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| import streamlit as st | |
| import requests | |
| import os # Import os to access environment variables | |
| # Get API token from environment variable | |
| API_TOKEN = os.getenv("HF_API_TOKEN") | |
| # Change MODEL_ID to a better model | |
| # MODEL_ID = "Salesforce/codet5p-770m" # CodeT5+ (Recommended) | |
| MODEL_ID = "bigcode/starcoder2-15b" # StarCoder2 | |
| # MODEL_ID = "meta-llama/CodeLlama-34b-Instruct" # Code Llama | |
| # MODEL_ID = "bigcode/starcoder" | |
| API_URL = f"https://api-inference.huggingface.co/models/{MODEL_ID}" | |
| HEADERS = {"Authorization": f"Bearer {API_TOKEN}"} | |
| def translate_code(code_snippet, source_lang, target_lang): | |
| """Translate code using Hugging Face API securely.""" | |
| prompt = f"Translate the following {source_lang} code to {target_lang}:\n\n{code_snippet}\n\nTranslated {target_lang} Code:\n" | |
| response = requests.post(API_URL, headers=HEADERS, json={ | |
| "inputs": prompt, | |
| "parameters": { | |
| "max_new_tokens": 150, | |
| "temperature": 0.2, | |
| "top_k": 50, | |
| "stop": ["\n\n", "#", "//", "'''"] | |
| } | |
| }) | |
| if response.status_code == 200: | |
| generated_text = response.json()[0]["generated_text"] | |
| translated_code = generated_text.split(f"Translated {target_lang} Code:\n")[-1].strip() | |
| return translated_code | |
| else: | |
| return f"Error: {response.status_code}, {response.text}" | |
| # Streamlit UI | |
| st.title("π Code Translator using StarCoder") | |
| st.write("Translate code between different programming languages using AI.") | |
| languages = ["Python", "Java", "C++", "C"] | |
| source_lang = st.selectbox("Select source language", languages) | |
| target_lang = st.selectbox("Select target language", languages) | |
| code_input = st.text_area("Enter your code here:", height=200) | |
| if st.button("Translate"): | |
| if code_input.strip(): | |
| with st.spinner("Translating..."): | |
| translated_code = translate_code(code_input, source_lang, target_lang) | |
| st.subheader("Translated Code:") | |
| st.code(translated_code, language=target_lang.lower()) | |
| else: | |
| st.warning("β οΈ Please enter some code before translating.") | |