{"name":"handit.ai: Your AI Teammate for Reliable Production AI","description":"handit.ai is an open-source AI teammate designed to ensure the reliability of your AI applications in production. It automatically detects issues like hallucinations and schema breaks, generates and tests fixes, and ships them as pull requests. This tool eliminates 2 AM debugging sessions, making AI truly dependable.","github":"https://github.com/Handit-AI/handit.ai","url":"https://osrepos.com/repo/handit-ai-handit.ai","source":"osrepos.com","sourceDescription":"This repository profile is provided by osrepos.com, an open source repository discovery platform.","repositoryProfile":"https://osrepos.com/repo/handit-ai-handit.ai","generatedFor":"open source discovery and AI-assisted research","markdown":"https://osrepos.com/repo/handit-ai-handit.ai.md","json":"https://osrepos.com/repo/handit-ai-handit.ai.json","topics":["AI","MLOps","Reliability","Automation","JavaScript","Python","Open Source","Debugging"],"keywords":["AI","MLOps","Reliability","Automation","JavaScript","Python","Open Source","Debugging"],"stars":null,"summary":"handit.ai is an open-source AI teammate designed to ensure the reliability of your AI applications in production. It automatically detects issues like hallucinations and schema breaks, generates and tests fixes, and ships them as pull requests. This tool eliminates 2 AM debugging sessions, making AI truly dependable.","content":"## Introduction\n\nModern AI applications are often fragile, prone to issues like hallucinations, broken schemas, PII leaks, and silent failures. Debugging these problems can be a nightmare, especially when they occur in production. handit.ai steps in as your dedicated AI teammate, providing 24/7 monitoring and automated solutions to these challenges.\n\nhandit.ai is an open-source platform that automatically detects issues in your AI, generates and tests fixes against real data, and then ships these improvements as pull requests to your GitHub repository. It's built to make AI truly reliable in production, allowing your team to focus on building features rather than firefighting.\n\n## Installation\n\nGetting your AI teammate up and running with handit.ai is straightforward and can be done in under 5 minutes.\n\n### Quick Start\n\n1.  **Start the Setup Process**: Navigate to your AI project directory and run:\n    bash\nnpx @handit/cli setup\n    \n    The CLI will guide you through connecting your handit.ai account, installing the SDK, configuring your API key, connecting evaluation models, and linking your GitHub repository for automated PRs.\n\n2.  **Verify Your Setup**:\n    *   Check your dashboard at [dashboard.handit.ai](https://dashboard.handit.ai) to see tracing data, quality scores, and agent performance.\n    *   Confirm GitHub integration by checking your repository settings; the handit app should be installed and ready for PRs.\n\n### Manual Setup (Advanced)\n\nFor custom control, you can manually install the SDK and add monitoring decorators to your agent functions.\n\n**Install the SDK:**\n\nbash\n# Python\npip install handit-ai\n\n# JavaScript/TypeScript  \nnpm install @handit.ai/handit-ai\n\n\n**Add monitoring to your main agent function:**\n\n**Python:**\npython\n# Auto-generated by handit-cli setup\nfrom handit_ai import tracing, configure\nimport os\n \nconfigure(HANDIT_API_KEY=os.getenv(\"HANDIT_API_KEY\"))\n \n# Tracing added to your main agent function (entry point)\n@tracing(agent=\"customer-service-agent\")\nasync def process_customer_request(user_message: str):\n    # Your existing agent logic (unchanged)\n    intent = await classify_intent(user_message)\n    context = await search_knowledge(intent)\n    response = await generate_response(context)\n    return response\n\n\n**JavaScript:**\njavascript\n// Auto-generated by handit-cli setup\nimport { configure, startTracing, endTracing } from '@handit.ai/handit-ai';\n \nconfigure({\n  HANDIT_API_KEY: process.env.HANDIT_API_KEY\n});\n \n// Tracing added to your main agent function (entry point)\nexport const processCustomerRequest = async (userMessage) => {\n  startTracing({ agent: \"customer-service-agent\" });\n  try {\n    // Your existing agent logic (unchanged)\n    const intent = await classifyIntent(userMessage);\n    const context = await searchKnowledge(intent);\n    const response = await generateResponse(context);\n    return response;\n    } finally {\n    endTracing();\n  }\n};\n\n\n## Examples\n\nhandit.ai can power self-improving AI agents across various use cases. One compelling example is the **Unstructured to Structured** agent.\n\nThis example demonstrates an AI agent that automatically converts messy, unstructured documents into clean, structured data and CSV tables. It's ideal for processing invoices, contracts, or medical reports. The key feature is its self-improvement capability, where handit.ai observes every agent interaction, detects failures, and automatically fixes them, making the agent better over time.\n\n**Key Features:**\n*   **Schema Inference**: AI analyzes documents and creates optimal JSON structures.\n*   **Data Extraction**: Maps document fields to schema with confidence scoring.\n*   **CSV Generation**: Automatically creates organized tables for data visualization.\n*   **Multimodal Support**: Handles images, PDFs, and text files.\n*   **Self-improvement**: Handit observes interactions and automatically fixes detected failures.\n\nYou can explore the source code for this example and others on the [handit-examples GitHub repository](https://github.com/Handit-AI/handit-examples/tree/main/examples/unstructured-to-structured).\n\n## Why Use handit.ai?\n\nhandit.ai addresses critical challenges in AI reliability by providing a comprehensive, automated solution.\n\n### Real-Time Failure Detection\nhandit.ai acts as your 24/7 on-call engineer, monitoring every request and catching failures before they impact customers. It detects:\n*   Hallucinations and incorrect responses\n*   Schema breaks and validation errors\n*   PII leaks and security issues\n*   Performance degradation and timeouts\n\n### Automated Fix Generation\nThe platform analyzes root causes, generates intelligent fixes, and tests solutions against actual production failure cases. This includes:\n*   Prompt improvements and optimizations\n*   Configuration changes and guardrails\n*   Code fixes for logic errors\n*   Model parameter adjustments\n\n### GitHub-Native Deployment\nOnce fixes are proven, handit.ai opens pull requests with detailed explanations, performance data, and A/B testing results. You can review and merge, or even configure auto-deployment with guardrails.\n\n### Proven Results\nTeams like Aspe.ai and XBuild have seen significant improvements:\n*   **Aspe.ai**: Achieved +62.3% accuracy improvement and +97.8% success rate within 48 hours.\n*   **XBuild**: Saw +34.6% accuracy improvement and +19.1% success rate, eliminating prompt drift with thousands of automatic evaluations.\n\n### Broad Language Support\nhandit.ai supports a wide range of languages and frameworks, including Python, JavaScript, TypeScript, Go, Java, C#, Ruby, PHP, LangChain, LangGraph, LlamaIndex, AutoGen, and CrewAI.\n\n## Links\n\n*   **Official Documentation**: [https://docs.handit.ai](https://docs.handit.ai)\n*   **GitHub Repository**: [https://github.com/Handit-AI/handit.ai](https://github.com/Handit-AI/handit.ai)\n*   **Discord Community**: [https://discord.com/invite/XCVWYCFen6](https://discord.com/invite/XCVWYCFen6)\n*   **Schedule a Demo**: [https://calendly.com/cristhian-handit/30min](https://calendly.com/cristhian-handit/30min)\n*   **Quick Start Guide**: [https://docs.handit.ai/quickstart](https://docs.handit.ai/quickstart)","metrics":{"detailViews":3,"githubClicks":10},"dates":{"published":null,"modified":"2025-11-07T08:01:19.000Z"}}