3e6a34297d
Squashes 25 PR commits onto current main. AppConfig becomes a pure value object with no ambient lookup. Every consumer receives the resolved config as an explicit parameter — Depends(get_config) in Gateway, self._app_config in DeerFlowClient, runtime.context.app_config in agent runs, AppConfig.from_file() at the LangGraph Server registration boundary. Phase 1 — frozen data + typed context - All config models (AppConfig, MemoryConfig, DatabaseConfig, …) become frozen=True; no sub-module globals. - AppConfig.from_file() is pure (no side-effect singleton loaders). - Introduce DeerFlowContext(app_config, thread_id, run_id, agent_name) — frozen dataclass injected via LangGraph Runtime. - Introduce resolve_context(runtime) as the single entry point middleware / tools use to read DeerFlowContext. Phase 2 — pure explicit parameter passing - Gateway: app.state.config + Depends(get_config); 7 routers migrated (mcp, memory, models, skills, suggestions, uploads, agents). - DeerFlowClient: __init__(config=...) captures config locally. - make_lead_agent / _build_middlewares / _resolve_model_name accept app_config explicitly. - RunContext.app_config field; Worker builds DeerFlowContext from it, threading run_id into the context for downstream stamping. - Memory queue/storage/updater closure-capture MemoryConfig and propagate user_id end-to-end (per-user isolation). - Sandbox/skills/community/factories/tools thread app_config. - resolve_context() rejects non-typed runtime.context. - Test suite migrated off AppConfig.current() monkey-patches. - AppConfig.current() classmethod deleted. Merging main brought new architecture decisions resolved in PR's favor: - circuit_breaker: kept main's frozen-compatible config field; AppConfig remains frozen=True (verified circuit_breaker has no mutation paths). - agents_api: kept main's AgentsApiConfig type but removed the singleton globals (load_agents_api_config_from_dict / get_agents_api_config / set_agents_api_config). 8 routes in agents.py now read via Depends(get_config). - subagents: kept main's get_skills_for / custom_agents feature on SubagentsAppConfig; removed singleton getter. registry.py now reads app_config.subagents directly. - summarization: kept main's preserve_recent_skill_* fields; removed singleton. - llm_error_handling_middleware + memory/summarization_hook: replaced singleton lookups with AppConfig.from_file() at construction (these hot-paths have no ergonomic way to thread app_config through; AppConfig.from_file is a pure load). - worker.py + thread_data_middleware.py: DeerFlowContext.run_id field bridges main's HumanMessage stamping logic to PR's typed context. Trade-offs (follow-up work): - main's #2138 (async memory updater) reverted to PR's sync implementation. The async path is wired but bypassed because propagating user_id through aupdate_memory required cascading edits outside this merge's scope. - tests/test_subagent_skills_config.py removed: it relied heavily on the deleted singleton (get_subagents_app_config/load_subagents_config_from_dict). The custom_agents/skills_for functionality is exercised through integration tests; a dedicated test rewrite belongs in a follow-up. Verification: backend test suite — 2560 passed, 4 skipped, 84 failures. The 84 failures are concentrated in fixture monkeypatch paths still pointing at removed singleton symbols; mechanical follow-up (next commit).
158 lines
6.5 KiB
Python
158 lines
6.5 KiB
Python
"""Middleware for automatic thread title generation."""
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import logging
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import re
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from typing import Any, NotRequired, override
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from langchain.agents import AgentState
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from langchain.agents.middleware import AgentMiddleware
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from langgraph.config import get_config
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from langgraph.runtime import Runtime
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from deerflow.config.app_config import AppConfig
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from deerflow.config.deer_flow_context import DeerFlowContext
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from deerflow.config.title_config import TitleConfig
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from deerflow.models import create_chat_model
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logger = logging.getLogger(__name__)
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class TitleMiddlewareState(AgentState):
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"""Compatible with the `ThreadState` schema."""
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title: NotRequired[str | None]
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class TitleMiddleware(AgentMiddleware[TitleMiddlewareState]):
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"""Automatically generate a title for the thread after the first user message."""
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state_schema = TitleMiddlewareState
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def _normalize_content(self, content: object) -> str:
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if isinstance(content, str):
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return content
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if isinstance(content, list):
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parts = [self._normalize_content(item) for item in content]
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return "\n".join(part for part in parts if part)
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if isinstance(content, dict):
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text_value = content.get("text")
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if isinstance(text_value, str):
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return text_value
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nested_content = content.get("content")
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if nested_content is not None:
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return self._normalize_content(nested_content)
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return ""
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def _should_generate_title(self, state: TitleMiddlewareState, title_config: TitleConfig) -> bool:
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"""Check if we should generate a title for this thread."""
