Update app.py

app.py

@@ -1,34 +1,18 @@
-import functions as funky
-import pandas as pd
-import gradio as gr
-import os
-from datasets import load_dataset
-from huggingface_hub import login
-import numpy as np
-from fastapi import FastAPI, Request
-import uvicorn
-from starlette.middleware.sessions import SessionMiddleware
-import fastapi
-from datetime import datetime
-
-login(token = os.environ['HUB_TOKEN'])
-
-
-logger = gr.HuggingFaceDatasetSaver(os.environ['HUB_TOKEN'], dataset_name='illustration_gdrive_logging_main', organization=None, private=True)
+
+logger = gr.HuggingFaceDatasetSaver(os.environ['HUB_TOKEN'], dataset_name='illustration_gdrive_logging', organization=None, private=True)
 logger.setup([gr.Text(label="clicked_url"), gr.Text(label="seach_term"),  gr.Text(label = 'sessionhash'), gr.Text(label = 'datetime')], './flagged_data_points')
 
+
 logging_js = '''
 function magicFunc(x){
     let script = document.createElement('script');    
-    script.innerHTML = "async function magicFunc(x){let z = document.getElementById('search_term').getElementsByTagName('textarea')[0].value; await fetch('/track?url=' + x + '&q=' + z)}";
+    script.innerHTML = "async function magicFunc(x){let z = document.getElementById('search_term').getElementsByTagName('textarea')[0].value; let data = {data: [x, z]}; var x = fetch('/api/track', {method: 'POST', headers: {'Content-Type': 'application/json'}, body: JSON.stringify(data)})}";
     document.head.appendChild(script);
 }
 '''
 
-dataset = load_dataset("bradley6597/illustration-test")
-df = pd.DataFrame(dataset['train']).drop_duplicates()
 
-ill_links = df.copy()
+ill_links = pd.read_csv("./data/data.csv").drop_duplicates()
 ill_links = ill_links[ill_links['Description'] != 'Moved'].copy()
 ill_links['code'] = ill_links['link'].str.replace("https://drive.google.com/file/d/", "", regex = False)
 ill_links['code'] = ill_links['code'].str.replace("/view?usp=drivesdk", "", regex = False)
@@ -39,6 +23,7 @@ ill_links['filename'] = ill_links['file'].str.replace(".*\\/", "", regex = True)
 ill_links['shared_drive'] = ill_links['file'].str.replace("/content/drive/Shareddrives/", "", regex = False)
 ill_links['shared_drive'] = ill_links['shared_drive'].str.replace("(.*?)\\/.*", "\\1", regex = True)
 ill_links['Description'] = ill_links['Description'].str.replace("No Description", "", regex = False)
+ill_links['image_code'].iloc[0]
 
 ill_links_title = ill_links.copy()
 
@@ -126,7 +111,7 @@ def search_index(search_text, sd, ks, sort_by, max_results, user_num, search_tit
         final_df = final_df.fillna('')
     else:
         final_df = pd.DataFrame(['<h3>No Results Found :(</h3>'])
-
+    
     if final_df.shape[0] == 0 :
         final_df = pd.DataFrame(['<h3>No Results Found :(</h3>'])
         
@@ -134,10 +119,11 @@ def search_index(search_text, sd, ks, sort_by, max_results, user_num, search_tit
            final_df.to_html(escape = False, render_links = True, index = False, header = False) +
            '</center>')
     
-    
-def search_logging(x: str, request: gr.Request):
+def search_logging(url: str, q: str, request: gr.Request):
+    if url == q:
+        url = ''
     session_id = getattr(request.cookies, 'access-token')
-    logger.flag(['', x, session_id, str(datetime.now())])
+    logger.flag([url, q, session_id, str(datetime.now())])
 
 
 with gr.Blocks(css="style.css") as app:
@@ -159,42 +145,18 @@ with gr.Blocks(css="style.css") as app:
                 search_button = gr.Button(value="Search!")
             with gr.Row(): 
                 output_df = gr.HTML() 
+    
     search_button.click(search_index, inputs=[search_prompt, shared_drive, key_stage, sort_by, max_return, user_num, title_search], outputs=output_df) 
-    search_prompt.submit(search_index, inputs=[search_prompt, shared_drive, key_stage, sort_by, max_return, user_num, title_search], outputs=output_df)
-    search_button.click(search_logging, inputs=[search_prompt], outputs=None) 
-    search_prompt.submit(search_logging, inputs=[search_prompt], outputs=None)
+    search_prompt.submit(search_index, inputs=[search_prompt, shared_drive, key_stage, sort_by, max_return, user_num, title_search], outputs=output_df) 
+    search_button.click(search_logging, inputs=[search_prompt, search_prompt], outputs=None, api_name='track') 
+    search_prompt.submit(search_logging, inputs=[search_prompt, search_prompt], outputs=None, api_name='track')
     app.load(_js = logging_js)
 
-app.auth = (same_auth)
-app.auth_message = ''
-
-
-fapi = FastAPI()
-
-fapi.add_middleware(SessionMiddleware, secret_key=os.environ['session_key'])
-
-@fapi.middleware("http")
-async def add_session_hash(request: Request, call_next):
-    response = await call_next(request)
-    session = request.cookies.get('session')
-    if session:
-        response.set_cookie(key='session', value=request.cookies.get('session'), httponly=True)
-    return response
-
-# custom get request handler with params to flag clicks
-@ fapi.get("/track")
-async def track(url: str, q: str, request: Request):
-    
-    if q is None:
-        q = ''
-    
-    logger.flag([url, q, request.cookies['access-token'], str(datetime.now())])
-    return {"message": "ok"}
-
+# app.auth = (same_auth)
+# app.auth_message = ''
 
-# mount Gradio app to FastAPI app
-app2 = gr.mount_gradio_app(fapi, app, path="/")
-# serve the app
-if __name__ == "__main__":
-    uvicorn.run(app2, host="0.0.0.0", port=7860)
- 
+app.launch(debug=True, 
+            share=False, 
+            height=768,
+            auth=(same_auth) 
+            )