less structured and templates buttons

app.py

@@ -4,55 +4,283 @@ from openai import OpenAI
 
 client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
 
-FORMAT_INSTRUCTION = """
-Please format your response exactly as:
+BASIC_PROMPT = """You are a helpful assistant that processes emails."""
+
+STRUCTURED_PROMPT = """You are an email triage agent.
+
+Your job is to read an email and decide how it should be handled.
+
+For each email:
+- Identify the main intent
+- Classify priority as Low, Medium, or High
+- Decide which team should own it
+- Suggest the next action
+- Draft a reply
+
+Format your response clearly and use labels.
+"""
+
+ADVANCED_PROMPT = """You are an enterprise email triage agent.
+
+Your job is to analyze incoming emails and decide how they should be handled.
+
+For each email:
+1. Identify the primary intent
+2. Classify priority as Low, Medium, or High
+3. Assign an owner from: Sales, Support, Finance, HR, Operations, Legal
+4. Determine the next action from: Respond, Escalate, Delegate, Request More Information
+5. Briefly explain your reasoning
+6. Draft a professional reply
+
+Output format:
 
 Intent:
 Priority:
 Owner:
-Action Required:
+Action:
 Reasoning:
 Draft Reply:
+
+Rules:
+- Be concise and practical
+- If the email is ambiguous, say so clearly
+- If there is urgency, reflect that in both priority and action
+- Keep the draft reply professional and appropriate for business use
 """
 
-def run_agent(system_prompt, email):
+SAMPLE_EMAILS = {
+    "Customer Complaint": """Subject: Delayed shipment and no updates
+
+We placed our order nearly two weeks ago and still have not received the shipment. We have also not had any meaningful update from your team despite following up twice.
+
+This delay is now affecting our own delivery commitments to customers. Please let us know what is going on and when we can expect resolution.
+
+Regards,
+A frustrated customer""",
+
+    "Sales Inquiry": """Subject: Exploring vendors for regional rollout
+
+Hello,
+
+We are evaluating potential partners for a Southeast Asia rollout later this year. We would like to understand your capabilities, pricing approach, and implementation timeline.
+
+Could someone from your team reach out to discuss next steps?
+
+Best,
+Regional Director""",
+
+    "Internal Finance": """Subject: Q3 budget clarification needed
+
+Hi Finance team,
+
+Can you confirm whether the additional marketing spend for Q3 has been approved? We need clarity before committing to the campaign launch next week.
+
+Thanks,
+Head of Marketing""",
+
+    "HR Issue": """Subject: Concern about manager conduct
+
+Hello,
+
+I would like to report a concern regarding repeated inappropriate comments made by my manager during team meetings. I am uncomfortable raising this directly with them and would appreciate guidance on how this should be handled.
+
+Please keep this confidential.
+
+Thank you.""",
+
+    "Urgent Escalation": """Subject: Production outage affecting client operations
+
+Team,
+
+A major system outage started 30 minutes ago and several enterprise clients are unable to access critical workflows. We are already receiving escalation calls.
+
+We need immediate support and clear ownership on incident response.
+
+Please advise urgently.""",
+}
+
+
+def format_output(raw_text: str) -> str:
+    """
+    Light formatting only.
+    We do NOT enforce a schema.
+    We simply make common label-based outputs easier to read.
+    """
+    if not raw_text:
+        return "No output received."
+
+    known_labels = [
+        "Intent:",
+        "Priority:",
+        "Owner:",
+        "Action:",
+        "Action Required:",
+        "Reasoning:",
+        "Draft Reply:",
+    ]
+
+    lines = raw_text.splitlines()
+    formatted_lines = []
+
+    for line in lines:
+        stripped = line.strip()
+        matched_label = next((label for label in known_labels if stripped.startswith(label)), None)
+
+        if matched_label:
+            value = stripped[len(matched_label):].strip()
+            formatted_lines.append(f"### {matched_label[:-1]}")
+            if value:
+                formatted_lines.append(value)
+            else:
+                formatted_lines.append("")
+            formatted_lines.append("")
+        else:
+            formatted_lines.append(line)
+
+    return "\n".join(formatted_lines).strip()
+
+
+def run_agent(system_prompt, email, show_raw_output):
+    if not system_prompt or not system_prompt.strip():
+        return "Please enter a system prompt.", ""
+
+    if not email or not email.strip():
+        return "Please enter an email to analyze.", ""
+
     try:
         response = client.chat.completions.create(
             model="gpt-4o-mini",
             messages=[
                 {"role": "system", "content": system_prompt},
-                {"role": "user", "content": email + "\n\n" + FORMAT_INSTRUCTION},
+                {"role": "user", "content": email},
             ],
             temperature=0.4,
         )
-        return response.choices[0].message.content
+
+        raw_output = response.choices[0].message.content or ""
+        formatted_output = format_output(raw_output)
+
+        if show_raw_output:
+            return formatted_output, raw_output
+        return formatted_output, ""
 
     except Exception as e:
-        return f"Error: {str(e)}"
+        error_message = f"Error: {str(e)}"
+        return error_message, error_message
+
+
+with gr.Blocks(title="Executive Agent Lab") as demo:
+    gr.Markdown("# Executive Agent Lab")
+    gr.Markdown(
+        "Build your own email triage agent by writing the system prompt, then test it on sample or custom emails."
+    )
 
