Update app.py

app.py

@@ -1,361 +1,211 @@
-import os
-import subprocess
-import random
-from huggingface_hub import InferenceClient, cached_download, hf_hub_url
-import gradio as gr
-from safe_search import safe_search
-from i_search import google
-from i_search import i_search as i_s
-from agent import (
-    ACTION_PROMPT,
-    ADD_PROMPT,
-    COMPRESS_HISTORY_PROMPT,
-    LOG_PROMPT,
-    LOG_RESPONSE,
-    MODIFY_PROMPT,
-    PREFIX,
-    SEARCH_QUERY,
-    READ_PROMPT,
-    TASK_PROMPT,
-    UNDERSTAND_TEST_RESULTS_PROMPT,
-)
-from utils import parse_action, parse_file_content, read_python_module_structure
-from datetime import datetime
-import json
-
-# --- Global Variables for App State ---
-app_state = {"components": []}
-terminal_history = ""
-
-# --- Component Library ---
-components_registry = {
-    "Button": {
-        "properties": {"label": "Click Me", "onclick": ""},
-        "description": "A clickable button",
-        "code_snippet": 'gr.Button(value="{label}", variant="primary")',
-    },
-    "Text Input": {
-        "properties": {"value": "", "placeholder": "Enter text"},
-        "description": "A field for entering text",
-        "code_snippet": 'gr.Textbox(label="{placeholder}")',
-    },
-    "Image": {
-        "properties": {"src": "#", "alt": "Image"},
-        "description": "Displays an image",
-        "code_snippet": 'gr.Image(label="{alt}")',
-    },
-    "Dropdown": {
-        "properties": {"choices": ["Option 1", "Option 2"], "value": ""},
-        "description": "A dropdown menu for selecting options",
-        "code_snippet": 'gr.Dropdown(choices={choices}, label="Dropdown")',
-    },
-    # Add more components here...
-}
-
-# --- NLP Model (Example using Hugging Face) ---
+import os import subprocess import random from huggingface_hub import InferenceClient, cached_download, hf_hub_url import gradio as gr from safe_search import safe_search from i_search import google from i_search import i_search as i_s from agent import ( ACTION_PROMPT, ADD_PROMPT, COMPRESS_HISTORY_PROMPT, LOG_PROMPT, LOG_RESPONSE, MODIFY_PROMPT, PREFIX, SEARCH_QUERY, READ_PROMPT, TASK_PROMPT, UNDERSTAND_TEST_RESULTS_PROMPT, ) from utils import parse_action, parse_file_content, read_python_module_structure from datetime import datetime import json
+
+--- Global Variables for App State ---
+app_state = {"components": []} terminal_history = ""
+
+--- Component Library ---
+components_registry = { "Button": { "properties": {"label": "Click Me", "onclick": ""}, "description": "A clickable button", "code_snippet": 'gr.Button(value="{label}", variant="primary")', }, "Text Input": { "properties": {"value": "", "placeholder": "Enter text"}, "description": "A field for entering text", "code_snippet": 'gr.Textbox(label="{placeholder}")', }, "Image": { "properties": {"src": "#", "alt": "Image"}, "description": "Displays an image", "code_snippet": 'gr.Image(label="{alt}")', }, "Dropdown": { "properties": {"choices": ["Option 1", "Option 2"], "value": ""}, "description": "A dropdown menu for selecting options", "code_snippet": 'gr.Dropdown(choices={choices}, label="Dropdown")', }, # Add more components here... }
+
+--- NLP Model (Example using Hugging Face) ---
 nlp_model_name = "google/flan-t5-small"
-# Check if the model exists in the cache
-try:
-    cached_download(hf_hub_url(nlp_model_name, revision="main"))
-    nlp_model = InferenceClient(nlp_model_name)
-except:
-    nlp_model = None
-
-# --- Function to get NLP model response ---
-def get_nlp_response(input_text):
-    if nlp_model:
-        response = nlp_model.text_generation(input_text)
-        return response.generated_text
-    else:
-        return "NLP model not available."
-
-# --- Component Class ---
-class Component:
-    def __init__(self, type, properties=None, id=None):
-        self.id = id or random.randint(1000, 9999)
-        self.type = type
-        self.properties = properties or components_registry[type]["properties"].copy()
-
-    def to_dict(self):
-        return {
-            "id": self.id,
-            "type": self.type,
-            "properties": self.properties,
-        }
-
-    def render(self):
-        # Properly format choices for Dropdown
-        if self.type == "Dropdown":
-            self.properties["choices"] = (
-                str(self.properties["choices"])
-                .replace("[", "")
-                .replace("]", "")
-                .replace("'", "")
-            )
-        return components_registry[self.type]["code_snippet"].format(
-            **self.properties
+
+Check if the model exists in the cache
+try: cached_download(hf_hub_url(nlp_model_name, revision="main")) nlp_model = InferenceClient(nlp_model_name) except: nlp_model = None
+
+--- Function to get NLP model response ---
+def get_nlp_response(input_text): if nlp_model: response = nlp_model.text_generation(input_text) return response.generated_text else: return "NLP model not available."
+
+--- Component Class ---
+class Component: def init(self, type, properties=None, id=None): self.id = id or random.randint(1000, 9999) self.type = type self.properties = properties or components_registry[type]["properties"].copy()
+
+def to_dict(self):
+    return {
+        "id": self.id,
+        "type": self.type,
+        "properties": self.properties,
+    }
+
+def render(self):
+    # Properly format choices for Dropdown
+    if self.type == "Dropdown":
+        self.properties["choices"] = (
+            str(self.properties["choices"])
+            .replace("[", "")
+            .replace("]", "")
+            .replace("'", "")
         )
+    return components_registry[self.type]["code_snippet"].format(
+        **self.properties
+    )
+--- Function to update the app canvas (for preview) ---
+def update_app_canvas(): components_html = "".join( [ f"<div>Component ID: {component['id']}, Type: {component['type']}, Properties: {component['properties']}</div>" for component in app_state["components"] ] ) return components_html
 
