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64 lines
2.3 KiB
Markdown
64 lines
2.3 KiB
Markdown
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# Core ChainLit Integration Sample
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In this sample, we will demonstrate how to build simple chat interface that
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interacts with a [Core](https://microsoft.github.io/autogen/stable/user-guide/core-user-guide/index.html)
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agent or a team, using [Chainlit](https://github.com/Chainlit/chainlit),
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and support streaming messages.
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## Overview
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The `core_chainlit` sample is designed to illustrate a simple use case of ChainLit integrated with a single-threaded agent runtime. It includes the following components:
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- **Single Agent**: A single agent that operates within the ChainLit environment.
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- **Group Chat**: A group chat setup featuring two agents:
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- **Assistant Agent**: This agent responds to user inputs.
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- **Critic Agent**: This agent reflects on and critiques the responses from the Assistant Agent.
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- **Closure Agent**: Utilizes a closure agent to aggregate output messages into an output queue.
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- **Token Streaming**: Demonstrates how to stream tokens to the user interface.
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- **Session Management**: Manages the runtime and output queue within the ChainLit user session.
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## Requirements
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To run this sample, you will need:
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- Python 3.8 or higher
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- Installation of necessary Python packages as listed in `requirements.txt`
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## Installation
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To run this sample, you will need to install the following packages:
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```shell
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pip install -U chainlit autogen-core autogen-ext[openai] pyyaml
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```
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To use other model providers, you will need to install a different extra
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for the `autogen-ext` package.
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See the [Models documentation](https://microsoft.github.io/autogen/stable/user-guide/agentchat-user-guide/tutorial/models.html) for more information.
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## Model Configuration
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Create a configuration file named `model_config.yaml` to configure the model
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you want to use. Use `model_config_template.yaml` as a template.
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## Running the Agent Sample
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The first sample demonstrate how to interact with a single AssistantAgent
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from the chat interface.
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Note: cd to the sample directory.
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```shell
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chainlit run app_agent.py
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```
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## Running the Team Sample
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The second sample demonstrate how to interact with a team of agents from the
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chat interface.
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```shell
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chainlit run app_team.py -h
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```
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There are two agents in the team: one is instructed to be generally helpful
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and the other one is instructed to be a critic and provide feedback.
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