Run prompts against OpenAI, Claude, Gemini, and dozens of local or remote models from one terminal command, logging every prompt and response to SQLite. Plugins add new providers, tools, and embeddings; supports schema extraction and function calling.
Translates plain-English questions into pandas/SQL code over CSV, Parquet, and SQL databases, returning tables and charts. Combines LLMs with RAG and a semantic layer so non-coders query data; a Docker sandbox isolates generated code.
Self-hostable chat UI that connects to any LLM and adds Agents, Web Search, RAG, connectors, code execution and image generation. Ships connectors to 40+ sources and deployment guides for Docker/K8s. Best for teams needing private, extensible chat platforms.
Edits code across an existing repo from the terminal: you describe a change in plain English, it maps the whole codebase, applies edits to the right files, and auto-commits each change as a reviewable git commit. Works with most LLMs.
Synchronized desktop chat browser that opens multiple LLM webapps (ChatGPT, Claude, Bard, Bing, Llama2) and submits the same prompt to each for fast cross-provider comparison. Offers keyboard shortcuts, local-model hooks, and prompt-improvement utilities.
Self-hostable chat client that unifies many LLM providers (OpenAI, Claude, Gemini, Ollama, DeepSeek) behind one UI. Adds file-upload knowledge-base RAG, vision/TTS, an MCP plugin system, and an agent marketplace, with one-click Vercel or Docker deployment.
Browser-first, local-first note app that stores your notes as plain Markdown files and offers a chat-like input flow. LLM-friendly file structure, offline-capable PWA, and Telegram bot integration — data stays on your device unless you enable syncing.
Runs retrieval-augmented Q&A over your own documents on local hardware, so files never leave your machine. Blends semantic, keyword, and late-chunking retrieval, with a router that picks RAG or a direct LLM answer per query and verifies it.
Adds agent-native UI patterns to apps through chat, generative UI, shared state, human-in-the-loop flows, and AG-UI-based frontend integrations.
Lets LLMs run code and control a user’s computer via natural language (Python, JavaScript, Shell, etc.) with interactive approval. Supports local or hosted models, terminal and Colab/Codespaces integrations, streaming output, and configurable safety/auto-run options.
Calls 100+ LLM providers — OpenAI, Anthropic, Gemini, Bedrock, Azure — through one OpenAI-compatible API, as a Python SDK or self-hosted proxy. The proxy adds virtual keys, spend tracking, rate limits, and load balancing across models and providers.
Chat with your documents via retrieval-augmented generation; each answer carries inline citations and a built-in viewer highlights the cited PDF passage. Pairs full-text with vector search and runs on OpenAI, Azure, Cohere, Ollama, or local models.