腾讯混元大模型集成LangChain

腾讯混元大模型集成LangChain

获取API密钥

登录控制台–>访问管理–>API密钥管理–>新建密钥，获取到SecretId和SecretKey。访问链接：https://console.cloud.tencent.com/cam/capi

python SDK方式调用大模型

可参考腾讯官方API

import json
import typesfrom tencentcloud.common import credential
from tencentcloud.common.profile.client_profile import ClientProfile
from tencentcloud.common.profile.http_profile import HttpProfile
from tencentcloud.common.exception.tencent_cloud_sdk_exception import TencentCloudSDKException
from tencentcloud.hunyuan.v20230901 import hunyuan_client, modelstry:cred = credential.Credential("SecretId", "SecretKey")httpProfile = HttpProfile()httpProfile.endpoint = "hunyuan.tencentcloudapi.com"clientProfile = ClientProfile()clientProfile.httpProfile = httpProfileclient = hunyuan_client.HunyuanClient(cred, "", clientProfile)# 实例化一个请求对象,每个接口都会对应一个request对象req = models.ChatCompletionsRequest()params = {"TopP": 1,"Temperature": 1,"Model": "hunyuan-pro","Messages": [{"Role": "system","Content": "将英文单词转换为包括中文翻译、英文释义和一个例句的完整解释。请检查所有信息是否准确，并在回答时保持简洁，不需要任何其他反馈。"},{"Role": "user","Content": "nice"}]}req.from_json_string(json.dumps(params))resp = client.ChatCompletions(req)if isinstance(resp, types.GeneratorType):  # 流式响应for event in resp:print(event)else:  # 非流式响应print(resp)except TencentCloudSDKException as err:print(err)

注：需要将上述"SecretId"和"SecretKey"替换成自己创建的API密钥。

集成LangChain

import jsonfrom langchain.llms.base import LLM
from typing import Any, List, Mapping, Optionalfrom pydantic import Field
from tencentcloud.common import credential
from tencentcloud.common.profile.client_profile import ClientProfile
from tencentcloud.common.profile.http_profile import HttpProfile
from tencentcloud.common.exception.tencent_cloud_sdk_exception import TencentCloudSDKException
from tencentcloud.hunyuan.v20230901 import hunyuan_client, modelsclass HunyuanAI(LLM):secret_id: str = Field(..., description="Tencent Cloud Secret ID")secret_key: str = Field(..., description="Tencent Cloud Secret Key")@propertydef _llm_type(self) -> str:return "hunyuan"def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str:try:cred = credential.Credential(self.secret_id, self.secret_key)httpProfile = HttpProfile()httpProfile.endpoint = "hunyuan.tencentcloudapi.com"clientProfile = ClientProfile()clientProfile.httpProfile = httpProfileclient = hunyuan_client.HunyuanClient(cred, "", clientProfile)req = models.ChatCompletionsRequest()params = {"TopP": 1,"Temperature": 1,"Model": "hunyuan-pro","Messages": [{"Role": "user","Content": prompt}]}req.from_json_string(json.dumps(params))resp = client.ChatCompletions(req)return resp.Choices[0].Message.Contentexcept TencentCloudSDKException as err:raise ValueError(f"Error calling Hunyuan AI: {err}")try:# 创建 HunyuanAI 实例llm = HunyuanAI(secret_id=SecretId, secret_key=SecretKey)question = input("请输入问题：")# 运行链result = llm.invoke(question)# 打印结果print(result)except Exception as err:print(f"An error occurred: {err}")

注：需要将上述"SecretId"和"SecretKey"替换成自己创建的API密钥。

集成LangChain且自定义输入提示模板

import jsonfrom langchain.llms.base import LLM
from langchain.prompts.chat import ChatPromptTemplate, HumanMessagePromptTemplate, SystemMessagePromptTemplate
from langchain.schema import HumanMessage, SystemMessage
from langchain.chains import LLMChain
from typing import Any, List, Mapping, Optional, Dictfrom pydantic import Field
from tencentcloud.common import credential
from tencentcloud.common.profile.client_profile import ClientProfile
from tencentcloud.common.profile.http_profile import HttpProfile
from tencentcloud.common.exception.tencent_cloud_sdk_exception import TencentCloudSDKException
from tencentcloud.hunyuan.v20230901 import hunyuan_client, modelsclass HunyuanAI(LLM):secret_id: str = Field(..., description="Tencent Cloud Secret ID")secret_key: str = Field(..., description="Tencent Cloud Secret Key")@propertydef _llm_type(self) -> str:return "hunyuan"def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str:# 将 prompt 解析为消息列表messages = self._parse_prompt(prompt)try:cred = credential.Credential(self.secret_id, self.secret_key)httpProfile = HttpProfile()httpProfile.endpoint = "hunyuan.tencentcloudapi.com"clientProfile = ClientProfile()clientProfile.httpProfile = httpProfileclient = hunyuan_client.HunyuanClient(cred, "", clientProfile)req = models.ChatCompletionsRequest()params = {"TopP": 1,"Temperature": 1,"Model": "hunyuan-pro","Messages": messages}req.from_json_string(json.dumps(params))resp = client.ChatCompletions(req)return resp.Choices[0].Message.Contentexcept TencentCloudSDKException as err:raise ValueError(f"Error calling Hunyuan AI: {err}")def _parse_prompt(self, prompt: str) -> List[Dict[str, str]]:"""将 LangChain 格式的 prompt 解析为 Hunyuan API 所需的消息格式"""messages = []for message in prompt.split('Human: '):if message.startswith('System: '):messages.append({"Role": "system", "Content": message[8:]})elif message:messages.append({"Role": "user", "Content": message})return messagestry:# 创建 HunyuanAI 实例llm = HunyuanAI(secret_id=SecretId, secret_key=SecretKey)# 创建系统消息模板system_template = "你是一个英语词典助手。你的任务是提供以下信息：\n1. 单词的中文翻译\n2. 英文释义\n3. 一个例句\n请保持回答简洁明了。"system_message_prompt = SystemMessagePromptTemplate.from_template(system_template)# 创建人类消息模板human_template = "请为英文单词 '{word}' 提供解释。如果这个词有多个常见含义，请列出最常见的 2-3 个含义。"human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)# 将系统消息和人类消息组合成聊天提示模板chat_prompt = ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])# 创建 LLMChainchain = LLMChain(llm=llm, prompt=chat_prompt)# 运行链word = input("请输入要查询的英文单词: ")result = chain.invoke(input={"word": word})# 打印结果print(result)except Exception as err:print(f"An error occurred: {err}")

注：需要将上述"SecretId"和"SecretKey"替换成自己创建的API密钥。