Merge pull request #19 from 00make/main

update: 添加Gemini LLM支持并更新配置
This commit is contained in:
欣南科技
2025-02-15 09:52:51 +08:00
committed by GitHub
3 changed files with 86 additions and 1 deletions
+5 -1
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@@ -82,7 +82,7 @@ LLM:
# 可在这里找到你的api key https://bigmodel.cn/usercenter/proj-mgmt/apikeys
model_name: glm-4-flash
url: https://open.bigmodel.cn/api/paas/v4/
api_key: 你的ChatGLMLLM api key
api_key: 47ab8569b25f4c3d8ea25830a33a64ca.4cF037cViBB1df5o
OllamaLLM:
# 定义LLM API类型
type: ollama
@@ -95,6 +95,10 @@ LLM:
# 如果使用DifyLLM,配置文件里prompt(提示词)是无效的,需要在dify控制台设置提示词
base_url: https://api.dify.cn/v1
api_key: 你的DifyLLM api key
GeminiLLM:
type: gemini
api_key: 你的gemini api key
model_name: "gemini-1.5-pro" # gemini-1.5-pro 是免费的
TTS:
# 当前支持的type为edge、doubao,可自行适配
EdgeTTS:
+80
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@@ -0,0 +1,80 @@
import logging
import google.generativeai as genai
from core.providers.llm.base import LLMProviderBase
logger = logging.getLogger(__name__)
class LLMProvider(LLMProviderBase):
def __init__(self, config):
"""初始化Gemini LLM Provider"""
self.model_name = config.get("model_name", "gemini-1.5-pro")
self.api_key = config.get("api_key")
if not self.api_key or "" in self.api_key:
logger.error("你还没配置Gemini LLM的密钥,请在配置文件中配置密钥,否则无法正常工作")
return
try:
# 初始化Gemini客户端
genai.configure(api_key=self.api_key)
self.model = genai.GenerativeModel(self.model_name)
# 设置生成参数
self.generation_config = {
"temperature": 0.7,
"top_p": 0.9,
"top_k": 40,
"max_output_tokens": 2048,
}
self.chat = None
except Exception as e:
logger.error(f"Gemini初始化失败: {e}")
self.model = None
def response(self, session_id, dialogue):
"""生成Gemini对话响应"""
if not self.model:
yield "【Gemini服务未正确初始化】"
return
try:
# 处理对话历史
chat_history = []
for msg in dialogue[:-1]: # 历史对话
role = "model" if msg["role"] == "assistant" else "user"
content = msg["content"].strip()
if content:
chat_history.append({
"role": role,
"parts": [content]
})
# 获取当前消息
current_msg = dialogue[-1]["content"]
# 创建新的聊天会话
chat = self.model.start_chat(history=chat_history)
# 发送消息并获取流式响应
response = chat.send_message(
current_msg,
stream=True,
generation_config=self.generation_config
)
# 处理流式响应
for chunk in response:
if hasattr(chunk, 'text') and chunk.text:
yield chunk.text
except Exception as e:
error_msg = str(e)
logger.error(f"Gemini响应生成错误: {error_msg}")
# 针对不同错误返回友好提示
if "Rate limit" in error_msg:
yield "【Gemini服务请求太频繁,请稍后再试】"
elif "Invalid API key" in error_msg:
yield "【Gemini API key无效】"
else:
yield f"【Gemini服务响应异常: {error_msg}"
+1
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@@ -8,5 +8,6 @@ pydub==0.25.1
funasr==1.2.3
torchaudio==2.2.2
openai==1.61.0
google-generativeai==0.8.4
edge_tts==7.0.0
httpx==0.27.2