Spaces:
Sleeping
Sleeping
Redesign UI with radio buttons for category
Browse files- gradio_ui.py +71 -143
gradio_ui.py
CHANGED
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"""
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gradio_ui.py — Interactive Gradio web interface for the Support Ticket Environment.
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Allows human exploration and debugging without writing code.
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Launched automatically when ENABLE_WEB_INTERFACE=true or run directly.
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Usage:
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python support_ticket_env/gradio_ui.py
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"""
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import json
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import sys
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import os
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@@ -20,71 +10,29 @@ sys.path.insert(0, ROOT)
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try:
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import gradio as gr
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except ImportError:
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print("gradio not installed.
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sys.exit(1)
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from support_ticket_env.server.support_environment import SupportTicketEnvironment
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from support_ticket_env.models import SupportAction
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# ─── shared env instance ────────────────────────────────────────
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_env = SupportTicketEnvironment()
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_history: list[dict] = []
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_current_obs = None
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def _format_history() -> str:
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if not _history:
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return "_No actions yet._"
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lines = []
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for i, h in enumerate(_history, 1):
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reward_str = f"{h['reward']:+.3f}" if h["reward"] is not None else "—"
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lines.append(
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f"**Step {i}** | `{h['action']}` → reward `{reward_str}`\n"
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f"> {h['feedback']}"
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)
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return "\n\n".join(lines)
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def _obs_to_display(obs) -> tuple[str, str, str]:
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"""Return (ticket_box, status_box, score_box)."""
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ticket = f"**[{obs.ticket_id}]** {obs.ticket_text}"
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status = (
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f"Task **{obs.task_id}** | Step **{obs.step_count}** | "
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f"Category: `{obs.current_category or 'unknown'}` | "
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f"Resolved: {'✅' if obs.resolved else '⬜'}"
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)
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score = f"Last step score: **{obs.score:.3f}** | reward: **{obs.reward or 0.0:+.3f}**"
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return ticket, status, score
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# ─── UI callbacks ────────────────────────────────────────────────
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def do_reset(task_id: int, seed: int):
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global _history, _current_obs
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_history = []
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obs = _env.reset(task_id=task_id, seed=seed)
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_current_obs = obs
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_format_history(),
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gr.update(interactive=True),
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obs.feedback,
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gr.update(value=False), # done flag
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)
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def do_step(action_type
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global _current_obs
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if _current_obs is None:
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return
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"⚠️ Please reset the environment first.",
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"", "", _format_history(), "", gr.update(value=False),
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)
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# Build action
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kwargs = {"action_type": action_type}
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if action_type == "classify" and category:
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kwargs["category"] = category
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@@ -92,120 +40,100 @@ def do_step(action_type: str, category: str, reply_text: str, reason: str):
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kwargs["reply_text"] = reply_text
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if reason:
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kwargs["reason"] = reason
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try:
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action = SupportAction(**kwargs)
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except Exception as e:
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return
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_current_obs.ticket_text,
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f"❌ Invalid action: {e}", "",
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_format_history(), "", gr.update(value=False),
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)
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obs = _env.step(action)
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_current_obs = obs
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_history.append({
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"action": f"{action_type}" + (f"/{category}" if category and action_type == "classify" else ""),
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"reward": obs.reward,
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"feedback": obs.feedback,
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})
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ticket, status, score = _obs_to_display(obs)
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done_msg = "🏁 Episode finished!" if obs.done else ""
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return (
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ticket, status, score,
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_format_history(),
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obs.feedback,
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gr.update(value=obs.done),
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)
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def do_state():
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state = _env.state
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return json.dumps({
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"episode_id": state.episode_id,
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"step_count": state.step_count,
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"task_id": state.task_id,
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"ticket_id": state.ticket_id,
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"correct_category": state.correct_category,
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"correct_action": state.correct_action,
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"classified": state.classified,
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"resolved": state.resolved,
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"total_reward": state.total_reward,
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"tickets_resolved": state.tickets_resolved,
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"tickets_total": state.tickets_total,
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}, indent=2)
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#
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DESCRIPTION = """
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# 🎫 Customer Support Ticket Resolution Environment
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An **OpenEnv** environment for training AI agents to handle customer support tickets.
