deleting app

streamlit_app.py

@@ -1,122 +0,0 @@
-import streamlit as st
-import requests
-import os
-import sqlite3
-import time
-import uuid
-import datetime
-import hashlib
-
-
-# FastAPI base URL
-#BASE_URL = "http://localhost:8000"
-
-import os
-
-API_URL=os.getenv("API_URL")
-API_TOKEN=os.getenv("API_TOKEN")
-
-BASE_URL=API_URL
-
-#API_URL = "https://api-inference.huggingface.co/models/your-username/your-private-model"
-headers = {"Authorization":f"Bearer {API_TOKEN}"}
-
-def query(payload):
-    response = requests.post(API_URL, headers=headers, json=payload)
-    return response.json()
-
-#data = query({"inputs": "Hello, how are you?"})
-#print(data)
-
-st.title("Performance Review Analyzer")
-
-def generate_unique_hash(filename: str, uuid: str) -> str:
-    # Generate a UUID for the session or device
-    device_uuid = uuid
-
-    # Get the current date and time
-    current_time = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-
-    # Combine filename, current time, and UUID into a single string
-    combined_string = f"{filename}-{current_time}-{device_uuid}"
-
-    # Generate a hash using SHA256
-    unique_hash = hashlib.sha256(combined_string.encode()).hexdigest()
-
-    return unique_hash
-
-# Function to generate or retrieve a UUID from local storage
-uuid_script = """
-<script>
-    if (!localStorage.getItem('uuid')) {
-        localStorage.setItem('uuid', '""" + str(uuid.uuid4()) + """');
-    }
-    const uuid = localStorage.getItem('uuid');
-    const streamlitUUIDInput = window.parent.document.querySelector('input[data-testid="stTextInput"][aria-label="UUID"]');
-    if (streamlitUUIDInput) {
-        streamlitUUIDInput.value = uuid;
-    }
-</script>
-"""
-
-ga_script = """
-<!-- Google tag (gtag.js) -->
-<script async src="https://www.googletagmanager.com/gtag/js?id=G-PWP4PRW5G5"></script>
-<script>
-  window.dataLayer = window.dataLayer || [];
-  function gtag(){dataLayer.push(arguments);}
-  gtag('js', new Date());
-
-  gtag('config', 'G-PWP4PRW5G5');
-</script>
-"""
-
-# Add Google Analytics to the Streamlit app
-st.components.v1.html(ga_script, height=0, width=0)
-
-# Execute the JavaScript in the Streamlit app
-st.components.v1.html(uuid_script, height=0, width=0)
-
-# Store and display UUID in a non-editable text field using session state
-if 'uuid' not in st.session_state:
-    st.session_state['uuid'] = str(uuid.uuid4())
-
-uuid_from_js = st.session_state['uuid']
-
-# Retrieve UUID from DOM
-if uuid_from_js is None:
-    st.error("Unable to retrieve UUID from the browser.")
-else:
-    # Display UUID in a non-editable text field
-    st.text_input("Your UUID", value=uuid_from_js, disabled=True)
-
-uploaded_file = st.file_uploader("Upload your reviews CSV file", type=["csv"])
-
-if uploaded_file is not None:
-    # Save uploaded file to FastAPI
-    en1 = generate_unique_hash(uploaded_file.name, uuid_from_js)
-    files = {"file": (en1, uploaded_file.getvalue(), "text/csv")}
-    st.info("Calling model inference. Please wait...")
-    response = requests.post(f"{BASE_URL}/upload/", files=files,headers=headers)
-    print(response)
-    if response.status_code == 200:
-        st.info("Processing started. Please wait...")
-
-        # Poll for completion
-        while True:
-            status_response = requests.get(f"{BASE_URL}/status/{en1}",headers=headers)
-            if status_response.status_code == 200 and status_response.json()["status"] == "complete":
-                st.success("File processed successfully.")
-                download_response = requests.get(f"{BASE_URL}/download/{en1}",headers=headers)
-
-                if download_response.status_code == 200:
-                    st.download_button(
-                        label="Download Processed File",
-                        data=download_response.content,
-                        file_name=f"processed_{en1}",
-                        mime="text/csv"
-                    )
-                break
-            time.sleep(2)
-    else:
-        st.error("Failed to upload file for processing.")