Athspi-promax / app.py
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import os
import threading
import gradio as gr
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")
# 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
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
def query_llama(user_input, results):
try:
completion = 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
except Exception as e:
results["Llama"] = f"Error: {str(e)}"
# Function to query Gemma model
def query_gemma(user_input, results):
try:
completion = 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
except Exception as e:
results["Gemma"] = f"Error: {str(e)}"
# Function to query DeepSeek (First Query)
def query_deepseek_1(user_input, results):
try:
completion = deepseek_client1.chat.completions.create(
model="deepseek/deepseek-r1:free",
messages=[{"role": "user", "content": user_input}]
)
results["DeepSeek1"] = completion.choices[0].message.content
except Exception as e:
results["DeepSeek1"] = f"Error: {str(e)}"
# Function to refine responses using DeepSeek (Final API)
def refine_response(user_input):
try:
results = {}
# Create threads for parallel API calls
threads = [
threading.Thread(target=query_llama, args=(user_input, results)),
threading.Thread(target=query_gemma, args=(user_input, results)),
threading.Thread(target=query_deepseek_1, args=(user_input, results))
]
# Start all threads
for thread in threads:
thread.start()
# Wait for all threads to complete
for thread in threads:
thread.join()
# Ensure all responses are received
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
improvement_prompt = f"""
Here are three 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.
"""
# Query DeepSeek-R1 for refinement using API key 4
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:
return f"Error refining response: {str(e)}"
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) β†’ Final Refinement with DeepSeek (API 4)"
)
# Launch app
iface.launch()