00270a5c01
- Introduce new fields `dify_api_url` and `dify_api_key` in `AssistantConfig` for Dify API integration. - Update `requirements.txt` to include `dify-client-python` for Dify SDK support. - Modify `config_resolver` to handle Dify connection information. - Add a new `globalNode` type in workflow specifications to provide unified settings across workflows. - Enhance node specifications with additional constraints and default values for better configuration management. - Update frontend components to support the new `globalNode` type and its properties, improving workflow editor functionality.
128 lines
4.3 KiB
Python
128 lines
4.3 KiB
Python
"""Dify chat applications exposed as a Pipecat LLM processor."""
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from __future__ import annotations
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from uuid import uuid4
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from dify_client import AsyncClient, models
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from loguru import logger
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from models import AssistantConfig
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from pipecat.frames.frames import (
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Frame,
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LLMContextFrame,
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LLMFullResponseEndFrame,
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LLMFullResponseStartFrame,
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LLMTextFrame,
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)
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from pipecat.processors.frame_processor import FrameDirection
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from pipecat.services.llm_service import LLMService
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from pipecat.services.settings import LLMSettings
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def normalize_api_base(url: str) -> str:
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"""Accept a Dify host, /v1 base URL, or full chat endpoint."""
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base = (url or "https://api.dify.ai").strip().rstrip("/")
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if base.endswith("/chat-messages"):
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base = base[: -len("/chat-messages")]
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if not base.endswith("/v1"):
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base = f"{base}/v1"
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return base
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def last_user_text(messages: list[dict]) -> str:
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for message in reversed(messages or []):
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if message.get("role") != "user":
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continue
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content = message.get("content")
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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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return "".join(
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str(part.get("text") or "")
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for part in content
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if isinstance(part, dict)
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)
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return ""
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class DifyLLMService(LLMService):
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"""Stream Dify answer events into Pipecat's standard text frames."""
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def __init__(
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self,
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cfg: AssistantConfig,
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*,
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client: AsyncClient | None = None,
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user_id: str | None = None,
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):
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super().__init__(
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settings=LLMSettings(
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model=None,
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system_instruction=None,
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temperature=None,
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max_tokens=None,
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top_p=None,
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top_k=None,
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frequency_penalty=None,
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presence_penalty=None,
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seed=None,
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filter_incomplete_user_turns=None,
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user_turn_completion_config=None,
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)
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)
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self._client = client or AsyncClient(
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api_key=cfg.dify_api_key,
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api_base=normalize_api_base(cfg.dify_api_url),
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)
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self._user_id = user_id or f"ai-video-{uuid4().hex}"
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self._conversation_id = ""
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async def process_frame(self, frame: Frame, direction: FrameDirection):
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await super().process_frame(frame, direction)
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if not isinstance(frame, LLMContextFrame):
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await self.push_frame(frame, direction)
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return
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user_text = last_user_text(frame.context.get_messages())
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if not user_text:
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return
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await self.push_frame(LLMFullResponseStartFrame())
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try:
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request = models.ChatRequest(
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query=user_text,
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inputs={},
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user=self._user_id,
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response_mode=models.ResponseMode.STREAMING,
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conversation_id=self._conversation_id,
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auto_generate_name=False,
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)
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events = await self._client.achat_messages(request, timeout=120.0)
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async for event in events:
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conversation_id = getattr(event, "conversation_id", "")
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if conversation_id:
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self._conversation_id = conversation_id
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event_name = str(getattr(event, "event", ""))
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if event_name == "error":
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logger.error(
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"Dify 流式错误: "
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f"code={getattr(event, 'code', '')} "
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f"message={getattr(event, 'message', '')}"
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)
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continue
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text = (
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getattr(event, "answer", "")
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if event_name in {"message", "agent_message"}
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else ""
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)
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if event_name == "text_chunk":
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text = getattr(getattr(event, "data", None), "text", "")
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if text:
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await self.push_frame(LLMTextFrame(text))
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except Exception as exc: # noqa: BLE001 - one failed turn must not kill the call
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logger.error(f"Dify 调用失败: {exc}")
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finally:
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await self.push_frame(LLMFullResponseEndFrame())
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