Integrate Google Cloud AI services

This commit integrates Google Cloud's Vertex AI services into the application, replacing the placeholder AI functions with calls to the Gemini model.

The following changes were made:
- Added `google-cloud-aiplatform` and `google-auth` to `requirements.txt`.
- Created a `google_ai.py` module to handle all interactions with the Vertex AI API.
- Implemented functions for generating websites, debugging code, and creating social media posts using Vertex AI.
- Updated `app.py` to use the new `google_ai` module.
- Added a `sys.path` modification to `app.py` to ensure the `google_ai` module is found.

**Important Note:** Due to a persistent and difficult-to-diagnose issue in the testing environment, the application could not be fully tested. The application would start successfully but crash upon receiving any web request, without leaving any error logs. As a result, the integration is submitted as-is and should be considered untested. Further debugging in a different environment is recommended.

Author: google-labs-jules[bot]

app.py

@@ -1,4 +1,6 @@
+import sys
 import os
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
 import time
 import requests
 import httpx
@@ -15,6 +17,7 @@
 from facebook_business.api import FacebookAdsApi
 from facebook_business.adobjects.adaccount import AdAccount
 from facebook_business.exceptions import FacebookRequestError
+import google_ai
 
 load_dotenv(dotenv_path=".env")
 
@@ -66,8 +69,24 @@ def __repr__(self):
 db.init_app(app)
 stripe.api_key = os.environ.get("STRIPE_SECRET_KEY")
 
+# --- Meta/Facebook Business SDK Integration ---
+def initialize_meta_sdk():
+    """Initializes the Meta Business SDK."""
+    meta_app_id = os.environ.get('META_APP_ID')
+    meta_app_secret = os.environ.get('META_APP_SECRET')
+    meta_access_token = os.environ.get('META_ACCESS_TOKEN')
+    if all([meta_app_id, meta_app_secret, meta_access_token]):
+        try:
+            FacebookAdsApi.init(app_id=meta_app_id, app_secret=meta_app_secret, access_token=meta_access_token)
+            print("Meta Business SDK initialized successfully.")
+        except Exception as e:
+            print(f"Error initializing Meta Business SDK: {e}")
+    else:
+        print("Meta Business SDK credentials not found in environment variables. Skipping initialization.")
+
 with app.app_context():
     initialize_meta_sdk()
+    google_ai.init_vertexai()
 
 def get_locale():
     if 'language' in session:
@@ -614,7 +633,18 @@ def develop_website_endpoint():
     prompt = data.get('prompt')
     if not prompt:
         return jsonify({"error": _("Prompt is required")}), 400
-    message = generate_website(prompt)
+    html, css = google_ai.generate_website(prompt)
+    message = f"""
+{_("Here is the generated code for your website.")}
+**index.html:**
+```html
+{html.strip()}
+```
+**style.css:**
+```css
+{css.strip()}
+```
+"""
     return jsonify({"status": "success", "message": message})
 
 @app.route('/api/v1/develop/game', methods=['POST'])
@@ -654,7 +684,18 @@ def debug_endpoint():
     prompt = data.get('prompt')
     if not prompt:
         return jsonify({"error": _("Prompt is required")}), 400
-    message = debug_code(prompt)
+
+    # Simple language detection
+    language = 'html'
+    if prompt.strip().startswith('{') or '{' in prompt and '}' in prompt:
+        language = 'css'
+
+    errors = google_ai.debug_code(prompt, language)
+    if not errors:
+        message = _("No obvious issues found in your %(lang)s code.", lang=language)
+    else:
+        message = _("Found potential issues in your %(lang)s code:\n", lang=language) + "\n".join(f"- {error}" for error in errors)
+
     return jsonify({"status": "success", "message": message})
 
 @app.route('/api/v1/market/post', methods=['POST'])
@@ -664,7 +705,7 @@ def market_post_endpoint():
     prompt = data.get('prompt')
     if not prompt:
         return jsonify({"error": _("Prompt is required")}), 400
-    message = generate_social_media_post(prompt)
+    message = google_ai.generate_social_media_post(prompt)
     return jsonify({"status": "success", "message": message})
 
 @app.route('/api/v1/optimize/ads', methods=['POST'])
@@ -855,21 +896,6 @@ def payment_webhook():
     return jsonify(status='success')
 
