useState } from "react";
import { Streamdown } from "streamdown";
import { reasoningPlugins } from "@/core/streamdown/plugins";
import { Shimmer } from "./shimmer";
import { ClipboardSafeStreamdown } from "./streamdown";
type ReasoningContextValue = {
isStreaming: boolean;
@@ -178,7 +178,9 @@ export const ReasoningContent = memo(
)}
{...props}
>
<Streamdown {...reasoningPlugins}>{children}</Streamdown>
<ClipboardSafeStreamdown {...reasoningPlugins}>
{children}
</ClipboardSafeStreamdown>
</CollapsibleContent>
),
);
@@ -0,0 +1,17 @@
"use client";
import { type ComponentProps } from "react";
import { Streamdown } from "streamdown";
import { installClipboardFallback } from "@/core/clipboard";
export type ClipboardSafeStreamdownProps = ComponentProps<typeof Streamdown>;
// Only patch browser globals in client context; skip during SSR
if (typeof document !== "undefined") {
installClipboardFallback();
}
export function ClipboardSafeStreamdown(props: ClipboardSafeStreamdownProps) {
return <Streamdown {...props} />;
}
@@ -10,7 +10,6 @@ import {
} from "lucide-react";
import { useCallback, useEffect, useMemo, useRef, useState } from "react";
import { toast } from "sonner";
import { Streamdown } from "streamdown";
import {
Artifact,
@@ -20,6 +19,7 @@ import {
ArtifactHeader,
ArtifactTitle,
} from "@/components/ai-elements/artifact";
import { ClipboardSafeStreamdown } from "@/components/ai-elements/streamdown";
import { Select, SelectItem } from "@/components/ui/select";
import {
SelectContent,
@@ -400,13 +400,13 @@ export function ArtifactFilePreview({
if (language === "markdown") {
return (
<div className="size-full px-4">
<Streamdown
<ClipboardSafeStreamdown
className="size-full"
{...streamdownPlugins}
components={{ a: ArtifactLink }}
>
{content ?? ""}
</Streamdown>
</ClipboardSafeStreamdown>
</div>
);
}

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