Update app.py

app.py

@@ -20,82 +20,37 @@ openai.api_key = os.getenv('OPENAI_API_KEY')
 # Below is the new deadline calculator tool
 
 @tool
-def multi_perspective_brainstorming(query: str) -> str:
-    """A tool that generates and ranks creative ideas by simulating a brainstorming swarm of AI instances.
+def chatgpt_conversation(prompt: str) -> str:
+    """A tool that interacts with the OpenAI API to simulate a conversation with a dynamic prompt.
     
     Args:
-        query: An open-ended query to brainstorm (e.g., 'Generate marketing ideas for a coffee shop').
+        prompt: The message to ChatGPT.
     Returns:
-        A prioritized list of the top ideas synthesized from multiple perspectives.
+        The assistant's response to the prompt.
     """
-    # 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 = "From the following list of ideas, rank the top 5 based on creativity, feasibility, and impact for '" + query + "':\n" + "\n".join(all_ideas)
-    ranked_response = openai.chat.completions.create(
+    response = openai.chat.completions.create(
         model="gpt-4o-mini",
         messages=[
-            {"role": "user", "content": ranking_prompt}
+            {"role": "user", "content": prompt}
         ],
     )
-
-    return ranked_response.choices[0].message.content
+    return response.choices[0].message.content
 
 
 @tool
-def realtime_collaborative_assistant(query: str) -> str:
-    """A tool that simulates a roundtable discussion with AI experts to provide a well-rounded response.
-    
+def get_current_time_in_timezone(timezone: str) -> str:
+    """A tool that fetches the current local time in a specified timezone.
     Args:
-        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.
+        timezone: A string representing a valid timezone (e.g., 'America/New_York').
     """
-    # 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 = "Synthesize the following expert opinions into a concise, well-rounded response to the query '" + query + "':\n" + "\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
+    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)}"
 
 
 final_answer = FinalAnswerTool()
@@ -119,7 +74,7 @@ with open("prompts.yaml", 'r') as stream:
     
 agent = CodeAgent(
     model=model,
-    tools=[final_answer, multi_perspective_brainstorming, realtime_collaborative_assistant], ## add your tools here (don't remove final answer)
+    tools=[final_answer, get_current_time_in_timezone, chatgpt_conversation], ## add your tools here (don't remove final answer)
     max_steps=6,
     verbosity_level=1,
     grammar=None,
@@ -130,5 +85,4 @@ agent = CodeAgent(
 )
 
 
-GradioUI(agent).launch()
-
+GradioUI(agent).launch()