python_packages={python_packages},
        )
        app.Trigger.RestAPI(
            inputs={{"prompt": beam.Types.String(), "max_length": beam.Types.String()}},
            outputs={{"text": beam.Types.String()}},
            handler="run.py:beam_langchain",
        )
        """
        )
        script_name = "app.py"
        with open(script_name, "w") as file:
            file.write(
                script.format(
                    name=self.name,
                    cpu=self.cpu,
                    memory=self.memory,
                    gpu=self.gpu,
                    python_version=self.python_version,
                    python_packages=self.python_packages,
                )
            )
[docs]    def run_creation(self) -> None:
        """Creates a Python file which will be deployed on beam."""
        script = textwrap.dedent(
            """
        import os
        import transformers
        from transformers import GPT2LMHeadModel, GPT2Tokenizer
        model_name = "{model_name}"
        def beam_langchain(**inputs):
            prompt = inputs["prompt"]
            length = inputs["max_length"]
            tokenizer = GPT2Tokenizer.from_pretrained(model_name)
            model = GPT2LMHeadModel.from_pretrained(model_name)
            encodedPrompt = tokenizer.encode(prompt, return_tensors='pt')
            outputs = model.generate(encodedPrompt, max_length=int(length),
              do_sample=True, pad_token_id=tokenizer.eos_token_id)
            output = tokenizer.decode(outputs[0], skip_special_tokens=True)
            print(output)
            return {{"text": output}}
        """
        )
        script_name = "run.py"
        with open(script_name, "w") as file:
            file.write(script.format(model_name=self.model_name))