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| import streamlit as st | |
| import requests | |
| import os | |
| # Load API token from environment | |
| API_TOKEN = os.getenv("HF_API_TOKEN") | |
| if not API_TOKEN: | |
| st.error("⚠️ Hugging Face API token is missing! Set `HF_API_TOKEN` in your environment variables.") | |
| st.stop() # Stop execution if the token is missing | |
| # Define model API endpoint | |
| 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): | |
| """Translates code from one language to another using Hugging Face API.""" | |
| prompt = f"""### Task: Convert {source_lang} code to {target_lang}. | |
| {source_lang} Code: | |
| ```{source_lang.lower()} | |
| {code_snippet} | |
| ``` | |
| Now convert it to {target_lang}: | |
| ```{target_lang.lower()} | |
| """ | |
| try: | |
| response = requests.post(API_URL, headers=HEADERS, json={ | |
| "inputs": prompt, | |
| "parameters": { | |
| "max_new_tokens": 200, | |
| "temperature": 0.2, | |
| "top_k": 50, | |
| } | |
| }) | |
| if response.status_code == 200: | |
| output = response.json() | |
| if isinstance(output, list) and len(output) > 0: | |
| generated_text = output[0].get("generated_text", "") | |
| # Extract translated code only | |
| translated_code = generated_text.split(f"```{target_lang.lower()}")[-1].strip() | |
| translated_code = translated_code.replace("```", "").strip() | |
| return translated_code if translated_code else "⚠️ Translation failed. No valid output received." | |
| else: | |
| return "⚠️ Unexpected response format from API." | |
| elif response.status_code == 400: | |
| return "⚠️ Error: Invalid request. Check input format." | |
| elif response.status_code == 401: | |
| return "⚠️ Error: Unauthorized. Check your API token." | |
| elif response.status_code == 403: | |
| return "⚠️ Error: Access forbidden. You may need special access to this model." | |
| elif response.status_code == 503: | |
| return "⚠️ Error: Model is loading. Please wait and try again." | |
| else: | |
| return f"⚠️ Error {response.status_code}: {response.text}" | |
| except requests.exceptions.RequestException as e: | |
| return f"⚠️ Network Error: {str(e)}" | |
| # Streamlit UI | |
| st.title("🔄 Code Translator using StarCoder") | |
| st.write("Translate code between different programming languages using AI.") | |
| # Define language options | |
| 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 source_lang == target_lang: | |
| st.warning("⚠️ Source and target languages cannot be the same.") | |
| elif code_input.strip(): | |
| with st.spinner("Translating..."): | |
| translated_code = translate_code(code_input, source_lang, target_lang) | |
| st.subheader(f"Translated {target_lang} Code:") | |
| st.code(translated_code, language=target_lang.lower()) | |
| else: | |
| st.warning("⚠️ Please enter some code before translating.") | |