Spaces:
Running
Running
File size: 6,155 Bytes
adb3bbe b560569 896ae69 b0464a9 f7fc39b d252c6d adb3bbe 538b42b 179ea1f f97b21b 493ca9b b0464a9 3038c7b b0464a9 3038c7b b0464a9 3038c7b b0464a9 4cc3230 b0464a9 f7fc39b b0464a9 538b42b adb3bbe 179ea1f b0464a9 adb3bbe 3038c7b adb3bbe b0464a9 f7fc39b b0464a9 f7fc39b 3038c7b b0464a9 73e88eb 179ea1f 3038c7b b0464a9 adb3bbe b0464a9 7ab0240 adb3bbe f7fc39b 179ea1f a9b7f24 b0464a9 88d3a6e b0464a9 2051c7a b0464a9 f466d89 b0464a9 6d43d2f b0464a9 179ea1f adb3bbe 179ea1f b0464a9 adb3bbe 06d22e5 538b42b b0464a9 538b42b 179ea1f b8b7e00 538b42b adb3bbe 179ea1f b0464a9 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 |
# -*- coding: utf-8 -*-
import gradio as gr
import json
import os
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
from gradio_utils import get_url_user_token
from Bubble_API_Calls import fetch_linkedin_token_from_bubble
def check_token_status(token_state):
return "β
Token available" if token_state and token_state.get("token") else "β Token not available"
def process_and_store_bubble_token(url_user_token, org_urn, token_state):
new_state = token_state.copy() if token_state else {"token": None, "client_id": None, "org_urn": None}
new_state.update({"token": None, "org_urn": org_urn})
client_id = os.environ.get("Linkedin_client_id")
if not client_id:
print("β CRITICAL ERROR: 'Linkedin_client_id' environment variable not set.")
new_state["client_id"] = "ENV VAR MISSING"
return check_token_status(new_state), new_state
new_state["client_id"] = client_id
if not url_user_token or "not found" in url_user_token or "Could not access" in url_user_token:
return check_token_status(new_state), new_state
print(f"Attempting to fetch token from Bubble with user token: {url_user_token}")
parsed = fetch_linkedin_token_from_bubble(url_user_token)
if isinstance(parsed, dict) and "access_token" in parsed:
new_state["token"] = parsed
print("β
Token successfully fetched from Bubble.")
else:
print("β Failed to fetch a valid token from Bubble.")
return check_token_status(new_state), new_state
def guarded_fetch_dashboard(token_state):
if not token_state or not token_state.get("token"):
return "<p style='color:red; text-align:center;'>β Access denied. No token available.</p>"
return fetch_and_render_dashboard(token_state.get("client_id"), token_state.get("token"))
def guarded_fetch_analytics(token_state):
if not token_state or not token_state.get("token"):
return ("<p style='color:red; text-align:center;'>β Access denied. No token available.</p>",
None, None, None, None, None, None, None)
return fetch_and_render_analytics(token_state.get("client_id"), token_state.get("token"))
def run_mentions_and_load(token_state):
if not token_state or not token_state.get("token"):
return ("<p style='color:red; text-align:center;'>β Access denied. No token available.</p>", None)
return generate_mentions_dashboard(token_state.get("client_id"), token_state.get("token"))
with gr.Blocks(theme=gr.themes.Soft(primary_hue="blue", secondary_hue="sky"),
title="LinkedIn Post Viewer & Analytics") as app:
token_state = gr.State(value={"token": None, "client_id": None, "org_urn": None})
gr.Markdown("# π LinkedIn Organization Post Viewer & Analytics")
gr.Markdown("Token is supplied via URL parameter for Bubble.io lookup. Then explore dashboard and analytics.")
url_user_token_display = gr.Textbox(label="User Token (from URL - Hidden)", interactive=False, visible=False)
status_box = gr.Textbox(label="Overall Token Status", interactive=False)
org_urn = gr.Textbox(visible=False) # Needed for input, was missing from initial script
app.load(fn=get_url_user_token, inputs=None, outputs=[url_user_token_display, org_urn])
url_user_token_display.change(
fn=process_and_store_bubble_token,
inputs=[url_user_token_display, org_urn, token_state],
outputs=[status_box, token_state]
)
app.load(fn=check_token_status, inputs=[token_state], outputs=status_box)
gr.Timer(5.0).tick(fn=check_token_status, inputs=[token_state], outputs=status_box)
with gr.Tabs():
with gr.TabItem("1οΈβ£ Dashboard"):
gr.Markdown("View your organization's recent posts and their engagement statistics.")
fetch_dashboard_btn = gr.Button("π Fetch Posts & Stats", variant="primary")
dashboard_html = gr.HTML("<p style='text-align: center; color: #555;'>Waiting for token...</p>")
fetch_dashboard_btn.click(fn=guarded_fetch_dashboard, inputs=[token_state], outputs=[dashboard_html])
with gr.TabItem("2οΈβ£ Analytics"):
gr.Markdown("View follower count and monthly gains for your organization.")
fetch_analytics_btn = gr.Button("π Fetch Follower Analytics", variant="primary")
follower_count = gr.Markdown("<p style='text-align: center; color: #555;'>Waiting for token...</p>")
with gr.Row():
follower_plot, growth_plot = gr.Plot(), gr.Plot()
with gr.Row():
eng_rate_plot = gr.Plot()
with gr.Row():
interaction_plot = gr.Plot()
with gr.Row():
eb_plot = gr.Plot()
with gr.Row():
mentions_vol_plot, mentions_sentiment_plot = gr.Plot(), gr.Plot()
fetch_analytics_btn.click(
fn=guarded_fetch_analytics,
inputs=[token_state],
outputs=[follower_count, follower_plot, growth_plot, eng_rate_plot,
interaction_plot, eb_plot, mentions_vol_plot, mentions_sentiment_plot]
)
with gr.TabItem("3οΈβ£ Mentions"):
gr.Markdown("Analyze sentiment of recent posts that mention your organization.")
fetch_mentions_btn = gr.Button("π§ Fetch Mentions & Sentiment", variant="primary")
mentions_html = gr.HTML("<p style='text-align: center; color: #555;'>Waiting for token...</p>")
mentions_plot = gr.Plot()
fetch_mentions_btn.click(
fn=run_mentions_and_load,
inputs=[token_state],
outputs=[mentions_html, mentions_plot]
)
if __name__ == "__main__":
if not os.environ.get("Linkedin_client_id"):
print("WARNING: The 'Linkedin_client_id' environment variable is not set. The application may not function correctly.")
app.launch(server_name="0.0.0.0", server_port=7860, share=True)
|