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# Full_Agent_build | ||
Full LLM powered application (Langchain and LlamaIndex) plus frontend (HTML, CSS and Flask) | ||
# Comprehensive AI Agents and Interactive UI | ||
# Project Description | ||
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Comprehensive AI agents comprise various tools aimed at enhancing tasks such as internet searches, web scraping, data conversation, and trip planning. The project includes: | ||
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- **Multi-Tool Agent**: Capable of navigating between utilities like internet searches, web scraping, and two RAG (Retrieval-Augmented Generation) tools for conversing with data. | ||
- **Agent Orchestration Tool**: Designed specifically for planning trips. | ||
- **Comprehensive RAG Tool**: Equipped with multiple retrieval methods for optimal information retrieval operations. | ||
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## Libraries Used: | ||
- Llama-index | ||
- Langchain | ||
- CrewAI | ||
- OpenAI | ||
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## Running the Project: | ||
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1. Download Ollama using the following command: | ||
``` | ||
curl -fsSL https://ollama.com/install.sh | sh | ||
``` | ||
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2. Make the Ollama model setup script within the setup directory executable using: | ||
``` | ||
chmod +x <filepath> | ||
``` | ||
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3. Run the Ollama model setup files. | ||
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4. Use the following command to run the Ollama server and utilize the models: | ||
``` | ||
ollama serve | ||
``` | ||
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5. Open the virtual environment using Poetry shell: | ||
``` | ||
poetry shell | ||
``` | ||
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6. Finally, run the Flask app using: | ||
``` | ||
python app.py | ||
``` | ||
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