import torch
from transformers import GPT2LMHeadModel, GPT2Tokenizer
class AutoGPTAgent:
def init(self):
self.commands = {
"generate": self.generate_text,
Add more commands as needed
}
self.tokenizer = GPT2Tokenizer.from_pretrained("gpt2")
self.model = GPT2LMHeadModel.from_pretrained("gpt2")
def generate_text(self, args):
# Join the arguments into a single string
prompt = " ".join(args)
# Encode the prompt and generate the text
inputs = self.tokenizer.encode(prompt, return_tensors="pt")
outputs = self.model.generate(inputs, max_length=100, temperature=0.7)
# Decode the generated text and print it
generated_text = self.tokenizer.decode(outputs[0])
print(generated_text)
def process_command(self, command, args):
if command in self.commands:
self.commandscommand
else:
print(f"Unknown command: {command}")
import torch from transformers import GPT2LMHeadModel, GPT2Tokenizer
class AutoGPTAgent: def init(self): self.commands = { "generate": self.generate_text,
Add more commands as needed
Usage:
agent = AutoGPTAgent() agent.process_command("generate", ["Hello, world!"])