Update app.py

app.py

@@ -1,8 +1,8 @@
-from flask import Flask, render_template, request, send_from_directory, jsonify
+from flask import Flask, render_template, request, send_from_directory
 from datetime import datetime
-import requests
 from langchain_community.llms import HuggingFaceHub
 from langchain.prompts import PromptTemplate
+import requests
 import json
 import nltk
 from textblob import TextBlob
@@ -12,9 +12,11 @@ from nltk.stem import WordNetLemmatizer
 import spacy
 from bs4 import BeautifulSoup
 
+# Download NLTK resources
 nltk.download('punkt')
 nltk.download('wordnet')
 
+# Download Spacy model
 def download_spacy_model():
     import spacy
     try:
@@ -29,8 +31,13 @@ nlp = spacy.load("en_core_web_sm")
 
 app = Flask(__name__)
 
-template = "Message: {message}\n\nSentiment Analysis: {sentiment}\n\nConversation History: {history}\n\nDate and Time: {date_time}\n\nBitcoin Price: ${bitcoin_price}\n\nBitcoin Data: {database_tag}\n\nResponse: {response}"
-prompt = PromptTemplate(template=template, input_variables=["message", "sentiment", "history", "date_time", "bitcoin_price", "database_tag", "response"])
+# Load the JSON data from the file
+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 History: {history}\n\nDate and Time: {date_time}\n\nBitcoin Price: ${bitcoin_price}\n\nBitcoin History: {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"])
 conversation_history = []
 
 MAX_HISTORY_LENGTH = 55
@@ -40,20 +47,26 @@ def update_conversation_history(message):
         conversation_history.pop(0)
     conversation_history.append(message)
 
+# Function to retrieve Bitcoin price
 def get_bitcoin_price():
+    current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
     url = 'https://api.coindesk.com/v1/bpi/currentprice.json'
     response = requests.get(url)
-    
+
     if response.status_code == 200:
         data = response.json()
         bitcoin_price = data['bpi']['USD']['rate']
-        current_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
         return bitcoin_price, current_time
     else:
-        return 'Error fetching data', None
+        return 'Error fetching data', current_time
+
+@app.route('/assets/<path:path>')
+def send_static(path):
+    return send_from_directory('assets', path)
 
 @app.route('/')
 def index():
+    global conversation_history
     return render_template('index.html', conversation=conversation_history)
 
 @app.route('/submit', methods=['POST'])
@@ -75,31 +88,30 @@ def submit():
 
     conversation_history.append("User: " + user_input)
 
-    history_tokens = word_tokenize(" ".join(conversation_history))
+    history_tokens = word_tokenize("\n".join(conversation_history))
     history_stemmed_tokens = [ps.stem(token) for token in history_tokens]
     history_lemmatized_tokens = [lemmatizer.lemmatize(token) for token in history_tokens]
 
-    model_input = prompt.format(message=user_input, sentiment=sentiment, history=" ".join(conversation_history), database_tag="Placeholder", date_time=current_time, bitcoin_price=bitcoin_price, response="")
+    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)
+
+    response = llm(model_input, context="<br>".join(conversation_history))
+
+    bot_response = response.split('Response:')[1].strip()
+    bot_response = bot_response.strip().replace('\n', '<br>')
 
-    response = "Placeholder response"  # Update with actual response generation logic
+    update_conversation_history("Bot: " + bot_response)
 
-     = "Bot: " + response
-    update_conversation_history(response_message)
+    conversation_html = '<br>'.join(conversation_history)
 
-    return response_message
-    
+    return bot_response
 
 @app.route('/clear_history')
 def clear_history():
     global conversation_history
     conversation_history = []
     return 'Conversation history cleared'
-    
-@app.route('/assets/<path:path>')
-def send_static(path):
-    return send_from_directory('assets', path)
 
-    
 with open('i.txt', 'r') as file:
     data = file.read()