Update app.py

app.py

@@ -1,73 +1,59 @@
-import os
-import threading
 import gradio as gr
+import threading
+import os
 from openai import OpenAI
-from dotenv import load_dotenv
-
-# Load API keys from .env file
-load_dotenv(override=True)
 
-# Retrieve API keys (Default to "MISSING_KEY" for debugging)
-API_KEY_LLAMA = os.getenv("OPENROUTER_API_KEY1", "MISSING_KEY")
-API_KEY_GEMMA = os.getenv("OPENROUTER_API_KEY2", "MISSING_KEY")
-API_KEY_DEEPSEEK1 = os.getenv("OPENROUTER_API_KEY3", "MISSING_KEY")
-API_KEY_DEEPSEEK2 = os.getenv("OPENROUTER_API_KEY4", "MISSING_KEY")
+# Load API Keys from environment variables
+API_KEY_LLAMA = os.getenv("OPENROUTER_API_KEY1")
+API_KEY_GEMMA = os.getenv("OPENROUTER_API_KEY2")
+API_KEY_DEEPSEEK1 = os.getenv("OPENROUTER_API_KEY3")
+API_KEY_DEEPSEEK2 = os.getenv("OPENROUTER_API_KEY4")
 
-# Debugging: Check API key values
-print(f"Llama API Key: {API_KEY_LLAMA[:5]}...")  # Show only first 5 characters
-print(f"Gemma API Key: {API_KEY_GEMMA[:5]}...")
-print(f"DeepSeek API Key 1: {API_KEY_DEEPSEEK1[:5]}...")
-print(f"DeepSeek API Key 2: {API_KEY_DEEPSEEK2[:5]}...")
-
-# Ensure all API keys are loaded
-if "MISSING_KEY" in [API_KEY_LLAMA, API_KEY_GEMMA, API_KEY_DEEPSEEK1, API_KEY_DEEPSEEK2]:
-    raise ValueError("❌ ERROR: One or more API keys are missing from the .env file!")
-
-# Create OpenAI clients for each model
+# Initialize OpenAI clients for each API key
 llama_client = OpenAI(base_url="https://openrouter.ai/api/v1", api_key=API_KEY_LLAMA)
 gemma_client = OpenAI(base_url="https://openrouter.ai/api/v1", api_key=API_KEY_GEMMA)
 deepseek_client1 = OpenAI(base_url="https://openrouter.ai/api/v1", api_key=API_KEY_DEEPSEEK1)
 deepseek_client2 = OpenAI(base_url="https://openrouter.ai/api/v1", api_key=API_KEY_DEEPSEEK2)
 
-# Function to query Llama model
+# Function to query Llama
 def query_llama(user_input, results):
     try:
-        completion = llama_client.chat.completions.create(
+        response = llama_client.chat.completions.create(
             model="meta-llama/llama-3.2-3b-instruct:free",
             messages=[{"role": "user", "content": user_input}]
         )
-        results["Llama"] = completion.choices[0].message.content
+        results["Llama"] = response.choices[0].message.content
     except Exception as e:
         results["Llama"] = f"Error: {str(e)}"
 
-# Function to query Gemma model
+# Function to query Gemma
 def query_gemma(user_input, results):
     try:
-        completion = gemma_client.chat.completions.create(
+        response = gemma_client.chat.completions.create(
             model="google/gemma-2-9b-it:free",
             messages=[{"role": "user", "content": user_input}]
         )
-        results["Gemma"] = completion.choices[0].message.content
+        results["Gemma"] = response.choices[0].message.content
     except Exception as e:
         results["Gemma"] = f"Error: {str(e)}"
 
-# Function to query DeepSeek (First Query)
+# Function to query DeepSeek-1
 def query_deepseek_1(user_input, results):
     try:
-        completion = deepseek_client1.chat.completions.create(
+        response = deepseek_client1.chat.completions.create(
             model="deepseek/deepseek-r1:free",
             messages=[{"role": "user", "content": user_input}]
         )
-        results["DeepSeek1"] = completion.choices[0].message.content
+        results["DeepSeek1"] = response.choices[0].message.content
     except Exception as e:
         results["DeepSeek1"] = f"Error: {str(e)}"
 
-# Function to refine responses using DeepSeek (Final API)
+# Function to refine responses using DeepSeek-2
 def refine_response(user_input):
     try:
         results = {}
 
-        # Create threads for parallel API calls
+        # Start threads for parallel API calls
         threads = [
             threading.Thread(target=query_llama, args=(user_input, results)),
             threading.Thread(target=query_gemma, args=(user_input, results)),
@@ -78,33 +64,33 @@ def refine_response(user_input):
         for thread in threads:
             thread.start()
 
-        # Wait for all threads to complete
+        # Wait for all threads to finish
         for thread in threads:
             thread.join()
 
-        # Ensure all responses are received
+        # Filter valid responses
         valid_responses = {k: v.strip() for k, v in results.items() if v and "Error" not in v}
-
         if len(valid_responses) < 2:
             return "\n\n".join(f"{k} Response: {v}" for k, v in valid_responses.items())
 
-        # Prepare refinement prompt
+        # Prepare refined prompt
         improvement_prompt = f"""
-        Here are three AI-generated responses:
+        Here are AI-generated responses:
 
         Response 1 (Llama): {results.get("Llama", "N/A")}
         Response 2 (Gemma): {results.get("Gemma", "N/A")}
         Response 3 (DeepSeek1): {results.get("DeepSeek1", "N/A")}
 
-        Please combine the best elements of all three, improve clarity, and provide a final refined answer.
+        Please improve the clarity and coherence, and generate a refined response.
         """
 
-        # Query DeepSeek-R1 for refinement using API key 4
+        # Send to DeepSeek-2 for final refinement
         try:
             refined_completion = deepseek_client2.chat.completions.create(
                 model="deepseek/deepseek-r1:free",
                 messages=[{"role": "user", "content": improvement_prompt}]
             )
+
             refined_content = refined_completion.choices[0].message.content
             return refined_content if refined_content.strip() else "Refinement failed, returning best response."
         except Exception as e:
@@ -113,14 +99,15 @@ def refine_response(user_input):
     except Exception as e:
         return f"Unexpected error: {str(e)}"
 
-# Create Gradio interface
-iface = gr.Interface(
-    fn=refine_response, 
-    inputs=gr.Textbox(lines=2, placeholder="Ask me anything..."), 
-    outputs="text",
-    title="Multi-Model AI Enhancer (4 API Keys)",
-    description="Llama (API 1) + Gemma (API 2) + DeepSeek (API 3) → Final Refinement with DeepSeek (API 4)"
+# Gradio Interface
+interface = gr.Interface(
+    fn=refine_response,
+    inputs=gr.Textbox(label="Enter your question"),
+    outputs=gr.Textbox(label="AI Response"),
+    title="Multi-API AI Chat",
+    description="Ask a question and receive a response refined by multiple AI models.",
 )
 
-# Launch app
-iface.launch()
+# Run the app
+if __name__ == "__main__":
+    interface.launch(debug=True)