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c41e80e
Create app.py
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app.py
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import gradio as gr
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import os
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import json
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import numpy as np
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import requests
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from openai import OpenAI
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def call_gpt3_5(prompt, api_key):
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client = OpenAI(api_key=api_key)
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try:
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response = client.chat.completions.create(
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model="gpt-3.5-turbo",
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messages=[
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{"role": "system", "content": "You are a helpful assistant capable of constructing and executing a Swarm Neural Network (SNN). Return only the formatted results of the SNN execution."},
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{"role": "user", "content": prompt}
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]
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)
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return response.choices[0].message.content
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except Exception as e:
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return f"Error calling GPT-3.5: {str(e)}"
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def execute_snn(api_url, openai_api_key, num_agents, calls_per_agent, special_config):
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prompt = f"""
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Construct and execute a Swarm Neural Network (SNN) with the following parameters:
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- API URL: {api_url}
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- Number of Agents: {num_agents}
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- Calls per Agent: {calls_per_agent}
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- Special Configuration: {special_config if special_config else 'None'}
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Simulate the execution of this SNN and provide only the formatted results. The results should include:
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1. A summary of the data retrieved from the API calls
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2. Any patterns or insights derived from the collective behavior of the agents
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3. Performance metrics of the SNN (e.g., execution time, success rate of API calls)
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Present the results in a clear, structured format without any additional explanations or descriptions of the SNN process.
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"""
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gpt_response = call_gpt3_5(prompt, openai_api_key)
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if gpt_response:
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return f"Results from the swarm neural network:\n\n{gpt_response}"
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else:
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return "Failed to execute SNN due to GPT-3.5 API call failure."
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# Define the Gradio interface
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iface = gr.Interface(
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fn=execute_snn,
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inputs=[
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gr.Textbox(label="API URL for your task"),
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gr.Textbox(label="OpenAI API Key", type="password"),
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gr.Number(label="Number of Agents", minimum=1, maximum=100, step=1),
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gr.Number(label="Calls per Agent", minimum=1, maximum=100, step=1),
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gr.Textbox(label="Special Configuration (optional)")
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],
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outputs="text",
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title="Swarm Neural Network Simulator",
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description="Enter the parameters for your Swarm Neural Network (SNN) simulation.",
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examples=[
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["https://meowfacts.herokuapp.com/", "your-api-key-here", 3, 1, ""],
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["https://api.publicapis.org/entries", "your-api-key-here", 5, 2, "category=Animals"]
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]
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)
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# Launch the interface
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iface.launch()
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