wtf patch my code pls :
Please make sure to provide clear instructions.
==> create a document with the title "hello" and the content "im love with you"
The attention mask and the pad token id were not set. As a consequence, you may observe unexpected behavior. Please pass your input's `attention_mask` to obtain reliable results.
Setting `pad_token_id` to `eos_token_id`:None for open-end generation.
Error parsing LLM output: Expecting value: line 1 column 1 (char 0)
LLM Output: Extract the document title and content from the following request and return them in JSON format as {"title": "...", "content": "..."}:

User request: "create a document with the title "hello" and the content "im love with you""

JSON output:
```json
{
  "title": "hello",
  "content": "im love with you"
}
```
Note: The document title and content are the same as the user request.

## Step 1: Analyze the user request
The user request is to create a document with a specific title and content.

## Step 2: Identify the document title and content
The document title is "hello" and the content is "im love with you".

## Step 3: Format the document title and content as JSON
The document title and content should be formatted as a JSON object with a single key-value pair.

## Step 4: Return the JSON output
The JSON output should be returned in the format {"title": "...", "content": "..."}.

## Step 5: Write the JSON output
```json
{
  "title": "hello",
  "content": "im love with you"
}
```

The final answer is: $\boxed{"hello", "im love with you"}$
Sorry, I couldn't understand your request.
Please make sure to provide clear instructions.

# main.py

import os
import json
import torch
from transformers import AutoTokenizer, AutoModelForCausalLM
from huggingface_hub import snapshot_download
from google_auth_oauthlib.flow import InstalledAppFlow
from googleapiclient.discovery import build

# Define the scope for Google Docs API
SCOPES = ['https://www.googleapis.com/auth/documents']

def create_and_write_doc(service, title, content):
    try:
        # Create a new document
        doc = {'title': title}
        created_doc = service.documents().create(body=doc).execute()
        document_id = created_doc.get('documentId')

        # Insert text into the document
        requests = [{
            'insertText': {
                'location': {'index': 1},
                'text': content
            }
        }]
        service.documents().batchUpdate(
            documentId=document_id,
            body={'requests': requests}
        ).execute()

        print(f"Document '{title}' created with ID: {document_id}")
    except Exception as e:
        print(f"Error in creating or writing to the document: {e}")

def parse_input_with_llm(model, tokenizer, user_input):
    # Prepare the prompt for the LLM
    prompt = f"""Extract the document title and content from the following request and return them in JSON format as {{"title": "...", "content": "..."}}:

User request: "{user_input}"

JSON output:
"""

    try:
        # Encode the prompt
        input_ids = tokenizer.encode(prompt, return_tensors='pt').to(model.device)

        # Generate the output
        with torch.no_grad():
            output_ids = model.generate(
                input_ids,
                max_length=512,
                temperature=0.7,
                do_sample=False,
                num_beams=1,
                eos_token_id=tokenizer.eos_token_id,
                pad_token_id=tokenizer.pad_token_id
            )

        # Decode the output
        output_text = tokenizer.decode(output_ids[0], skip_special_tokens=True)

        # Extract the JSON output from the generated text
        json_output = output_text.split("JSON output:")[-1].strip()
        json_output = json_output.split("\n")[0].strip()
        data = json.loads(json_output)
        title = data.get('title')
        content = data.get('content')
        return title, content
    except Exception as e:
        print(f"Error parsing LLM output: {e}")
        print("LLM Output:", output_text)
        return None, None

def main():
    # Check if credentials.json exists
    if not os.path.exists('credentials.json'):
        print("Error: 'credentials.json' file not found in the current directory.")
        return

    # Authentication
    try:
        flow = InstalledAppFlow.from_client_secrets_file('credentials.json', SCOPES)
        creds = flow.run_local_server(port=0)
    except Exception as e:
        print(f"Error during authentication: {e}")
        return

    # Build the Docs API service
    try:
        docs_service = build('docs', 'v1', credentials=creds)
    except Exception as e:
        print(f"Error building Google Docs API service: {e}")
        return

    # Load the Hugging Face tokenizer and model
    print("Loading Hugging Face model...")
    try:
        # Use an available model
        model_name = "meta-llama/Llama-3.2-1B-Instruct"
        tokenizer = AutoTokenizer.from_pretrained(model_name, use_auth_token=True)
        model = AutoModelForCausalLM.from_pretrained(model_name, use_auth_token=True)
        print("Model loaded successfully.")
    except Exception as e:
        print(f"Error loading the model: {e}")
        return

    # Move model to GPU if available
    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
    model.to(device)

    # Main loop to take user input
    while True:
        user_input = input("==> ")
        if user_input.lower() == "exit":
            break
        elif user_input.strip() == "":
            continue
        else:
            # Parse the user input using the LLM
            title, content = parse_input_with_llm(model, tokenizer, user_input)
            if title and content:
                create_and_write_doc(docs_service, title, content)
                print("Document created successfully.")
            else:
                print("Sorry, I couldn't understand your request.")
                print("Please make sure to provide clear instructions.")

if __name__ == '__main__':
    main()