From 438d6a00d981d824ef2406072d7f64d9babe1d97 Mon Sep 17 00:00:00 2001 From: eezd Date: Wed, 14 Oct 2026 23:27:51 +0800 Subject: [PATCH] Detect truncated model output and skip truncated tool calls --- backend/src/alphapulse/ai/llm.py | 14 +++++++++++--- backend/src/alphapulse/api/chat.py | 11 +++++++++-- 2 files changed, 20 insertions(+), 5 deletions(-) diff --git a/backend/src/alphapulse/ai/llm.py b/backend/src/alphapulse/ai/llm.py index 17858b6..55af8ae 100644 --- a/backend/src/alphapulse/ai/llm.py +++ b/backend/src/alphapulse/ai/llm.py @@ -54,6 +54,8 @@ class Completion: usage: dict = field(default_factory=dict) # Anthropic 的 thinking / redacted_thinking 块：工具调用循环中必须原样回传，否则接口报错 thinking_blocks: list[dict] = field(default_factory=list) + # 达到 max_tokens 被截断：工具调用的参数可能不完整，不能执行 + truncated: bool = False @dataclass @@ -175,6 +177,8 @@ async def _stream_openai(provider: AiProvider, system: str, messages: list[dict] result.usage = {"input_tokens": chunk.usage.prompt_tokens, "output_tokens": chunk.usage.completion_tokens} if not chunk.choices: continue + if chunk.choices[0].finish_reason == "length": + result.truncated = True delta = chunk.choices[0].delta if delta.content: result.text += delta.content @@ -187,7 +191,7 @@ async def _stream_openai(provider: AiProvider, system: str, messages: list[dict] call["name"] += tc.function.name if tc.function and tc.function.arguments: call["arguments"] += tc.function.arguments - result.tool_calls = [_parse_call(c["id"], c["name"], c["arguments"]) for _, c in sorted(calls.items())] + result.tool_calls = [_parse_call(c["id"], c["name"], c["arguments"], result.truncated) for _, c in sorted(calls.items())] yield result @@ -260,12 +264,16 @@ async def _stream_anthropic(provider: AiProvider, system: str, messages: list[di thinking[event.index]["signature"] += event.delta.signature elif event.type == "message_delta": result.usage["output_tokens"] = event.usage.output_tokens - result.tool_calls = [_parse_call(b["id"], b["name"], b["arguments"]) for _, b in sorted(blocks.items())] + result.truncated = event.delta.stop_reason == "max_tokens" + result.tool_calls = [_parse_call(b["id"], b["name"], b["arguments"], result.truncated) for _, b in sorted(blocks.items())] result.thinking_blocks = [b for _, b in sorted(thinking.items())] yield result -def _parse_call(call_id: str, name: str, arguments: str) -> dict: +def _parse_call(call_id: str, name: str, arguments: str, truncated: bool) -> dict: + if truncated: + # 截断的参数是半截 JSON，不解析；调用方不会执行它 + return {"id": call_id, "name": name, "arguments": {}} try: parsed = json.loads(arguments) if arguments else {} except json.JSONDecodeError as e: diff --git a/backend/src/alphapulse/api/chat.py b/backend/src/alphapulse/api/chat.py index d9ae6e6..5089f4f 100644 --- a/backend/src/alphapulse/api/chat.py +++ b/backend/src/alphapulse/api/chat.py @@ -15,7 +15,7 @@ from sqlalchemy.ext.asyncio import AsyncSession from alphapulse.ai import llm from alphapulse.ai.prompt import build_system_prompt, current_context, estimate_tokens -from alphapulse.ai.tools import run_tool, tool_specs +from alphapulse.ai.tools import ToolOutcome, run_tool, tool_specs from alphapulse.core.auth import require_admin from alphapulse.core.db import SessionLocal, get_session from alphapulse.models import AiProvider, ChatMessage, ChatSession, ContextVersion @@ -27,6 +27,7 @@ MAX_TOOL_ROUNDS = 8 # 发给前端展示的工具结果长度 TOOL_PREVIEW_CHARS = 2000 STOPPED_RESULT = json.dumps({"error": "用户已停止生成，工具未执行"}, ensure_ascii=False) +TRUNCATED_RESULT = json.dumps({"error": "输出达到最大输出上限被截断，工具参数不完整，未执行。请精简内容后重新调用"}, ensure_ascii=False) # api 只有一个进程：同一时间只允许一轮生成，Reset 也要等生成结束 generating = asyncio.Lock() @@ -177,10 +178,15 @@ async def send_message(body: SendIn) -> AsyncIterator[ServerSentEvent]: assistant = {"text": completion.text, "tool_calls": completion.tool_calls} if completion.thinking_blocks: assistant["thinking_blocks"] = completion.thinking_blocks + truncated_message = f"模型输出达到最大输出上限（{provider.max_tokens} token）被截断，可在「环境变量」页调大「最大输出」" + if completion.truncated and not completion.tool_calls: + assistant["error"] = truncated_message await save_messages(ChatMessage(session_id=current.id, role="assistant", content=assistant, provider_id=provider.id, usage=completion.usage)) messages.append({"role": "assistant", **assistant}) yield event("usage", completion.usage) if not completion.tool_calls: + if completion.truncated: + yield event("error", {"message": truncated_message}) break pending = list(completion.tool_calls) @@ -188,7 +194,8 @@ async def send_message(body: SendIn) -> AsyncIterator[ServerSentEvent]: while pending: call = pending[0] yield event("tool_call", {"id": call["id"], "name": call["name"], "arguments": call["arguments"]}) - outcome = await run_tool(call["name"], call["arguments"]) + # 截断时不执行，把原因告诉模型，让它精简后重试 + outcome = ToolOutcome(TRUNCATED_RESULT) if completion.truncated else await run_tool(call["name"], call["arguments"]) result = {"tool_call_id": call["id"], "name": call["name"], "result": outcome.result} await save_messages(ChatMessage(session_id=current.id, role="tool", content=result)) pending.pop(0)