mirror of
https://github.com/xinnan-tech/xiaozhi-esp32-server.git
synced 2026-07-22 23:23:55 +08:00
feature: 新增Gemini模型支持function_call功能，支持在代理模式下使用流式stream对话模式。
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caixypromise
@@ -1,140 +1,133 @@
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import google.generativeai as genai
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from core.utils.util import check_model_key
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from core.providers.llm.base import LLMProviderBase
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from config.logger import setup_logging
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import requests
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import json
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# core/providers/llm/gemini_sdk.py
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import os, json, uuid
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from types import SimpleNamespace
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from typing import Any, Dict, List
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from google import generativeai as genai
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from google.generativeai import types, GenerationConfig
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from core.providers.llm.base import LLMProviderBase
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from core.utils.util import check_model_key
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from config.logger import setup_logging
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from google.generativeai.types import GenerateContentResponse
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log = setup_logging()
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TAG = __name__
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logger = setup_logging()
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class LLMProvider(LLMProviderBase):
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def __init__(self, config):
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"""初始化Gemini LLM Provider"""
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self.model_name = config.get("model_name", "gemini-1.5-pro")
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self.api_key = config.get("api_key")
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self.http_proxy = config.get("http_proxy")
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self.https_proxy = config.get("https_proxy")
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have_key = check_model_key("LLM", self.api_key)
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def __init__(self, cfg: Dict[str, Any]):
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self.model_name = cfg.get("model_name", "gemini-2.0-flash")
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self.api_key = cfg["api_key"]
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proxy = cfg.get("https_proxy") or cfg.get("http_proxy")
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if not have_key:
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return
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if not check_model_key("LLM", self.api_key):
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raise ValueError("无效的Gemini API Key，请检查是否配置正确")
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try:
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# 初始化Gemini客户端
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# 配置代理（如果提供了代理配置）
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self.proxies = None
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if self.http_proxy is not "" or self.https_proxy is not "":
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if proxy:
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os.environ["HTTPS_PROXY"] = os.environ["HTTP_PROXY"] = proxy
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log.bind(tag=TAG).info(f"Gemini 代理地址: {proxy}")
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self.proxies = {
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"http": self.http_proxy,
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"https": self.https_proxy,
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}
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logger.bind(tag=TAG).info(f"Gemini set proxys:{self.proxies}")
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# 使用猴子补丁修改 google-generativeai 库的请求会话
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genai.configure(api_key=self.api_key)
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self.model = genai.GenerativeModel(self.model_name)
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# 使用 session 对象配置 genai
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self.gen_cfg = GenerationConfig(
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temperature=0.7,
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top_p=0.9,
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top_k=40,
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max_output_tokens=2048,
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)
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genai.configure(api_key=self.api_key)
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self.model = genai.GenerativeModel(self.model_name)
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# 设置生成参数
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self.generation_config = {
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"temperature": 0.7,
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"top_p": 0.9,
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"top_k": 40,
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"max_output_tokens": 2048,
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}
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self.chat = None
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except Exception as e:
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logger.bind(tag=TAG).error(f"Gemini初始化失败: {e}")
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self.model = None
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@staticmethod
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def _build_tools(funcs: List[Dict[str, Any]] | None):
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if not funcs:
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return None
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return [types.Tool(function_declarations=[
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types.FunctionDeclaration(
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name=f["function"]["name"],
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description=f["function"]["description"],
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parameters=f["function"]["parameters"],
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)
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for f in funcs
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])]
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# Gemini文档提到，无需维护session-id，直接用dialogue拼接而成
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def response(self, session_id, dialogue):
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"""生成Gemini对话响应"""
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if not self.model:
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yield "【Gemini服务未正确初始化】"
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return
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try:
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# 处理对话历史
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chat_history = []
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for msg in dialogue[:-1]: # 历史对话
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role = "model" if msg["role"] == "assistant" else "user"
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content = msg["content"].strip()
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if content:
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chat_history.append({"role": role, "parts": [{"text": content}]})
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# 获取当前消息
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current_msg = dialogue[-1]["content"]
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# 构建请求体
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request_body = {
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"contents": chat_history
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+ [{"role": "user", "parts": [{"text": current_msg}]}],
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"generationConfig": self.generation_config,
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}
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# 构建请求URL
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url = f"https://generativelanguage.googleapis.com/v1beta/models/{self.model_name}:generateContent?key={self.api_key}"
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# 构建请求头
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headers = {
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"Content-Type": "application/json",