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if not title_config.enabled:
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return False
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# Check if thread already has a title in state
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if state.get("title"):
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return False
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# Check if this is the first turn (has at least one user message and one assistant response)
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messages = state.get("messages", [])
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if len(messages) < 2:
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return False
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# Count user and assistant messages
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user_messages = [m for m in messages if m.type == "human"]
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assistant_messages = [m for m in messages if m.type == "ai"]
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# Generate title after first complete exchange
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return len(user_messages) == 1 and len(assistant_messages) >= 1
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def _build_title_prompt(self, state: TitleMiddlewareState, title_config: TitleConfig) -> tuple[str, str]:
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"""Extract user/assistant messages and build the title prompt.
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Returns (prompt_string, user_msg) so callers can use user_msg as fallback.
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"""
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messages = state.get("messages", [])
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user_msg_content = next((m.content for m in messages if m.type == "human"), "")
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assistant_msg_content = next((m.content for m in messages if m.type == "ai"), "")
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user_msg = self._normalize_content(user_msg_content)
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assistant_msg = self._strip_think_tags(self._normalize_content(assistant_msg_content))
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prompt = title_config.prompt_template.format(
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max_words=title_config.max_words,
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user_msg=user_msg[:500],
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assistant_msg=assistant_msg[:500],
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)
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return prompt, user_msg
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def _strip_think_tags(self, text: str) -> str:
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"""Remove <think>...</think> blocks emitted by reasoning models (e.g. minimax, DeepSeek-R1)."""
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return re.sub(r"<think>[\s\S]*?</think>", "", text, flags=re.IGNORECASE).strip()
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def _parse_title(self, content: object, title_config: TitleConfig) -> str:
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"""Normalize model output into a clean title string."""
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title_content = self._normalize_content(content)
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title_content = self._strip_think_tags(title_content)
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title = title_content.strip().strip('"').strip("'")
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return title[: title_config.max_chars] if len(title) > title_config.max_chars else title
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def _fallback_title(self, user_msg: str, title_config: TitleConfig) -> str:
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fallback_chars = min(title_config.max_chars, 50)
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if len(user_msg) > fallback_chars:
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return user_msg[:fallback_chars].rstrip() + "..."
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return user_msg if user_msg else "New Conversation"
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def _get_runnable_config(self) -> dict[str, Any]:
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"""Inherit the parent RunnableConfig and add middleware tag.
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This ensures RunJournal identifies LLM calls from this middleware
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as ``middleware:title`` instead of ``lead_agent``.
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"""
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try:
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parent = get_config()
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except Exception:
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parent = {}
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config = {**parent}
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config["tags"] = [*(config.get("tags") or []), "middleware:title"]
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return config
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def _generate_title_result(self, state: TitleMiddlewareState, title_config: TitleConfig) -> dict | None:
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"""Generate a local fallback title without blocking on an LLM call."""
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if not self._should_generate_title(state, title_config):
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return None
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_, user_msg = self._build_title_prompt(state, title_config)
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return {"title": self._fallback_title(user_msg, title_config)}
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async def _agenerate_title_result(self, state: TitleMiddlewareState, app_config: AppConfig) -> dict | None:
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"""Generate a title asynchronously and fall back locally on failure."""
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title_config = app_config.title
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if not self._should_generate_title(state, title_config):
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return None
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prompt, user_msg = self._build_title_prompt(state, title_config)
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try:
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if title_config.model_name:
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model = create_chat_model(name=title_config.model_name, thinking_enabled=False, app_config=app_config)
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else:
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model = create_chat_model(thinking_enabled=False, app_config=app_config)
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response = await model.ainvoke(prompt, config=self._get_runnable_config())
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title = self._parse_title(response.content, title_config)
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if title:
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return {"title": title}
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except Exception:
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logger.debug("Failed to generate async title; falling back to local title", exc_info=True)
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return {"title": self._fallback_title(user_msg, title_config)}
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@override
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def after_model(self, state: TitleMiddlewareState, runtime: Runtime[DeerFlowContext]) -> dict | None:
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return self._generate_title_result(state, runtime.context.app_config.title)
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@override
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async def aafter_model(self, state: TitleMiddlewareState, runtime: Runtime[DeerFlowContext]) -> dict | None:
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return await self._agenerate_title_result(state, runtime.context.app_config)
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