#python #agents #document_search #evaluation #guardrails #llms #optimization #prompts #rag #vector_stores

Ragbits is a tool that helps build and deploy GenAI applications quickly. It offers features like swapping between many language models, ensuring safe interactions with these models, and connecting to various data storage systems. Ragbits also includes tools for managing data and testing prompts, making it easier to develop reliable AI applications. This helps users create more accurate and efficient AI systems by integrating the latest data and reducing errors. Overall, Ragbits makes it faster and more efficient to develop and deploy AI applications.

https://github.com/deepsense-ai/ragbits

#jupyter_notebook #ai #llm #llms #multi_modal #openai #python #rag

Retrieval-Augmented Generation (RAG) is a technique that helps improve the accuracy of large language models by fetching relevant information from databases or documents. This approach ensures that the model's responses are based on up-to-date and accurate data, reducing errors and "hallucinations" where the model might provide false information. For users, RAG offers more reliable and trustworthy responses, allowing them to verify the sources used to generate those responses. This method also saves resources by avoiding the need to retrain models with new data.

https://github.com/FareedKhan-dev/all-rag-techniques

#typescript #agents #ai #embedders #genkit #llm #machine_learning #multimodal #rag #vector_database

Genkit is an open-source framework by Google Firebase that helps you easily build AI-powered apps using a single interface to connect many AI models like Google Gemini, OpenAI, and Anthropic. It supports JavaScript/TypeScript (stable), Go (beta), and Python (alpha), letting you create chatbots, automations, and recommendations quickly with simple code. Genkit works well with web and mobile platforms, offers tools for testing and debugging AI features locally, and lets you deploy and monitor your AI apps on Firebase or other cloud services. This saves you time and effort in developing and managing AI applications efficiently.

https://github.com/firebase/genkit

#other #agent #llm #rag

Happy-LLM is a free, open-source learning project that helps you deeply understand large language models (LLMs) from basics to advanced training and applications. It teaches you key concepts like NLP, Transformer architecture, pretraining, and how to build and train your own LLaMA2 model step-by-step. You also learn practical skills like fine-tuning and using cutting-edge techniques such as Retrieval-Augmented Generation (RAG) and intelligent agents. This project is ideal if you know some Python and deep learning, and it offers both theory and hands-on code to help you master LLM development and apply it in real-world AI tasks. This can boost your skills and confidence in AI model building and research.

https://github.com/datawhalechina/happy-llm

#rust #ai_agent #developer_tools #enterprise #fine_tuning #on_prem #open_source #rag #self_hosted #swe_bench #vscode

Refact.ai is a free, open-source AI software development agent that helps you code faster and smarter by deeply understanding your code and integrating with tools like GitHub, databases, Docker, and debuggers. It offers unlimited, context-aware code auto-completion, can generate, refactor, explain, debug code, and create tests and documentation across 25+ programming languages. You can run it securely on your own servers, use top AI models like GPT-4o, and connect your own API keys. This means you save time on repetitive tasks, improve code quality, and collaborate better, making your development workflow much more efficient and productive[1][3][5].

https://github.com/smallcloudai/refact

#typescript #12_factor #12_factor_agents #agents #ai #context_window #framework #llms #memory #orchestration #prompt_engineering #rag

The 12-Factor Agents are a set of proven principles to build reliable, scalable, and maintainable AI applications powered by large language models (LLMs). They help you combine the creativity of AI with the stability of traditional software by managing prompts, context, tool calls, error handling, and human collaboration effectively. Instead of relying solely on complex frameworks, you can apply these modular concepts to improve your existing products quickly and reach high-quality AI performance for real users. This approach makes AI software easier to develop, debug, and scale, ensuring it works well in production environments[1][3][5].

https://github.com/humanlayer/12-factor-agents

#python #agent #alibaba #artificial_intelligence #information_seeking #llm #multi_agent #rag #web_agent

You can use advanced AI models like WebSailor and WebDancer from Alibaba's Tongyi Lab to perform complex web tasks such as searching, browsing, and answering questions automatically. These models are trained to think deeply and handle difficult information-seeking tasks that were hard before. WebSailor excels in reasoning and can solve very challenging problems, while WebDancer learns to search and reason on its own through a special training process. Using these tools helps you get accurate, multi-step answers from the web quickly and efficiently, saving you time and effort in research or information gathering. They are open-source and come with demos to try out easily[3].

https://github.com/Alibaba-NLP/WebAgent

#typescript #ai #chatgpt #docsgpt #hacktoberfest #information_retrieval #language_model #llm #machine_learning #natural_language_processing #python #pytorch #rag #react #semantic_search #transformers #web_app

DocsGPT is an open-source AI tool that helps you quickly find accurate answers from many types of documents and web sources without errors. It supports formats like PDF, DOCX, images, and integrates with websites, APIs, and chat platforms like Discord and Telegram. You can deploy it privately for security, customize it to fit your brand, and connect it to tools for advanced actions. This means you save time searching for information, get reliable answers with sources, and improve productivity whether you’re a developer, support team, or business user. It’s easy to set up and scales well for many users[2][3][4].

https://github.com/arc53/DocsGPT

#typescript #agent_workflow #agentic_workflow #agents #ai #aiagents #anthropic #artificial_intelligence #automation #chatbot #deepseek #gemini #low_code #nextjs #no_code #openai #rag #react #typescript

Sim Studio is an easy-to-use, open-source platform that lets you build AI workflows visually without coding by dragging and connecting blocks on a canvas. It supports many AI models and integrates with over 60 popular tools like Gmail, Slack, and Google Sheets. You can run workflows via chat, APIs, or scheduled jobs and deploy them as APIs or plugins. It also offers real-time collaboration and built-in monitoring. This helps you quickly create, test, and deploy AI-powered applications or automation, saving time and effort while allowing flexibility and control over your AI projects[1][2][3][4].

https://github.com/simstudioai/sim

#python #chatbi #deepseek #llm #nl2sql #rag #sqlbot #text_to_sql #text2sql

SQLBot is an easy-to-use intelligent system that turns natural language questions into SQL queries using advanced AI models and retrieval-augmented generation (RAG). You just need to set up your AI model and data source to start asking questions about your data. It integrates smoothly with other business systems and AI platforms, making it simple to add smart data querying to your apps. It also ensures data security with workspace-based resource isolation and fine-grained access control. You can quickly deploy it on a Linux server using Docker, enabling fast, secure, and intelligent data interaction without needing deep SQL knowledge. This saves you time and improves data accessibility.

https://github.com/dataease/SQLBot