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}
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# 发送POST请求,经测试手动 request 无法使用 stream 模式
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if self.proxies:
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response = requests.post(
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url,
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headers=headers,
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json=request_body,
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stream=False,
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proxies=self.proxies,
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)
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try:
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data = response.json() # 直接解析JSON
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if "candidates" in data and data["candidates"]:
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yield data["candidates"][0]["content"]["parts"][0]["text"]
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else:
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yield "未找到候选回复。"
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except json.JSONDecodeError as e:
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yield f"JSON解码错误：{e}"
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except Exception as e:
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yield f"发生错误：{e}"
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else:
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logger.bind(tag=TAG).info(f"Gemini stream mode ")
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chat = self.model.start_chat(history=chat_history)
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# 发送消息并获取流式响应
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response = chat.send_message(
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current_msg, stream=True, generation_config=self.generation_config
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)
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# 处理流式响应
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for chunk in response:
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if hasattr(chunk, "text") and chunk.text:
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yield chunk.text
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except Exception as e:
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error_msg = str(e)
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logger.bind(tag=TAG).error(f"Gemini响应生成错误: {error_msg}")
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# 针对不同错误返回友好提示
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if "Rate limit" in error_msg:
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yield "【Gemini服务请求太频繁,请稍后再试】"
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elif "Invalid API key" in error_msg:
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yield "【Gemini API key无效】"
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else:
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yield f"【Gemini服务响应异常: {error_msg}】"
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except requests.exceptions.RequestException as e:
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yield f"请求失败：{e}"
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except json.JSONDecodeError as e:
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yield f"JSON解码错误：{e}"
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except Exception as e:
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yield f"发生错误：{e}"
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yield from self._generate(dialogue, None)
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def response_with_functions(self, session_id, dialogue, functions=None):
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logger.bind(tag=TAG).info(f"gemini暂未实现完整的工具调用（function call）")
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return self.response(session_id, dialogue)
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yield from self._generate(dialogue, self._build_tools(functions))
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def _generate(self, dialogue, tools):
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role_map = {"assistant": "model", "user": "user"}
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contents: list = []
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# 拼接对话
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for m in dialogue:
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r = m["role"]
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if r == "assistant" and "tool_calls" in m:
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tc = m["tool_calls"][0]
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contents.append({
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"role": "model",
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"parts": [{"function_call": {
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"name": tc["function"]["name"],
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"args": json.loads(tc["function"]["arguments"]),
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}}],
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})
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continue
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if r == "tool":
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contents.append({
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"role": "model",
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"parts": [{"text": str(m.get("content", ""))}],
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})
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continue
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contents.append({
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"role": role_map.get(r, "user"),
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"parts": [{"text": str(m.get("content", ""))}],
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})
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stream: GenerateContentResponse = self.model.generate_content(
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contents=contents,
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generation_config=self.gen_cfg,
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tools=tools,
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stream=True,
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)
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try:
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for chunk in stream:
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cand = chunk.candidates[0]
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for part in cand.content.parts:
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# a) 函数调用-通常是最后一段话才是函数调用
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if getattr(part, "function_call", None):
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fc = part.function_call
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yield None, [SimpleNamespace(
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id=uuid.uuid4().hex,
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type="function",
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function=SimpleNamespace(
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name=fc.name,
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arguments=json.dumps(dict(fc.args),
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ensure_ascii=False),
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),
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)]
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return
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# b) 普通文本
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if getattr(part, "text", None):
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yield part.text if tools is None else (part.text, None)
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finally:
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if tools is not None:
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yield None, None # function‑mode 结束，返回哑包
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# 关闭stream，预留后续打断对话功能的功能方法，官方文档推荐打断对话要关闭上一个流，可以有效减少配额计费和资源占用
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@staticmethod
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def _safe_finish_stream(stream: GenerateContentResponse):
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if hasattr(stream, "resolve"):
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stream.resolve() # Gemini SDK version ≥ 0.5.0
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elif hasattr(stream, "close"):
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stream.close() # Gemini SDK version < 0.5.0
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else:
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for _ in stream: # 兜底耗尽
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pass
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