Banana Prompts is a free online platform that collects, verifies, and shares AI prompt templates for image and video generation models. By offering real prompts that produce actual results, it helps both beginners and experienced users to improve their AI-driven creative projects. Users can access exact wording, settings, and techniques from a large community, allowing faster learning and better outcomes in AI art production.

Banana Prompts is an online prompt library designed specifically for Nano Banana AI image generation. It provides users with professionally tested and optimized prompt templates across various artistic styles. Users can browse, filter, and easily copy prompts to generate high-quality images, making the creative process quicker and more efficient. The platform supports prompt discovery for digital artists, content creators, marketers, designers, and hobbyists, enabling them to unlock the full potential of AI-driven image creation.

Claude-Code-OpenAI transforms Anthropic’s Claude API into a drop-in replacement for OpenAI models in Python applications. After installing via pip and configuring your OPENAI_API_KEY and CLAUDE_API_KEY environment variables, you can use familiar methods like openai.ChatCompletion.create(), openai.Completion.create(), or openai.Embedding.create() with Claude model names (e.g., claude-2, claude-1.3). The library intercepts calls, routes them to the corresponding Claude endpoints, and normalizes responses to match OpenAI’s data structures. It supports real-time streaming, rich parameter mapping, error handling, and prompt templating. This allows teams to experiment with Claude and GPT models interchangeably without refactoring code, enabling rapid prototyping for chatbots, content generation, semantic search, and hybrid LLM workflows.

CrewAI Agent Generator leverages a command-line interface to let you initialize a new AI agent project with opinionated folder structures, sample prompt templates, tool definitions, and testing stubs. You can configure connections to OpenAI, Azure, or custom LLM endpoints; manage agent memory using vector stores; orchestrate multiple agents in collaborative workflows; view detailed conversation logs; and deploy your agents to Vercel, AWS Lambda, or Docker with built-in scripts. It accelerates development and ensures consistent architecture across AI agent projects.

Ernie Bot Agent is a developer framework designed to streamline the creation of AI-driven conversational agents using Baidu ERNIE Bot. It provides abstractions for API calls, prompt templates, memory management, and tool integration. The SDK supports multi-turn conversations with context awareness, custom workflows for task execution, and a plugin system for domain-specific extensions. With built-in logging, error handling, and configuration options, it reduces boilerplate and enables rapid prototyping of chatbots, virtual assistants, and automation scripts.

GPTMe provides a robust platform for orchestrating AI agents that retain conversational context, integrate external tools, and expose a consistent API. Developers install a lightweight Python package, define agents with plug-and-play memory backends, register custom tools (e.g., web search, database queries, file operations), and spin up a local or cloud service. GPTMe handles session tracking, multi-step reasoning, prompt templating, and model switching, delivering production-ready assistants for customer service, productivity, data analysis, and more.

micro-agent provides a minimalistic yet powerful set of abstractions for creating autonomous AI agents. Built in TypeScript, it runs seamlessly in both browser and Node.js contexts, allowing you to define agents with custom prompt templates, decision logic, and extensible tool integrations. Agents can leverage chain-of-thought reasoning, interact with external APIs, and maintain conversational or task-specific memory. The library includes utilities for handling API responses, error management, and session persistence. With micro-agent, developers can prototype and deploy agents for a range of tasks—such as automating workflows, building conversational interfaces, or orchestrating data-processing pipelines—without the overhead of larger frameworks. Its modular design and clear API surface make it easy to extend and integrate into existing applications.

AI-OnChain-Agent integrates OpenAI GPT models with Web3 protocols to create autonomous blockchain agents. It connects to Ethereum networks via configurable RPC endpoints, uses LangChain for prompt orchestration, and Ethers.js/Hardhat for smart contract interactions. Developers can specify trading or governance strategies through prompt templates, monitor token metrics in real time, sign transactions with private keys, and execute buy/sell or stake/unstake operations. Detailed logs track decisions and on-chain results, and the modular design supports extending to oracles, liquidity management, or automated governance voting across multiple DeFi protocols.

Claude Code MCP (Memory Context Provider) is a Python-based CLI tool designed to streamline interactions with Anthropic’s Claude Code model. It offers persistent conversation history, reusable prompt templates, and utilities for generating, reviewing, and refactoring code. Developers can invoke commands for code generation, automated edits, diff comparisons, and inline explanations, while extending functionality through a plugin system. MCP simplifies integrating Claude Code into development pipelines for more consistent, context-aware coding assistance.

Pydantic AI uses Pydantic models to encapsulate AI agent definitions, enforcing type-safe inputs and outputs. Developers declare prompt templates as model fields, automatically validating user data and agent responses. The framework offers built-in error handling, retry logic, and function‐calling support. It integrates with popular LLMs (OpenAI, Azure, Anthropic, etc.), supports asynchronous workflows, and enables modular agent composition. With clear schemas and validation layers, Pydantic AI reduces runtime errors, simplifies prompt management, and accelerates the creation of robust, maintainable AI agents.

