Update app.py

app.py

@@ -12,6 +12,10 @@ from llama_cpp import Llama, LlamaCppPythonProvider, LlamaCppAgent
 from llama_cpp.llama_cpp_agent import get_messages_formatter_type, get_context_by_model
 from io import StringIO
 import tempfile
+import importlib
+import time
+import sys
+from flask import Flask
 
 # --- Global Variables ---
 CURRENT_PROJECT = {}  # Store project data (code, packages, etc.)
@@ -105,19 +109,16 @@ def execute_pip_command(command, add_message):
             time.sleep(0.1)  # Simulate delay for more realistic streaming
     rc = process.poll()
     return rc
-
 def generate_text(input_text):
     """Generates text using the loaded language model."""
     inputs = tokenizer(input_text, return_tensors="pt")
     output = model.generate(**inputs, max_length=500, num_return_sequences=1)
     return tokenizer.decode(output[0], skip_special_tokens=True)
-
 # --- AI Agent Functions ---
 def analyze_user_intent(user_input):
     """Classifies the user's intent based on their input."""
     classification = classifier(user_input)
     return classification[0]['label']
-
 def generate_mini_app_ideas(theme):
     """Generates mini-app ideas based on the user's theme."""
     if theme.lower() == "productivity":
@@ -140,14 +141,12 @@ def generate_mini_app_ideas(theme):
         ]
     else:
         return ["No matching mini-apps found. Try a different theme."]
-
 def generate_app_code(app_name, app_description, model_name, history):
     """Generates code for the selected mini-app using the specified GGUF model."""
     prompt = f"'"Write a Python script for a {app_description} named {app_name} using Gradio and Streamlit:"
     agent = get_agent(model_name)
     generated_code = agent.chat(prompt, history)
     return generated_code
-
 def execute_terminal_command(command):
     """Executes a terminal command and returns the output."""
     try:
@@ -155,7 +154,6 @@ def execute_terminal_command(command):
         return result.strip(), None
     except subprocess.CalledProcessError as e:
         return e.output.strip(), str(e)
-
 def install_package(package_name):
     """Installs a package using pip."""
     output, error = execute_terminal_command(f"'"pip install {package_name}")
@@ -163,22 +161,17 @@ def install_package(package_name):
         return f"'"Error installing package: {error}"
     else:
         return f"'"Package `{package_name}` installed successfully."
-
 def get_project_data():
     """Returns the current project data."""
     return CURRENT_PROJECT
-
 def update_project_data(key, value):
     """Updates the project data."""
     CURRENT_PROJECT[key] = value
-
 def handle_chat(input_text, history):
     """Handles user input in the chat interface."""
     def add_message(sender, message):
         history.append((sender, message))
-
     add_message("User", input_text)
-
     if input_text.startswith("pip install ") or input_text.startswith("https://pypi.org/project/"):
         package_name = extract_package_name(input_text)
         add_message("System", f"'"Installing `{package_name}`...")
@@ -186,7 +179,6 @@ def handle_chat(input_text, history):
         add_message("System", result)
         update_project_data("packages", CURRENT_PROJECT.get("packages", []) + [package_name])
         return history, dynamic_functions
-
     # --- AI Agent Interaction ---
     if USER_INTENT is None:
         add_message("System", analyze_user_intent(input_text))
@@ -203,10 +195,7 @@ def handle_chat(input_text, history):
             add_message("System", f"'"Generating code for {app_description}...")
             code = generate_app_code(selected_app, app_description, "CodeQwen", history)  # Use CodeQwen by default
             add_message("System", f"'"
-
-
 python\n{code}\n
-
 add_message("System", "Code generated! What else can I do for you?")
             update_project_data("code", code)
             update_project_data("app_name", selected_app)
@@ -215,29 +204,23 @@ add_message("System", "Code generated! What else can I do for you?")
             add_message("System", "Please choose from the provided mini-app ideas.")
     else:
         add_message("System", "You already have an app in progress. Do you want to start over?")
-
     return history, dynamic_functions
-
 # --- Prebuilt Tools ---
 def generate_code_tool(input_text, history):
     """Prebuilt tool for code generation."""
     code = generate_app_code("MyTool", "A tool to do something", "CodeQwen", history)  # Use CodeQwen by default
     return f"'" python {code}"
-
 def analyze_code_tool(input_text, history):
     """Prebuilt tool for code analysis."""
     agent = get_agent("Codestral")
     analysis = agent.chat(input_text, history)
     return analysis
-
 # --- Streamlit Interface ---
 st.title("AI4ME: Your Personal AI App Workshop")
 st.markdown("## Let's build your dream app together! 🤖")
-
 # --- Hugging Face Token Input ---
 huggingface_token = st.text_input("Enter your Hugging Face Token", type="password", key="huggingface_token")
 os.environ["huggingface_token"] = huggingface_token
-
 # --- Chat Interface ---
 chat_history = []
 chat_input = st.text_input("Tell me your idea...", key="chat_input")
@@ -245,16 +228,13 @@ if chat_input:
     chat_history, dynamic_functions = handle_chat(chat_input, chat_history)
     for sender, message in chat_history:
         st.markdown(f"**{sender}:** {message}")
-
 # --- Code Execution and Deployment ---
 if CURRENT_APP["code"]:
     st.markdown("## Your App Code:")
     code_area = st.text_area("Your App Code", value=CURRENT_APP["code"], key="code_area")
-
     st.markdown("## Deploy Your App (Coming Soon!)")
     # Add deployment functionality here using Streamlit's deployment features.
     # For example, you could use Streamlit's `st.button` to trigger deployment.
-
     # --- Code Execution ---
     st.markdown("## Run Your App:")
     if st.button("Execute Code"):
@@ -266,27 +246,21 @@ if CURRENT_APP["code"]:
             st.success(f"'"Code executed successfully!{output}")
         except Exception as e:
             st.error(f"'"Error executing code: {e}")
-
     # --- Code Editing ---
     st.markdown("## Edit Your Code:")
     if st.button("Edit Code"):
         try:
             # Use Hugging Face's text-generation pipeline for code editing
             prompt = f"'"Improve the following Python code: python {code_area}"
-
 inputs = tokenizer(prompt, return_tensors="pt")
             output = model.generate(**inputs, max_length=500, num_return_sequences=1)
             edited_code = tokenizer.decode(output[0], skip_special_tokens=True).split("
-
-
 python\n")[1].split("\n
-
 st.success(f"'"Code edited successfully!\n{edited_code}")            
             update_project_data("code", edited_code)
             code_area.value = edited_code
         except Exception as e:
             st.error(f"'"Error editing code: {e}")
-
 # --- Prebuilt Tools ---
 st.markdown("## Prebuilt Tools:")
 with st.expander("Generate Code"):
@@ -294,13 +268,11 @@ with st.expander("Generate Code"):
     if st.button("Generate"):
         code_output = generate_code_tool(code_input, chat_history)
         st.markdown(code_output)
-
 with st.expander("Analyze Code"):
     code_input = st.text_area("Enter your code:", key="analyze_code_input")
     if st.button("Analyze"):
         analysis_output = analyze_code_tool(code_input, chat_history)
         st.markdown(analysis_output)
-
 # --- Additional Features ---
 # Add features like:
 # - Code editing