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**Tasks:** 1 = Classify · 2 = Classify + Action · 3 = Full Queue Resolution
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"""
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with gr.Blocks(title="Support Ticket Env") as demo:
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gr.Markdown(DESCRIPTION)
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with gr.Row():
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# ── Left panel: controls ────────────────────────────────
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with gr.Column(scale=1):
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gr.Markdown("##
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)
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label="Category (for classify)",
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value=None,
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)
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reply_box
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reason_box = gr.Textbox(label="Reason (optional)")
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step_btn
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state_btn
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# ── Right panel: observation ────────────────────────────
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with gr.Column(scale=2):
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gr.Markdown("##
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gr.Markdown("##
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# ── wire up ─────────────────────────────────────────────────
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reset_btn.click(
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do_reset,
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inputs=[
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outputs=[
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history_display, step_btn, feedback_box, done_checkbox],
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)
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step_btn.click(
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do_step,
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inputs=[
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outputs=[
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history_display, feedback_box, done_checkbox],
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)
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state_btn.click(
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do_state,
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)
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if __name__ == "__main__":
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demo.launch(server_name="0.0.0.0", server_port=7861, share=False)
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import json
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import sys
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import os
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try:
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import gradio as gr
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except ImportError:
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print("gradio not installed.")
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sys.exit(1)
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from support_ticket_env.server.support_environment import SupportTicketEnvironment
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from support_ticket_env.models import SupportAction
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_env = SupportTicketEnvironment()
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_current_obs = None
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_history = []
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def do_reset(task_id, seed):
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global _current_obs, _history
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_history = []
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obs = _env.reset(task_id=int(task_id), seed=int(seed))
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_current_obs = obs
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state = _env.state
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info = f"TICKET: {obs.ticket_text}\n\nFeedback: {obs.feedback}"
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return info, "Episode started! Now classify the ticket.", ""
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def do_step(action_type, category, reply_text, reason):
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global _current_obs
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if _current_obs is None:
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return "Please click Reset first!", "", ""
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kwargs = {"action_type": action_type}
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if action_type == "classify" and category:
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kwargs["category"] = category
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kwargs["reply_text"] = reply_text
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if reason:
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kwargs["reason"] = reason
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try:
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action = SupportAction(**kwargs)
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obs = _env.step(action)
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_current_obs = obs
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_history.append(f"Step: {action_type}/{category or ''} -> Reward: {obs.reward:.2f}")
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result = f"Feedback: {obs.feedback}\nReward: {obs.reward:.2f}\nDone: {obs.done}"
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history = "\n".join(_history)
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ticket = f"TICKET: {obs.ticket_text}"
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return ticket, result, history
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except Exception as e:
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return _current_obs.ticket_text, f"Error: {e}", ""
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def do_state():
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state = _env.state
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return json.dumps({
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"task_id": state.task_id,
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"ticket_id": state.ticket_id,
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"correct_category": state.correct_category,
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"correct_action": state.correct_action,
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"classified": state.classified,
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"resolved": state.resolved,
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"step_count": state.step_count,
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"total_reward": state.total_reward,
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}, indent=2)
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with gr.Blocks(title="Support Ticket Environment") as demo:
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gr.Markdown("# Customer Support Ticket Resolution Environment")
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gr.Markdown("Train AI agents to handle customer support tickets.")
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with gr.Row():
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with gr.Column(scale=1):
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gr.Markdown("## Setup")
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task_radio = gr.Radio(
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choices=[1, 2, 3],
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value=1,
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label="Task (1=Easy, 2=Medium, 3=Hard)"
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)
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seed_box = gr.Number(value=42, label="Seed")
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reset_btn = gr.Button("RESET", variant="primary")
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gr.Markdown("## Action")
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action_radio = gr.Radio(
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choices=["classify", "reply", "escalate", "close"],
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value="classify",
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label="Action Type"
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)
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category_radio = gr.Radio(
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choices=["billing", "technical", "account", "general", "refund"],
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value=None,
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label="Category (select for classify)"
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)
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reply_box = gr.Textbox(label="Reply Text (for reply action)", lines=2)
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reason_box = gr.Textbox(label="Reason (optional)")
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step_btn = gr.Button("STEP", variant="secondary")
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state_btn = gr.Button("GET STATE")
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with gr.Column(scale=2):
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gr.Markdown("## Current Ticket")
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ticket_box = gr.Textbox(
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label="Ticket",
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value="Click RESET to start",
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lines=3,
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interactive=False
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)
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gr.Markdown("## Result")
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result_box = gr.Textbox(
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label="Last Step Result",
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lines=4,
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interactive=False
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)
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gr.Markdown("## History")
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history_box = gr.Textbox(
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label="Action History",
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lines=5,
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interactive=False
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)
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gr.Markdown("## State")
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state_box = gr.Code(language="json", label="Environment State")
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reset_btn.click(
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do_reset,
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inputs=[task_radio, seed_box],
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outputs=[ticket_box, result_box, history_box]
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)
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step_btn.click(
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do_step,
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inputs=[action_radio, category_radio, reply_box, reason_box],
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outputs=[ticket_box, result_box, history_box]
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)
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state_btn.click(
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do_state,
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inputs=[],
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outputs=[state_box]
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)
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if __name__ == "__main__":
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demo.launch(server_name="0.0.0.0", server_port=7861, share=False)
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