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It supports dynamic dataset loading for seamless updates. The chatbot’s language model is evaluated on relevance, accuracy, coherence, completeness, creativity, tone, and alignment with intent, ensuring high-quality, user-focused interactions.\n\n## Techstack used\n- React\n- Tailwindcss\n- FastAPI\n- ChromaDB\n- Langchain\n- OpenAI\n- Docker\n\n\n## Flowchart\nThis diagram illustrates the high level components involved and thier interaction\n\u003cimg src=\"./media/flowchart.JPG\" alt=\"Flowchart\"/\u003e\n\n## Demo\n\u003cimg src=\"./media/chatbot.JPG\" alt=\"Chatbot\"/\u003e\n\n\u003cvideo width=\"320\" height=\"240\" controls\u003e\n  \u003csource src=\"./media/ai_support_bot_demo.mp4\" type=\"video/mp4\"\u003e\n\u003c/video\u003e\n\n\nhttps://github.com/user-attachments/assets/49a82013-c936-4f13-8739-646039b77d55\n\n\n\n\n\n## Project Configuration\nBefore running the project, make sure to adjust the following configuration files:\n\n### Backend Configuration\n- Adjust the `.env` file located in the backend folder if any environment variables need modification.\n\n\n\n## Start Containers\nTo start the project, use Docker Compose to build and run the containers:\n```\ndocker compose up --build\n```\n\n### Frontend URL\nOnce the containers are running, you can access the frontend application at:\n```\nhttp://localhost:5173/\n```\n\n### Backend URL\nOnce the containers are running, you can access the backend application at:\n```\nhttp://localhost:8081/\n```\n\n## Pending Improvements\n- Add SQL/NoSQL DB to store the user queries and generated reponses\n\nhttps://github.com/pixegami/langchain-rag-tutorial\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fysskrishna%2Fai-support-bot","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fysskrishna%2Fai-support-bot","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fysskrishna%2Fai-support-bot/lists"}