Update app.py

app.py

@@ -1,34 +1,47 @@
-import openai
 import gradio as gr
+from transformers import AutoTokenizer, pipeline, GPTNeoForCausalLM
+import sympy as sp
 
-# Set your OpenAI API key
-openai.api_key = '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'
+# Load model function
+def load_model():
+    try:
+        model = GPTNeoForCausalLM.from_pretrained("EleutherAI/gpt-neo-125M")
+        tokenizer = AutoTokenizer.from_pretrained("EleutherAI/gpt-neo-125M")
+        generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
+        return generator
+    except Exception as e:
+        return f"Error loading model: {e}"
+
+# Function to check if the question is mathematical
+def is_mathematical_question(question):
+    keywords = ["mean", "area", "volume", "solve", "what is", "calculate", "add", "subtract", "multiply", "divide"]
+    return any(keyword in question.lower() for keyword in keywords)
+
+# Function to process and evaluate the question
+def process_math_question(question):
+    if not is_mathematical_question(question):
+        return "This chatbot only answers questions related to mathematics. Please ask a mathematical question."
 
-# Function to process the mathematical question
-def math_chatbot(question):
     try:
-        # Call the OpenAI API to get the answer
-        response = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",  # You can also use "gpt-4" if you have access
-            messages=[
-                {"role": "user", "content": question}
-            ]
-        )
-        # Extract the response text
-        answer = response['choices'][0]['message']['content']
+        result = sp.sympify(question)
+        return f"The answer is: {result}"
     except Exception as e:
-        answer = str(e)
+        return f"Could not evaluate the expression. Error: {str(e)}"
 
-    return answer
+# Load the model once when starting the app
+generator = load_model()
 
-# Gradio interface using the updated syntax
-iface = gr.Interface(
-    fn=math_chatbot,
-    inputs=gr.Textbox(label="Ask a Mathematical Question", placeholder="e.g., What is 2 + 2?"),
-    outputs="text",
-    title="Math Chatbot",
-    description="Ask any mathematical question and get an answer!"
-)
+# Gradio Interface
+def chatbot_interface(user_input):
+    return process_math_question(user_input)
 
-# Launch the Gradio app
-iface.launch()
+if __name__ == "__main__":
+    # Create Gradio Interface
+    iface = gr.Interface(
+        fn=chatbot_interface,
+        inputs=gr.inputs.Textbox(label="Enter your mathematical question:"),
+        outputs="text",
+        title="Math Chatbot (Open Source)",
+        description="Ask any mathematical question and get an answer. Non-mathematical questions will be restricted."
+    )
+    iface.launch()