Update app.py

app.py

@@ -6,7 +6,7 @@ import os
 # Get the Hugging Face token from environment variable
 hf_token = os.environ.get('MISTRAL_ACCESS_TOKEN')
 
-# Load the Mistral 7B model and tokenizer from Hugging Face
+# Load the Mistral 7B Instruct model and tokenizer from Hugging Face
 model_name = "mistralai/Mistral-7B-Instruct-v0.3"
 tokenizer = AutoTokenizer.from_pretrained(model_name, token=hf_token)
 model = AutoModelForCausalLM.from_pretrained(model_name, torch_dtype=torch.float16, device_map="auto", token=hf_token)
@@ -19,8 +19,7 @@ def generate_text(prompt, max_length=500):
 
 # Function to generate personalized learning plan
 def generate_learning_plan(name, age, subject, learning_style, strengths, weaknesses):
-    prompt = f"""
-    Create a personalized learning plan for a student with the following details:
+    prompt = f"""<s>[INST] Create a personalized learning plan for a student with the following details:
     Name: {name}
     Age: {age}
     Subject: {subject}
@@ -33,8 +32,7 @@ def generate_learning_plan(name, age, subject, learning_style, strengths, weakne
     2. Suggested resources
     3. Personalized learning goals
     4. Strategies to address weaknesses
-    5. Ways to leverage strengths
-    """
+    5. Ways to leverage strengths [/INST]"""
     
     response = generate_text(prompt)
     return response