Update other_function.py

other_function.py

@@ -1,5 +1,7 @@
 import os
 from bs4 import BeautifulSoup
+import os
+from mistralai import Mistral
 import requests
 from requests.auth import HTTPBasicAuth
 from PIL import Image
@@ -17,6 +19,11 @@ from ai71 import AI71
 import os
 import PyPDF2
 import pandas as pd
+model = "mistral-large-latest"
+api_key='xQ2Zhfsp4cLar4lvBRDWZKljvp0Ej427'
+
+client = Mistral(api_key=api_key)
+
 def extract_text_from_image(image_path):
     img = cv2.imread(image_path)
     if img is None:
@@ -35,19 +42,17 @@ if not os.path.exists(UPLOAD_FOLDER):
 pdf_text=''
 AI71_API_KEY = os.environ.get('AI71_API_KEY')
 def generate_response(query,chat_history):
-    response = ''
-    for chunk in AI71(AI71_API_KEY).chat.completions.create(
-            model="tiiuae/falcon-180b-chat",
-            messages=[
-                {"role": "system", "content": "You are a best agricultural assistant.Remember to give response not more than 2 sentence.Greet the user if user greets you."},
-                {"role": "user",
-                 "content": f'''Answer the query based on history {chat_history}:{query}'''},
-            ],
-            stream=True,
-    ):
-        if chunk.choices[0].delta.content:
-            response += chunk.choices[0].delta.content
-    return response.replace("###", '').replace('\nUser:','')
+    
+    chat_response = client.chat.complete(
+        model= model,
+        messages = [
+            {
+                "role": "user",
+                "content": f"{User_querry}? provide response within 2 sentence",
+            },
+        ]
+    )
+    return chat_response.choices[0].message.content
 class ConversationBufferMemory:
     def __init__(self, max_size):
         self.memory = []