-with gr.Blocks() as demo:
     with gr.Row():
-        with gr.Column():
+        with gr.Column(scale=1):
             gr.Markdown("## Agent Builder")
+            gr.Markdown(
+                "Define the agent's role, rules, decision logic, and output format."
+            )
+
+            agent_name = gr.Textbox(
+                label="Agent Name (optional)",
+                placeholder="Email Triage Agent",
+            )
+
             system_prompt = gr.Textbox(
                 label="System Prompt",
-                lines=15,
-                value="You are an assistant that processes emails."
+                lines=18,
+                value=BASIC_PROMPT,
+                placeholder="Write the instructions for your agent here..."
             )
 
-        with gr.Column():
-            gr.Markdown("## Email Input")
+            gr.Markdown("### Starter Prompts")
+            with gr.Row():
+                load_basic_btn = gr.Button("Load Basic")
+                load_structured_btn = gr.Button("Load Structured")
+                load_advanced_btn = gr.Button("Load Advanced")
+
+            with gr.Accordion("What makes a good agent prompt?", open=False):
+                gr.Markdown(
+                    """- role  
+- task  
+- decision criteria  
+- routing rules  
+- output format  
+- tone  
+- handling ambiguity"""
+                )
+
+        with gr.Column(scale=1):
+            gr.Markdown("## Test Input")
+            gr.Markdown("Load a sample email or paste your own.")
+
+            gr.Markdown("### Sample Emails")
+            with gr.Row():
+                btn_customer = gr.Button("Customer Complaint")
+                btn_sales = gr.Button("Sales Inquiry")
+            with gr.Row():
+                btn_finance = gr.Button("Internal Finance")
+                btn_hr = gr.Button("HR Issue")
+            with gr.Row():
+                btn_urgent = gr.Button("Urgent Escalation")
+
             email = gr.Textbox(
-                label="Email",
-                lines=15,
-                value="We have not received our shipment and this is causing major delays. Please respond urgently."
+                label="Email Content",
+                lines=20,
+                value=SAMPLE_EMAILS["Customer Complaint"],
+                placeholder="Paste or type an email here..."
             )
 
-        with gr.Column():
-            gr.Markdown("## Output")
-            output = gr.Markdown()
+            run_btn = gr.Button("Run Agent", variant="primary")
+
+        with gr.Column(scale=1):
+            gr.Markdown("## Agent Output")
+            gr.Markdown(
+                "The app lightly formats common label-based outputs, but your prompt determines the structure."
+            )
+
+            formatted_output = gr.Markdown(
+                value="Run the agent to see results here."
+            )
+
+            show_raw_output = gr.Checkbox(
+                label="Show raw output",
+                value=False
+            )
+
+            raw_output = gr.Textbox(
+                label="Raw Output",
+                lines=12,
+                visible=True
+            )
+
+    def load_basic():
+        return BASIC_PROMPT
+
+    def load_structured():
+        return STRUCTURED_PROMPT
+
+    def load_advanced():
+        return ADVANCED_PROMPT
+
+    def load_email(sample_name):
+        return SAMPLE_EMAILS[sample_name]
+
+    load_basic_btn.click(fn=load_basic, outputs=system_prompt)
+    load_structured_btn.click(fn=load_structured, outputs=system_prompt)
+    load_advanced_btn.click(fn=load_advanced, outputs=system_prompt)
+
+    btn_customer.click(fn=lambda: load_email("Customer Complaint"), outputs=email)
+    btn_sales.click(fn=lambda: load_email("Sales Inquiry"), outputs=email)
+    btn_finance.click(fn=lambda: load_email("Internal Finance"), outputs=email)
+    btn_hr.click(fn=lambda: load_email("HR Issue"), outputs=email)
+    btn_urgent.click(fn=lambda: load_email("Urgent Escalation"), outputs=email)
 
-    run_btn = gr.Button("Run Agent")
-    run_btn.click(run_agent, inputs=[system_prompt, email], outputs=output)
+    run_btn.click(
+        fn=run_agent,
+        inputs=[system_prompt, email, show_raw_output],
+        outputs=[formatted_output, raw_output],
+    )
 
-demo.launch()
+demo.launch(server_name="0.0.0.0", server_port=7860)