app.py

import os
import uuid
import asyncio.base_events as base_events
import gradio as gr
from PIL import Image

from nivra_agent import nivra_chat, nivra_vision, log_call


def _patch_asyncio_event_loop_del():
    """
    Suppress known event loop cleanup crashes seen on some HF Space runtimes.
    """
    original_del = getattr(base_events.BaseEventLoop, "__del__", None)
    if original_del is None:
        return

    def patched_del(self):
        try:
            original_del(self)
        except ValueError as exc:
            if "Invalid file descriptor" not in str(exc):
                raise

    base_events.BaseEventLoop.__del__ = patched_del


_patch_asyncio_event_loop_del()

# ==================================================
# Constants
# ==================================================

UPLOAD_DIR = "/tmp/uploads"
os.makedirs(UPLOAD_DIR, exist_ok=True)

SPACE_HOST = os.environ.get(
    "SPACE_HOST",
    "https://datdevsteve-nivra-ai-agent.hf.space"
)

# ==================================================
# CHAT ENDPOINT
# ==================================================

def chat_fn(message, history):
    history = history or []
    history.append({"role": "user", "content": message})

    response = nivra_chat(message, history)

    history.append({"role": "assistant", "content": response})

    # 🔥 LOG CHAT CALL
    log_call(
        input_type="TEXT",
        input_value=message,
        output_value=response
    )

    return history, ""

# ==================================================
# 🆕 VISION ENDPOINT (URL-BASED)
# ==================================================

def vision_fn(image_url: str, hint_text: str):
    response = nivra_vision(image_url, hint_text)

    # 🔥 LOG IMAGE CALL AT API ENTRY LEVEL
    log_call(
        input_type="IMAGE",
        input_value=image_url,
        output_value=response
    )

    return response

# ==================================================
# UI + API
# ==================================================

with gr.Blocks(title="🩺 Nivra AI Agent") as demo:
    gr.Markdown(
        "# 🩺 Nivra AI Agent\n"
        "_AI-powered healthcare assistant for preliminary guidance._"
    )

    # -------------------------------
    # Chat UI
    # -------------------------------
    chatbot = gr.Chatbot(show_label=False, type="messages") # type: ignore
    txt = gr.Textbox(
        placeholder="Describe your symptoms (e.g. fever, headache, rash)..."
    )
    send = gr.Button("Send")

    send.click(chat_fn, inputs=[txt, chatbot], outputs=[chatbot, txt])
    txt.submit(chat_fn, inputs=[txt, chatbot], outputs=[chatbot, txt])

    # -------------------------------
    # 🔒 Hidden Vision API (Flutter)
    # -------------------------------
    gr.Button(visible=False).click(
        vision_fn,
        inputs=[
            gr.Textbox(label="image_url"),
            gr.Textbox(label="hint_text"),
        ],
        outputs=[gr.Textbox()],
        api_name="vision_fn",
    )

# ==================================================
# Launch (HF-safe)
# ==================================================

launch_kwargs = {
    "server_name": "0.0.0.0",
    "ssr_mode": False,
    "show_error": True,
}

configured_port = os.environ.get("GRADIO_SERVER_PORT") or os.environ.get("PORT")
if configured_port:
    launch_kwargs["server_port"] = int(configured_port)

demo.launch(**launch_kwargs)