#typescript #ai_gateway #gateway #generative_ai #hacktoberfest #langchain #llama_index #llmops #llms #openai #prompt_engineering #router
The AI Gateway by Portkey lets you connect to over 1600 AI models quickly and securely through one simple API, making it easy to integrate any language, vision, or audio AI model in under two minutes. It ensures fast responses with less than 1ms latency, automatic retries, load balancing, and fallback options to keep your AI apps reliable and scalable. It also offers strong security with role-based access, guardrails, and compliance with standards like SOC2 and GDPR. You can save costs with smart caching and optimize usage without changing your code. This helps you build powerful, cost-effective, and secure AI applications faster and with less hassle.
https://github.com/Portkey-AI/gateway
The AI Gateway by Portkey lets you connect to over 1600 AI models quickly and securely through one simple API, making it easy to integrate any language, vision, or audio AI model in under two minutes. It ensures fast responses with less than 1ms latency, automatic retries, load balancing, and fallback options to keep your AI apps reliable and scalable. It also offers strong security with role-based access, guardrails, and compliance with standards like SOC2 and GDPR. You can save costs with smart caching and optimize usage without changing your code. This helps you build powerful, cost-effective, and secure AI applications faster and with less hassle.
https://github.com/Portkey-AI/gateway
GitHub
GitHub - Portkey-AI/gateway: A blazing fast AI Gateway with integrated guardrails. Route to 1,600+ LLMs, 50+ AI Guardrails with…
A blazing fast AI Gateway with integrated guardrails. Route to 1,600+ LLMs, 50+ AI Guardrails with 1 fast & friendly API. - Portkey-AI/gateway
#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
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
GitHub
GitHub - humanlayer/12-factor-agents: What are the principles we can use to build LLM-powered software that is actually good enough…
What are the principles we can use to build LLM-powered software that is actually good enough to put in the hands of production customers? - humanlayer/12-factor-agents
#python #agents #ai #api_gateway #asyncio #authentication_middleware #devops #docker #fastapi #federation #gateway #generative_ai #jwt #kubernetes #llm_agents #mcp #model_context_protocol #observability #prompt_engineering #python #tools
The MCP Gateway is a powerful tool that unifies different AI service protocols like REST and MCP into one easy-to-use endpoint. It helps you manage multiple AI tools and services securely with features like authentication, retries, rate-limiting, and real-time monitoring through an admin UI. You can run it locally or in scalable cloud environments using Docker or Kubernetes. It supports various communication methods (HTTP, WebSocket, SSE, stdio) and offers observability with OpenTelemetry for tracking AI tool usage and performance. This gateway simplifies connecting AI clients to diverse services, making development and management more efficient and secure.
https://github.com/IBM/mcp-context-forge
The MCP Gateway is a powerful tool that unifies different AI service protocols like REST and MCP into one easy-to-use endpoint. It helps you manage multiple AI tools and services securely with features like authentication, retries, rate-limiting, and real-time monitoring through an admin UI. You can run it locally or in scalable cloud environments using Docker or Kubernetes. It supports various communication methods (HTTP, WebSocket, SSE, stdio) and offers observability with OpenTelemetry for tracking AI tool usage and performance. This gateway simplifies connecting AI clients to diverse services, making development and management more efficient and secure.
https://github.com/IBM/mcp-context-forge
GitHub
GitHub - IBM/mcp-context-forge: An AI Gateway, registry, and proxy that sits in front of any MCP, A2A, or REST/gRPC APIs, exposing…
An AI Gateway, registry, and proxy that sits in front of any MCP, A2A, or REST/gRPC APIs, exposing a unified endpoint with centralized discovery, guardrails and management. Optimizes Agent &...
#javascript #ai #anthropic #chatbots #chatgpt #claude #gemini #generative_ai #google_deepmind #large_language_models #llm #openai #prompt_engineering #prompt_injection #prompts
There is a collection of system prompts used by popular chatbots like ChatGPT and others. These prompts are instructions that guide how chatbots respond. They are now available publicly on GitHub, which can be very helpful for users. By seeing these prompts, users can understand how chatbots work and even learn how to create their own AI tools. This can help developers build better AI applications and improve their understanding of AI technology.
https://github.com/asgeirtj/system_prompts_leaks
There is a collection of system prompts used by popular chatbots like ChatGPT and others. These prompts are instructions that guide how chatbots respond. They are now available publicly on GitHub, which can be very helpful for users. By seeing these prompts, users can understand how chatbots work and even learn how to create their own AI tools. This can help developers build better AI applications and improve their understanding of AI technology.
https://github.com/asgeirtj/system_prompts_leaks
GitHub
GitHub - asgeirtj/system_prompts_leaks: Extracted system prompts from Anthropic - Claude Fable 5, Opus 4.8, Claude Code, Claude…
Extracted system prompts from Anthropic - Claude Fable 5, Opus 4.8, Claude Code, Claude Design. OpenAI - ChatGPT GPT-5.6, Codex GPT-5.6, GPT-5.5. Google - Gemini 3.5 Flash, 3.1 Pro, Antigravity. xA...
