Welcome to Prompto, an open-source Angular chat interface designed to provide a user-friendly way of interacting with a variety of Large Language Models (LLMs) via LangChain.js. Prompto, a blend of the word 'Prompt' and the Italian word 'Pronto' (meaning ready and quick), offers a modern chat UI that allows for quick and easy switching between different AI chat models, directly from your browser.
- Frontend: Angular ^17
- UI Framework: TailwindCSS
- Markdown Processing: Marked with syntax highlighting via highlight.js
- LLM Integration: LangChain.js
- PWA Support: Service Worker
- Modern Chat Interface: Clean and intuitive chat UI similar to popular chat applications, with message threading and real-time responses.
- Multiple LLMs: Effortlessly switch between a range of Large Language Models (LLMs) supported by LangChain Js.
- Temperature Settings: Adjust the temperature to fine-tune the responses from your chosen LLM.
- Chatbot UI: Engage with a chatbot interface that remembers the conversation context.
- Notebook: Utilize a notebook feature to send prompts to the LLM and receive responses without prior context or memory.
- Templates: Create, save, and reuse prompts for specific use cases. Incorporate a "contextual" prompt alongside your saved template for dynamic interaction.
- Arena: Engage in a conversation with multiple LLMs simultaneously, comparing their responses side by side.
- Discussion: Create dynamic conversations between multiple AI personas to explore topics from different perspectives.
Important Note: Prompto saves your chat history, prompt templates, and settings on your browser for easy access. This is convenient, but there's a small catch: information saved on your local storage can be accessed by others in some situations.
Prompto provides a button on the settings page that allows you to clear all saved data, including chat conversations, prompt templates, and settings.
You can view a live example of Prompto by visiting the following link: Prompto. The application can be installed as a PWA on your device.
- Clone the repository to your local machine
- Navigate to the project directory
- Install dependencies:
npm install
- Start the development server:
ng serve
- Open your browser and navigate to
http://localhost:4200
To create a production build:
ng build --configuration=productionThe build artifacts will be stored in the dist/prompto directory.
The project uses Angular's latest features including:
- Standalone components
- Lazy loading for all routes
- Service workers for PWA support
- TypeScript strict mode enabled
If you are running Ollama and you want to connect it to Prompto from a different domain than localhost, you will need to add the domain to the CORS configuration in the Ollama server. To do this, read the following blog post: How to Handle CORS Settings in OLLAMA: A Comprehensive Guide or the official documentation: How do I configure Ollama server?.
- Broaden the spectrum of LLMs supported by LangChain.js.
- Enhance the Chat Conversation Memory feature by adding an option for summarization, reducing the need to pass the entire chat history.
- Introduce the ability to create custom tools and agents.
Contributions are welcome! Please follow these steps:
- Fork the repository
- Create a new branch for your feature
- Follow the existing code style (2 spaces for indentation as per .editorconfig)
- Submit a pull request
Whether it's feature enhancements, bug fixes, or documentation improvements, all contributions are greatly appreciated.
This project is open-sourced under the MIT License.
Note: As this project is in beta, I am actively working on improvements and new features. I appreciate your support and contributions during this phase.
This project is not affiliated with OpenAI, LangChain or any other provider. It is an independent project designed to provide a user-friendly interface for interacting with LLMs.
This project is not associated with the french trademark Prompto registered in the field of AI.