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Update app.py
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app.py
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@@ -472,46 +472,16 @@ def perform_ai_lookup(query):
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st.write('🔍Run of Multi-Agent System Paper Summary Spec is Complete')
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st.markdown(response2)
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# ArXiv searcher ~-<>-~ Paper References - Update with RAG
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client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
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"Arxiv Search - Latest - (EXPERIMENTAL)",
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"mistralai/Mixtral-8x7B-Instruct-v0.1", # Literal['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'google/gemma-7b-it', 'None'] in 'LLM Model' Dropdown component
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api_name="/update_with_rag_md"
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responseall = response2 + response1[0] + response1[1]
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st.markdown(responseall)
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"""Perform AI lookup using Gradio client."""
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st.write("Performing AI Lookup...")
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client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
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result1 = client.predict(
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prompt=query,
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llm_model_picked="mistralai/Mixtral-8x7B-Instruct-v0.1",
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stream_outputs=True,
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api_name="/ask_llm"
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)
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st.markdown("### Mixtral-8x7B-Instruct-v0.1 Result")
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st.markdown(result1)
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result2 = client.predict(
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prompt=query,
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llm_model_picked="mistralai/Mistral-7B-Instruct-v0.2",
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stream_outputs=True,
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api_name="/ask_llm"
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)
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st.markdown("### Mistral-7B-Instruct-v0.2 Result")
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st.markdown(result2)
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combined_result = f"{result1}\n\n{result2}"
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#return combined_result
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return responseall
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def display_file_content(file_path):
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"""Display file content with editing capabilities."""
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st.write('🔍Run of Multi-Agent System Paper Summary Spec is Complete')
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st.markdown(response2)
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client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
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result = client.predict(
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message=response2,
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llm_results_use=5,
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database_choice="Semantic Search",
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llm_model_picked="mistralai/Mistral-7B-Instruct-v0.2",
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api_name="/update_with_rag_md"
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)
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return result
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def display_file_content(file_path):
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"""Display file content with editing capabilities."""
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