configured to use local model.

app.py

@@ -7,12 +7,35 @@ import os
 import openai
 import requests
 import json
-
+from openai import OpenAI
 openai.organization = "org-5Z0c3Uk1VG7t3TsczN6M4FCi"
 #openai.api_key = os.getenv("OPENAI_API_KEY")
 openai.api_key_path ="./key.txt" 
 
 def askGPT(prompt="what can I make with potato?"):
+
+    client = OpenAI(
+        base_url='http://localhost:11434/v1/',
+
+        # required but ignored
+        api_key='ollama',
+    )
+
+    chat_completion = client.chat.completions.create(
+            messages=[
+                {
+                    'role': 'user',
+                    'content': prompt,
+                }
+            ],
+            model='llama3',
+        )
+
+    result = chat_completion.choices[0].message.content
+    #print(chat_completion.choices[0].message.content)
+    return result
+
+'''def askGPT(prompt="what can I make with potato?"):
     response = openai.ChatCompletion.create(
       model="gpt-3.5-turbo",
       messages=[
@@ -31,7 +54,7 @@ def askGPT(prompt="what can I make with potato?"):
       presence_penalty=0
     )
     result = response["choices"][0]["message"]["content"]
-    return result
+    return result'''
 
 def classifyImage(image):
     pipe = pipeline("image-classification", model="microsoft/resnet-50")