* Auto create conversation when the user starts * Add conversation rename rule check * Fix empty name during save * Confirm deleting conversation * Show warning if users don't select file when upload files in the File Index * Feedback when user uploads duplicated file * Limit the file types * Fix valid username * Allow login when username with leading and trailing whitespaces * Improve the user * Disable admin panel for non-admnin user * Refresh user lists after creating/deleting users * Auto logging in * Clear admin information upon signing out * Fix unable to receive uploaded filename that include special characters, like !@#$%^&*().pdf * Set upload validation for FileIndex * Improve user management UI/UIX * Show extraction error when indexing file * Return selected user -1 when signing out * Fix default supported file types in file index * Validate changing password * Allow the selector to contain mulitple gradio components * A more tolerable placeholder screen * Allow chat suggestion box * Increase concurrency limit * Make adobe loader optional * Use BaseReasoning --------- Co-authored-by: trducng <trungduc1992@gmail.com> |
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.github/workflows | ||
docs | ||
libs | ||
scripts | ||
templates | ||
.env | ||
.gitattributes | ||
.gitignore | ||
.pre-commit-config.yaml | ||
doc_env_reqs.txt | ||
LICENSE.txt | ||
mkdocs.yml | ||
pyproject.toml | ||
README.md |
kotaemon
Build and use local RAG-based Question Answering (QA) applications.
This repository would like to appeal to both end users who want to do QA on their documents and developers who want to build their own QA pipeline.
- For end users:
- A local Question Answering UI for RAG-based QA.
- Supports LLM API providers (OpenAI, AzureOpenAI, Cohere, etc) and local LLMs
(currently only GGUF format is supported via
llama-cpp-python
). - Easy installation scripts, no environment setup required.
- For developers:
- A framework for building your own RAG-based QA pipeline.
- See your RAG pipeline in action with the provided UI (built with Gradio).
- Share your pipeline so that others can use it.
This repository is under active development. Feedback, issues, and PRs are highly appreciated. Your input is valuable as it helps us persuade our business guys to support open source.
Installation
Manual installation
-
Clone the repo
git clone git@github.com:Cinnamon/kotaemon.git cd kotaemon
-
Install the environment
-
Create a conda environment (python >= 3.10 is recommended)
conda create -n kotaemon python=3.10 conda activate kotaemon # install dependencies cd libs/kotaemon pip install -e ".[all]"
-
Or run the installer (one of the
scripts/run_*
scripts depends on your OS), then you will have all the dependencies installed as a conda environment atinstall_dir/env
.conda activate install_dir/env
-
-
Pre-commit
pre-commit install
-
Test
pytest tests
From installation scripts
- Clone the repository.
- Navigate to the
scripts
folder and start an installer that matches your OS:- Linux:
run_linux.sh
- Windows:
run_windows.bat
- macOS:
run_macos.sh
- Linux:
- After the installation, the installer will ask to launch the ktem's UI,answer to continue.
- If launched, the application will be available at
http://localhost:7860/
. - The conda environment is located in the
install_dir/env
folder.
Here is the setup and update strategy:
- Run the
run_*
script: This setup environment, including downloading Miniconda (in case Conda is not available in your machine) and installing necessary dependencies ininstall_dir
folder. - Launch the UI: To launch the ktem's UI after initial setup or any changes, simply run
run_*
script again. - Reinstall dependencies: Simply delete the
install_dir/env
folder and runrun_*
script again. The script will recreate the folder with fresh dependencies.