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chore: updated README

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ShubhamSaboo
2025-02-04 01:16:22 +01:00
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README.md
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@@ -39,6 +39,7 @@ A curated collection of awesome LLM apps built with RAG and AI agents. This repo
- [👨‍⚖️ AI Legal Agent Team](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/ai_agent_tutorials/ai_legal_agent_team)
- [💼 AI Recruitment Agent Team](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/ai_agent_tutorials/ai_recruitment_agent_team)
- [👨‍💼 AI Services Agency](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/ai_agent_tutorials/ai_services_agency)
- [🧲 AI Competitor Intelligence Agent Team](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/ai_agent_tutorials/ai_competitor_intelligence_agent_team)
- [🏋️‍♂️ AI Health & Fitness Planner Agent](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/ai_agent_tutorials/ai_health_fitness_agent)
- [📈 AI Startup Trend Analysis Agent](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/ai_agent_tutorials/ai_startup_trend_analysis_agent)
- [🗞️ AI Journalist Agent](https://github.com/Shubhamsaboo/awesome-llm-apps/tree/main/ai_agent_tutorials/ai_journalist_agent)

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rag_tutorials/gemini_agentic_rag/README.md
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# Agentic RAG with Gemini Thinking ⌘G
# 🤔 Agentic RAG with Gemini 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.

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rag_tutorials/gemini_agentic_rag/agentic_rag_gemini.py
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@@ -39,7 +39,7 @@ COLLECTION_NAME = "gemini-thinking-agent-agno"
# Streamlit App Initialization
st.title("🤖 Agentic RAG with Gemini Thinking and Agno")
st.title("🤔 Agentic RAG with Gemini Thinking and Agno")
# Session State Initialization
if 'google_api_key' not in st.session_state: