autogen - 💡(How to fix) Fix AI Agent 效率工具实践分享 [1 participants]

Fix Plan

To improve the AI productivity toolkit, we will focus on optimizing the Prompt Optimizer component.

Code Changes

Here are the steps to optimize the Prompt Optimizer:

• Update the prompt_optimizer.py file to use a more efficient algorithm, such as the beam search algorithm.
• Install the required libraries by running pip install transformers.
• Use the AutoModelForSeq2SeqLM class from the transformers library to fine-tune a pre-trained model for prompt optimization.

Example code:

from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

# Load pre-trained model and tokenizer
model = AutoModelForSeq2SeqLM.from_pretrained("t5-base")
tokenizer = AutoTokenizer.from_pretrained("t5-base")

# Define a function to optimize prompts
def optimize_prompt(prompt):
    inputs = tokenizer(prompt, return_tensors="pt")
    outputs = model.generate(**inputs, max_length=100)
    optimized_prompt = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return optimized_prompt

Verification

To verify the fix, test the optimize_prompt function with a sample prompt and check if the optimized prompt is more effective in generating the desired output.

Extra Tips

• Use a more efficient hardware accelerator, such as a GPU, to speed up the prompt optimization process.
• Experiment with different pre-trained models and hyperparameters to achieve better results.