chore: updated README

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ShubhamSaboo
2025-02-07 00:03:03 +01:00
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- [👨‍🏫 AI Teaching Agent Team](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/ai_agent_tutorials/ai_teaching_agent_team)
- [🛫 AI Travel Agent](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/ai_agent_tutorials/ai_travel_agent)
- [🎬 AI Movie Production Agent](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/ai_agent_tutorials/ai_movie_production_agent)
-[💻 Multimodal AI Coding Agent Team with o3-mini and Gemini](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/ai_agent_tutorials/ai_coding_agent_o3-mini)
- [📰 Multi-Agent AI Researcher](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/ai_agent_tutorials/multi_agent_researcher)
- [📑 AI Meeting Agent](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/ai_agent_tutorials/ai_meeting_agent)
- [♜ AI Chess Agent Game](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/ai_agent_tutorials/ai_chess_agent)
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### RAG (Retrieval Augmented Generation)
- [🔍 Autonomous RAG](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/rag_tutorials/autonomous_rag)
- [🔗 Agentic RAG](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/rag_tutorials/agentic_rag)
- [🤔 Agentic RAG with Gemini Flash Thinking](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/rag_tutorials/gemini_agentic_rag)
- [🔄 Llama3.1 Local RAG](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/rag_tutorials/llama3.1_local_rag)
- [🧩 RAG-as-a-Service](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/rag_tutorials/rag-as-a-service)
- [🦙 Local RAG Agent](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/rag_tutorials/local_rag_agent)

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# 💻 Multimodal AI Coding Agent with o3-mini and Gemini
# 💻 Multimodal AI Coding Agent Team with o3-mini and Gemini
An AI Powered Streamlit application that serves as your personal coding assistant, powered by multiple Agents built on the new o3-mini model. You can also upload an image of a coding problem or describe it in text, and the AI agent will analyze, generate an optimal solution, and execute it in a sandbox environment.
## Features

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# 🤔 Agentic RAG with Gemini Thinking
# 🤔 Agentic RAG with Gemini Flash Thinking
A RAG Agentic system built with the new Gemini 2.0 Flash Thinking model and gemini-exp-1206, Qdrant for vector storage, and Agno (phidata prev) for agent orchestration. This application features intelligent query rewriting, document processing, and web search fallback capabilities to provide comprehensive AI-powered responses.