Merge pull request #1 from Gitfoe/dev

Dev

NOTICE

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+llm-app-interface
+Copyright 2024 Julian Calvin Rill
+
+This product includes software developed at
+Osnabrück University (https://www.uni-osnabrueck.de).

README.md

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-# llm-app-interface
-A flexible and intelligent context-aware navigation interface utilizing LangChain and LLMs, enhancing interoperability with accessibility apps for vision impaired individuals.
+# Flexible Context-Aware Navigation Interface for Accessibitiy Apps
+
+This project is a **flexible and intelligent context-aware navigation interface** designed to enhance interoperability with accessibility applications for vision-impaired individuals. Utilizing **LangChain** and **LLMs (Large Language Models)**, it provides a seamless API that supports both human and system inputs, enabling back-and-forth communication and clarifying interactions. It is designed to work with accesibility apps such as the [Natural Language Interface](https://github.com/StudyProject-NLI/NLInterface).
+
+### Features
+
+- **API Interface**: Exposed via `LangServe` for interaction with other apps.
+- **Context-aware**: Uses a `LangGraph` based approach for efficient state management and future-proofing.
+- **Interoperability**: Designed to enhance accessibility apps and facilitate communication with LLMs.
+- **Support for OAuth**: User authentication using `OAuth2`.
+- **Back-and-Forth Communication**: Enables real-time clarifying questions and data exchange between apps and users.
+- **Customizable for Accessibility Apps**: Currently configured for a single accessibility app but designed with ambitions for broader app support.
+
+---
+
+## Getting Started
+
+### Prerequisites
+
+- **Python 3.x** installed
+- API keys from **LangChain** and **OpenAI**.
+
+### Installation
+
+1. Clone the repository:
+   ```bash
+   git clone https://github.com/Gitfoe/llm-app-interface
+   cd your-repo-url
+   ```
+
+2. Install the required Python packages:
+   ```bash
+   pip install -r requirements.txt
+   ```
+
+3. Set up your environment variables by creating a `.env` file in the project root and filling in the required fields:
+   ```env
+   LANGCHAIN_TRACING_V2=true
+   LANGCHAIN_API_KEY=your_langchain_api_key_here
+   OPENAI_API_KEY=your_openai_api_key_here
+   SECRET_KEY=your_secret_key_here
+   ```
+
+   To generate a secure `SECRET_KEY`, you can run:
+   ```bash
+   openssl rand -hex 32
+   ```
+
+### Usage
+
+1. Start the server locally:
+   ```bash
+   python serve.py
+   ```
+
+   By default, the API will be accessible at:
+   ```
+   http://localhost:8000/llm-app-interface
+   ```
+
+2. The application currently supports one user:
+   - **Username**: `johndoe`
+   - **Password**: `secret`
+
+3. Use the `/token` endpoint to generate a JWT token for authentication:
+   ```bash
+   curl -X POST "http://localhost:8000/token" -H "Content-Type: application/x-www-form-urlencoded" -d "username=johndoe&password=secret"
+   ```
+
+---
+
+## API Endpoints
+
+- **`/llm-app-interface/invoke`**  
+  The primary endpoint for invoking LLM interactions, supporting both system and human input.
+
+  **Example Request**:
+  ```bash
+  curl -X POST "http://localhost:8000/llm-app-interface/invoke" \
+       -H "Authorization: Bearer <your_jwt_token>" \
+       -H "Content-Type: application/json" \
+       -d '{"messages": "Hello, can you assist me?"}'
+  ```
+
+  **Note**: Ensure you include a valid JWT token for authorization.
+
+---
+
+## Integrating your Accessibility App
+
+You can extend the model to accommodate additional accessibility apps by adding descriptions of your app functionalities to the documents within the `tools.py` file.
+
+---
+
+## Security
+
+- **OAuth2** is implemented for user authentication. The `SECRET_KEY` is used to sign and validate JWT tokens.
+- Currently, one user (`johndoe`) is supported. For more users, you can extend the `fake_users_db` or integrate with a proper database.
+
+---
+
+## Future Plans
+
+- **Multi-App Support**: The current version only supports one accessibility app at a time, but we aim to generalize this for multiple apps.
+- **LLM Flexibility**: While this system is configured for OpenAI models, it can easily be adapted to other LLMs by swapping out the model initialization.
+- **Increasing Reliability**: A base of the model has been implemented, but reliability can be improved by i.e. utilizing additional nodes within the graph.
+
+---
+
+## Contributing
+
+We welcome contributions! Please submit a pull request or open an issue for discussion.

playground/client.py

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+from langserve import RemoteRunnable
+
+remote_chain = RemoteRunnable("http://localhost:8000/chain/")
+remote_chain.invoke({"language": "japanese", "text": "hi"})