AIPE centralizes AI agent orchestration with pluggable modules for memory, planning, tool use, and multi-agent collaboration. Developers can define agent personas, incorporate context via vector stores, and integrate external APIs or databases. The framework offers a built-in web dashboard and CLI for testing prompts, monitoring agent state, and chaining tasks. AIPE supports multiple memory backends like Redis, SQLite, and in-memory stores. Its multi-agent setups allow assigning specialized roles—data extractor, analyst, summarizer—to tackle complex queries collaboratively. By abstracting prompt engineering, API wrappers, and error handling, AIPE speeds up deployment of AI-driven assistants for document QA, customer support and automated workflows.

BasicPrompt is a platform designed to streamline the process of building, versioning, and deploying prompts. It ensures that prompts are compatible with every model, allowing you to test and refine them quickly. The platform offers various tools to improve prompt engineering efficiency, from inception to deployment. With BasicPrompt, users get a faster, more reliable way to work with AI models, ensuring optimal performance and results.

BuildOwn.AI is a comprehensive guide designed to help developers build real-world AI applications using large language models. It's ideal for both beginners and experienced developers, focusing on essential AI concepts and practical applications. The guide covers topics like running models locally, prompt engineering, data extraction, fine-tuning, and advanced techniques like Retrieval-Augmented Generation (RAG) and tool automation. Whether you code in Python, JavaScript, or another language, BuildOwn.AI provides valuable insights that you can adapt to your preferred platform.

CL4R1T4S empowers developers to build AI agents by offering core abstractions: Agent, Memory, Tools, and Chain. Agents can use LLMs to process input, call external functions, and maintain context across sessions. Memory modules allow storing conversation history or domain knowledge. Tools can wrap API calls, allowing agents to fetch data or perform actions. Chains define sequential steps for complex tasks like document analysis, data extraction, or iterative querying. The framework handles prompt templates, function calling, and error handling transparently. With CL4R1T4S, teams can prototype chatbots, automations, and decision support systems, leveraging Clojure’s functional paradigm and rich ecosystem.

DelphiGemini provides a lightweight, easy-to-use wrapper around Google’s Gemini LLM API for Delphi developers. It handles authentication, request formatting, and response parsing, allowing you to send prompts and receive text completions or chat responses. With support for streaming output, you can display tokens in real time. The library also offers synchronous and asynchronous methods, configurable timeouts, and detailed error reporting. Use it to build chatbots, content generators, translators, summarizers, or any AI-powered feature directly in your Delphi applications.

DB-conv is a lightweight Python library designed to enable conversational AI over SQL databases. After installation, developers configure it with database connection details and LLM provider credentials. DB-conv handles schema introspection, constructs optimized SQL from user prompts, executes queries, and returns results in tables or charts. It supports multiple database engines, caching, query logging, and custom prompt templates. By abstracting prompt engineering and SQL generation, DB-conv simplifies building chatbots, voice assistants, or web interfaces for self-service data exploration.

EasyPrompt is an innovative AI tool that enhances the ChatGPT user experience by providing handpicked prompts, searchable chat history, and note-taking capabilities. It offers a Telegram chatbot which significantly improves AI interactions, making it suitable for personal and professional use. This tool aims to simplify and optimize prompt engineering, ensuring users get the most out of their AI-generated content without needing technical expertise.

Prompt Dress is an innovative browser extension tailored to organize and save your generative AI prompts effortlessly. Whether you're a casual user of AI models or an advanced prompt engineer, this tool simplifies the management and retrieval of various prompts. It supports a multitude of platforms, ensuring that you always have your essential AI prompts at your fingertips. Boost your productivity and streamline your prompting processes with Prompt Dress. Enhance your AI interaction, and never lose track of your prompts again.

Unremarkable AI Experts is a scalable platform hosting dozens of specialized AI agents—called experts—that tackle common workflows without manual prompt engineering. Each expert is optimized for tasks like meeting summary generation, code debugging, email composition, sentiment analysis, market research, and advanced data querying. Developers can browse the experts directory, test agents in a web playground, and integrate them into applications using REST endpoints or SDKs. Customize expert behavior through adjustable parameters, chain multiple experts for complex pipelines, deploy isolated instances for data privacy, and access usage analytics for cost control. This streamlines building versatile AI assistants across industries and use cases.

