xuhdandClaude Sonnet 4.6
adeace0f7b
添加 multi-llm 路由智能体（LangGraph），支持多 LLM 分发能力；在 Gateway 中注册 /api/multi-llm 路由，并豁免其 CSRF 和认证校验；同时新增 asyncmy 依赖和聊天流格式文档。 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
89 lines
3.0 KiB
Python
89 lines
3.0 KiB
Python
"""Stream parsers for 6 external LLM systems.
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Each system returns a different streaming format. All parsers normalize the
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raw HTTP byte stream into a sequence of StreamChunk(type, content) where
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type is either "thinking" (reasoning process) or "text" (final output).
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Systems: fast, bigmodel, hxchat, moreModes, rag, taskChat
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Currently implemented: fast (Vercel AI SDK Data Stream Protocol / POST /new_chat)
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Others: TODO — using plain-text placeholder until formats are confirmed.
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"""
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from __future__ import annotations
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import abc
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import json
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from dataclasses import dataclass
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from typing import AsyncIterator, Literal
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@dataclass
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class StreamChunk:
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type: Literal["thinking", "text"]
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content: str
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class BaseSystemParser(abc.ABC):
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"""Parse a raw httpx response stream into normalized StreamChunks."""
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@abc.abstractmethod
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async def parse(self, response) -> AsyncIterator[StreamChunk]:
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...
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class FastParser(BaseSystemParser):
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"""fast: Vercel AI SDK Data Stream Protocol (POST /new_chat).
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Relevant event types:
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text-delta → StreamChunk(type="text", content=payload["delta"])
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reasoning-delta → StreamChunk(type="thinking", content=payload["delta"])
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All other event types (start, finish, start-step, finish-step,
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tool-input-*, tool-output-*, data-*, source-*, error, etc.) are silently
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skipped — they are UI-control signals, not content.
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"""
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async def parse(self, response) -> AsyncIterator[StreamChunk]:
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async for line in response.aiter_lines():
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if not line.startswith("data:"):
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continue
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raw = line[5:].strip()
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if not raw or raw == "[DONE]":
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continue
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try:
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payload = json.loads(raw)
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except json.JSONDecodeError:
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continue
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ev_type = payload.get("type", "")
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if ev_type == "text-delta":
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delta = payload.get("delta", "")
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if delta:
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yield StreamChunk(type="text", content=delta)
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elif ev_type == "reasoning-delta":
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delta = payload.get("delta", "")
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if delta:
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yield StreamChunk(type="thinking", content=delta)
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class PlainTextParser(BaseSystemParser):
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"""Fallback: plain text stream, no thinking content.
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Used as placeholder for bigmodel / hxchat / moreModes / rag / taskChat
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until their real streaming formats are confirmed.
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"""
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async def parse(self, response) -> AsyncIterator[StreamChunk]:
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async for chunk in response.aiter_text():
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if chunk:
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yield StreamChunk(type="text", content=chunk)
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PARSERS: dict[str, BaseSystemParser] = {
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"fast": FastParser(),
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"bigmodel": PlainTextParser(), # TODO: replace with real parser
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"hxchat": PlainTextParser(), # TODO: replace with real parser
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"moreModes": PlainTextParser(), # TODO: replace with real parser
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"rag": PlainTextParser(), # TODO: replace with real parser
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"taskChat": PlainTextParser(), # TODO: replace with real parser
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}
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