import gradio as gr
import base64
import httpx
import os
from fastapi.middleware.cors import CORSMiddleware
from src.main import app as fastapi_backend

# 1. Configuration
API_URL = "http://127.0.0.1:7860/api/document-analyze"
API_KEY = os.getenv("API_KEY", "sk_track2_987654321")

# 2. UI Helper Functions (The "Usual" Logic)
def on_file_upload():
    return "*Results will appear here...*", gr.update(label="File Uploaded Successfully! ✅")

async def process_pipeline(file):
    if file is None:
        yield "### ⚠️ Please upload a file first."
        return 
    
    file_name = os.path.basename(file.name)
    yield f"⏳ **Processing {file_name}...** Analysing content."
    
    try:
        with open(file.name, "rb") as f:
            encoded_string = base64.b64encode(f.read()).decode('utf-8')

        payload = {
            "fileName": file_name,
            "fileType": file_name.split('.')[-1].lower(),
            "fileBase64": encoded_string
        }
        
        async with httpx.AsyncClient(timeout=120.0) as client:
            response = await client.post(API_URL, json=payload, headers={"x-api-key": API_KEY})
            res = response.json()

            if response.status_code == 200:
                report = f"""
# ✅ Analysis Complete: {res.get('fileName')}
### 🤖 AI Summary
{res.get('summary')}
### 📊 Sentiment: {res.get('sentiment')}
"""
                yield report
            else:
                yield f"### ❌ Error: {res.get('detail')}"
    except Exception as e:
        yield f"### ❌ System Error: {str(e)}"

# 3. The "Usual" UI Design (Indigo Theme)
with gr.Blocks(theme=gr.themes.Soft(primary_hue="indigo"), title="AI IDP Dashboard") as demo:
    gr.Markdown("# 🏢 Intelligent Document Processing (IDP) Dashboard")
    
    with gr.Row():
        with gr.Column(scale=1):
            file_uploader = gr.File(label="Upload Document", file_types=[".pdf", ".docx", ".jpg", ".png", ".jpeg"])
            submit_btn = gr.Button("🚀 Analyze Document", variant="primary")
        with gr.Column(scale=2):
            output_panel = gr.Markdown(value="*Results will appear here...*")

    file_uploader.upload(fn=on_file_upload, inputs=None, outputs=[output_panel, file_uploader])
    submit_btn.click(fn=process_pipeline, inputs=file_uploader, outputs=output_panel)

# 4. The Mount (Crucial Step)
# This removes any accidental root routes and attaches the Indigo GUI
for route in fastapi_backend.routes:
    if getattr(route, "path", None) == "/":
        fastapi_backend.routes.remove(route)

fastapi_backend.add_middleware(CORSMiddleware, allow_origins=["*"], allow_methods=["*"], allow_headers=["*"])

app = gr.mount_gradio_app(fastapi_backend, demo, path="/")