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OpenChatKit

OpenChatKit: Open-Source ChatGPT Alternative

OpenChatKit is a free, open-source toolkit for building specialized and general-purpose chatbots, complete with a tunable language model, retrieval system, and moderation tools.

AI Developer ToolsOpen Source AI ModelsAI Dialogue GeneratorAI Text ClassifierAI Content DetectorLarge Language Models (LLMs)AI AnswerAI ChatbotAI Document ExtractionAI Summarizer

Overview

OpenChatKit is a groundbreaking open-source alternative to ChatGPT, giving developers and researchers full access to the building blocks needed to create powerful conversational AI. Rather than a single model release, it's a complete ecosystem featuring an instruction-tuned large language model (built on EleutherAI's GPT-NeoX architecture), fine-tuning recipes, a retrieval system for live data augmentation, and a moderation layer to keep conversations on-topic and appropriate. Born from a collaboration between Together, LAION, and Ontocord, it was engineered as a community-driven project rather than a closed commercial product. What sets OpenChatKit apart is its focus on extensibility and transparency. The included retrieval system allows chatbots to pull in up-to-date external information rather than relying solely on static training data, while the moderation model helps filter out inappropriate or off-domain questions before they reach the core model. Combined with customization recipes for fine-tuning, teams can adapt the base model to niche industries or specialized use cases without starting from scratch. Because the entire stack—including source code, model weights, and training datasets—is publicly available on GitHub and Hugging Face, OpenChatKit appeals strongly to organizations and individuals who want full control over their AI infrastructure. Its open, community-fed development model (with active channels on Discord, Twitter, and Medium) means the project continuously evolves based on real user feedback rather than a single vendor's roadmap.

Capabilities & Features

  • Open-source chatbot
  • Large language model
  • Natural language processing
  • Chatbot development
  • Retrieval system
  • Moderation model
  • Instruction tuning
  • AI
  • Machine learning

Core Features

  • Instruction-tuned 20B parameter large language model based on GPT-NeoX
  • Extensible retrieval system for augmenting responses with live, up-to-date information
  • Built-in moderation model to filter inappropriate or out-of-domain queries
  • Customization recipes for fine-tuning the model to specific domains
  • Fully open-source codebase, model weights, and training datasets

Use Cases

  • Building domain-specific chatbots for industries like healthcare, finance, or customer support
  • Developing general-purpose conversational assistants for internal or public use
  • Augmenting chatbot knowledge with real-time external data via the retrieval system
  • Filtering and moderating chatbot conversations to avoid inappropriate content
  • Research and experimentation with fine-tuning large language models

Best For

  • Developers
  • Researchers
  • Data scientists
  • AI engineers
  • Organizations building custom chatbots

Pros

  • •Completely open-source with full access to code, weights, and datasets
  • •Modular design combines LLM, retrieval, and moderation in one toolkit
  • •Highly customizable through fine-tuning recipes for specialized use cases
  • •Strong performance on question-answering, extraction, and classification tasks
  • •Active community support via GitHub, Discord, and other channels

Cons

  • •Requires technical expertise to set up, fine-tune, and deploy effectively
  • •Struggles with knowledge-based closed Q&A, coding tasks, and creative writing
  • •Prone to repetition and difficulty with context switching in longer conversations
  • •No managed hosting or official support plans, relying on self-hosting and community help

How to Use

Visit the OpenChatKit online playground to test the chatbot directly in your browser and submit feedback through the built-in feedback app. To go deeper, clone the source code and model weights from GitHub or Hugging Face, then use the provided customization recipes to fine-tune the model for your specific domain. Join the community on Discord, Twitter, or Medium to share ideas, report issues, and stay updated on new releases.

Frequently Asked Questions

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Pricing

OpenChatKit is completely free and open-source, with no paid tiers—users are responsible for their own hosting and compute costs.

Pricing data is provided as a summary. Visit the vendor website for full tier details.