Improve manuals (#19)
* Rename Admin -> Resources * Improve ui * Update docs
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@ -1,4 +1,6 @@
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# Package overview
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# Contributing
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## Package overview
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`kotaemon` library focuses on the AI building blocks to implement a RAG-based QA application. It consists of base interfaces, core components and a list of utilities:
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@ -47,14 +49,14 @@ mindmap
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Documentation Support
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```
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# Common conventions
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## Common conventions
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- PR title: One-line description (example: Feat: Declare BaseComponent and decide LLM call interface).
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- [Encouraged] Provide a quick description in the PR, so that:
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- Reviewers can quickly understand the direction of the PR.
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- It will be included in the commit message when the PR is merged.
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# Environment caching on PR
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## Environment caching on PR
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- To speed up CI, environments are cached based on the version specified in `__init__.py`.
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- Since dependencies versions in `setup.py` are not pinned, you need to pump the version in order to use a new environment. That environment will then be cached and used by your subsequence commits within the PR, until you pump the version again
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@ -65,7 +67,7 @@ mindmap
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- When you want to run the CI, push a commit with the message containing `[ignore cache]`.
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- Once the PR is final, pump the version in `__init__.py` and push a final commit not containing `[ignore cache]`.
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# Merge PR guideline
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## Merge PR guideline
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- Use squash and merge option
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- 1st line message is the PR title.
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@ -1,10 +1,12 @@
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# Data & Data Structure Components
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The data & data structure components include:
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- The `Document` class.
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- The document store.
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- The vector store.
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### Data Loader
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## Data Loader
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- PdfLoader
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- Layout-aware with table parsing PdfLoader
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@ -22,11 +24,11 @@ The data & data structure components include:
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- "page_label": page number in the original PDF document
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```
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### Document Store
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## Document Store
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- InMemoryDocumentStore
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### Vector Store
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## Vector Store
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- ChromaVectorStore
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- InMemoryVectorStore
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@ -1,4 +1,4 @@
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Utilities detail can be referred in the sub-pages of this section.
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# Utilities
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## Prompt engineering UI
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@ -36,7 +36,7 @@ done by the developers, while step 7 happens exclusively in Excel file).
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Command:
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```
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```shell
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$ kotaemon promptui export <module.path.piplineclass> --output <path/to/config/file.yml>
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```
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@ -59,38 +59,32 @@ Declared as above, and `param1` will show up in the config YAML file, while `par
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developers can further edit the config file in this step to get the most suitable UI (step 4) with their tasks. The exported config will have this overall schema:
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```
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```yml
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<module.path.pipelineclass1>:
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params:
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... (Detail param information to initiate a pipeline. This corresponds to the pipeline init parameters.)
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inputs:
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... (Detail the input of the pipeline e.g. a text prompt. This corresponds to the params of `run(...)` method.)
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outputs:
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... (Detail the output of the pipeline e.g. prediction, accuracy... This is the output information we wish to see in the UI.)
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logs:
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... (Detail what information should show up in the log.)
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params: ... (Detail param information to initiate a pipeline. This corresponds to the pipeline init parameters.)
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inputs: ... (Detail the input of the pipeline e.g. a text prompt. This corresponds to the params of `run(...)` method.)
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outputs: ... (Detail the output of the pipeline e.g. prediction, accuracy... This is the output information we wish to see in the UI.)
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logs: ... (Detail what information should show up in the log.)
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```
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##### Input and params
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The inputs section have the overall schema as follow:
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```
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```yml
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inputs:
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<input-variable-name-1>:
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component: <supported-UI-component>
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params: # this section is optional)
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value: <default-value>
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<input-variable-name-2>:
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... # similar to above
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<input-variable-name-2>: ... # similar to above
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params:
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<param-variable-name-1>:
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... # similar to those in the inputs
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<param-variable-name-1>: ... # similar to those in the inputs
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```
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The list of supported prompt UI and their corresponding gradio UI components:
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```
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```python
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COMPONENTS_CLASS = {
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"text": gr.components.Textbox,
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"checkbox": gr.components.CheckboxGroup,
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@ -107,7 +101,7 @@ COMPONENTS_CLASS = {
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The outputs are a list of variables that we wish to show in the UI. Since in Python, the function output doesn't have variable name, so output declaration is a little bit different than input and param declaration:
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```
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```yml
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outputs:
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- component: <supported-UI-component>
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step: <name-of-pipeline-step>
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@ -125,7 +119,7 @@ where:
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The logs show a list of sheetname and how to retrieve the desired information.
