feat: add agents/utils/llm_api

agents/README.md

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+# EmoLLM——MetaGPT
+
+## 使用
+
+```bash
+pip install -r requirements.txt
+pip install .
+```
+
+## key 配置
+
+为确保项目正常运行，请在项目内新建`.env`文件，并在其中设置你的API密钥，你可以根据下列例子写入对应的 key，即可成功运行调用，目前默认使用 zhipuai，你可以仅写入`ZHIPUAI_API_KEY`即可使用。
+
+```bash
+OPENAI_API_KEY=
+OPENAI_API_BASE=
+ZHIPUAI_API_KEY=
+BAIDU_API_KEY=
+OPENAI_API_MODEL=
+```
+
+## MetaGPT Version
+
+https://gitee.com/jujimeizuo/meta-gpt-tianji

agents/utils/common_llm_api.py

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+from dotenv import load_dotenv
+load_dotenv()
+
+import asyncio
+import os
+import erniebot
+from zhipuai import ZhipuAI
+from metagpt.logs import logger
+
+
+
+class BaiduAPI:
+ def __init__(self):
+ pass
+
+ async def _aask(self, prompt, stream=False, model="ernie-4.0", top_p=0.95):
+ messages = [{"role": "user", "content": prompt}]
+ response = erniebot.ChatCompletion.create(
+ model=model, messages=messages, top_p=top_p, stream=stream
+ )
+ return response.result
+
+
+class ZhipuAPI:
+ def __init__(self, glm=None):
+ if glm is None:
+ raise RuntimeError("ZhipuApi is Error!")
+ self.glm = glm
+
+ async def _aask(self, prompt, stream=False, model="glm-3-turbo", top_p=0.95):
+ messages = [{"role": "user", "content": prompt}]
+ response = self.glm.chat.completions.create(
+ model=model, messages=messages, top_p=top_p, stream=stream
+ )
+ return response.choices[0].message.content
+
+
+class LLMAPI:
+ def __init__(self):
+ self.llm_api = None
+
+ # select api
+ if os.environ["ZHIPUAI_API_KEY"] is not None:
+ glm = ZhipuAI(api_key=os.environ["ZHIPUAI_API_KEY"])
+ self.llm_api = ZhipuAPI(glm=glm)
+ elif os.environ["BAIDU_API_KEY"] is not None:
+ erniebot.api_type = "aistudio"
+ erniebot.access_token = os.environ["BAIDU_API_KEY"]
+ self.llm_api = BaiduAPI()
+ else:
+ raise RuntimeError("No api_key found!")
+
+ # 这里的 model 的 default value 逻辑不对，应该是根据 api_type 来决定，不一定必须是 zhipuai
+ async def _aask(self, prompt, stream=False, model="glm-3-turbo", top_p=0.95):
+ logger.info(f"call llm_api, response is below")
+ rsp = await self.llm_api._aask(prompt, stream=stream, model=model, top_p=top_p)
+ return rsp
+
+
+if __name__ == "__main__":
+ # models = erniebot.Model.list()
+ # print("可用模型",models)
+
+ llm_api = LLMAPI()
+ # result = asyncio.run(baidu_api._aask("你好啊"))
+ result = asyncio.run(llm_api._aask("你好啊"))
+ print("result", result)