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docs: improve installation instructions (#620) #none
* docs: update instructions * fix: typo in CONTRIBUTING.md (#614) * fix: typo in usage.md (#598) minor typo fix (tt -> it) --------- Co-authored-by: Varun Sharma <contactvarun27@gmail.com> Co-authored-by: natowi <natowi@users.noreply.github.com>
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@ -33,7 +33,7 @@ git checkout -b descriptive-name-for-your-changes
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4. **Setup the development environment**: If you are working on the code, make sure to install the necessary dependencies for development
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```sh
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pip install -e "libs/kotaemon[dev]
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pip install -e "libs/kotaemon[dev]"
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```
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5. **Make your changes**: Ensure your code follows the project's coding style and passes all test cases.
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@ -101,6 +101,7 @@ documents and developers who want to build their own RAG pipeline.
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docker run \
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-e GRADIO_SERVER_NAME=0.0.0.0 \
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-e GRADIO_SERVER_PORT=7860 \
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-v ./ktem_app_data:/app/ktem_app_data \
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-p 7860:7860 -it --rm \
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ghcr.io/cinnamon/kotaemon:main-lite
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```
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@ -111,6 +112,7 @@ documents and developers who want to build their own RAG pipeline.
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docker run \
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-e GRADIO_SERVER_NAME=0.0.0.0 \
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-e GRADIO_SERVER_PORT=7860 \
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-v ./ktem_app_data:/app/ktem_app_data \
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-p 7860:7860 -it --rm \
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ghcr.io/cinnamon/kotaemon:main-full
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```
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@ -122,6 +124,7 @@ documents and developers who want to build their own RAG pipeline.
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docker run \
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-e GRADIO_SERVER_NAME=0.0.0.0 \
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-e GRADIO_SERVER_PORT=7860 \
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-v ./ktem_app_data:/app/ktem_app_data \
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-p 7860:7860 -it --rm \
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--platform linux/arm64 \
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ghcr.io/cinnamon/kotaemon:main-lite
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@ -28,6 +28,7 @@ Download the `kotaemon-app.zip` file from the [latest release](https://github.co
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- Linux: `run_linux.sh`. Please run the script using `bash run_linux.sh` in your terminal.
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2. After the installation, the installer will ask to launch the ktem's UI, answer to continue.
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3. If launched, the application will be open automatically in your browser.
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4. Default login information is: `username: admin / password: admin`. You should change this credential right after the first login on the UI.
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## Launch
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@ -5,7 +5,7 @@
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- The tool uses Large Language Model (LLMs) to perform various tasks in a QA pipeline.
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So, you need to provide the application with access to the LLMs you want
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to use.
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- You only need to provide at least one. However, tt is recommended that you include all the LLMs
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- You only need to provide at least one. However, it is recommended that you include all the LLMs
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that you have access to, you will be able to switch between them while using the
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application.
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