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README.md
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# LLM-Based Chat Application
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This is a language model-based chat application that provides users with relevant, up-to-date, and easy-to-understand responses by leveraging web search and a powerful language model. The basic flow involves performing a web search using DuckDuckGo, followed by generating a response using the Qwen2.5-0.5b-Instruct language model.
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## Features
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- **Web Search**: Performs real-time searches using DuckDuckGo to retrieve the latest relevant information.
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- **Simple Interface**: Built with Gradio to offer an easy-to-use web interface for users to interact with the model.
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- **Efficient and Scalable**: Optimized for performance using Intel-specific optimizations via `optimum-intel` and other acceleration libraries.
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## Dependencies
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The following dependencies are required for running this application:
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```
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emoji: 👀
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colorFrom: indigo
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sdk: gradio
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sdk_version: 5.4.0
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app_file: app.py
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pinned: false
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---
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---
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title: Llm Chatbot
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emoji: 👀
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colorFrom: indigo
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colorTo: red
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sdk: gradio
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sdk_version: 5.4.0
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app_file: app.py
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pinned: false
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license: apache-2.0
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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# LLM-Based Chat Application
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This is a language model-based chat application that provides users with relevant, up-to-date, and easy-to-understand responses by leveraging web search and a powerful language model. The basic flow involves performing a web search using DuckDuckGo, followed by generating a response using the Qwen2.5-0.5b-Instruct language model.
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Live project:
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## Features
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- **Web Search**: Performs real-time searches using DuckDuckGo to retrieve the latest relevant information.
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- **Simple Interface**: Built with Gradio to offer an easy-to-use web interface for users to interact with the model.
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- **Efficient and Scalable**: Optimized for performance using Intel-specific optimizations via `optimum-intel` and other acceleration libraries.
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## Model Used
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- Language Model: qwen2.5-0.5b-instruct
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- A powerful and efficient model that generates human-like responses based on the query.
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## Application Flow
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- **User Query**: The user inputs a question or request.
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- **Web Search**: The system performs a web search using DuckDuckGo to gather recent and relevant information.
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- **Response Generation**: The gathered data is used to generate a clear, relevant, and easy-to-understand response using the qwen2.5-0.5b-instruct language model.
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- **User Response**: The application returns the generated response to the user.
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## Dependencies
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The following dependencies are required for running this application:
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```
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## License
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- This project is licensed under the Apache License 2.0. See the LICENSE file for details.
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## Acknowledgements
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- **OpenVINO**: For efficient acceleration of the language model.
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- **DuckDuckGo**: For providing real-time web search capabilities.
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- **Hugging Face**: For providing powerful transformer models and tools.
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