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1. Install the necessary Python Libraries

Run the following commands from your terminal to install the required libraries:

2. Import necessary libraries

• Streamlit for the web interface
• asyncio for asynchronous operations
• Together AI for LLM interactions

3. Set up the Streamlit app and API key input.

• Creates a title for the app
• Adds a secure input field for the Together API key

4. Initialize Together AI clients.

• Sets up Together API key as an environment variable
• Initializes both synchronous and asynchronous Together clients

5. Define the models and aggregator system prompt.

• Specifies the LLMs to be used for generating responses
• Defines the aggregator model and its system prompt

6. Implement the LLM call function.

• Asynchronously calls the LLM with the user's prompt
• Returns the model name and its response

7. Define the main function to run all LLMs and aggregate results.

• Runs all reference models asynchronously
• Displays individual responses in expandable sections
• Aggregates responses using the aggregator model
• Streams the aggregated response.

8. Set up the user interface and trigger the main function.

• Provides an input field for the user's question
• Triggers the main function when the user clicks "Get Answer"

🐍 Tip of the day for experienced Python developers

📌 Use decorators with parameters — a powerful technique for logging, control, caching, and custom checks.

Example: a logger that can set the logging level with an argument:

import functools
import logging

def log(level=logging.INFO):
   def decorator(func):
       @functools.wraps(func)
       def wrapper(*args, **kwargs):
           logging.log(level, f"Call {func.__name__} with args={args}, kwargs={kwargs}")
           return func(*args, **kwargs)
       return wrapper
   return decorator

@log(logging. DEBUG)
def compute(x, y):
   return x + y

✅ Why you need it:

The decorator is flexibly adjustable;

Suitable for prod tracing and debugging in maiden;

Retains the signature and docstring thanks to @functools.wraps.

⚠️ Tip: avoid nesting >2 levels and always write tests for decorator behavior.

Python gives you tools that look like magic, but work stably if you know how to use them.