Update app.py

app.py

@@ -1,49 +1,77 @@
-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")  # Fetch token securely
-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("🔄 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("⚠️ Please enter some code before translating.")
+import streamlit as st
+import requests
+import os
+
+# Ensure the Hugging Face API Token is available
+API_TOKEN = os.getenv("HF_API_TOKEN")
+if not API_TOKEN:
+    st.error("⚠️ API Token is missing! Please set HF_API_TOKEN as an environment variable.")
+    st.stop()
+
+# Define Hugging Face Model and 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):
+    """Translate code between languages using Hugging Face API."""
+    prompt = f"""You are an expert AI in code translation. Convert the following {source_lang} code to {target_lang}:
+    
+    {source_lang} Code:
+    ```{source_lang.lower()}
+    {code_snippet}
+    ```
+
+    Now, provide the equivalent {target_lang} code:
+    """
+
+    try:
+        response = requests.post(API_URL, headers=HEADERS, json={"inputs": prompt})
+
+        # Handle API response
+        if response.status_code == 200:
+            result = response.json()
+            if isinstance(result, list) and result:
+                generated_text = result[0].get("generated_text", "")
+                translated_code = generated_text.split(f"```{target_lang.lower()}")[-1].strip("```").strip()
+                return translated_code
+            else:
+                return "⚠️ Error: Unexpected API response format."
+
+        elif response.status_code == 400:
+            return "⚠️ Error: Bad request. Please check your input."
+
+        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 model access."
+
+        elif response.status_code == 503:
+            return "⚠️ Error: Model is loading. Please wait a moment and try again."
+
+        else:
+            return f"⚠️ API Error {response.status_code}: {response.text}"
+
+    except requests.exceptions.RequestException as e:
+        return f"⚠️ Network Error: {str(e)}"
+
+# Streamlit UI
+st.title("🔄 AI Code Translator")
+st.write("Convert code between Python, Java, C++, and C.")
+
+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:", height=200)
+
+if st.button("Translate"):
+    if source_lang == target_lang:
+        st.warning("⚠️ Source and target languages must be different!")
+    elif not code_input.strip():
+        st.warning("⚠️ Please enter some code before translating.")
+    else:
+        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())