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import gradio as gr
import requests
import os
API_URL = "https://api-inference.huggingface.co/models/openai-gpt"
API_TOKEN = os.environ.get("API_TOKEN")
headers = {"Authorization": f"Bearer {API_TOKEN}"}
# Function to translate code using the Hugging Face model API
# Function to translate code using the Hugging Face model API
# Function to translate code using the Hugging Face model API
def translate_code(input_text, source_lang, target_lang):
payload = {
"inputs": f"convert the below {source_lang} code to {target_lang} code: {input_text}"
}
response = requests.post(API_URL, headers=headers, json=payload)
response_data = response.json() # Store the entire response for inspection
print("API Response:", response_data) # Print the response for inspection
# Extract the translated code from the response
translated_code = "No translation available" # Default value
if response_data:
if isinstance(response_data, list) and len(response_data) > 0:
translated_code = response_data[0].get("generated_text", "").strip()
return translated_code
# Interface for the Gradio app
iface = gr.Interface(
fn=translate_code,
inputs=[
gr.inputs.Textbox(label="Enter code to translate"),
gr.inputs.Textbox(label="Source Language (e.g., C++,python,java...)"),
gr.inputs.Textbox(label="Target Language (e.g., C++,python,java...)")
],
outputs=gr.outputs.Textbox(label="Translated Code"),
title="Code Translator",
description="Translate code snippets between programming languages"
)
# Launch the Gradio app
iface.launch()
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