+--- Function to handle component addition ---
+def add_component(component_type): if component_type in components_registry: new_component = Component(component_type) app_state["components"].append(new_component.to_dict()) return ( update_app_canvas(), f"System: Added component: {component_type}\n", ) else: return None, f"Error: Invalid component type: {component_type}\n"
 
-# --- Function to update the app canvas (for preview) ---
-def update_app_canvas():
-    components_html = "".join(
-        [
-            f"<div>Component ID: {component['id']}, Type: {component['type']}, Properties: {component['properties']}</div>"
-            for component in app_state["components"]
-        ]
-    )
-    return components_html
+--- Function to handle terminal input ---
+def run_terminal_command(command, history): global terminal_history output = "" try: # Basic command parsing (expand with NLP) if command.startswith("add "): component_type = command.split("add ", 1)[1].strip() _, output = add_component(component_type) elif command.startswith("set "): _, output = set_component_property(command) elif command.startswith("search "): search_query = command.split("search ", 1)[1].strip() output = i_s(search_query) elif command.startswith("deploy "): app_name = command.split("deploy ", 1)[1].strip() output = deploy_to_huggingface(app_name) else: # Attempt to execute command as Python code try: result = subprocess.check_output( command, shell=True, stderr=subprocess.STDOUT, text=True ) output = result except Exception as e: output = f"Error executing Python code: {str(e)}" except Exception as e: output = f"Error: {str(e)}" finally: terminal_history += f"User: {command}\n" terminal_history += f"{output}\n" return terminal_history
 
+def set_component_property(command): try: # Improved 'set' command parsing set_parts = command.split(" ", 2)[1:] if len(set_parts) != 2: raise ValueError("Invalid 'set' command format.")
 
