---
title: Client of Baidu Intelligent Cloud's Qianfan LLM Platform
 | Developer Documentation
---

Baidu Intelligent Cloud’s Qianfan LLM Platform offers API services for all Baidu LLMs, such as ERNIE-3.5-8K and ERNIE-4.0-8K. It also provides a small number of open-source LLMs like Llama-2-70b-chat.

Before using the chat client, you need to activate the LLM service on the Qianfan LLM Platform console’s [online service](https://console.bce.baidu.com/qianfan/ais/console/onlineService) page. Then, Generate an Access Key and a Secret Key in the [Security Authentication](https://console.bce.baidu.com/iam/#/iam/accesslist) page of the console.

## Installation

Install the necessary package:

```
%pip install llama-index-llms-qianfan
```

## Initialization

```
from llama_index.llms.qianfan import Qianfan
import asyncio


access_key = "XXX"
secret_key = "XXX"
model_name = "ERNIE-Speed-8K"
endpoint_url = "https://aip.baidubce.com/rpc/2.0/ai_custom/v1/wenxinworkshop/chat/ernie_speed"
context_window = 8192
llm = Qianfan(access_key, secret_key, model_name, endpoint_url, context_window)
```

## Synchronous Chat

Generate a chat response synchronously using the `chat` method:

```
from llama_index.core.base.llms.types import ChatMessage


messages = [
    ChatMessage(role="user", content="Tell me a joke."),
]
chat_response = llm.chat(messages)
print(chat_response.message.content)
```

## Synchronous Stream Chat

Generate a streaming chat response synchronously using the `stream_chat` method:

```
messages = [
    ChatMessage(role="system", content="You are a helpful assistant."),
    ChatMessage(role="user", content="Tell me a story."),
]
content = ""
for chat_response in llm.stream_chat(messages):
    content += chat_response.delta
    print(chat_response.delta, end="")
```

## Asynchronous Chat

Generate a chat response asynchronously using the `achat` method:

```
async def async_chat():
    messages = [
        ChatMessage(role="user", content="Tell me an async joke."),
    ]
    chat_response = await llm.achat(messages)
    print(chat_response.message.content)




asyncio.run(async_chat())
```

## Asynchronous Stream Chat

Generate a streaming chat response asynchronously using the `astream_chat` method:

```
async def async_stream_chat():
    messages = [
        ChatMessage(role="system", content="You are a helpful assistant."),
        ChatMessage(role="user", content="Tell me an async story."),
    ]
    content = ""
    response = await llm.astream_chat(messages)
    async for chat_response in response:
        content += chat_response.delta
        print(chat_response.delta, end="")




asyncio.run(async_stream_chat())
```