167kPython+58/daypushed 0d ago
Use it for: Use and train state-of-the-art pretrained models for text, vision, audio, video and multimodal tasks from the Hugging Face Hub.
Quick start
- Make sure you have Python 3.10+ and PyTorch 2.6+
- Create and activate a virtual environment
- Follow the README installation section to install transformers
- Pick a model checkpoint from the Hugging Face Hub and run inference or training
147kPython+101/daypushed 0d ago
Use it for: Build agents and LLM-powered applications by chaining together interoperable components and third-party model integrations.
Quick start
- Install the package with: uv add langchain
- Import init_chat_model from langchain.chat_models and create a model
- Call model.invoke("Hello, world!") to get a response
- Explore LangGraph or Deep Agents in the docs for more advanced agent workflows
125kTypeScript+91/daypushed 0d ago
Use it for: Build your own customizable, accessible UI component library using composable components whose code you own and can edit.
Quick start
- Visit https://ui.shadcn.com/docs to read the documentation
- Follow the docs to set up the components in your project
- Customize and extend the component code to fit your design
66.9kPython+55/daypushed 1d ago
Use it for: Add persistent long-term memory to AI agents and apps so they remember context across sessions.
Quick start
- Clone the repo and follow the README install section
- Add Mem0 to your agent or app
- Store memories from conversations
- Retrieve relevant memories when the agent responds
1.1kTypeScript+2/daypushed 17d ago
Use it for: Build and run AI workflows and chatbots across channels using YAML, tools, MCP, memory and RAG.
Quick start
- Install the CLI with: npm install -g @hexabot-ai/cli
- Create a project with: hexabot create my-project
- Run: cd my-project
- Start it with: hexabot dev, then open http://localhost:3000