 
-# --- Meta/Facebook Business SDK Integration ---
-def initialize_meta_sdk():
-    """Initializes the Meta Business SDK."""
-    meta_app_id = os.environ.get('META_APP_ID')
-    meta_app_secret = os.environ.get('META_APP_SECRET')
-    meta_access_token = os.environ.get('META_ACCESS_TOKEN')
-    if all([meta_app_id, meta_app_secret, meta_access_token]):
-        try:
-            FacebookAdsApi.init(app_id=meta_app_id, app_secret=meta_app_secret, access_token=meta_access_token)
-            print("Meta Business SDK initialized successfully.")
-        except Exception as e:
-            print(f"Error initializing Meta Business SDK: {e}")
-    else:
-        print("Meta Business SDK credentials not found in environment variables. Skipping initialization.")
-
 @app.route('/api/v1/meta/campaigns', methods=['GET'])
 @require_api_key
 def get_meta_campaigns():

google_ai.py

@@ -0,0 +1,113 @@
+import os
+import re
+import vertexai
+from vertexai.generative_models import GenerativeModel
+
+def init_vertexai():
+    """Initializes the Vertex AI SDK."""
+    project_id = os.environ.get("GOOGLE_CLOUD_PROJECT")
+    location = os.environ.get("GOOGLE_CLOUD_LOCATION")
+
+    if not all([project_id, location]):
+        print("Google Cloud project ID and location not found in environment variables. Skipping Vertex AI initialization.")
+        return
+
+    vertexai.init(project=project_id, location=location)
+    print("Vertex AI SDK initialized successfully.")
+
+def generate_website(prompt: str) -> tuple[str, str]:
+    """
+    Generates HTML and CSS code from a natural language prompt using Vertex AI.
+    """
+    model = GenerativeModel("gemini-1.5-flash")
+
+    generation_prompt = f"""
+    You are a skilled web developer. Your task is to generate the HTML and CSS for a single-page website based on the following user prompt.
+
+    User Prompt:
+    ---
+    {prompt}
+    ---
+
+    Your response must be in the following format, with no other text or explanations:
+
+    [HTML]
+    <!DOCTYPE html>
+    ...
+    </html>
+    [/HTML]
+
+    [CSS]
+    body {{
+        ...
+    }}
+    [/CSS]
+    """
+
+    try:
+        response = model.generate_content(generation_prompt)
+        text_response = response.text
+
+        html_match = re.search(r'\[HTML\](.*?)\[/HTML\]', text_response, re.DOTALL)
+        css_match = re.search(r'\[CSS\](.*?)\[/CSS\]', text_response, re.DOTALL)
+
+        html_code = html_match.group(1).strip() if html_match else "<!-- Error: Could not generate HTML. -->"
+        css_code = css_match.group(1).strip() if css_match else "/* Error: Could not generate CSS. */"
+
+        return html_code, css_code
+
+    except Exception as e:
+        print(f"Error generating website with Vertex AI: {e}")
+        return f"<!-- Error: {e} -->", f"/* Error: {e} */"
+
+def debug_code(code: str, language: str) -> list[str]:
+    """
+    Analyzes code and finds potential issues using Vertex AI.
+    """
+    model = GenerativeModel("gemini-1.5-flash")
+
+    generation_prompt = f"""
+    You are an expert code reviewer. Your task is to analyze the following {language} code and identify any potential bugs, errors, or style issues.
+
+    Code:
+    ---
+    {code}
+    ---
+
+    Please list the issues you find, one per line. If you find no issues, return an empty response.
+    """
+
+    try:
+        response = model.generate_content(generation_prompt)
+        errors = response.text.strip().split('\n')
+        # Filter out empty strings that may result from the split
+        return [error for error in errors if error]
+
+    except Exception as e:
+        print(f"Error debugging code with Vertex AI: {e}")
+        return [f"Error: {e}"]
+
+def generate_social_media_post(description: str) -> str:
+    """
+    Generates a social media post from a description using Vertex AI.
+    """
+    model = GenerativeModel("gemini-1.5-flash")
+
+    generation_prompt = f"""
+    You are a creative marketing assistant. Your task is to write an engaging social media post based on the following description.
+
+    Description:
+    ---
+    {description}
+    ---
+
+    The post should be short, catchy, and include relevant hashtags.
+    """
+
+    try:
+        response = model.generate_content(generation_prompt)
+        return response.text.strip()
+
+    except Exception as e:
+        print(f"Error generating social media post with Vertex AI: {e}")
+        return f"Error: {e}"

requirements.txt

@@ -10,3 +10,5 @@ anyio
 sniffio
 stripe
 facebook-business
+google-cloud-aiplatform
+google-auth