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feat(uploads): inject document outline into agent context for converted files (#1738)
* feat(uploads): inject document outline into agent context for converted files
Extract headings from converted .md files and inject them into the
<uploaded_files> context block so the agent can navigate large documents
by line number before reading.
- Add `extract_outline()` to `file_conversion.py`: recognises standard
Markdown headings (#/##/###) and SEC-style bold structural headings
(**ITEM N. BUSINESS**, **PART II**); caps at 50 entries; excludes
cover-page boilerplate (WASHINGTON DC, CURRENT REPORT, SIGNATURES)
- Add `_extract_outline_for_file()` helper in `uploads_middleware.py`:
looks for a sibling `.md` file produced by the conversion pipeline
- Update `UploadsMiddleware._create_files_message()` to render the outline
under each file entry with `L{line}: {title}` format and a `read_file`
prompt for range-based reading
- Tests: 10 new tests for `extract_outline()`, 4 new tests for outline
injection in `UploadsMiddleware`; existing test updated for new `outline`
field in `uploaded_files` state
Partially addresses #1647 (agent ignores uploaded files).
* fix(uploads): stream outline file reads and strip inline bold from heading titles
- Switch extract_outline() from read_text().splitlines() to open()+line iteration
so large converted documents are not loaded into memory on every agent turn;
exits as soon as MAX_OUTLINE_ENTRIES is reached (Copilot suggestion)
- Strip **...** wrapper from standard Markdown heading titles before appending
to outline so agent context stays clean (e.g. "## **Overview**" → "Overview")
(Copilot suggestion)
- Remove unused pathlib.Path import and fix import sort order in test_file_conversion.py
to satisfy ruff CI lint
* fix(uploads): show truncation hint when outline exceeds MAX_OUTLINE_ENTRIES
When extract_outline() hits the cap it now appends a sentinel entry
{"truncated": True} instead of silently dropping the rest of the headings.
UploadsMiddleware reads the sentinel and renders a hint line:
... (showing first 50 headings; use `read_file` to explore further)
Without this the agent had no way to know the outline was incomplete and
would treat the first 50 headings as the full document structure.
* fix(uploads): fall back to configurable.thread_id when runtime.context lacks thread_id
runtime.context does not always carry thread_id (depends on LangGraph
invocation path). ThreadDataMiddleware already falls back to
get_config().configurable.thread_id — apply the same pattern so
UploadsMiddleware can resolve the uploads directory and attach outlines
in all invocation paths.
* style: apply ruff format
---------
Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
This commit is contained in:
@@ -10,10 +10,27 @@ from langchain_core.messages import HumanMessage
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from langgraph.runtime import Runtime
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from deerflow.config.paths import Paths, get_paths
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from deerflow.utils.file_conversion import extract_outline
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logger = logging.getLogger(__name__)
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def _extract_outline_for_file(file_path: Path) -> list[dict]:
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"""Return the document outline for *file_path* if a converted .md exists.
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Looks for a sibling ``<stem>.md`` file produced by the upload conversion
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pipeline. Returns an empty list when the file is not a converted document
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or when no headings are found.
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"""
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md_path = file_path.with_suffix(".md")
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if not md_path.is_file():
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return []
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outline = extract_outline(md_path)
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if outline:
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logger.debug("Extracted %d outline entries from %s", len(outline), file_path.name)
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return outline
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class UploadsMiddlewareState(AgentState):
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"""State schema for uploads middleware."""
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@@ -39,12 +56,31 @@ class UploadsMiddleware(AgentMiddleware[UploadsMiddlewareState]):
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super().__init__()
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self._paths = Paths(base_dir) if base_dir else get_paths()
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def _format_file_entry(self, file: dict, lines: list[str]) -> None:
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"""Append a single file entry (name, size, path, optional outline) to lines."""
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size_kb = file["size"] / 1024
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size_str = f"{size_kb:.1f} KB" if size_kb < 1024 else f"{size_kb / 1024:.1f} MB"
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lines.append(f"- {file['filename']} ({size_str})")
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lines.append(f" Path: {file['path']}")
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outline = file.get("outline") or []
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if outline:
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truncated = outline[-1].get("truncated", False) if outline else False
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visible = [e for e in outline if not e.get("truncated")]
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lines.append(" Document outline (use `read_file` with line ranges to read sections):")
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for entry in visible:
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lines.append(f" L{entry['line']}: {entry['title']}")
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if truncated:
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lines.append(f" ... (showing first {len(visible)} headings; use `read_file` to explore further)")
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lines.append("")
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def _create_files_message(self, new_files: list[dict], historical_files: list[dict]) -> str:
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"""Create a formatted message listing uploaded files.
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Args:
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new_files: Files uploaded in the current message.
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historical_files: Files uploaded in previous messages.
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Each file dict may contain an optional ``outline`` key — a list of
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``{title, line}`` dicts extracted from the converted Markdown file.
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Returns:
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Formatted string inside <uploaded_files> tags.
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@@ -55,23 +91,16 @@ class UploadsMiddleware(AgentMiddleware[UploadsMiddlewareState]):
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lines.append("")
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if new_files:
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for file in new_files:
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size_kb = file["size"] / 1024
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size_str = f"{size_kb:.1f} KB" if size_kb < 1024 else f"{size_kb / 1024:.1f} MB"
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lines.append(f"- {file['filename']} ({size_str})")
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lines.append(f" Path: {file['path']}")
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lines.append("")
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self._format_file_entry(file, lines)
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else:
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lines.append("(empty)")
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lines.append("")
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if historical_files:
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lines.append("The following files were uploaded in previous messages and are still available:")
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lines.append("")
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for file in historical_files:
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size_kb = file["size"] / 1024
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size_str = f"{size_kb:.1f} KB" if size_kb < 1024 else f"{size_kb / 1024:.1f} MB"
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lines.append(f"- {file['filename']} ({size_str})")
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lines.append(f" Path: {file['path']}")
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lines.append("")
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self._format_file_entry(file, lines)
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lines.append("You can read these files using the `read_file` tool with the paths shown above.")
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lines.append("</uploaded_files>")
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@@ -172,9 +201,16 @@ class UploadsMiddleware(AgentMiddleware[UploadsMiddlewareState]):
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"size": stat.st_size,
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"path": f"/mnt/user-data/uploads/{file_path.name}",
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"extension": file_path.suffix,
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"outline": _extract_outline_for_file(file_path),
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}
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)
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# Attach outlines to new files as well
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if uploads_dir:
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for file in new_files:
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phys_path = uploads_dir / file["filename"]
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file["outline"] = _extract_outline_for_file(phys_path)
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if not new_files and not historical_files:
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return None
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