push

app.py

@@ -91,7 +91,7 @@ def search(query):
     return all_results
 
 def process_query(user_input, history):
-    gr.Info('ℹ️📈 interpreting your request',duration = 4)
+    
     # Accumulate streamed content from the initial request
     stream_search = client.chat_completion(
         model="Qwen/Qwen2.5-72B-Instruct",
@@ -106,16 +106,16 @@ def process_query(user_input, history):
         content = chunk.choices[0].delta.content or ''
         streamed_search_query += content
 
-    
+    print("Search Query:", streamed_search_query)  # Debugging: Check the final search term
 
     # Perform the web search based on the accumulated query
     search_results = search(streamed_search_query)
     search_results_str = json.dumps(search_results)
-    gr.Info('ℹ️📈 thinking...', duration = 3.5)
+    
     # Create the response request with HuggingFace using search results
     response = client.chat_completion(
         model="Qwen/Qwen2.5-72B-Instruct",
-        messages=[{"role": "user", "content": f"YOU ARE IM.S, AN INVESTMENT CHATBOT BUILT BY automatedstockmining.org. Answer the user's request '{user_input}' using the following information: {search_results_str} and the chat history {history}. Provide a concise, direct answer in no more than 2-3 sentences, with appropriate emojis. If the user asks for a smart sheet, generate up to 3000 tokens analyzing all trends and patterns. IF THE USER ASKS YOU WHO YOU ARE, JUST SAY THAT YOU ARE IM.S BUILT BY automatedstockmining.org"}],
+        messages=[{"role": "user", "content": f"YOU ARE IM.S, AN INVESTMENT CHATBOT BUILT BY automatedstockmining.org. Answer the user's request '{user_input}' using the following information: {search_results_str} and the chat history {history}. Provide a concise, direct answer in no more than 2-3 sentences, with appropriate emojis. If the user asks for a smart sheet, generate up to 3000 tokens analyzing all trends and patterns as though you are a stock analyst, look for every pattern and form conclusions."}],
         max_tokens=3000,
         stream=True
     )
@@ -133,7 +133,6 @@ theme = gr.themes.Citrus(
 )
 
 examples = [
-    
     ["whats the trending social sentiment like for Nvidia"],
     ["What's the latest news on Cisco Systems stock"],
     ["Analyze technical indicators for Adobe, are they presenting buy or sell signals"],
@@ -158,7 +157,6 @@ examples = [
     ["What is the latest guidance on revenue for Meta?"],
     ["What is the current beta of Amazon stock and how does it compare to the industry average?"],
     ["What are the top-rated ETFs for technology exposure this quarter?"]
-
 ]
 
 chatbot = gr.Chatbot(