-# --- Function to handle component addition ---
-def add_component(component_type):
-    if component_type in components_registry:
-        new_component = Component(component_type)
-        app_state["components"].append(new_component.to_dict())
-        return (
-            update_app_canvas(),
-            f"System: Added component: {component_type}\n",
-        )
-    else:
-        return None, f"Error: Invalid component type: {component_type}\n"
-
-
-# --- Function to handle terminal input ---
-def run_terminal_command(command, history):
-    global terminal_history
-    output = ""
-    try:
-        # Basic command parsing (expand with NLP)
-        if command.startswith("add "):
-            component_type = command.split("add ", 1)[1].strip()
-            _, output = add_component(component_type)
-        elif command.startswith("set "):
-            _, output = set_component_property(command)
-        elif command.startswith("search "):
-            search_query = command.split("search ", 1)[1].strip()
-            output = i_s(search_query)
-        else:
-            # Attempt to execute command as Python code
-            try:
-                result = subprocess.check_output(
-                    command, shell=True, stderr=subprocess.STDOUT, text=True
-                )
-                output = result
-            except Exception as e:
-                output = f"Error executing Python code: {str(e)}"
-    except Exception as e:
-        output = f"Error: {str(e)}"
-    finally:
-        terminal_history += f"User: {command}\n"
-        terminal_history += f"{output}\n"
-    return terminal_history
-
-
-def set_component_property(command):
-    try:
-        # Improved 'set' command parsing
-        set_parts = command.split(" ", 2)[1:]
-        if len(set_parts) != 2:
-            raise ValueError("Invalid 'set' command format.")
-
-        component_id = int(set_parts[0])  # Use component ID
-        property_name, property_value = set_parts[1].split("=", 1)
-
-        # Find component by ID
-        component_found = False
-        for component in app_state["components"]:
-            if component["id"] == component_id:
-                if property_name in component["properties"]:
-                    component["properties"][
-                        property_name.strip()
-                    ] = property_value.strip()
-                    component_found = True
-                    return (
-                        update_app_canvas(),
-                        f"System: Property '{property_name}' set to '{property_value}' for component {component_id}\n",
-                    )
-                else:
-                    return (
-                        None,
-                        f"Error: Property '{property_name}' not found in component {component_id}\n",
-                    )
-        if not component_found:
-            return (
-                None,
-                f"Error: Component with ID {component_id} not found.\n",
-            )
-
-    except Exception as e:
-        return None, f"Error: Invalid 'set' command format or error setting property: {str(e)}\n"
-
-
-# --- Function to handle chat interaction ---
-def run_chat(message, history):
-    global terminal_history
-    if message.startswith("!"):
-        command = message[1:]
-        terminal_history = run_terminal_command(command, history)
-        return history, terminal_history
-    else:
-        # ... (Your regular chat response generation)
-        return history, terminal_history
-
-
-# --- Code Generation ---
-def generate_python_code(app_name):
-    code = f"""
-import gradio as gr
-
-# Define your Gradio components here
-with gr.Blocks() as {app_name}:
-"""
+component_id = int(set_parts[0])  # Use component ID
+    property_name, property_value = set_parts[1].split("=", 1)
+
+    # Find component by ID
+    component_found = False
     for component in app_state["components"]:
-        code += "    " + Component(**component).render() + "\n"
-
-    code += f"""
-{app_name}.launch()
-"""
-    return code
-
-
-# --- Save/Load App State ---
-def save_app_state(filename="app_state.json"):
-    with open(filename, "w") as f:
-        json.dump(app_state, f)
-
-
-def load_app_state(filename="app_state.json"):
-    global app_state
-    try:
-        with open(filename, "r") as f:
-            app_state = json.load(f)
-    except FileNotFoundError:
-        print("App state file not found. Starting with a blank slate.")
-
-
-# --- Hugging Face Deployment ---
-def deploy_to_huggingface(app_name):
-    # Generate Python code
-    code = generate_python_code(app_name)
-
-    # Create requirements.txt
-    with open("requirements.txt", "w") as f:
-        f.write("gradio==3.32.0\n")
-
-    # Create the app.py file
-    with open("app.py", "w") as f:
-        f.write(code)
-
-    # Execute the deployment command
-    try:
-        subprocess.run(
-            [
-                "huggingface-cli",
-                "repo",
-                "create",
-                "--type",
-                "space",
-                "--space_sdk",
-                "gradio",
-                app_name,
-            ],
-            check=True,
-        )
-        subprocess.run(
-            ["git", "init"], cwd=f"./{app_name}", check=True
-        )
-        subprocess.run(
-            ["git", "add", "."], cwd=f"./{app_name}", check=True
-        )
-        subprocess.run(
-            ['git', 'commit', '-m', '"Initial commit"'], cwd=f"./{app_name}", check=True
-        )
-        subprocess.run(
-            ["git", "push", "https://huggingface.co/spaces/" + app_name, "main"], cwd=f"./{app_name}", check=True
-        )
+        if component["id"] == component_id:
+            if property_name in component["properties"]:
+                component["properties"][
+                    property_name.strip()
+                ] = property_value.strip()
+                component_found = True
+                return (
+                    update_app_canvas(),
+                    f"System: Property '{property_name}' set to '{property_value}' for component {component_id}\n",
+                )
+            else:
+                return (
+                    None,
+                    f"Error: Property '{property_name}' not found in component {component_id}\n",
+                )
+    if not component_found:
         return (
-            f"Successfully deployed to Hugging Face Spaces: https://huggingface.co/spaces/{app_name}"
-        )
-    except Exception as e:
-        return f"Error deploying to Hugging Face Spaces: {e}"
-
-
-# --- Gradio Interface ---
-with gr.Blocks() as iface:
-    with gr.Row():
-        # --- Chat Interface ---
-        chat_history = gr.Chatbot(label="Chat with Agent")
-        chat_input = gr.Textbox(label="Your Message")
-        chat_button = gr.Button("Send")
-
-        chat_button.click(
-            run_chat,
-            inputs=[chat_input, chat_history],
-            outputs=[chat_history, terminal_output],
+            None,
+            f"Error: Component with ID {component_id} not found.\n",
         )
 
