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https://gitee.com/wanwujie/deer-flow
synced 2026-04-23 06:04:46 +08:00
feat: add IM channels for Feishu, Slack, and Telegram (#1010)
* feat: add IM channels system for Feishu, Slack, and Telegram integration Bridge external messaging platforms to DeerFlow via LangGraph Server with async message bus, thread management, and per-channel configuration. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * fix: address review comments on IM channels system Fix topic_id handling in store remove/list_entries and manager commands, correct Telegram reply threading, remove unused imports/variables, update docstrings and docs to match implementation, and prevent config mutation. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> * update skill creator * fix im reply text * fix comments --------- Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
DanielWalnut
367
backend/src/channels/manager.py
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367
backend/src/channels/manager.py
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"""ChannelManager — consumes inbound messages and dispatches them to the DeerFlow agent via LangGraph Server."""
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from __future__ import annotations
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import asyncio
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import logging
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from src.channels.message_bus import InboundMessage, InboundMessageType, MessageBus, OutboundMessage
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from src.channels.store import ChannelStore
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logger = logging.getLogger(__name__)
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DEFAULT_LANGGRAPH_URL = "http://localhost:2024"
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DEFAULT_GATEWAY_URL = "http://localhost:8001"
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DEFAULT_ASSISTANT_ID = "lead_agent"
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def _extract_response_text(result: dict | list) -> str:
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"""Extract the last AI message text from a LangGraph runs.wait result.
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``runs.wait`` returns the final state dict which contains a ``messages``
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list. Each message is a dict with at least ``type`` and ``content``.
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Handles special cases:
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- Regular AI text responses
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- Clarification interrupts (``ask_clarification`` tool messages)
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- AI messages with tool_calls but no text content
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"""
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if isinstance(result, list):
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messages = result
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elif isinstance(result, dict):
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messages = result.get("messages", [])
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else:
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return ""
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# Walk backwards to find usable response text
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for msg in reversed(messages):
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if not isinstance(msg, dict):
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continue
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msg_type = msg.get("type")
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# Check for tool messages from ask_clarification (interrupt case)
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if msg_type == "tool" and msg.get("name") == "ask_clarification":
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content = msg.get("content", "")
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if isinstance(content, str) and content:
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return content
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# Regular AI message with text content
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if msg_type == "ai":
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content = msg.get("content", "")
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if isinstance(content, str) and content:
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return content
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# content can be a list of content blocks
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if isinstance(content, list):
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parts = []
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for block in content:
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if isinstance(block, dict) and block.get("type") == "text":
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parts.append(block.get("text", ""))
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elif isinstance(block, str):
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parts.append(block)
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text = "".join(parts)
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if text:
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return text
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return ""
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def _extract_artifacts(result: dict | list) -> list[str]:
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"""Extract artifact paths from the last AI response cycle only.
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Instead of reading the full accumulated ``artifacts`` state (which contains
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all artifacts ever produced in the thread), this inspects the messages after
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the last human message and collects file paths from ``present_files`` tool
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calls. This ensures only newly-produced artifacts are returned.
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"""
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if isinstance(result, list):
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messages = result
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elif isinstance(result, dict):
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messages = result.get("messages", [])
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else:
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return []
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artifacts: list[str] = []
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for msg in reversed(messages):
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if not isinstance(msg, dict):
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continue
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# Stop at the last human message — anything before it is a previous turn
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if msg.get("type") == "human":
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break
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# Look for AI messages with present_files tool calls
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if msg.get("type") == "ai":
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for tc in msg.get("tool_calls", []):
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if isinstance(tc, dict) and tc.get("name") == "present_files":
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args = tc.get("args", {})
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paths = args.get("filepaths", [])
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if isinstance(paths, list):
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artifacts.extend(p for p in paths if isinstance(p, str))
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return artifacts
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def _format_artifact_text(artifacts: list[str]) -> str:
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"""Format artifact paths into a human-readable text block listing filenames."""
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import posixpath
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filenames = [posixpath.basename(p) for p in artifacts]
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if len(filenames) == 1:
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return f"Created File: 📎 {filenames[0]}"
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return "Created Files: 📎 " + "、".join(filenames)
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class ChannelManager:
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"""Core dispatcher that bridges IM channels to the DeerFlow agent.
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It reads from the MessageBus inbound queue, creates/reuses threads on
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the LangGraph Server, sends messages via ``runs.wait``, and publishes
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outbound responses back through the bus.