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```
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```yml
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logs:
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<logname>:
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inputs:
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@ -143,7 +137,7 @@ logs:
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Command:
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```
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```shell
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$ kotaemon promptui run <path/to/config/file.yml>
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```
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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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@ -103,7 +19,7 @@ Here is how to get the full path of your model file:
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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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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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142
docs/usage.md
142
docs/usage.md
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@ -1,59 +1,137 @@
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# Basic Usage
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## Chat tab
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## 1. Add your AI models
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The chat tab is divided into 3 columns:
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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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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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- Left: Conversation settings
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- Middle: Chat interface
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- Right: Information panel
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To add a model:
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### Conversation settings
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1. Navigate to the `Resources` tab.
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2. Select `LLM Management`.
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3. Select `Add`.
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4. Config the model to add:
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- Give it a name.
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- Pick a vendor/provider (e.g. `ChatOpenAI`).
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- Provide the specifications.
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- Optionally, set the model as default.
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5. Click `Add LLM`.
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#### Conversation control
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<details close>
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Create, rename, and delete conversations.
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<summary>Configures model via the .env file</summary>
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Alternatively, you can configure the models via the `.env` file with the information needed to connect to the LLMs. This file is located in
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the folder of the application. If you don't see it, you can create one.
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#### File index
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Currently, the following providers are supported:
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Choose which files to retrieve references from. If no file is selected, all files will be used.
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### OpenAI
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|
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|
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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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|
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### Chat interface
|
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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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Interact with the chatbot.
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### Azure OpenAI
|
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|
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|
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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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|
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### Information panel
|
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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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|
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Supporting information such as the retrieved evidence and reference will be displayed
|
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here.
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### Local models
|
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|
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|
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- Pros:
|
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- Privacy. Your documents will be stored and process locally.
|
||||
- Choices. There are a wide range of LLMs in terms of size, domain, language to choose
|
||||
from.
|
||||
- Cost. It's free.
|
||||
- Cons:
|
||||
- Quality. Local models are much smaller and thus have lower generative quality than
|
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paid APIs.
|
||||
- Speed. Local models are deployed using your machine so the processing speed is
|
||||
limited by your hardware.
|
||||
|
||||
## File index tab
|
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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
|
||||
Hub](https://huggingface.co/models). Currently, these model formats are supported:
|
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|
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### File upload
|
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- GGUF
|
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|
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In order for a file to be used as an index for retrieval, it must be processed by the
|
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application first. Do this uploading your file to the UI and then select `Upload and Index`.
|
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You should choose a model whose size is less than your device's memory and should leave
|
||||
about 2 GB. For example, if you have 16 GB of RAM in total, of which 12 GB is available,
|
||||
then you should choose a model that take up at most 10 GB of RAM. Bigger models tend to
|
||||
give better generation but also take more processing time.
|
||||
|
||||
|
||||
Here are some recommendations and their size in memory:
|
||||
|
||||
The application will take some time to process the file and show a message once it is
|
||||
done. Then you will be able to select it in the [File index section](#file-index) of the [Chat tab](#chat-tab).
|
||||
- [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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|
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### File list
|
||||
#### Enable local models
|
||||
|
||||
This section shows the list of files that have been uploaded to the application and
|
||||
allows users to delete them.
|
||||
To add a local model to the model pool, set the `LOCAL_MODEL` variable in the `.env`
|
||||
file to the path of the model file.
|
||||
|
||||
|
||||
```shell
|
||||
LOCAL_MODEL=<full path to your model file>
|
||||
```
|
||||
|
||||
Here is how to get the full path of your model file:
|
||||
|
||||
- On Windows 11: right click the file and select `Copy as Path`.
|
||||
</details>
|
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|
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## Upload your documents
|
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|
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|
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|
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In order to do QA on your documents, you need to upload them to the application first.
|
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Navigate to the `File Index` tab and you will see 2 sections:
|
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|
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1. File upload:
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- Drag and drop your file to the UI or select it from your file system.
