Deleted main.py in favor of newer versio

main.py

@@ -1,60 +0,0 @@
-import transformers
-import torch
-import gradio as gr
-from datasets import load_dataset
-
-# Remember to add access token to huggingface-cli login
-
-# Load the model once when the script starts
-model_id = "meta-llama/Meta-Llama-3.1-8B-Instruct"
-
-# Load the model into memory (on GPU if available)
-pipeline = transformers.pipeline(
-    "text-generation",
-    model=model_id,
-    model_kwargs={"torch_dtype": torch.bfloat16},
-    device_map="auto",  # Auto-detect GPU
-)
-
-# Load the dataset from Hugging Face
-dataset = load_dataset("quantumminds/cisco_cli_commands")
-
-# Function to search the dataset for a matching command
-def search_dataset(user_input):
-    # Check if any command in the dataset matches the user input
-    for entry in dataset['train']:  # assuming the dataset is in the 'train' split
-        if entry["command"].lower() in user_input.lower():  # Match the command with user input (case-insensitive)
-            return f"**Command:** {entry['command']}\n\n**Description:** {entry['description']}\n\n**Example:** {entry['examples'][0]['example_command'] if 'examples' in entry else 'No example available'}"
-    return None  # If no match found
-
-# Function to generate response using the dataset or fallback to the pipeline
-def generate_response(user_input):
-    # First, try to find a match in the dataset
-    dataset_response = search_dataset(user_input)
-    
-    if dataset_response:
-        return dataset_response
-    
-    # If no match, fallback to the LLM
-    messages = [
-        {"role": "system", "content": "You are a pirate chatbot who specializes in Cisco switch and router configurations"},
-        {"role": "user", "content": user_input},
-    ]
-    
-    # Generate the response from the LLM
-    outputs = pipeline(messages, max_new_tokens=256)
-    
-    # Return the generated text
-    return outputs[0]["generated_text"]
-
-# Create Gradio interface
-iface = gr.Interface(
-    fn=generate_response,  # Function to call
-    inputs=gr.Textbox(lines=2, placeholder="Enter your Cisco switch/router question here..."),
-    outputs="text",
-    title="Cisco Configuration Assistant",  # Title for the UI
-    description="Ask the chatbot questions about Cisco switch/router configurations",
-)
-
-# Launch the Gradio app
-iface.launch()