langchain1.x学习笔记（三）：langchain之init_chat_model的新用法

在langchain1.x中，使用init_chat_model函数进行构建model。

1. 第一种方式：支持硅基流动的调用

python 复制代码

from envs.envs import OPENAI_BASE_URL, OPENAI_BASE_MODEL, OPENAI_API_KEY
from langchain.chat_models import init_chat_model

model = init_chat_model(
    model_provider="openai",
    model=OPENAI_BASE_MODEL,
    api_key=OPENAI_API_KEY,
    base_url=OPENAI_BASE_URL,
    temperature=0,
)

response = model.invoke(input="hello")

print(response)

2. 第二种方式：后配置

python 复制代码

from envs.envs import OPENAI_BASE_URL, OPENAI_BASE_MODEL, OPENAI_API_KEY
from langchain.chat_models import init_chat_model

model = init_chat_model(
    temperature=0,
)

response = model.invoke(
    input="hello",
    config={
        "model_provider": "openai",
        "model": OPENAI_BASE_MODEL,
        "api_key": OPENAI_API_KEY,
        "base_url": OPENAI_BASE_URL,
        "max_tokens": 4096,
    },
)

print(response)

3. 第三种：流式输出

python 复制代码

from envs.envs import OPENAI_BASE_URL, OPENAI_BASE_MODEL, OPENAI_API_KEY
from langchain.chat_models import init_chat_model

model = init_chat_model(
    temperature=0,
)

stream = model.stream(
    input="hello",
    config={
        "model_provider": "openai",
        "model": OPENAI_BASE_MODEL,
        "api_key": OPENAI_API_KEY,
        "base_url": OPENAI_BASE_URL,
        "max_tokens": 4096,
    },
)

for chunk in stream:
    print(chunk.content, end="", flush=True)

4. 第四种：异步流式输出

python 复制代码

from envs.envs import OPENAI_BASE_URL, OPENAI_BASE_MODEL, OPENAI_API_KEY
from langchain.chat_models import init_chat_model
import asyncio


async def async_stream():
    model = init_chat_model(
        temperature=0,
    )

    stream = model.astream(
        input="hello",
        config={
            "model_provider": "openai",
            "model": OPENAI_BASE_MODEL,
            "api_key": OPENAI_API_KEY,
            "base_url": OPENAI_BASE_URL,
            "max_tokens": 4096,
        },
    )

    async for chunk in stream:
        print(chunk.content, end="", flush=True)


if __name__ == "__main__":
    asyncio.run(async_stream())

5. 提示词模板结合管道进行使用

python 复制代码

from envs.envs import OPENAI_BASE_URL, OPENAI_BASE_MODEL, OPENAI_API_KEY
from langchain.chat_models import init_chat_model
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.output_parsers import StrOutputParser


prompt = ChatPromptTemplate.from_messages(
    [
        ("system", "You are a helpful assistant."),
        ("human", "{question}"),
    ]
)

model = init_chat_model(
    model_provider="openai",
    model=OPENAI_BASE_MODEL,
    api_key=OPENAI_API_KEY,
    base_url=OPENAI_BASE_URL,
)


chain = prompt | model | StrOutputParser()


result = chain.invoke({"question": "你是谁?"})

print(result)