Merge pull request #32 from GYFX35/feat/financial-advisor-integration-10343148600686743474

Integrate Financial Advisor Role

Author: GYFX35

app.py

@@ -432,12 +432,6 @@ def get_data():
 """
     return response_message.strip()
 
-def get_financial_advice(prompt):
-    advice = _("Based on your query, here is some general financial advice: diversify your investments and create a budget.")
-    # In a real application, this would involve more sophisticated logic,
-    # possibly integrating with financial data APIs or a fine-tuned LLM.
-    return advice
-
 def generate_art_criticism(prompt):
     criticism = _("This is a placeholder for an art criticism based on your prompt: %(prompt)s", prompt=prompt)
     # In a real application, this would connect to a generative AI model
@@ -749,7 +743,7 @@ def financial_advice_endpoint():
     prompt = data.get('prompt')
     if not prompt:
         return jsonify({"error": _("Prompt is required")}), 400
-    message = get_financial_advice(prompt)
+    message = google_ai.provide_financial_advice(prompt)
     return jsonify({"status": "success", "message": message})
 
 @app.route('/api/v1/art/criticism', methods=['POST'])

google_ai.py

@@ -214,3 +214,29 @@ def analyze_data(prompt: str) -> str:
     except Exception as e:
         print(f"Error analyzing data with Vertex AI: {e}")
         return f"Error: {e}"
+
+
+def provide_financial_advice(prompt: str) -> str:
+    """
+    Provides financial advice for a given issue using Vertex AI.
+    """
+    model = GenerativeModel("gemini-1.5-flash")
+
+    generation_prompt = f"""
+    You are an expert financial advisor. Your task is to provide financial advice based on the following user prompt.
+
+    User Prompt:
+    ---
+    {prompt}
+    ---
+
+    The advice should be comprehensive and include actionable steps.
+    """
+
+    try:
+        response = model.generate_content(generation_prompt)
+        return response.text.strip()
+
+    except Exception as e:
+        print(f"Error providing financial advice with Vertex AI: {e}")
+        return f"Error: {e}"