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Then click `Upload and Index`.
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- The application will take some time to process the file and show a message once it is done.
|
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2. File list:
|
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- This section shows the list of files that have been uploaded to the application and allows users to delete them.
|
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|
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## Chat with your documents
|
||||
|
||||
|
||||
|
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Now navigate back to the `Chat` tab. The chat tab is divided into 3 regions:
|
||||
|
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1. Conversation Settings Panel
|
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- Here you can select, create, rename, and delete conversations.
|
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- By default, a new conversation is created automatically if no conversation is selected.
|
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- Below that you have the file index, where you can select which files to retrieve references from.
|
||||
- These are the files you have uploaded to the application from the `File Index` tab.
|
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- If no file is selected, all files will be used.
|
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2. Chat Panel
|
||||
- This is where you can chat with the chatbot.
|
||||
3. Information panel
|
||||
- Supporting information such as the retrieved evidence and reference will be
|
||||
displayed here.
|
||||
|
|
|
|||
|
|
@ -1,3 +1,7 @@
|
|||
:root {
|
||||
--main-area-height: calc(100vh - 110px);
|
||||
}
|
||||
|
||||
/* no footer */
|
||||
footer {
|
||||
display: none !important;
|
||||
|
|
@ -14,11 +18,13 @@ footer {
|
|||
background-clip: content-box;
|
||||
}
|
||||
::-webkit-scrollbar-corner {
|
||||
background: var(--border-color-primary);
|
||||
background: var(--background-fill-primary);
|
||||
}
|
||||
|
||||
.gradio-container {
|
||||
max-width: 100% !important;
|
||||
/* overflow: scroll !important;
|
||||
height: 100% !important; */
|
||||
}
|
||||
|
||||
/* styling for header bar */
|
||||
|
|
@ -70,15 +76,25 @@ button.selected {
|
|||
}
|
||||
|
||||
#main-chat-bot {
|
||||
/* span the chat area to occupy full height minus space for chat input */
|
||||
height: calc(100vh - 180px) !important;
|
||||
flex: 1;
|
||||
}
|
||||
|
||||
#chat-area {
|
||||
height: var(--main-area-height) !important;
|
||||
}
|
||||
|
||||
#chat-info-panel {
|
||||
max-height: calc(100vh - 180px) !important;
|
||||
max-height: var(--main-area-height) !important;
|
||||
overflow-y: scroll !important;
|
||||
}
|
||||
|
||||
#conv-settings-panel {
|
||||
max-height: var(--main-area-height) !important;
|
||||
flex-wrap: unset;
|
||||
overflow-y: scroll !important;
|
||||
position: sticky;
|
||||
}
|
||||
|
||||
.setting-answer-mode-description {
|
||||
margin: 5px 5px 2px !important;
|
||||
}
|
||||
|
|
@ -124,6 +140,18 @@ button.selected {
|
|||
}
|
||||
|
||||
/* for setting height limit for buttons */
|
||||
.cap-height {
|
||||
.cap-button-height {
