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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() | |