## QianfanChatEndpoint

Baidu AI Cloud Qianfan Platform is a one-stop large model development and service operation platform for enterprise developers. Qianfan not only provides including the model of Wenxin Yiyan (ERNIE-Bot) and the third-party open-source models, but also provides various AI development tools and the whole set of development environment, which facilitates customers to use and develop large model applications easily.

Basically, those model are split into the following type:

*   Embedding
*   Chat
*   Completion

In this notebook, we will introduce how to use langchain with [Qianfan](https://cloud.baidu.com/doc/WENXINWORKSHOP/index.html) mainly in `Chat` corresponding to the package `langchain/chat_models` in langchain:

## API Initialization[​](#api-initialization "Direct link to API Initialization")

To use the LLM services based on Baidu Qianfan, you have to initialize these parameters:

You could either choose to init the AK,SK in environment variables or init params:

```
export QIANFAN_AK=XXXexport QIANFAN_SK=XXX
```

## Current supported models:[​](#current-supported-models "Direct link to Current supported models:")

*   ERNIE-Bot-turbo (default models)
*   ERNIE-Bot
*   BLOOMZ-7B
*   Llama-2-7b-chat
*   Llama-2-13b-chat
*   Llama-2-70b-chat
*   Qianfan-BLOOMZ-7B-compressed
*   Qianfan-Chinese-Llama-2-7B
*   ChatGLM2-6B-32K
*   AquilaChat-7B

## Set up[​](#set-up "Direct link to Set up")

```
"""For basic init and call"""import osfrom langchain_community.chat_models import QianfanChatEndpointfrom langchain_core.language_models.chat_models import HumanMessageos.environ["QIANFAN_AK"] = "Your_api_key"os.environ["QIANFAN_SK"] = "You_secret_Key"
```

## Usage[​](#usage "Direct link to Usage")

```
chat = QianfanChatEndpoint(streaming=True)messages = [HumanMessage(content="Hello")]chat.invoke(messages)
```

```
AIMessage(content='您好！请问您需要什么帮助？我将尽力回答您的问题。')
```

```
await chat.ainvoke(messages)
```

```
AIMessage(content='您好！有什么我可以帮助您的吗？')
```

```
[AIMessage(content='您好！有什么我可以帮助您的吗？')]
```

### Streaming[​](#streaming "Direct link to Streaming")

```
try:    for chunk in chat.stream(messages):        print(chunk.content, end="", flush=True)except TypeError as e:    print("")
```

## Use different models in Qianfan[​](#use-different-models-in-qianfan "Direct link to Use different models in Qianfan")

The default model is ERNIE-Bot-turbo, in the case you want to deploy your own model based on Ernie Bot or third-party open-source model, you could follow these steps:

1.  (Optional, if the model are included in the default models, skip it) Deploy your model in Qianfan Console, get your own customized deploy endpoint.
2.  Set up the field called `endpoint` in the initialization:

```
chatBot = QianfanChatEndpoint(    streaming=True,    model="ERNIE-Bot",)messages = [HumanMessage(content="Hello")]chatBot.invoke(messages)
```

```
AIMessage(content='Hello，可以回答问题了，我会竭尽全力为您解答，请问有什么问题吗？')
```

## Model Params:[​](#model-params "Direct link to Model Params:")

For now, only `ERNIE-Bot` and `ERNIE-Bot-turbo` support model params below, we might support more models in the future.

*   temperature
*   top\_p
*   penalty\_score

```
chat.invoke(    [HumanMessage(content="Hello")],    **{"top_p": 0.4, "temperature": 0.1, "penalty_score": 1},)
```

```
AIMessage(content='您好！有什么我可以帮助您的吗？')
```

* * *

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