changes 2

pyproject.toml

@@ -28,4 +28,4 @@ dependencies = [
 include = ["openenv*"]
 
 [project.scripts]
-server = "server.app:start"
+server = "server.app:main"

server/app.py

@@ -44,6 +44,97 @@ def step_env(action_req: ActionRequest):
 
 # --- Gradio UI ---
 
+def ui_reset(task_choice):
+    mapping = {"Easy (Classification)": "easy", "Medium (Assignment)": "medium", "Hard (Resolution)": "hard"}
+    task_name = mapping.get(task_choice, "easy")
+    res = env.reset(task_name)
+    return f"Environment reset to {task_name}.", res.observation.model_dump_json(indent=2)
+
+def ui_step(a_type, t_name, resp_text):
+    if env.done:
+        return "Episode is already done! Please reset.", env.state().model_dump_json(indent=2), ""
+
+    try:
+        act = Action(action_type=a_type, team=t_name if t_name else None, response=resp_text if resp_text else None)
+        res = env.step(act)
+        feedback = f"Reward: {res.reward}\nDone: {res.done}\nInfo: {res.info}"
+        return feedback, res.observation.model_dump_json(indent=2), "-> " + "\n-> ".join(env.history)
+    except Exception as e:
+        obs_json = env.get_current_observation().model_dump_json(indent=2) if env.current_scenario else "{}"
+        return f"Error: {e}", obs_json, ""
+
+with gr.Blocks(title="OpenEnv Support Agent") as demo:
+    gr.Markdown("# 🎧 OpenEnv-Based Autonomous Customer Support Agent")
+    gr.Markdown("This interface lets you manually step the environment or view the state. For agent evaluation, use `inference.py`.")
+    
+    with gr.Row():
+        task_dropdown = gr.Dropdown(
+            choices=["Easy (Classification)", "Medium (Assignment)", "Hard (Resolution)"], 
+            value="Easy (Classification)", label="Select Task Level"
+        )
+        reset_btn = gr.Button("Reset Environment")
+        
+    with gr.Row():
+        with gr.Column():
+            gr.Markdown("### Observation (Current State)")
+            obs_box = gr.Code(language="json", label="Observation JSON")
+            history_box = gr.Textbox(label="Action History", lines=5, interactive=False)
+            
+        with gr.Column():
+            gr.Markdown("### Take Action")
+            act_type = gr.Dropdown(choices=["classify", "assign", "respond", "refund", "escalate"], value="classify", label="Action Type")
+            act_team = gr.Textbox(label="Team (optional)")
+            act_resp = gr.Textbox(label="Response text (optional)")
+            step_btn = gr.Button("Step Environment", variant="primary")
+            
+            feedback_box = gr.Textbox(label="Reward / Step Info", interactive=False)
+
+import os
+import uvicorn
+import gradio as gr
+from fastapi import FastAPI, BackgroundTasks
+from pydantic import BaseModel
+from dotenv import load_dotenv
+
+load_dotenv()
+
+from openenv.env import SupportEnv
+from openenv.models import Action
+
+app = FastAPI(title="OpenEnv Support Agent API")
+
+# Global environment instance for the UI/API
+# In a real deployed multiuser scenario, this would be session-based.
+env = SupportEnv(task_name="easy")
+env.reset()
+
+# --- FastAPI Routes ---
+
+class ActionRequest(BaseModel):
+    action_type: str
+    team: str = None
+    response: str = None
+
+@app.get("/api/state")
+@app.get("/state")
+def get_state():
+    return env.state()
+
+@app.post("/api/reset")
+@app.post("/reset")
+def reset_env(task_name: str = "easy"):
+    res = env.reset(task_name=task_name)
+    return res
+
+@app.post("/api/step")
+@app.post("/step")
+def step_env(action_req: ActionRequest):
+    act = Action(**action_req.model_dump())
+    res = env.step(act)
+    return res
+
+# --- Gradio UI ---
+
 def ui_reset(task_choice):
     mapping = {"Easy (Classification)": "easy", "Medium (Assignment)": "medium", "Hard (Resolution)": "hard"}
     task_name = mapping.get(task_choice, "easy")
@@ -95,9 +186,9 @@ with gr.Blocks(title="OpenEnv Support Agent") as demo:
 demo.queue()
 app = gr.mount_gradio_app(app, demo, path="/")
 
-def start():
+def main():
     port = int(os.environ.get("PORT", 7860))
     uvicorn.run("server.app:app", host="0.0.0.0", port=port, reload=True)
 
 if __name__ == "__main__":
-    start()
+    main()