Update app.py

app.py

@@ -3,41 +3,40 @@ from openai import OpenAI
 import os
 
 ACCESS_TOKEN = os.getenv("HF_TOKEN")
+print("Access token loaded.")
 TAVILY_API_KEY = os.getenv("TAVILY_API_KEY")
 client = OpenAI(
     base_url="https://api-inference.huggingface.co/v1/",
     api_key=ACCESS_TOKEN,
 )
+print("OpenAI client initialized.")
 
 # Search Tool
 from langchain_community.tools.tavily_search import TavilySearchResults
 search_tool = TavilySearchResults(tavily_api_key=TAVILY_API_KEY)
-
 # Define a comprehensive system prompt
 SYSTEM_PROMPT = """
 You are a highly knowledgeable and reliable Crypto Trading Advisor and Analyzer. 
 Your goal is to assist users in understanding, analyzing, and making informed decisions about cryptocurrency trading. 
-You provide accurate, concise, and actionable advice based on real-time data, historical trends, and established best practices. 
-If you are provided with relevant search results, incorporate that information into your analysis.
+You provide accurate, concise, and actionable advice based on real-time data, historical trends, and established best practices.
 """
 
-# Fixed settings for LLM
-MAX_TOKENS = 512
-TEMPERATURE = 0.7
-TOP_P = 0.95
-FREQUENCY_PENALTY = 0.0
-SEED = -1  # Use None if random seed is preferred
-
 # Function to handle chatbot responses
-def respond(message, history: list[tuple[str, str]]):
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    max_tokens,
+    temperature,
+    top_p,
+    frequency_penalty,
+    seed
+):
     print(f"Received message: {message}")
     print(f"History: {history}")
 
     # Convert seed to None if -1 (meaning random)
-    if SEED == -1:
+    if seed == -1:
         seed = None
-    else:
-        seed = SEED
 
     messages = [{"role": "system", "content": SYSTEM_PROMPT}]
     print("System prompt added to messages.")
@@ -54,31 +53,17 @@ def respond(message, history: list[tuple[str, str]]):
     # Append the latest user message
     messages.append({"role": "user", "content": message})
 
-    try:
-        # Correct method to get relevant results based on the message
-        search_results = search_tool.query(message)
-        print(f"Search Results: {search_results}")  # Debugging line
-    except Exception as e:
-        print(f"Error during search: {str(e)}")
-        search_results = []
-
-    if search_results:
-        search_results_text = "Here are the search results related to the bitcoin price:\n"
-        for result in search_results:
-            search_results_text += f"- {result['title']}: {result['url']}\n"
-        messages.append({"role": "assistant", "content": search_results_text})
-
     # Start response generation
     response = ""
     print("Sending request to OpenAI API.")
 
     for message_chunk in client.chat.completions.create(
         model="meta-llama/Llama-3.3-70B-Instruct",
-        max_tokens=MAX_TOKENS,
+        max_tokens=max_tokens,
         stream=True,
-        temperature=TEMPERATURE,
-        top_p=TOP_P,
-        frequency_penalty=FREQUENCY_PENALTY,
+        temperature=temperature,
+        top_p=top_p,
+        frequency_penalty=frequency_penalty,
         seed=seed,
         messages=messages,
     ):
@@ -88,14 +73,57 @@ def respond(message, history: list[tuple[str, str]]):
 
     print("Completed response generation.")
 
-# Gradio UI (no sliders for the user, settings are fixed in code)
+# Gradio UI
 chatbot = gr.Chatbot(height=600, show_copy_button=True, placeholder="Ask about crypto trading or analysis.", likeable=True)
 
+max_tokens_slider = gr.Slider(
+    minimum=1,
+    maximum=4096,
+    value=512,
+    step=1,
+    label="Max new tokens"
+)
+temperature_slider = gr.Slider(
+    minimum=0.1,
+    maximum=4.0,
+    value=0.7,
+    step=0.1,
+    label="Temperature"
+)
+top_p_slider = gr.Slider(
+    minimum=0.1,
+    maximum=1.0,
+    value=0.95,
+    step=0.05,
+    label="Top-P"
+)
+frequency_penalty_slider = gr.Slider(
+    minimum=-2.0,
+    maximum=2.0,
+    value=0.0,
+    step=0.1,
+    label="Frequency Penalty"
+)
+seed_slider = gr.Slider(
+    minimum=-1,
+    maximum=65535,
+    value=-1,
+    step=1,
+    label="Seed (-1 for random)"
+)
+
 demo = gr.ChatInterface(
     fn=respond,
+    additional_inputs=[
+        max_tokens_slider,
+        temperature_slider,
+        top_p_slider,
+        frequency_penalty_slider,
+        seed_slider,
+    ],
     fill_height=True,
     chatbot=chatbot,
 )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()