push

app.py

@@ -1,4 +1,3 @@
-from typing import final
 import gradio as gr
 import os
 import json
@@ -6,7 +5,6 @@ from bs4 import BeautifulSoup
 import requests
 from huggingface_hub import InferenceClient
 
-
 # Define global variables
 BOT_AVATAR = 'https://automatedstockmining.org/wp-content/uploads/2024/08/south-west-value-mining-logo.webp'
 hf_token = os.getenv("HF_TOKEN")
@@ -93,29 +91,36 @@ def search(query):
     return all_results
 
 def process_query(user_input, history):
-    gr.Info('ℹ️ thinking...',duration = 6)
-    # Start with a system message
-    messages = [{'role': 'system', 'content': "YOU ARE IM.S, AN INVESTMENT CHATBOT BUILT BY automatedstockmining.org. IF THE USER ASKS WHO YOU ARE YOU SAY YOU ARE IM.S AND YOU WERE MADE BY automatedstockmining.org "}]
-
-    # Append history to messages
-    for user, assistant in history:
-        messages.append({'role': 'user', 'content': user})
-        messages.append({'role': 'assistant', 'content': assistant})
-    messages.append({'role': 'user', 'content': user_input})
-
-    # Perform the web search based on user input
-    search_results = search(user_input)
-    search_results_str = json.dumps(search_results)
-    
+    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",
+        messages=[{"role": "user", "content": f"Based on this chat history {history} and the user's request '{user_input}', suggest a Google search term in a single line without assuming any specific dates (use 'this year', 'this month', etc.)"}],
+        max_tokens=400,
+        stream=True
+    )
     
-    # Create completion request to HuggingFace client
+    # Accumulate content from the streamed response
+    streamed_search_query = ""
+    for chunk in stream_search:
+        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. MAKE SURE YOU REFERENCE IT AND USE IT FOR CONTEXT {history}. Provide a concise, direct answer in no more than 2-3 sentences. use the appropriate emojis for some of your responses. IF THE USER ASKS WHO YOU ARE YOU SAY YOU ARE IM.S AND YOU WERE MADE BY automatedstockmining.org. HOWEVER IF THE USER IS ASKING FOR A SMART SHEET ON ANYTHING, WRITE UP TO 3000 TOKENS AND MAKE IT VERY DETAILED AND ANALYTICAL, BEHAVE LIKE YOU ARE A STOCK ANALYST, ANALYSING ALL THE TRENDS AND PATTERNS IN THE DATA TO FORM A CONCLUSION"}],
+        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 detailed analysis, 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"}],
         max_tokens=3000,
         stream=True
     )
 
+    # Accumulate the final response and stream it
     final_response = ""
     for chunk in response:
         content = chunk.choices[0].delta.content or ''
@@ -128,6 +133,7 @@ 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"],
@@ -152,6 +158,7 @@ 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(
@@ -159,12 +166,14 @@ chatbot = gr.Chatbot(
     avatar_images=[None, BOT_AVATAR],
     show_copy_button=True,
     layout="panel",
-    height = 700
-    
+    height=700
+)
+
+chat_interface = gr.ChatInterface(
+    theme=theme,
+    fn=process_query,
+    chatbot=chatbot,
+    examples=examples,
 )
-gr.ChatInterface(
-        theme = theme,
-        fn=process_query,
-        chatbot=chatbot,
-        examples=examples,
-    ).launch()
+
+chat_interface.launch()