-    with gr.Row():
-        # --- App Builder Section ---
-        app_canvas = gr.HTML(
-            "<div>App Canvas Preview:</div>", label="App Canvas"
-        )
-        with gr.Column():
-            component_list = gr.Dropdown(
-                choices=list(components_registry.keys()), label="Components"
-            )
-            add_button = gr.Button("Add Component")
-
-            add_button.click(
-                add_component,
-                inputs=component_list,
-                outputs=[app_canvas, terminal_output],
-            )
-
-    with gr.Row():
-        # --- Terminal ---
-        terminal_output = gr.Textbox(
-            lines=8, label="Terminal", value=terminal_history
-        )
-        terminal_input = gr.Textbox(label="Enter Command")
-        terminal_button = gr.Button("Run")
+except Exception as e:
+    return None, f"Error: Invalid 'set' command format or error setting property: {str(e)}\n"
+--- Function to handle chat interaction ---
+def run_chat(message, history): global terminal_history if message.startswith("!"): command = message[1:] terminal_history = run_terminal_command(command, history) return history, terminal_history else: # ... (Your regular chat response generation) return history, terminal_history
 
-        terminal_button.click(
-            run_terminal_command,
-            inputs=[terminal_input, terminal_output],
-            outputs=terminal_output,
-        )
+--- Code Generation ---
+def generate_python_code(app_name): code = f""" import gradio as gr
 
