app.py

# -*- coding: utf-8 -*-
import gradio as gr
import json
from Data_Fetching_and_Rendering import fetch_and_render_dashboard
from analytics_fetch_and_rendering import fetch_and_render_analytics
from mentions_dashboard import generate_mentions_dashboard


# Shared state
token_received = {"status": False, "token": None, "client_id": None}

# --- Handlers for token reception and status ---
def receive_token(accessToken: str, client_id: str):
    """
    Called by a hidden POST mechanism to supply the OAuth code/token and client ID.
    """
    try:
        token_dict = json.loads(accessToken.replace("'", '"'))
    except json.JSONDecodeError as e:
        return {
            "status": "❌ Invalid token format",
            "token": "",
            "client_id": client_id
        }
    
    token_received["status"] = True
    token_received["token"] = token_dict
    token_received["client_id"] = client_id
    return {
        "status": "✅ Token received",
        "token": token_dict.get("access_token", ""),
        "client_id": client_id
    }

def check_status():
    return "✅ Token received" if token_received["status"] else "❌ Waiting for token…"

def show_token():
    return token_received["token"].get("access_token", "") if token_received["status"] else ""

def show_client():
    return token_received["client_id"] or "" if token_received["status"] else ""

# --- Guarded fetch functions ---
def guarded_fetch_dashboard():
    if not token_received["status"]:
        return "<p style='color:red; text-align:center;'>❌ Access denied. No token available. Please send token first.</p>"
    # token_received["client_id"] and token_received["token"] required by fetch function
    html = fetch_and_render_dashboard(
        token_received["client_id"],
        token_received["token"]
    )
    return html


def guarded_fetch_analytics():
    if not token_received["status"]:
        return (
            "<p style='color:red; text-align:center;'>❌ Access denied. No token available.</p>",
            None,
            None
        )
    count_md, plot, growth_plot, avg_post_eng_rate, interaction_metrics = fetch_and_render_analytics(
        token_received["client_id"],
        token_received["token"]
    )
    return count_md, plot, growth_plot, avg_post_eng_rate, interaction_metrics


def run_mentions_and_load():
    html, fig = generate_mentions_dashboard(
        token_received["client_id"],
        token_received["token"]
    )
    return html, fig


# --- Build the Gradio UI ---
with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
               title="LinkedIn Post Viewer & Analytics") as app:
    gr.Markdown("# 🚀 LinkedIn Organization Post Viewer & Analytics")
    gr.Markdown("Send your OAuth token via API call, then explore dashboard and analytics.")

    # Hidden elements: simulate POST endpoint
    hidden_token = gr.Textbox(visible=False, elem_id="hidden_token")
    hidden_client = gr.Textbox(visible=False, elem_id="hidden_client_id")
    hidden_btn = gr.Button(visible=False, elem_id="hidden_btn")

    status_box = gr.Textbox(value=check_status(), label="Status", interactive=False)
    token_display = gr.Textbox(value=show_token(), label="Access Token", interactive=False)
    client_display = gr.Textbox(value=show_client(), label="Client ID", interactive=False)

    # Wire hidden POST handler
    hidden_btn.click(
        fn=receive_token,
        inputs=[hidden_token, hidden_client],
        outputs=[status_box, token_display, client_display]
    )

    # Polling timer to update status and displays
    timer = gr.Timer(1.0)
    timer.tick(fn=check_status, outputs=status_box)
    timer.tick(fn=show_token, outputs=token_display)
    timer.tick(fn=show_client, outputs=client_display)

    # Tabs for functionality
    with gr.Tabs():
        with gr.TabItem("1️⃣ Dashboard"):
            gr.Markdown("View your organization's recent posts and their engagement statistics.")
            fetch_dashboard_btn = gr.Button("📊 Fetch Posts & Stats", variant="primary")
            dashboard_html = gr.HTML(value="<p style='text-align: center; color: #555;'>Waiting for token...</p>")
            fetch_dashboard_btn.click(
                fn=guarded_fetch_dashboard,
                inputs=[],
                outputs=[dashboard_html]
            )

        with gr.TabItem("2️⃣ Analytics"):
            gr.Markdown("View follower count and monthly gains for your organization.")
            fetch_analytics_btn = gr.Button("📈 Fetch Follower Analytics", variant="primary")
            
            follower_count = gr.Markdown("<p style='text-align: center; color: #555;'>Waiting for token...</p>")
            
            with gr.Row():  # Use Row to align the two plots side-by-side
                follower_plot = gr.Plot(visible=False)
                growth_rate_plot = gr.Plot(visible=False)

            with gr.Row():
                post_eng_rate_plot = gr.Plot(visible=False)

            with gr.Row():
                interaction_data = gr.Plot(visible=False)
        
            fetch_analytics_btn.click(
                fn=guarded_fetch_analytics,
                inputs=[],
                outputs=[follower_count, follower_plot, growth_rate_plot, post_eng_rate_plot, interaction_data]
            )


        with gr.TabItem("3️⃣ Mentions"):
            gr.Markdown("Analyze sentiment of recent posts that mention your organization.")
            fetch_mentions_btn = gr.Button("🧠 Fetch Mentions & Sentiment", variant="primary")
            mentions_html = gr.HTML()
            mentions_plot = gr.Plot(visible=False)
            fetch_mentions_btn.click(
                fn=run_mentions_and_load,
                inputs=[],
                outputs=[mentions_html, mentions_plot]
            )



# Launch the app
if __name__ == "__main__":
    app.launch(server_name="0.0.0.0", server_port=7860, share=True)