#jupyter_notebook #chatgpt #finance #fingpt #fintech #large_language_models #machine_learning #nlp #prompt_engineering #pytorch #reinforcement_learning #robo_advisor #sentiment_analysis #technical_analysis
FinGPT is an open-source AI tool designed specifically for finance, helping you analyze financial news, predict stock prices, and get personalized investment advice quickly and affordably. Unlike costly models like BloombergGPT, FinGPT can be updated frequently with new data at a low cost, making it more accessible and timely. It uses advanced techniques like reinforcement learning from human feedback to tailor advice to your preferences, such as risk tolerance. You can use FinGPT for tasks like sentiment analysis, robo-advising, fraud detection, and portfolio optimization, helping you make smarter financial decisions with up-to-date insights.
https://github.com/AI4Finance-Foundation/FinGPT
FinGPT is an open-source AI tool designed specifically for finance, helping you analyze financial news, predict stock prices, and get personalized investment advice quickly and affordably. Unlike costly models like BloombergGPT, FinGPT can be updated frequently with new data at a low cost, making it more accessible and timely. It uses advanced techniques like reinforcement learning from human feedback to tailor advice to your preferences, such as risk tolerance. You can use FinGPT for tasks like sentiment analysis, robo-advising, fraud detection, and portfolio optimization, helping you make smarter financial decisions with up-to-date insights.
https://github.com/AI4Finance-Foundation/FinGPT
GitHub
GitHub - AI4Finance-Foundation/FinGPT: FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the…
FinGPT: Open-Source Financial Large Language Models! Revolutionize 🔥 We release the trained model on HuggingFace. - AI4Finance-Foundation/FinGPT
#javascript #ai #github_copilot #prompt_engineering
You can improve your GitHub Copilot experience by using the Awesome GitHub Copilot Customizations, a collection of ready-made prompts, instructions, and chat modes tailored for different coding tasks and roles. This toolkit helps you write better code faster by providing focused code suggestions, enforcing coding standards, and offering expert AI personas for specialized help. You can easily add these customizations to editors like VS Code using the MCP Server. This saves you time, boosts productivity, ensures consistent code quality, and helps you learn best practices while coding. It also supports collaboration and onboarding by standardizing workflows and documentation.
https://github.com/github/awesome-copilot
You can improve your GitHub Copilot experience by using the Awesome GitHub Copilot Customizations, a collection of ready-made prompts, instructions, and chat modes tailored for different coding tasks and roles. This toolkit helps you write better code faster by providing focused code suggestions, enforcing coding standards, and offering expert AI personas for specialized help. You can easily add these customizations to editors like VS Code using the MCP Server. This saves you time, boosts productivity, ensures consistent code quality, and helps you learn best practices while coding. It also supports collaboration and onboarding by standardizing workflows and documentation.
https://github.com/github/awesome-copilot
GitHub
GitHub - github/awesome-copilot: Community-contributed instructions, agents, skills, and configurations to help you make the most…
Community-contributed instructions, agents, skills, and configurations to help you make the most of GitHub Copilot. - github/awesome-copilot
#jupyter_notebook #aiagent #chatgpt #finance #fingpt #large_language_models #multimodal_deep_learning #prompt_engineering #robo_advisor
FinRobot is a free open-source platform using AI agents and large language models for easy financial analysis. It automates stock predictions, equity reports from 10-K filings, risk checks, valuations like P/E ratios, and trading strategies with real-time data from news and markets. Install via Python, add API keys, and run demos for instant insights. This saves you hours on complex research, delivers pro-level reports and forecasts accurately, and helps make smarter investment decisions without expert skills.
https://github.com/AI4Finance-Foundation/FinRobot
FinRobot is a free open-source platform using AI agents and large language models for easy financial analysis. It automates stock predictions, equity reports from 10-K filings, risk checks, valuations like P/E ratios, and trading strategies with real-time data from news and markets. Install via Python, add API keys, and run demos for instant insights. This saves you hours on complex research, delivers pro-level reports and forecasts accurately, and helps make smarter investment decisions without expert skills.