-    with gr.Row():
-        # --- Code Generation ---
-        code_output = gr.Code(
-            generate_python_code("app_name"),
-            language="python",
-            label="Generated Code",
-        )
-        app_name_input = gr.Textbox(label="App Name")
-        generate_code_button = gr.Button("Generate Code")
-        generate_code_button.click(
-            generate_python_code,
-            inputs=[app_name_input],
-            outputs=code_output,
+Define your Gradio components here
+with gr.Blocks() as {app_name}: """ for component in app_state["components"]: code += " " + Component(**component).render() + "\n"
+
+code += f"""
+{app_name}.launch() """ return code
+
+--- Save/Load App State ---
+def save_app_state(filename="app_state.json"): with open(filename, "w") as f: json.dump(app_state, f)
+
+def load_app_state(filename="app_state.json"): global app_state try: with open(filename, "r") as f: app_state = json.load(f) except FileNotFoundError: print("App state file not found. Starting with a blank slate.")
+
+--- Hugging Face Deployment --- def deploy_to_huggingface(app_name): # Generate Python code code = generate_python_code(app_name)
+
+# Create requirements.txt
+with open("requirements.txt", "w") as f:
+    f.write("gradio==3.32.0\n")
+
+# Create the app.py file
+with open("app.py", "w") as f:
+    f.write(code)
+
+# Execute the deployment command
+try:
+    subprocess.run(
+        [
+            "huggingface-cli",
+            "repo",
+            "create",
+            "--type",
+            "space",
+            "--space_sdk",
+            "gradio",
+            app_name,
+        ],
+        check=True,
+    )
+    subprocess.run(
+        ["git", "init"], cwd=f"./{app_name}", check=True
+    )
+    subprocess.run(
+        ["git", "add", "."], cwd=f"./{app_name}", check=True
+    )
+    subprocess.run(
+        ['git', 'commit', '-m', '"Initial commit"'], cwd=f"./{app_name}", check=True
+    )
+    subprocess.run(
+        ["git", "push", "https://huggingface.co/spaces/" + app_name, "main"], cwd=f"./{app_name}", check=True
+    )
+    return (
+        f"Successfully deployed to Hugging Face Spaces: https://huggingface.co/spaces/{app_name}"
+    )
+except Exception as e:
+    return f"Error deploying to Hugging Face Spaces: {e}"
+--- Gradio Interface ---
+with gr.Blocks() as iface: with gr.Row(): # --- Chat Interface --- chat_history = gr.Chatbot(label="Chat with Agent") chat_input = gr.Textbox(label="Your Message") chat_button = gr.Button("Send")
+
+chat_button.click(
+        run_chat,
+        inputs=[chat_input, chat_history],
+        outputs=[chat_history, terminal_output],
+    )
+
+with gr.Row():
+    # --- App Builder Section ---
+    app_canvas = gr.HTML(
+        "<div>App Canvas Preview:</div>", label="App Canvas"
+    )
+    with gr.Column():
+        component_list = gr.Dropdown(
+            choices=list(components_registry.keys()), label="Components"
         )
+        add_button = gr.Button("Add Component")
 
-    with gr.Row():
-        # --- Save/Load Buttons ---
-        save_button = gr.Button("Save App State")
-        load_button = gr.Button("Load App State")
-
-        save_button.click(save_app_state)
-        load_button.click(load_app_state)
-
-    with gr.Row():
-        # --- Deploy Button ---
-        deploy_button = gr.Button("Deploy to Hugging Face")
-        deploy_output = gr.Textbox(label="Deployment Output")
-        deploy_button.click(
-            deploy_to_huggingface,
-            inputs=[app_name_input],
-            outputs=[deploy_output],
+        add_button.click(
+            add_component,
+            inputs=component_list,
+            outputs=[app_canvas, terminal_output],
         )
+
+with gr.Row():
+    # --- Terminal ---
+    terminal_output = gr.Textbox(
+        lines=8, label="Terminal", value=terminal_history
+    )
+    terminal_input = gr.Textbox(label="Enter Command")
+    terminal_button = gr.Button("Run")
+
+    terminal_button.click(
+        run_terminal_command,
+        inputs=[terminal_input, terminal_output],
+        outputs=terminal_output,
+    )
+
+with gr.Row():
+    # --- Code Generation ---
+    code_output = gr.Code(
+        generate_python_code("app_name"),
+        language="python",
+        label="Generated Code",
+    )
+    app_name_input = gr.Textbox(label="App Name")
+    generate_code_button = gr.Button("Generate Code")
+    generate_code_button.click(
+        generate_python_code,
+        inputs=[app_name_input],
+        outputs=code_output,
+    )
+
+with gr.Row():
+    # --- Save/Load Buttons ---
+    save_button = gr.Button("Save App State")
+    load_button = gr.Button("Load App State")
+
+    save_button.click(save_app_state)
+    load_button.click(load_app_state)
+
+with gr.Row():
+    # --- Deploy Button ---
+    deploy_button = gr.Button("Deploy to Hugging Face")
+    deploy_output = gr.Textbox(label="Deployment Output")
+    deploy_button.click(
+        deploy_to_huggingface,
+        inputs=[app_name_input],
+        outputs=[deploy_output],
+    )
 iface.launch()