Improve manuals (#19)
* Rename Admin -> Resources * Improve ui * Update docs
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@@ -7,90 +7,6 @@ This page is intended for end users who want to use the `kotaemon` tool for Ques
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Download and upzip the latest version of `kotaemon` by clicking this
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[link](https://github.com/Cinnamon/kotaemon/archive/refs/heads/main.zip).
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## Choose what model to use
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The tool uses Large Language Model (LLMs) to perform various tasks in a QA pipeline. So
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prior to running, you need to provide the application with access to the LLMs you want
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to use.
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Please edit the `.env` file with the information needed to connect to the LLMs. You only
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need to provide at least one. However, tt 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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Currently, the following providers are supported:
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### OpenAI
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In the `.env` file, set the `OPENAI_API_KEY` variable with your OpenAI API key in order
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to enable access to OpenAI's models. There are other variables that can be modified,
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please feel free to edit them to fit your case. Otherwise, the default parameter should
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work for most people.
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```shell
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OPENAI_API_BASE=https://api.openai.com/v1
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OPENAI_API_KEY=<your OpenAI API key here>
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OPENAI_CHAT_MODEL=gpt-3.5-turbo
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OPENAI_EMBEDDINGS_MODEL=text-embedding-ada-002
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```
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### Azure OpenAI
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For OpenAI models via Azure platform, you need to provide your Azure endpoint and API
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key. Your might also need to provide your developments' name for the chat model and the
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embedding model depending on how you set up Azure development.
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```shell
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AZURE_OPENAI_ENDPOINT=
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AZURE_OPENAI_API_KEY=
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OPENAI_API_VERSION=2024-02-15-preview
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AZURE_OPENAI_CHAT_DEPLOYMENT=gpt-35-turbo
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AZURE_OPENAI_EMBEDDINGS_DEPLOYMENT=text-embedding-ada-002
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```
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### Local models
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- Pros:
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- Privacy. Your documents will be stored and process locally.
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- Choices. There are a wide range of LLMs in terms of size, domain, language to choose
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from.
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- Cost. It's free.
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- Cons:
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- Quality. Local models are much smaller and thus have lower generative quality than
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paid APIs.
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- Speed. Local models are deployed using your machine so the processing speed is
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limited by your hardware.
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#### Find and download a LLM
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You can search and download a LLM to be ran locally from the [Hugging Face
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Hub](https://huggingface.co/models). Currently, these model formats are supported:
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- GGUF
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You should choose a model whose size is less than your device's memory and should leave
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about 2 GB. For example, if you have 16 GB of RAM in total, of which 12 GB is available,
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then you should choose a model that take up at most 10 GB of RAM. Bigger models tend to
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give better generation but also take more processing time.
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Here are some recommendations and their size in memory:
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- [Qwen1.5-1.8B-Chat-GGUF](https://huggingface.co/Qwen/Qwen1.5-1.8B-Chat-GGUF/resolve/main/qwen1_5-1_8b-chat-q8_0.gguf?download=true):
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around 2 GB
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#### Enable local models
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To add a local model to the model pool, set the `LOCAL_MODEL` variable in the `.env`
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file to the path of the model file.
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```shell
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LOCAL_MODEL=<full path to your model file>
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```
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Here is how to get the full path of your model file:
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- On Windows 11: right click the file and select `Copy as Path`.
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## Installation
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1. Navigate to the `scripts` folder and start an installer that matches your OS:
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@@ -102,8 +18,8 @@ Here is how to get the full path of your model file:
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4. From now on, double click on your file and it should work.
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- Linux: `run_linux.sh`. If you are using Linux, you would know how to run a bash
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script, right ?
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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 available at `http://localhost:7860/`.
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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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## Launch
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@@ -111,11 +27,12 @@ To launch the app after initial setup or any changes, simply run the `run_*` scr
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A browser window will be opened and greet you with this screen:
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## Usage
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For how to use the application, see [Usage](/usage). Have fun !
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For how to use the application, see [Usage](/usage). This page will also be available to
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you within the application.
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## Feedback
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