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"""
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def __init__(
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self,
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bus: MessageBus,
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store: ChannelStore,
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*,
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max_concurrency: int = 5,
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langgraph_url: str = DEFAULT_LANGGRAPH_URL,
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gateway_url: str = DEFAULT_GATEWAY_URL,
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assistant_id: str = DEFAULT_ASSISTANT_ID,
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) -> None:
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self.bus = bus
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self.store = store
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self._max_concurrency = max_concurrency
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self._langgraph_url = langgraph_url
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self._gateway_url = gateway_url
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self._assistant_id = assistant_id
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self._client = None # lazy init — langgraph_sdk async client
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self._semaphore: asyncio.Semaphore | None = None
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self._running = False
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self._task: asyncio.Task | None = None
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# -- LangGraph SDK client (lazy) ----------------------------------------
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def _get_client(self):
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"""Return the ``langgraph_sdk`` async client, creating it on first use."""
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if self._client is None:
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from langgraph_sdk import get_client
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self._client = get_client(url=self._langgraph_url)
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return self._client
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# -- lifecycle ---------------------------------------------------------
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async def start(self) -> None:
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"""Start the dispatch loop."""
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if self._running:
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return
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self._running = True
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self._semaphore = asyncio.Semaphore(self._max_concurrency)
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self._task = asyncio.create_task(self._dispatch_loop())
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logger.info("ChannelManager started (max_concurrency=%d)", self._max_concurrency)
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async def stop(self) -> None:
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"""Stop the dispatch loop."""
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self._running = False
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if self._task:
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self._task.cancel()
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try:
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await self._task
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except asyncio.CancelledError:
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pass
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self._task = None
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logger.info("ChannelManager stopped")
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# -- dispatch loop -----------------------------------------------------
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async def _dispatch_loop(self) -> None:
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logger.info("[Manager] dispatch loop started, waiting for inbound messages")
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while self._running:
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try:
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msg = await asyncio.wait_for(self.bus.get_inbound(), timeout=1.0)
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except TimeoutError:
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continue
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except asyncio.CancelledError:
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break
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logger.info(
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"[Manager] received inbound: channel=%s, chat_id=%s, type=%s, text=%r",
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msg.channel_name,
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msg.chat_id,
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msg.msg_type.value,
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msg.text[:100] if msg.text else "",
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)
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task = asyncio.create_task(self._handle_message(msg))
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task.add_done_callback(self._log_task_error)
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@staticmethod
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def _log_task_error(task: asyncio.Task) -> None:
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"""Surface unhandled exceptions from background tasks."""
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if task.cancelled():
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return
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exc = task.exception()
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if exc:
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logger.error("[Manager] unhandled error in message task: %s", exc, exc_info=exc)
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async def _handle_message(self, msg: InboundMessage) -> None:
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async with self._semaphore:
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try:
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if msg.msg_type == InboundMessageType.COMMAND:
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await self._handle_command(msg)
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else:
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await self._handle_chat(msg)
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except Exception:
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logger.exception(
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"Error handling message from %s (chat=%s)",
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msg.channel_name,
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msg.chat_id,
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)
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await self._send_error(msg, "An internal error occurred. Please try again.")
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# -- chat handling -----------------------------------------------------
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async def _create_thread(self, client, msg: InboundMessage) -> str:
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"""Create a new thread on the LangGraph Server and store the mapping."""
