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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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- ---
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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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- ---
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
 
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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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+
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+ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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+
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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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+
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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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+
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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.