Update app.py

app.py

@@ -36,11 +36,21 @@ with open('ai_chatbot_data.json', 'r') as file:
     json_data = json.load(file)
 
 # Updated prompt template for Bitcoin trading
-template = "User Message: {message}\n\nUser Sentiment: {sentiment}\n\nConversation now: {history}\n\nDate and Time: {date_time}\n\nBitcoin Price: ${bitcoin_price}\n\nBTC price from 1 jan (DATE,OPEN,HIGH,LOW,CLOSE,ADJ CLOSE,VOLUME<br/>): {database_tag}\n\nAI System Data: {json_data}\n\nResponse:"
-prompt = PromptTemplate(template=template, input_variables=["message", "sentiment", "history", "date_time", "bitcoin_price", "database_tag", "json_data"])
+template = "User Message: {message}\n\nUser Sentiment: {sentiment}\n\nConversation now: {history}\n\nDate and Time: {date_time}\n\nBitcoin Price: ${bitcoin_price}\n\nBTC price from 1 jan (DATE,OPEN,HIGH,LOW,CLOSE,ADJ CLOSE,VOLUME<br/>): {div_content}\n\nAI System Data: {json_data}\n\nResponse:"
+prompt = PromptTemplate(template=template, input_variables=["message", "sentiment", "history", "date_time", "bitcoin_price", "div_content", "json_data"])
 conversation_history = []
 
 MAX_HISTORY_LENGTH = 55
+url = "https://dooratre-info.hf.space/?logs=container&__sign=eyJhbGciOiJFZERTQSJ9.eyJyZWFkIjp0cnVlLCJwZXJtaXNzaW9ucyI6eyJyZXBvLmNvbnRlbnQucmVhZCI6dHJ1ZX0sIm9uQmVoYWxmT2YiOnsia2luZCI6InVzZXIiLCJfaWQiOiI2NWIyYzMyNjJiZTk2NjBmMGIxMjg0MDAiLCJ1c2VyIjoiRG9vcmF0cmUifSwiaWF0IjoxNzEyNjgwNTY4LCJzdWIiOiIvc3BhY2VzL0Rvb3JhdHJlL2luZm8iLCJleHAiOjE3MTI3NjY5NjgsImlzcyI6Imh0dHBzOi8vaHVnZ2luZ2ZhY2UuY28ifQ.R_PX6Hw5SMheYTQWPGe1Qla9q8gVBU0mAFF_u8Iad06jSpZ9sPzZqquSowWn7PGVLRYBW21DnvqSwXIoNZ4CAA"
+
+response = requests.get(url)
+soup = BeautifulSoup(response.content, 'html.parser')
+
+div_content = soup.find('div', {'id': '45'})
+if div_content:
+    print(div_content)
+else:
+    print("No div with id=45 found on the page.")
 
 def update_conversation_history(message):
     if len(conversation_history) >= MAX_HISTORY_LENGTH:
@@ -93,7 +103,7 @@ def submit():
     history_lemmatized_tokens = [lemmatizer.lemmatize(token) for token in history_tokens]
 
     model_input = prompt.format(message=user_input, sentiment=sentiment, history="\n".join(conversation_history), 
-                                database_tag="Bitcoin Data Placeholder", date_time=current_time, bitcoin_price=bitcoin_price, json_data=json_data)
+                                div_content="Bitcoin Data Placeholder", date_time=current_time, bitcoin_price=bitcoin_price, json_data=json_data)
 
     response = llm(model_input, context="<br>".join(conversation_history))