https://github.com/chainlit/chainlit-help
https://github.com/chainlit/chainlit-help
Last synced: about 2 months ago
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- Host: GitHub
- URL: https://github.com/chainlit/chainlit-help
- Owner: Chainlit
- Created: 2024-02-20T12:59:14.000Z (about 2 years ago)
- Default Branch: main
- Last Pushed: 2025-04-15T13:03:01.000Z (about 1 year ago)
- Last Synced: 2025-06-01T22:43:09.089Z (11 months ago)
- Language: Python
- Size: 1.24 MB
- Stars: 5
- Watchers: 3
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Chainlit Help
The Chainlit copilot for the Chainlit [documentation](https://docs.chainlit.io/get-started/overview).
## How to use?
### The Chainlit Application
- `cp app/.env.example app/.env`
- Obtain a Literal API key [here](https://docs.getliteral.ai/python-client/get-started/authentication#how-to-get-my-api-key)
- `pip install -r app/requirements.txt`
- `chainlit run app/app.py`
### The Chainlit Copilot
- Make sure the Chainlit application is running.
- `python -m http.server 3004 --directory copilot`
### Create context
#### Codebase context
Go to https://gitingest.com for repo `https://github.com/chainlit/chainlit` with exclude
```
.editorconfig, .eslintignore, .eslintrc, .npmrc, .prettierrc, *.json, *.lock, *.yaml, *.toml, *.md, *.js, .github, .husky, cypress, frontend, images, libs/copilot, */tests,README.md, **/__pycache__, **/*.spec.py, **/wavtools, **/.git, */__init__.py, backend, LICENSE, *.config.ts
```
to generate `codebase.txt`
#### Documentation context
Go to https://gitingest.com for repo `https://github.com/chainlit/docs` with exclude `*.json` to generate `documentation.txt`
#### Cookbook context
Go to https://gitingest.com for repo `https://github.com/chainlit/cookbook` with include `map-canvas/, realtime-assistant/` to generate `cookbook.txt`
## How to contribute?
Make all the changes you want to the application, then validate them in local against [Test dataset to ship RAG](https://cloud.getliteral.ai/projects/chainlit-doc-JicvnMkIcofi/datasets/a24f9233-d03e-4dc4-98c6-c5fec438f757).
Follow the `Experiments.ipynb` notebook to run your experiments against that dataset.
To have a locally exposed endpoint you can test with, run the `main.py` Fast API server from the root directory:
```shell
uvicorn --app-dir app main:app --host 0.0.0.0 --port 80
```
This will expose the http://localhost:80/app/ endpoint where you can put your question at the end.