Update app.py

app.py

@@ -20,37 +20,88 @@ openai.api_key = os.getenv('OPENAI_API_KEY')
 # Below is the new deadline calculator tool
 
 @tool
-def chatgpt_conversation(prompt: str) -> str:
-    """A tool that interacts with the OpenAI API to simulate a conversation with a dynamic prompt.
+def multi_perspective_brainstorming(query: str) -> str:
+    """A tool that generates and ranks creative ideas by simulating a brainstorming swarm of AI instances.
     
     Args:
-        prompt: The message to ChatGPT.
+        query: An open-ended query to brainstorm (e.g., 'Generate marketing ideas for a coffee shop').
     Returns:
-        The assistant's response to the prompt.
+        A prioritized list of the top ideas synthesized from multiple perspectives.
     """
-    response = openai.chat.completions.create(
+    # Define brainstorming perspectives
+    perspectives = [
+        {"focus": "Social Media", "prompt": f"Generate 3 creative marketing ideas for a coffee shop focused on social media: {query}"},
+        {"focus": "Loyalty Programs", "prompt": f"Generate 3 creative marketing ideas for a coffee shop focused on loyalty programs: {query}"},
+        {"focus": "Sustainability", "prompt": f"Generate 3 creative marketing ideas for a coffee shop focused on sustainability: {query}"},
+    ]
+
+    # Collect ideas from each perspective
+    all_ideas = []
+    for perspective in perspectives:
+        response = openai.chat.completions.create(
+            model="gpt-4o-mini",
+            messages=[
+                {"role": "user", "content": perspective["prompt"]}
+            ],
+        )
+        ideas = response.choices[0].message.content.split("\n")  # Assume ideas are newline-separated
+        all_ideas.extend([f"{perspective['focus']}: {idea.strip()}" for idea in ideas if idea.strip()])
+
+    # Rank the ideas by simulating a consensus
+    ranking_prompt = (
+        f"From the following list of ideas, rank the top 5 based on creativity, feasibility, and impact for '{query}':\n"
+        f"{'\n'.join(all_ideas)}"
+    )
+    ranked_response = openai.chat.completions.create(
         model="gpt-4o-mini",
         messages=[
-            {"role": "user", "content": prompt}
+            {"role": "user", "content": ranking_prompt}
         ],
     )
-    return response.choices[0].message.content
+
+    return ranked_response.choices[0].message.content
 
 
 @tool
-def get_current_time_in_timezone(timezone: str) -> str:
-    """A tool that fetches the current local time in a specified timezone.
+def realtime_collaborative_assistant(query: str) -> str:
+    """A tool that simulates a roundtable discussion with AI experts to provide a well-rounded response.
+    
     Args:
-        timezone: A string representing a valid timezone (e.g., 'America/New_York').
+        query: The user’s question or topic to discuss (e.g., 'How can I improve my website’s UX?').
+    Returns:
+        A synthesized response combining insights from multiple AI perspectives.
     """
-    try:
-        # Create timezone object
-        tz = pytz.timezone(timezone)
-        # Get current time in that timezone
-        local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S")
-        return f"The current local time in {timezone} is: {local_time}"
-    except Exception as e:
-        return f"Error fetching time for timezone '{timezone}': {str(e)}"
+    # Define expert personas with distinct roles
+    experts = [
+        {"role": "UX Designer", "prompt": f"As a UX designer, provide practical suggestions for: {query}"},
+        {"role": "Marketing Strategist", "prompt": f"As a marketing strategist, suggest how to approach: {query}"},
+        {"role": "Tech Analyst", "prompt": f"As a tech analyst, offer technical insights on: {query}"},
+    ]
+
+    # Collect responses from each AI expert
+    expert_opinions = []
+    for expert in experts:
+        response = openai.chat.completions.create(
+            model="gpt-4o-mini",
+            messages=[
+                {"role": "user", "content": expert["prompt"]}
+            ],
+        )
+        expert_opinions.append(f"{expert['role']}: {response.choices[0].message.content}")
+
+    # Synthesize the responses into a cohesive answer
+    synthesis_prompt = (
+        f"Synthesize the following expert opinions into a concise, well-rounded response to the query '{query}':\n"
+        f"{'\n'.join(expert_opinions)}"
+    )
+    final_response = openai.chat.completions.create(
+        model="gpt-4o-mini",
+        messages=[
+            {"role": "user", "content": synthesis_prompt}
+        ],
+    )
+
+    return final_response.choices[0].message.content
 
 
 final_answer = FinalAnswerTool()
@@ -74,7 +125,7 @@ with open("prompts.yaml", 'r') as stream:
     
 agent = CodeAgent(
     model=model,
-    tools=[final_answer, get_current_time_in_timezone, chatgpt_conversation], ## add your tools here (don't remove final answer)
+    tools=[final_answer, multi_perspective_brainstorming, realtime_collaborative_assistant], ## add your tools here (don't remove final answer)
     max_steps=6,
     verbosity_level=1,
     grammar=None,