|
||||
max-height: 42px;
|
||||
}
|
||||
|
||||
.scrollable {
|
||||
overflow-y: auto;
|
||||
}
|
||||
|
||||
.fill-main-area-height {
|
||||
max-height: var(--main-area-height);
|
||||
}
|
||||
|
||||
.unset-overflow {
|
||||
overflow: unset !important;
|
||||
}
|
||||
|
|
|
|||
|
|
@ -101,15 +101,16 @@ class FileIndexPage(BasePage):
|
|||
with gr.Column(scale=1):
|
||||
gr.Markdown("## File Upload")
|
||||
with gr.Column() as self.upload:
|
||||
msg = self.upload_instruction()
|
||||
if msg:
|
||||
gr.Markdown(msg)
|
||||
|
||||
self.files = File(
|
||||
file_types=self._supported_file_types,
|
||||
file_count="multiple",
|
||||
container=True,
|
||||
)
|
||||
|
||||
msg = self.upload_instruction()
|
||||
if msg:
|
||||
gr.Markdown(msg)
|
||||
|
||||
with gr.Accordion("Advanced indexing options", open=True):
|
||||
with gr.Row():
|
||||
self.reindex = gr.Checkbox(
|
||||
|
|
@ -346,7 +347,7 @@ class FileIndexPage(BasePage):
|
|||
# download the file
|
||||
text = "\n\n".join([each.text for each in output_nodes])
|
||||
handler, file_path = tempfile.mkstemp(suffix=".txt")
|
||||
with open(file_path, "w") as f:
|
||||
with open(file_path, "w", encoding="utf-8") as f:
|
||||
f.write(text)
|
||||
os.close(handler)
|
||||
|
||||
|
|
|
|||
|
|
@ -1,8 +1,8 @@
|
|||
import gradio as gr
|
||||
from ktem.app import BaseApp
|
||||
from ktem.pages.admin import AdminPage
|
||||
from ktem.pages.chat import ChatPage
|
||||
from ktem.pages.help import HelpPage
|
||||
from ktem.pages.resources import ResourcesTab
|
||||
from ktem.pages.settings import SettingsPage
|
||||
|
||||
|
||||
|
|
@ -57,14 +57,16 @@ class App(BaseApp):
|
|||
elem_id="resources-tab",
|
||||
id="resources-tab",
|
||||
visible=not self.f_user_management,
|
||||
elem_classes=["fill-main-area-height", "scrollable"],
|
||||
) as self._tabs["resources-tab"]:
|
||||
self.admin_page = AdminPage(self)
|
||||
self.resources_page = ResourcesTab(self)
|
||||
|
||||
with gr.Tab(
|
||||
"Settings",
|
||||
elem_id="settings-tab",
|
||||
id="settings-tab",
|
||||
visible=not self.f_user_management,
|
||||
elem_classes=["fill-main-area-height", "scrollable"],
|
||||
) as self._tabs["settings-tab"]:
|
||||
self.settings_page = SettingsPage(self)
|
||||
|
||||
|
|
@ -73,6 +75,7 @@ class App(BaseApp):
|
|||
elem_id="help-tab",
|
||||
id="help-tab",
|
||||
visible=not self.f_user_management,
|
||||
elem_classes=["fill-main-area-height", "scrollable"],
|
||||
) as self._tabs["help-tab"]:
|
||||
self.help_page = HelpPage(self)
|
||||
|
||||
|
|
|
|||
|
|
@ -27,7 +27,7 @@ class ChatPage(BasePage):
|
|||
def on_building_ui(self):
|
||||
with gr.Row():
|
||||
self.chat_state = gr.State(STATE)
|
||||
with gr.Column(scale=1):
|
||||
with gr.Column(scale=1, elem_id="conv-settings-panel"):
|
||||
self.chat_control = ConversationControl(self._app)
|
||||
|
||||
if getattr(flowsettings, "KH_FEATURE_CHAT_SUGGESTION", False):
|
||||
|
|
@ -60,7 +60,7 @@ class ChatPage(BasePage):
|
|||
|
||||
self.report_issue = ReportIssue(self._app)
|
||||
|
||||
with gr.Column(scale=6):
|
||||
with gr.Column(scale=6, elem_id="chat-area"):
|
||||
self.chat_panel = ChatPanel(self._app)
|
||||
|
||||
with gr.Column(scale=3):
|
||||
|
|
|
|||
|
|
@ -22,19 +22,20 @@ class ChatPanel(BasePage):
|
|||
placeholder="Chat input",
