Update app.py

app.py

@@ -1,13 +1,14 @@
 import gradio as gr
-import google.generativeai as genai
-import os
+from transformers import pipeline, AutoTokenizer, AutoModelForSeq2SeqLM
 
-# Use your Hugging Face variable for the Gemini API key
-GEMINI_API_KEY = os.getenv("GOOGLEAPI", "PASTE_YOUR_GEMINI_API_KEY_HERE")
-genai.configure(api_key=GEMINI_API_KEY)
+def load_model():
+    model_name = "Salesforce/codet5-small"
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+    return pipeline("summarization", model=model, tokenizer=tokenizer)
 
 def explain_code(files):
-    model = genai.GenerativeModel("models/gemini-1.0")  # Use free-tier Gemini model
+    explainer = load_model()
     explanations = []
     for file in files:
         filename = file.name if hasattr(file, 'name') else 'Uploaded File'
@@ -22,16 +23,16 @@ def explain_code(files):
         for idx, line in enumerate(lines):
             if not line.strip():
                 continue
-            prompt = f"Explain this line of code:\n{line}"
-            response = model.generate_content(prompt)
-            result = response.text if hasattr(response, 'text') else str(response)
+            input_length = len(line.split())
+            max_length = max(1, input_length // 2)
+            result = explainer(line, max_length=max_length, do_sample=False)[0].get('summary_text', '')
             line_explanations.append(f"Line {idx+1}: {line}\nExplanation: {result.strip()}\n")
         explanations.append(f"## {filename}\n" + "\n".join(line_explanations))
     return "\n\n".join(explanations)
 
 def main():
     with gr.Blocks() as demo:
-        gr.Markdown("# CodeExplainerBot (Gemini Free API)")
+        gr.Markdown("# CodeExplainerBot (Local CodeT5-small)")
         code_input = gr.File(label="Upload code files", file_count="multiple", type="binary")
         output = gr.Textbox(label="Line-by-line Explanation", lines=20)
         explain_btn = gr.Button("Explain Code")