Build Conversational AI in minutes ⚡️
Build python production-ready conversational AI applications in minutes, not weeks ⚡️
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NOTE
Chainlit is maintained by Literal AI, an LLMOps platform to monitor and evaluate LLM applications! It works with any Python or TypeScript applications and seamlessly with Chainlit. For enterprise support, please fill this form.
Open a terminal and run:
pip install chainlit
chainlit hello
If this opens the hello app in your browser, you're all set!
The latest in-development version can be installed straight from GitHub with:
pip install git+https://github.com/Chainlit/chainlit.git#subdirectory=backend/
(Requires Node and pnpm installed on the system.)
Create a new file demo.py with the following code:
import chainlit as cl
@cl.step(type="tool")
async def tool():
# Fake tool
await cl.sleep(2)
return "Response from the tool!"
@cl.on_message # this function will be called every time a user inputs a message in the UI
async def main(message: cl.Message):
"""
This function is called every time a user inputs a message in the UI.
It sends back an intermediate response from the tool, followed by the final answer.
Args:
message: The user's message.
Returns:
None.
"""
# Call the tool
tool_res = await tool()
await cl.Message(content=tool_res).send()
Now run it!
chainlit run demo.py -w
You can find various examples of Chainlit apps here that leverage tools and services such as OpenAI, Anthropiс, LangChain, LlamaIndex, ChromaDB, Pinecone and more.
Tell us what you would like to see added in Chainlit using the Github issues or on Discord.
As an open-source initiative in a rapidly evolving domain, we welcome contributions, be it through the addition of new features or the improvement of documentation.
For detailed information on how to contribute, see here.
Chainlit is open-source and licensed under the Apache 2.0 license.