https://github.com/AI4Finance-Foundation/FinRobot
GitHub
GitHub - AI4Finance-Foundation/FinRobot: FinRobot: An Open-Source AI Agent Platform for Financial Analysis using LLMs 🚀 🚀 🚀
FinRobot: An Open-Source AI Agent Platform for Financial Analysis using LLMs 🚀 🚀 🚀 - AI4Finance-Foundation/FinRobot
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#python #agentic_ai #agentic_coding #ai_coding_agent #ai_plugins #anthropic_claude #claude_ai #claude_ai_skills #claude_code #claude_code_plugins #claude_code_skills #claude_skills #claudecode_subagents #developer_tools #devtools #mcp_tools #openai_codex #prompt_engineering
Claude Code Skills offers 169 free, ready-to-use plugins that turn AI coding agents like Claude Code, OpenAI Codex, and OpenClaw into experts in engineering, marketing, product, compliance, and more. Install easily via simple commands to add skills like security auditing, test automation, or C-level advice, with 160+ Python tools included. This saves you time by automating complex tasks, boosting code quality, and handling grunt work so you focus on creative problem-solving and faster results.
https://github.com/alirezarezvani/claude-skills
Claude Code Skills offers 169 free, ready-to-use plugins that turn AI coding agents like Claude Code, OpenAI Codex, and OpenClaw into experts in engineering, marketing, product, compliance, and more. Install easily via simple commands to add skills like security auditing, test automation, or C-level advice, with 160+ Python tools included. This saves you time by automating complex tasks, boosting code quality, and handling grunt work so you focus on creative problem-solving and faster results.
https://github.com/alirezarezvani/claude-skills
GitHub
GitHub - alirezarezvani/claude-skills: 345 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 330+ skills…
345 Claude Code skills & agent skills & plugins (30+ Agents, 70+ custom commands, 330+ skills, customizable references, scripts)for Claude Code, Codex, Gemini CLI, Cursor, and 8 mor...
#typescript #analytics #autogen #evaluation #langchain #large_language_models #llama_index #llm #llm_evaluation #llm_observability #llmops #monitoring #observability #open_source #openai #playground #prompt_engineering #prompt_management #self_hosted #ycombinator
Langfuse is a free, open-source platform to build, monitor, evaluate, and debug AI apps using large language models (LLMs). It offers tracing for app logic, prompt management, evaluations, datasets, a playground, and easy integrations like OpenAI, LangChain, and LlamaIndex. Deploy it on Langfuse Cloud (free tier) or self-host with Docker in minutes. This helps you quickly spot issues, improve prompts without slowing apps, test reliably, and speed up development—saving time and boosting AI performance.
https://github.com/langfuse/langfuse
Langfuse is a free, open-source platform to build, monitor, evaluate, and debug AI apps using large language models (LLMs). It offers tracing for app logic, prompt management, evaluations, datasets, a playground, and easy integrations like OpenAI, LangChain, and LlamaIndex. Deploy it on Langfuse Cloud (free tier) or self-host with Docker in minutes. This helps you quickly spot issues, improve prompts without slowing apps, test reliably, and speed up development—saving time and boosting AI performance.
https://github.com/langfuse/langfuse
GitHub
GitHub - langfuse/langfuse: 🪢 Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground…
🪢 Open source AI engineering platform: LLM evals, observability, metrics, prompt management, playground, datasets. Integrates with OpenTelemetry, LangChain, OpenAI SDK, LiteLLM, and more. 🍊YC W23 ...
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#python #academic_pipeline #academic_writing #ai_research #claude #claude_code #literature_review #peer_review #prompt_engineering
# Academic Research Skills for Claude Code
This is a comprehensive toolkit that helps you write research papers from start to finish. Instead of AI writing your paper alone, it works as your research partner—handling the tedious work like finding sources, checking citations, and organizing arguments, while you focus on the thinking and writing that only you can do.
The system includes four main tools: Deep Research (for finding and organizing information), Academic Paper (for writing), Academic Paper Reviewer (for getting feedback), and Academic Pipeline (which coordinates everything together). You can use individual tools or run the complete pipeline. It supports multiple languages, citation formats, and paper types. The toolkit emphasizes human control at every step—you make the final decisions, and the AI flags potential problems like hallucinated references or weak arguments. Installation takes 30 seconds via plugin marketplace, and it costs roughly $4–6 to write a complete 15,000-word paper.
https://github.com/Imbad0202/academic-research-skills
# Academic Research Skills for Claude Code
This is a comprehensive toolkit that helps you write research papers from start to finish. Instead of AI writing your paper alone, it works as your research partner—handling the tedious work like finding sources, checking citations, and organizing arguments, while you focus on the thinking and writing that only you can do.
