baml-py

import os # NOTE: This example assumes you have run 'baml-cli init' and 'baml-cli generate'. # A 'baml_src' directory with a BAML function (e.g., ExtractResume) and a 'baml_client' # directory with generated code must exist in your project. # Example BAML function definition (e.g., in baml_src/main.baml): # class Resume { # name string # title string # } # function ExtractResume(resume_text: string) -> Resume { # client "openai/gpt-4o" # prompt """ # Parse the following resume and return structured data. # {{ resume_text }} # {{ ctx.output_format }} # """ # } # Ensure your OpenAI API key is set as an environment variable os.environ['OPENAI_API_KEY'] = os.environ.get('OPENAI_API_KEY', 'sk-fake-key-for-test') from baml_client.sync_client import b from baml_client.types import Resume def process_resume(resume_text: str) -> Resume: print(f"Processing resume: {resume_text[:50]}...") try: # Call your BAML function, which is now a Python method on 'b' response = b.ExtractResume(resume_text=resume_text) print("Successfully extracted resume data:") print(f" Name: {response.name}") print(f" Title: {response.title}") return response except Exception as e: print(f"An error occurred: {e}") # In a real application, you'd handle specific BAML errors like BamlValidationError raise if __name__ == "__main__": sample_resume = ( "Name: Alice Wonderland\n" "Title: Software Engineer\n" "Experience: 5 years at ExampleCorp, developing scalable backend services.\n" "Education: M.S. Computer Science, University of XYZ" ) # This call would only succeed if a baml_src/main.baml with ExtractResume is defined # and baml-cli generate has been run. # mock_resume_data = process_resume(sample_resume) print("To run this, ensure baml-cli init and baml-cli generate have been executed.") print("And OPENAI_API_KEY is set in your environment.")