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thread = await client.threads.create()
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thread_id = thread["thread_id"]
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self.store.set_thread_id(
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msg.channel_name,
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msg.chat_id,
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thread_id,
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topic_id=msg.topic_id,
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user_id=msg.user_id,
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)
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logger.info("[Manager] new thread created on LangGraph Server: thread_id=%s for chat_id=%s topic_id=%s", thread_id, msg.chat_id, msg.topic_id)
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return thread_id
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async def _handle_chat(self, msg: InboundMessage) -> None:
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client = self._get_client()
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# Look up existing DeerFlow thread by topic_id (if present)
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thread_id = None
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if msg.topic_id:
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thread_id = self.store.get_thread_id(msg.channel_name, msg.chat_id, topic_id=msg.topic_id)
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if thread_id:
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logger.info("[Manager] reusing thread: thread_id=%s for topic_id=%s", thread_id, msg.topic_id)
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# No existing thread found — create a new one
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if thread_id is None:
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thread_id = await self._create_thread(client, msg)
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logger.info("[Manager] invoking runs.wait(thread_id=%s, text=%r)", thread_id, msg.text[:100])
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result = await client.runs.wait(
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thread_id,
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self._assistant_id,
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input={"messages": [{"role": "human", "content": msg.text}]},
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config={"recursion_limit": 100},
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context={
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"thread_id": thread_id,
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"thinking_enabled": True,
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"is_plan_mode": False,
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"subagent_enabled": False,
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},
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)
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response_text = _extract_response_text(result)
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artifacts = _extract_artifacts(result)
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logger.info(
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"[Manager] agent response received: thread_id=%s, response_len=%d, artifacts=%d",
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thread_id,
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len(response_text) if response_text else 0,
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len(artifacts),
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)
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# Append artifact filenames when present
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if artifacts:
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artifact_text = _format_artifact_text(artifacts)
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if response_text:
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response_text = response_text + "\n\n" + artifact_text
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else:
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response_text = artifact_text
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if not response_text:
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response_text = "(No response from agent)"
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outbound = OutboundMessage(
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channel_name=msg.channel_name,
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chat_id=msg.chat_id,
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thread_id=thread_id,
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text=response_text,
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artifacts=artifacts,
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thread_ts=msg.thread_ts,
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)
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logger.info("[Manager] publishing outbound message to bus: channel=%s, chat_id=%s", msg.channel_name, msg.chat_id)
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await self.bus.publish_outbound(outbound)
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# -- command handling --------------------------------------------------
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async def _handle_command(self, msg: InboundMessage) -> None:
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text = msg.text.strip()
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parts = text.split(maxsplit=1)
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command = parts[0].lower().lstrip("/")
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if command == "new":
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# Create a new thread on the LangGraph Server
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client = self._get_client()
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thread = await client.threads.create()
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new_thread_id = thread["thread_id"]
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self.store.set_thread_id(
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msg.channel_name,
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msg.chat_id,
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new_thread_id,
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topic_id=msg.topic_id,
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user_id=msg.user_id,
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)
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reply = "New conversation started."
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elif command == "status":
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thread_id = self.store.get_thread_id(msg.channel_name, msg.chat_id, topic_id=msg.topic_id)
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reply = f"Active thread: {thread_id}" if thread_id else "No active conversation."
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elif command == "models":
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reply = await self._fetch_gateway("/api/models", "models")
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elif command == "memory":
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reply = await self._fetch_gateway("/api/memory", "memory")
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elif command == "help":
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reply = "Available commands:\n/new — Start a new conversation\n/status — Show current thread info\n/models — List available models\n/memory — Show memory status\n/help — Show this help"
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else:
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reply = f"Unknown command: /{command}. Type /help for available commands."
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outbound = OutboundMessage(
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channel_name=msg.channel_name,
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chat_id=msg.chat_id,
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thread_id=self.store.get_thread_id(msg.channel_name, msg.chat_id) or "",
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text=reply,
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thread_ts=msg.thread_ts,
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)
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await self.bus.publish_outbound(outbound)
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async def _fetch_gateway(self, path: str, kind: str) -> str:
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"""Fetch data from the Gateway API for command responses."""
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import httpx
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try:
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async with httpx.AsyncClient() as http:
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resp = await http.get(f"{self._gateway_url}{path}", timeout=10)
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resp.raise_for_status()
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data = resp.json()
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except Exception:
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logger.exception("Failed to fetch %s from gateway", kind)
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return f"Failed to fetch {kind} information."
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if kind == "models":
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names = [m["name"] for m in data.get("models", [])]
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return ("Available models:\n" + "\n".join(f"• {n}" for n in names)) if names else "No models configured."
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elif kind == "memory":
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facts = data.get("facts", [])
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return f"Memory contains {len(facts)} fact(s)."
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return str(data)
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# -- error helper ------------------------------------------------------
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async def _send_error(self, msg: InboundMessage, error_text: str) -> None:
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outbound = OutboundMessage(
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channel_name=msg.channel_name,
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chat_id=msg.chat_id,
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thread_id=self.store.get_thread_id(msg.channel_name, msg.chat_id) or "",
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text=error_text,
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thread_ts=msg.thread_ts,
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)
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await self.bus.publish_outbound(outbound)
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