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GitHub
AI Agent Tutorials·2025
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Awesome AI Apps

Arindam Majumder, Shivay Lamba +1

Curates 80+ hands-on LLM-powered examples, tutorials and recipes for building agents, RAG systems, voice assistants, and agentic workflows. Includes starter templates, course playlists, and reference apps for rapid prototyping and learning.

#RAG#mcp#ai-agent#llm#ai-workflow+5
GitHub
AI Agent·2025
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Hands-On AI Engineering

Sumanth (maintainer), AI Engineering Community

Curated collection of production-oriented AI projects that implement OCR, RAG, multi-agent systems, and multimodal pipelines. Each entry provides runnable code, setup notes, and engineering patterns to help developers move prototypes toward production.

#ocr#RAG#ai-agent#multimodal#LLM+3
GitHub
AI Agent·2025
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Agent Starter Pack

Google Cloud Platform·Google Cloud

Scaffolds production-ready GenAI agents on Google Cloud from one CLI command, wrapping your agent logic in Terraform, CI/CD, observability, and evaluation. Ships ADK, LangGraph, and multimodal RAG templates for Cloud Run or Vertex AI Agent Engine.

#google#ai-agent#gemini#RAG#mlops+1
GitHub
AI Infra·2025
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CocoIndex

cocoindex-io·CocoIndex

Keeps codebases, PDFs, Slack, and docs continuously indexed for RAG and knowledge graphs by recomputing only what changed, not the whole dataset. You declare target state in Python; a Rust engine maintains it with per-row lineage back to the source.

#github#mlops#ai-library#ai-workflow#RAG+1
GitHub
MCP Server·2025
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PipesHub

PipesHub, pipeshub-ai

Unifies enterprise knowledge into a permission-aware context layer that delivers citation-backed, explainable search and no-code or SDK-driven agentic workflow automation. Supports 50+ connectors, knowledge-graph retrieval, an MCP server, and bring-your-own-model self-hosting.

#mcp-server#mcp#RAG#retrieval#embeddings+8
GitHub
AI Infra·2025
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QuantMind

LLMQuant

Transforms unstructured financial content—papers, news, blogs, and filings—into a queryable semantic knowledge graph for retrieval-augmented research. Combines domain-tuned LLMs, embedding-based search, and modular ingestion pipelines; aimed at quant research teams and institutional workflows.

#finance#RAG#embeddings#python#llm+3
GitHub
AI Agent·2025
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Biomni: A General-Purpose Biomedical AI Agent

Kexin Huang, Serena Zhang +8

Autonomously executes diverse biomedical research tasks by combining LLM reasoning, retrieval-augmented planning, and code-based execution. Includes a web UI and Gradio demo, a curated Know‑How library, MCP integration, and a biology-tailored reasoning model (Biomni‑R0).

#ai-agent#biology#genomics#drug-discovery#agent-skills+7
GitHub
AI Video·2025
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ViMax: Agentic Video Generation

HKUDS·Data Intelligence Lab @ HKU

Turns a raw idea, novel, or screenplay into a complete multi-shot video through a multi-agent pipeline that scripts, storyboards, and renders shots while a vision model checks character and scene consistency across the whole story.

#ai-video#video#ai-agent#agent-skills#python+6
GitHub
AI Agent·2025
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PageIndex

Vectify AI, Mingtian Zhang +2·Vectify AI

Builds a table-of-contents tree index over long PDFs and uses LLM tree search to fetch relevant sections — no embeddings, chunking, or vector database. Hits 98.7% on FinanceBench, for financial, legal, and technical docs where relevance needs reasoning.

#RAG#ai-agent#llm#nlp#python+4
GitHub
AI Agent·2025
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Agent Development Kit (ADK) Samples

Google

Provides ready-to-use sample agents for Google’s Agent Development Kit across Python, TypeScript, Go, Java, Kotlin, and Android, from simple assistants to multi-agent workflows.

#ai-agent#agent-skills#RAG#llm#python+4
GitHub
AI Infra·2025
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OpenDataLoader PDF

OpenDataLoader Project

Converts PDFs into AI-ready structured outputs (Markdown, JSON with bounding boxes, HTML) for RAG and accessibility workflows; offers deterministic local parsing plus a hybrid AI mode for complex tables, OCR, formulas, and auto-tagging previews.

#ocr#RAG#github#ai-tools#ai-library+2
GitHub
AI Agent·2025
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DeepCode: Open Agentic Coding

Zongwei Li, Zhonghang Li +4·Data Intelligence Lab, The University of Hong Kong

Transforms research papers, natural-language specs, and technical descriptions into runnable code via a multi-agent system. Covers Paper2Code, Text2Web, and Text2Backend; scores 75.9% on OpenAI's PaperBench, ahead of top ML PhDs.

#ai-agent#ai-coding#mcp#mcp-client#github+5
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