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import gradio as gr
import requests
import json
import os
# Retrieve the OpenRouter API Key from the Space secrets
API_KEY = os.getenv("OpenRouter_API_KEY")
# Define available models for selection
MODEL_OPTIONS = [
"openai/gpt-4o-mini-2024-07-18",
"meta-llama/llama-3.1-405b-instruct",
"nvidia/llama-3.1-nemotron-70b-instruct",
"qwen/qwen-2.5-7b-instruct",
"mistralai/mistral-large-2411",
"microsoft/phi-3-medium-128k-instruct",
"meta-llama/llama-3.1-405b-instruct:free",
"nousresearch/hermes-3-llama-3.1-405b:free",
"mistralai/mistral-7b-instruct:free",
"microsoft/phi-3-medium-128k-instruct:free",
"liquid/lfm-40b:free"
]
def generate_comparisons(input_text, selected_models):
results = {}
for model in selected_models:
response = requests.post(
url="https://openrouter.ai/api/v1/chat/completions",
headers={
"Authorization": f"Bearer {API_KEY}",
"Content-Type": "application/json"
},
data=json.dumps({
"model": model, # Use the current model
"messages": [{"role": "user", "content": input_text}],
"top_p": 1,
"temperature": 1,
"frequency_penalty": 0,
"presence_penalty": 0,
"repetition_penalty": 1,
"top_k": 0,
})
)
# Parse the response
if response.status_code == 200:
try:
response_json = response.json()
results[model] = response_json.get("choices", [{}])[0].get("message", {}).get("content", "No content returned.")
except json.JSONDecodeError:
results[model] = "Error: Unable to parse response."
else:
results[model] = f"Error: {response.status_code}, {response.text}"
return results
# Create Gradio interface with multiple model selection
iface = gr.Interface(
fn=generate_comparisons,
inputs=[
gr.Textbox(lines=2, label="Input Text", placeholder="Enter your query here"),
gr.CheckboxGroup(choices=MODEL_OPTIONS, label="Select Models", value=[MODEL_OPTIONS[0]])
],
outputs=gr.JSON(label="Model Comparisons"),
title="Compare Outputs from Multiple Models"
)
iface.launch()
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