Update app.py

app.py

@@ -456,32 +456,76 @@ def display_terms_with_links(terms):
         links_md = ' '.join([f"[{emoji}]({url(term)})" for emoji, url in search_urls.items()])
         st.markdown(f"- **{term}** {links_md}", unsafe_allow_html=True)
 
-def perform_ai_lookup(query):
-    all=""
-    st.markdown(f"- {query}")
+def search_arxiv(query):
     
-    # 🔍Run 1 - ArXiv RAG researcher expert ~-<>-~ Paper Summary & Ask LLM
+    st.write("Performing AI Lookup...")
     client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
-    response2 = client.predict(
-            query,	# str  in 'parameter_13' Textbox component
-            #"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
-            #"mistralai/Mistral-7B-Instruct-v0.2",	# Literal['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'google/gemma-7b-it', 'None']  in 'LLM Model' Dropdown component
-            "google/gemma-7b-it",	# Literal['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'google/gemma-7b-it', 'None']  in 'LLM Model' Dropdown component
-            True,	# bool  in 'Stream output' Checkbox component
-            api_name="/ask_llm"
-    )
-    st.write('🔍Run of Multi-Agent System Paper Summary Spec is Complete')
-    st.markdown(response2)
     
+    result1 = client.predict(
+        prompt=query,
+        llm_model_picked="mistralai/Mixtral-8x7B-Instruct-v0.1",
+        stream_outputs=True,
+        api_name="/ask_llm"
+    )
+    st.markdown("### Mixtral-8x7B-Instruct-v0.1 Result")
+    st.markdown(result1)
+
+    result2 = client.predict(
+        prompt=query,
+        llm_model_picked="mistralai/Mistral-7B-Instruct-v0.2",
+        stream_outputs=True,
+        api_name="/ask_llm"
+    )
+    st.markdown("### Mistral-7B-Instruct-v0.2 Result")
+    st.markdown(result2)
+    combined_result = f"{result1}\n\n{result2}"
+    #return combined_result
+
+    return responseall
+
+
+def perform_ai_lookup(query):
+    start_time = time.strftime("%Y-%m-%d %H:%M:%S")
     client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
-    result = client.predict(
-    		message=response2,
-    		llm_results_use=5,
-    		database_choice="Semantic Search",
-    		llm_model_picked="mistralai/Mistral-7B-Instruct-v0.2",
-    		api_name="/update_with_rag_md"
+    response1 = client.predict(
+        query,
+        20,
+        "Semantic Search - up to 10 Mar 2024",
+        "mistralai/Mixtral-8x7B-Instruct-v0.1",
+        api_name="/update_with_rag_md"
     )
-    return result     
+    Question = '### 🔎 ' + query + '\r\n'  # Format for markdown display with links
+    References =  response1[0]  
+    ReferenceLinks = extract_urls(References)
+
+    RunSecondQuery = True
+    results=''
+    if RunSecondQuery:
+        # Search 2 - Retrieve the Summary with Papers Context and Original Query
+        response2 = client.predict(
+            query,
+            "mistralai/Mixtral-8x7B-Instruct-v0.1",
+            True,
+            api_name="/ask_llm"
+        )
+        if len(response2) > 10:
+            Answer = response2
+            SpeechSynthesis(Answer)
+            # Restructure results to follow format of Question, Answer, References, ReferenceLinks
+            results = Question + '\r\n' + Answer + '\r\n' + References + '\r\n' + ReferenceLinks
+            st.markdown(results)
+
+    st.write('🔍Run of Multi-Agent System Paper Summary Spec is Complete')
+    end_time = time.strftime("%Y-%m-%d %H:%M:%S")
+    start_timestamp = time.mktime(time.strptime(start_time, "%Y-%m-%d %H:%M:%S"))
+    end_timestamp = time.mktime(time.strptime(end_time, "%Y-%m-%d %H:%M:%S"))
+    elapsed_seconds = end_timestamp - start_timestamp
+    st.write(f"Start time: {start_time}")
+    st.write(f"Finish time: {end_time}")
+    st.write(f"Elapsed time: {elapsed_seconds:.2f} seconds")
+    filename = generate_filename(query, "md")
+    create_file(filename, query, results, should_save)
+    return results
 
 def display_file_content(file_path):
     """Display file content with editing capabilities."""