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Update app.py
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app.py
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@@ -403,7 +403,7 @@ def create_vector_db_and_annoy_index(pdf_path, vector_db_path, annoy_index_path)
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print("Vector database and Annoy index creation completed.")
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def chatbot_interface(file, user_query, response_style
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vector_db_path = "vector_db.pkl"
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annoy_index_path = "vector_index.ann"
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@@ -411,8 +411,8 @@ def chatbot_interface(file, user_query, response_style, selected_retrieval_metho
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chatbot = MistralRAGChatbot(vector_db_path, annoy_index_path)
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selected_retrieval_methods_list = [
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selected_reranking_methods_list = [
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response, retrieved_docs, source_info = asyncio.run(chatbot.generate_response_with_rag(
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user_query=user_query,
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@@ -440,11 +440,9 @@ iface = gr.Interface(
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inputs=[
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gr.File(label="Upload a PDF"),
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gr.Textbox(lines=5, label="User Query"),
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gr.Dropdown(["Detailed", "Concise", "Creative", "Technical"], label="
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gr.
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gr.
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gr.Slider(minimum=1024, maximum=2048, step=128, value=2048, label="Chunk Size"),
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gr.Slider(minimum=100, maximum=300, step=100, value=200, label="Overlap")
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],
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outputs=gr.Textbox(label="RAG Response"),
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title="Chance RAG"
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print("Vector database and Annoy index creation completed.")
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def chatbot_interface(file, user_query, response_style):
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vector_db_path = "vector_db.pkl"
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annoy_index_path = "vector_index.ann"
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chatbot = MistralRAGChatbot(vector_db_path, annoy_index_path)
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selected_retrieval_methods_list = ['annoy', 'bm25']
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selected_reranking_methods_list = ["advanced_fusion"]
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response, retrieved_docs, source_info = asyncio.run(chatbot.generate_response_with_rag(
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user_query=user_query,
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inputs=[
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gr.File(label="Upload a PDF"),
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gr.Textbox(lines=5, label="User Query"),
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gr.Dropdown(["Detailed", "Concise", "Creative", "Technical"], label="Retreival Style"),
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gr.Markdown("#Retreival Method"),
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gr.Mardown("##advanced_fusion")
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],
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outputs=gr.Textbox(label="RAG Response"),
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title="Chance RAG"
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