GenAI Processors provides a library of reusable, configurable processors to build end-to-end generative AI workflows. Developers can ingest documents, break them into semantic chunks, generate embeddings, store and query vectors, apply retrieval strategies, and dynamically construct prompts for large language model calls. Its plug-and-play design allows easy extension of custom processing steps, seamless integration with Google Cloud services or external vector stores, and orchestration of complex RAG pipelines for tasks such as question answering, summarization, and knowledge retrieval.

The Gemini Agent Cookbook is a curated open-source toolkit offering a variety of hands-on examples for constructing intelligent agents powered by Google’s Gemini language models. It includes sample code for orchestrating multi-step reasoning chains, dynamically invoking external APIs, integrating toolkits for data retrieval, and managing conversation flows. The cookbook demonstrates best practices for error handling, context management, and prompt engineering, supporting use cases like autonomous chatbots, task automation, and decision support systems. It guides developers through building custom agents that can interpret user requests, fetch real-time data, perform computations, and generate formatted outputs. By following these recipes, engineers can accelerate agent prototyping and deploy robust AI-driven applications in diverse domains.

Ollama Workflows is an open-source library of configurable AI agent pipelines built on top of the Ollama LLM framework. It offers dozens of ready-made workflows—like summarization, translation, code review, data extraction, email drafting, and more—that can be chained together in YAML or JSON definitions. Users install Ollama, clone the repository, select or customize a workflow, and run it via CLI. All processing happens locally on your machine, preserving data privacy while allowing you to iterate quickly and maintain consistent output across projects.

HandyPrompts is an innovative Chrome extension aimed at making artificial intelligence more accessible and useful through one-click prompt engineering solutions. Whether you're in sales, marketing, content creation, development, or any other field, this tool simplifies the integration and use of AI. By providing tailored prompts, HandyPrompts ensures that you can easily harness the power of AI, making your tasks more efficient and creative.

Prompt Picker is a SaaS tool designed to optimize system prompts for generative AI applications by leveraging example user interactions. It allows users to run experiments, evaluate generated outputs, and determine the best configurations. This process helps improve the performance of LLM-powered applications, resulting in more effective and efficient AI operations.

This bootcamp covers the LangChain framework end-to-end, enabling you to build AI Agents in Python. You’ll explore prompt templates, chain composition, agent tooling, conversational memory, and document retrieval. Through interactive notebooks and detailed exercises, you’ll implement chatbots, automated workflows, question-answering systems, and custom agent chains. By course end, you’ll understand how to deploy and optimize LangChain-based agents for diverse tasks.

Nestor offers a modular architecture to assemble AI agents that maintain conversation state, invoke external tools, and customize processing pipelines. Key features include session-based memory stores, a registry for tool functions or plugins, flexible prompt templating, and unified LLM client interfaces. Agents can execute sequential tasks, perform decision branching, and integrate with REST APIs or local scripts. Nestor is framework-agnostic, enabling users to work with OpenAI, Azure, or self-hosted LLM providers.

LLM-Culture provides a structured approach to embed organizational culture into large language model interactions. You start by defining your brand’s values and style rules in a simple configuration file. The framework then offers a library of prompt templates designed to enforce these guidelines. After generating outputs, the built-in evaluation toolkit measures alignment against your cultural criteria and highlights any inconsistencies. Finally, you deploy the framework alongside your LLM pipeline—whether via API or on-premise—so that each response consistently adheres to your company’s tone, ethics, and brand personality.

llmChef simplifies AI interaction by offering a collection of over 100 tailored recipes designed to elicit the best responses from various large language models (LLMs). Users can access different types of queries, covering a broad range of topics, thereby streamlining the process of getting high-quality AI-generated content. This tool is perfect for those looking to leverage AI technology without needing deep technical skills, making it accessible to a wider audience. Its user-friendly design ensures that generating intelligent and relevant AI responses is now within everyone's reach.

LLMOps.Space serves as a dedicated community for practitioners interested in the intricacies of deploying and managing large language models (LLMs) in production environments. The platform emphasizes standardized content, discussions, and events to meet the unique challenges posed by LLMs. By focusing on practices like fine-tuning, prompt management, and lifecycle governance, LLMOps.Space aims to arm its members with the knowledge and tools necessary to scale and optimize LLM deployments. It also features educational resources, company news, open-source LLM modules, and much more.

Lore is a native macOS IDE tailored for prompt engineering in GPT models. Key features include time travel to revisit past versions, versioning for better management of code, and full-text search to quickly locate important prompt details. Lore aims to simplify and enhance your development workflow by making interactions with GPT models more intuitive and efficient.