Enhance AssistantConfig and pipeline for FastGPT integration
- Add new fields in AssistantConfig for FastGPT connection details, including `fastgpt_api_url`, `fastgpt_api_key`, and `fastgpt_app_id`. - Update the pipeline to utilize the new FastGPT configuration, ensuring proper integration with external services. - Introduce type handling for different assistant types, including support for realtime modes and external brain management. - Refactor frontend components to include hints for FastGPT configuration inputs, improving user guidance during setup.
This commit is contained in:
Xin Wang
161
backend/services/brains/fastgpt_llm.py
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161
backend/services/brains/fastgpt_llm.py
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"""FastGPT 作为 pipecat LLM 槽位。
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与普通 LLM 的关键不同:context / 知识库 / 工具全在 FastGPT 服务端,靠 chatId
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维持会话。所以本服务只发「最后一条 user 文本」+ 稳定 chatId,把流式 answer
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事件转成 LLMTextFrame 交给下游 TTS;不消费/不依赖本地 LLMContext 的历史。
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"""
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from __future__ import annotations
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from typing import Any
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from fastgpt_client import AsyncChatClient, aiter_stream_events
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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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# 承载回复文本的事件种类。detail=False 时 FastGPT 走 OpenAI 兼容流,文本以裸
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# data: 块下发(无 event 名 → kind="data");detail=True / 旧版则用 answer/fastAnswer。
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_ANSWER_KINDS = {"data", "answer", "fastAnswer"}
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# SDK 会自动在 base_url 后拼 /api/v1/chat/completions(并去掉末尾 /api)。
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# 用户常把「完整接口地址」填进 api_url,这里剥掉这些后缀,归一成主机根地址,
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# 避免路径重复导致 404。
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_ENDPOINT_SUFFIXES = (
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"/api/v1/chat/completions",
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"/v1/chat/completions",
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"/chat/completions",
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)
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def normalize_base_url(url: str) -> str:
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base = (url or "").strip().rstrip("/")
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for suffix in _ENDPOINT_SUFFIXES:
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if base.endswith(suffix):
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base = base[: -len(suffix)]
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break
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return base or "http://localhost:3000"
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def _last_user_text(messages: list[dict]) -> str:
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"""取最近一条 user 消息的纯文本(兼容多模态分片)。"""
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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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def _event_text(data: Any) -> str:
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"""从一个流事件里取增量文本。
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兼容两种形态(对齐 SDK examples 的解析):
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- 直接 text 字段(answer/fastAnswer 详情流);
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- OpenAI 兼容块 choices[0].delta.content / message.content(detail=False)。
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"""
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if not isinstance(data, dict):
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return ""
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text = data.get("text")
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if isinstance(text, str) and text:
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return text
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choices = data.get("choices")
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if not isinstance(choices, list) or not choices:
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return ""
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first = choices[0] if isinstance(choices[0], dict) else {}
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delta = first.get("delta")
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if isinstance(delta, dict):
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content = delta.get("content")
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if isinstance(content, str) and content:
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return content
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message = first.get("message")
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if isinstance(message, dict):
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content = message.get("content")
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if isinstance(content, str) and content:
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return content
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return ""
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class FastGPTLLMService(LLMService):
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"""包 FastGPT OpenAPI 的伪 LLM 服务。"""
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def __init__(self, cfg: AssistantConfig, chat_id: str):
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# FastGPT 自管 model/温度等参数,这里把所有 LLM 设置初始化为 None,
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# 满足基类 validate_complete(否则启动期会报 NOT_GIVEN)。
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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._chat_id = chat_id
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self._base_url = normalize_base_url(cfg.fastgpt_api_url)
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self._client = AsyncChatClient(
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api_key=cfg.fastgpt_api_key,
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base_url=self._base_url,
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)
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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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response = await self._client.create_chat_completion(
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messages=[{"role": "user", "content": user_text}],
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stream=True,
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chatId=self._chat_id,
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detail=False,
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)
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async for event in aiter_stream_events(response):
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if event.kind in _ANSWER_KINDS:
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text = _event_text(event.data)
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if text:
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await self.push_frame(LLMTextFrame(text))
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elif event.kind == "error":
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logger.error(f"FastGPT 流式错误: {event.data}")
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except Exception as exc: # noqa: BLE001 - 单轮失败不应中断通话
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logger.error(
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f"FastGPT 调用失败: {exc} "
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f"(base_url={self._base_url},拼接后应为 {self._base_url}/api/v1/chat/completions)"
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)
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finally:
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await self.push_frame(LLMFullResponseEndFrame())
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