|
||||
scale=15,
|
||||
container=False,
|
||||
max_lines=10,
|
||||
)
|
||||
self.submit_btn = gr.Button(
|
||||
value="Send",
|
||||
scale=1,
|
||||
min_width=10,
|
||||
variant="primary",
|
||||
elem_classes=["cap-height"],
|
||||
elem_classes=["cap-button-height"],
|
||||
)
|
||||
self.regen_btn = gr.Button(
|
||||
value="Regen",
|
||||
scale=1,
|
||||
min_width=10,
|
||||
elem_classes=["cap-height"],
|
||||
elem_classes=["cap-button-height"],
|
||||
)
|
||||
|
||||
def submit_msg(self, chat_input, chat_history):
|
||||
|
|
|
|||
|
|
@ -37,6 +37,7 @@ class ConversationControl(BasePage):
|
|||
container=False,
|
||||
filterable=False,
|
||||
interactive=True,
|
||||
elem_classes=["unset-overflow"],
|
||||
)
|
||||
|
||||
with gr.Row() as self._new_delete:
|
||||
|
|
|
|||
|
|
@ -28,8 +28,10 @@ class ReportIssue(BasePage):
|
|||
label="Other issue:",
|
||||
)
|
||||
self.more_detail = gr.Textbox(
|
||||
placeholder="More detail (e.g. how wrong is it, what is the "
|
||||
"correct answer, etc...)",
|
||||
placeholder=(
|
||||
"More detail (e.g. how wrong is it, what is the "
|
||||
"correct answer, etc...)"
|
||||
),
|
||||
container=False,
|
||||
lines=3,
|
||||
)
|
||||
|
|
|
|||
|
|
@ -7,18 +7,15 @@ class HelpPage:
|
|||
def __init__(self, app):
|
||||
self._app = app
|
||||
self.dir_md = Path(__file__).parent.parent / "assets" / "md"
|
||||
self.doc_dir = Path(__file__).parents[4] / "docs"
|
||||
|
||||
with gr.Accordion("User Guide"):
|
||||
with (self.doc_dir / "usage.md").open(encoding="utf-8") as fi:
|
||||
gr.Markdown(fi.read())
|
||||
|
||||
with gr.Accordion("Changelogs"):
|
||||
gr.Markdown(self.get_changelogs())
|
||||
|
||||
with gr.Accordion("About Kotaemon (temporary)"):
|
||||
with (self.dir_md / "about_kotaemon.md").open(encoding="utf-8") as fi:
|
||||
gr.Markdown(fi.read())
|
||||
|
||||
with gr.Accordion("About Cinnamon AI (temporary)", open=False):
|
||||
with (self.dir_md / "about_cinnamon.md").open(encoding="utf-8") as fi:
|
||||
gr.Markdown(fi.read())
|
||||
|
||||
def get_changelogs(self):
|
||||
with (self.dir_md / "changelogs.md").open(encoding="utf-8") as fi:
|
||||
return fi.read()
|
||||
|
|
|
|||
|
|
@ -8,7 +8,7 @@ from sqlmodel import Session, select
|
|||
from .user import UserManagement
|
||||
|
||||
|
||||
class AdminPage(BasePage):
|
||||
class ResourcesTab(BasePage):
|
||||
def __init__(self, app):
|
||||
self._app = app
|
||||
self.on_building_ui()
|
||||
|
|
@ -21,7 +21,7 @@ class AdminPage(BasePage):
|
|||
with gr.Tab("LLMs") as self.llm_management_tab:
|
||||
self.llm_management = LLMManagement(self._app)
|
||||
|
||||
with gr.Tab("Embeddings") as self.llm_management_tab:
|
||||
with gr.Tab("Embedding Models") as self.llm_management_tab:
|
||||
self.emb_management = EmbeddingManagement(self._app)
|
||||
|
||||
def on_subscribe_public_events(self):
|
||||
|
|
@ -20,6 +20,7 @@ nav:
|
|||
- Customize UI: pages/app/customize-ui.md
|
||||
- Functional description: pages/app/functional-description.md
|
||||
- Development:
|
||||
- development/index.md
|
||||
- Contributing: development/contributing.md
|
||||
- Data & Data Structure Components: development/data-components.md
|
||||
- Creating a Component: development/create-a-component.md
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user