The system includes four main tools: Deep Research (for finding and organizing information), Academic Paper (for writing), Academic Paper Reviewer (for getting feedback), and Academic Pipeline (which coordinates everything together). You can use individual tools or run the complete pipeline. It supports multiple languages, citation formats, and paper types. The toolkit emphasizes human control at every step—you make the final decisions, and the AI flags potential problems like hallucinated references or weak arguments. Installation takes 30 seconds via plugin marketplace, and it costs roughly $4–6 to write a complete 15,000-word paper.
https://github.com/Imbad0202/academic-research-skills
GitHub
GitHub - Imbad0202/academic-research-skills: Academic Research Skills for Claude Code: research → write → review → revise → finalize
Academic Research Skills for Claude Code: research → write → review → revise → finalize - Imbad0202/academic-research-skills
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#python #agent #ai #anthropic #claude_code #compression #context_engineering #context_window #cursor #fastapi #langchain #llm #mcp #openai #prompt_engineering #proxy #python #rag #token_optimization #tokens #typescript
Headroom is a local tool for AI agents that shrinks prompts, logs, files, and chat history before sending them to an LLM, often cutting tokens by 60–95% while keeping the same answer quality. It can work as a library, proxy, MCP server, or agent wrapper, so you can save tokens, speed up workflows, and still recover the original content when needed.
https://github.com/chopratejas/headroom
Headroom is a local tool for AI agents that shrinks prompts, logs, files, and chat history before sending them to an LLM, often cutting tokens by 60–95% while keeping the same answer quality. It can work as a library, proxy, MCP server, or agent wrapper, so you can save tokens, speed up workflows, and still recover the original content when needed.
https://github.com/chopratejas/headroom
GitHub
GitHub - headroomlabs-ai/headroom: Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens…
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server. - headrooml...
#javascript #ai #anthropic #caveman #claude #claude_code #llm #meme #prompt_engineering #skill #tokens
This tool helps agents answer in caveman style: fewer words, same technical meaning, and often much lower token cost. You can choose levels like lite, full, ultra, or wenyan, and it also includes commands for shorter commit messages, quick PR reviews, stats, and compressing memory files; the benefit is faster replies, lower cost, and longer context for your work.
https://github.com/JuliusBrussee/caveman
This tool helps agents answer in caveman style: fewer words, same technical meaning, and often much lower token cost. You can choose levels like lite, full, ultra, or wenyan, and it also includes commands for shorter commit messages, quick PR reviews, stats, and compressing memory files; the benefit is faster replies, lower cost, and longer context for your work.
https://github.com/JuliusBrussee/caveman
GitHub
GitHub - JuliusBrussee/caveman: 🪨 why use many token when few token do trick — Claude Code skill that cuts 65% of tokens by talking…
🪨 why use many token when few token do trick — Claude Code skill that cuts 65% of tokens by talking like caveman - JuliusBrussee/caveman
#python #cfg #generative_ai #json #llms #prompt_engineering #regex #structured_generation #symbolic_ai
Outlines is a Python library that guarantees large language models produce structured outputs (like JSON, XML, or custom schemas) directly during generation, not after. By simply specifying your desired output type using Python syntax (e.g., `int` or a Pydantic model), it mathematically ensures the result matches your structure exactly. This benefits you by eliminating broken JSON, parsing errors, and fragile regex code, making your AI applications reliable, predictable, and ready for production use without post-generation fixes.
https://github.com/dottxt-ai/outlines
Outlines is a Python library that guarantees large language models produce structured outputs (like JSON, XML, or custom schemas) directly during generation, not after. By simply specifying your desired output type using Python syntax (e.g., `int` or a Pydantic model), it mathematically ensures the result matches your structure exactly. This benefits you by eliminating broken JSON, parsing errors, and fragile regex code, making your AI applications reliable, predictable, and ready for production use without post-generation fixes.
https://github.com/dottxt-ai/outlines
GitHub
GitHub - dottxt-ai/outlines: Structured Outputs
Structured Outputs. Contribute to dottxt-ai/outlines development by creating an account on GitHub.