Update app.py

app.py

@@ -5,7 +5,6 @@ import os
 
 openai.api_key = os.getenv("OPENAI_API_KEY")
 
-# Load the model
 learn = load_learner('model.pkl')
 
 # Define the labels
@@ -13,38 +12,38 @@ labels = learn.dls.vocab
 
 # Define a function for generating text
 def generate_text(prompt):
-  response = openai.Completion.create(
-      engine="davinci",
-      prompt=prompt,
-      max_tokens=1024,
-      n=1,
-      stop=None,
-      temperature=0.7,
-  )
-  return response.choices[0].text.strip()
+ response = openai.Completion.create(
+     engine="davinci",
+     prompt=prompt,
+     max_tokens=1024,
+     n=1,
+     stop=None,
+     temperature=0.7,
+ )
+ return response.choices[0].text.strip()
 
 # Define a function to handle user queries
 def handle_query(query, chat_history):
-  response = openai.ChatCompletion.create(
-      model="gpt-3.5-turbo",
-      messages=[{"role": "system", "content": "You are a helpful assistant you kow about plant Disease."},
-               {"role": "user", "content": query}] + chat_history
-  )
-  return response.choices[0].message['content']
+ response = openai.ChatCompletion.create(
+     model="gpt-3.5-turbo",
+     messages=[{"role": "system", "content": "You are a helpful assistant."},
+              {"role": "user", "content": query}] + chat_history
+ )
+ return response.choices[0].message['content']
 
 # Define the prediction function
 def predict(img):
-  img = PILImage.create(img)
-  pred,pred_idx,probs = learn.predict(img)
-  prediction = {labels[i]: float(probs[i]) for i in range(len(labels))}
-  chat_prompt = f"The model predicted {prediction}."
-  chat_response = generate_text(chat_prompt)
-  return {**prediction, 'chat_response': chat_response}
+ img = PILImage.create(img)
+ pred,pred_idx,probs = learn.predict(img)
+ prediction = {labels[i]: float(probs[i]) for i in range(len(labels))}
+ chat_prompt = f"The model predicted {prediction}."
+ chat_response = generate_text(chat_prompt)
+ return {**prediction, 'chat_response': chat_response}
 
 # Define the chat function
 def chat(query, chat_history):
-  chat_response = handle_query(query, chat_history)
-  return chat_response
+ chat_response = handle_query(query, chat_history)
+ return chat_response
 
 # Define the examples
 examples = ['image.jpg']