PHP AI Tool Bridge is a flexible PHP framework designed to abstract away the complexity of interacting with various AI and large language model APIs. By defining a standard AiTool interface, it allows developers to switch between providers such as OpenAI, Azure OpenAI, and Hugging Face without modifying business logic. The library includes support for prompt templates, parameter configuration, streaming, function calls, request caching, and logging. It also features a tool execution pattern that enables chaining multiple AI tools, building conversational agents, and managing state through memory stores. PHP AI Tool Bridge accelerates the development of AI-powered features by reducing boilerplate and ensuring consistent API usage.

KoG Playground is an open-source, browser-based platform designed to simplify the development of retrieval-augmented generation (RAG) agents. It connects to popular vector stores like Pinecone or FAISS, allowing users to ingest text corpora, compute embeddings, and configure retrieval pipelines visually. The interface offers modular components to define prompt templates, LLM backends (OpenAI, Hugging Face), and chain handlers. Real-time logs display token usage and latency metrics for each API call, helping optimize performance and cost. Users can adjust similarity thresholds, re-ranking algorithms, and result fusion strategies on the fly, then export their configuration as code snippets or reproducible projects. KoG Playground streamlines prototyping for knowledge-driven chatbots, semantic search applications, and custom AI assistants with minimal coding overhead.

Micro-agent is a lightweight, unopinionated JavaScript library designed to simplify the creation of sophisticated AI agents using large language models. It exposes core abstractions such as agents, tools, planners, and memory stores, allowing developers to assemble custom conversational flows. Agents can invoke external APIs or internal utilities as tools, enabling dynamic data retrieval and action execution. The library supports both short-term conversational memory and long-term persistent memory to maintain context across sessions. Planners orchestrate chain-of-thought processes, breaking down complex tasks into tool calls or language model queries. With configurable prompt templates and execution strategies, micro-agent adapts seamlessly to frontend web applications, Node.js services, and edge environments, providing a flexible foundation for chatbots, virtual assistants, or autonomous decision-making systems.

LLM-Powered RAG System is a developer-focused framework for building retrieval-augmented generation (RAG) pipelines. It provides modules for embedding document collections, indexing via FAISS, Pinecone, or Weaviate, and retrieving relevant context at runtime. The system uses LangChain wrappers to orchestrate LLM calls, supports prompt templates, streaming responses, and multi-vector store adapters. It simplifies end-to-end RAG deployment for knowledge bases, allowing customization at each stage—from embedding model configuration to prompt design and result post-processing.

The ChatGPT Sidebar - Model Aggregation offers a comprehensive chatbot experience directly from your browser sidebar. Supporting multiple models such as ChatGPT 3.5, GPT-4, Google Gemini, and more, it enables users to overcome domestic connection restrictions. With features including diverse output formats, cloud-stored chat history, and rich prompt templates, users can easily interact with advanced AI models. The sidebar display ensures it won't disrupt your browsing, making it an efficient tool for various use cases.

AI Prompt Master is an advanced tool to supercharge your interactions with generative AI platforms like ChatGPT, DALL-E, Midjourney, and more. It provides users with the ability to create custom prompts through an intuitive interface that includes radio buttons and checkboxes to tailor prompts to specific needs. With access to predefined templates and one-click copy features, transferring prompts to AI tools becomes seamless. AI Prompt Master aims to improve efficiency, save time, and ensure accurate AI responses, making it ideal for professionals, students, and AI enthusiasts.

The Prompt Tool for Midjourney assists users in generating high-quality prompts with ease. By providing an intuitive interface and customizable features, it reduces the learning curve for new AI art creators. This tool is designed to save time and enhance efficiency, making it ideal for artists, designers, and content creators looking to harness the power of Midjourney's AI capabilities quickly and effectively.

AIPRM for SEO is a powerful Chrome extension designed to streamline and enhance your ChatGPT experience. It provides a curated library of prompt templates specifically aimed at SEO professionals. By integrating AIPRM for SEO into your browser, you can effortlessly access advanced features and prompts, saving time and boosting productivity.

Prompt Affix is an advanced tool designed to help users customize the responses of AI models like ChatGPT. By providing detailed prompts, users can dictate the tone, structure, and specificity of the AI’s replies. This tool makes it easy for users to enhance the quality of interactions by ensuring AI outputs align perfectly with intended objectives. Whether you’re in need of formal, informal, detailed, or concise responses, Prompt Affix provides the flexibility to achieve those results with ease.

Team-GPT provides a platform for seamless collaboration through group chats with ChatGPT. Teams can interact, organize chats in folders, and share knowledge easily. The platform aims to enhance team AI skills with learning resources and prompt templates. It's designed to integrate into daily workflows to boost understanding and adoption of AI technologies within teams.