Update app.py

app.py

@@ -8,46 +8,31 @@ debug = True
 logging_level = logging.DEBUG if debug else logging.INFO
 logging.basicConfig(level=logging_level)
 
-os.system("pip install -r requirements.txt")
-os.system("pip freeze")
-os.system("pip install gradio==2.3.0")
-os.system("pip install requests==2.26.0")
-os.system("pip install transformers==4.11.3")
-
 # Initialize the CodeBERT model and tokenizer
 tokenizer = AutoTokenizer.from_pretrained("microsoft/CodeBERT-base")
 model = AutoModelForSeq2SeqLM.from_pretrained("microsoft/CodeBERT-base")
 
 def fetch_repo_contents(repo_url):
-    # Extract username and repo name from URL
     username, repo_name = repo_url.split("github.com/")[-1].split("/")
-    
-    # Fetch repo contents using GitHub API
     api_url = f"https://api.github.com/repos/{username}/{repo_name}/contents"
     response = requests.get(api_url)
     response.raise_for_status()
     return response.json()
 
 def generate_chatbot_response(repo_url, question):
-    # Fetch repository contents
     repo_contents = fetch_repo_contents(repo_url)
-
-    # Generate a prompt based on the user's question and repository contents
     prompt = f"Answer the question about the repository {repo_url}: {question}\n\n"
     for item in repo_contents:
         prompt += f"{item['name']}:\n{item['download_url']}\n\n"
-
-    # Tokenize the prompt and generate a response using the CodeBERT model
     inputs = tokenizer.encode(prompt, return_tensors="pt", max_length=1024, truncation=True)
     outputs = model.generate(inputs, max_length=150, num_return_sequences=1)
     response = tokenizer.decode(outputs[0], skip_special_tokens=True)
-
     return response
 
 # Gradio UI
-repo_url_input = gr.inputs.Textbox(lines=1, label="GitHub Repository URL")
-question_input = gr.inputs.Textbox(lines=2, label="Question")
-output_text = gr.outputs.Textbox(label="Answer")
+repo_url_input = gr.inputs.Text(label="GitHub Repository URL")
+question_input = gr.inputs.Text(label="Question")
+output_text = gr.outputs.Text(label="Answer")
 
 gr.Interface(
     generate_chatbot_response,