Update app.py

app.py

@@ -1,49 +1,81 @@
-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
+
+# Get API token from environment variable
+API_TOKEN = os.getenv("HF_API_TOKEN")  # Ensure you set this in your environment
+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 with improved prompt."""
+    prompt = f"""You are a code translation AI. Your task is to translate {source_lang} code into {target_lang} accurately.
+    
+    Example Translation:
+    Python:
+    ```python
+    name = input("Enter your name: ")
+    print("Hello, " + name)
+    ```
+    
+    Java:
+    ```java
+    import java.util.Scanner;
+    public class Main {{
+        public static void main(String[] args) {{
+            Scanner scanner = new Scanner(System.in);
+            System.out.print("Enter your name: ");
+            String name = scanner.nextLine();
+            System.out.println("Hello, " + name);
+        }}
+    }}
+    ```
+
+    Now translate the following {source_lang} code to {target_lang}:
+    
+    {code_snippet}
+
+    Translated {target_lang} Code:
+    """
+
+    response = requests.post(API_URL, headers=HEADERS, json={
+        "inputs": prompt,
+        "parameters": {
+            "max_new_tokens": 200,
+            "temperature": 0.2,
+            "top_k": 50,
+            "stop": ["\n\n", "#", "//", "'''"]
+        }
+    })
+
+    if response.status_code == 200:
+        generated_text = response.json()[0]["generated_text"]
+
+        # Extract only the translated code
+        translated_code = generated_text.split(f"Translated {target_lang} Code:\n")[-1].strip()
+        
+        # Clean output by removing unnecessary text
+        translated_code = translated_code.replace("```", "").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.")