llama-cloud

import os from llama_cloud import LlamaCloud from pathlib import Path # Ensure LLAMA_CLOUD_API_KEY is set in your environment variables # e.g., os.environ['LLAMA_CLOUD_API_KEY'] = 'llx-...' or using a .env file client = LlamaCloud( api_key=os.environ.get('LLAMA_CLOUD_API_KEY', '') ) # Example: Upload a dummy file and create a parsing job # Replace with a real file path for actual usage # file_path = Path("path/to/your/document.pdf") # with open(file_path, "rb") as f: # file_obj = client.files.create( # file=(file_path.name, f.read(), "application/pdf"), # purpose="parse", # ) # For demonstration, simulate a file_id to create a parsing job # In a real scenario, file_id would come from client.files.create() or an existing file. dummy_file_id = "your-example-file-id" # Replace with actual file_id if uploading if not dummy_file_id: print("Please provide a valid file_id or upload a file first.") else: try: job = client.parsing.create( tier="agentic", # or "fast", "cost_effective" version="latest", file_id=dummy_file_id, # For example, to get markdown output: output_options={ "markdown": { "tables": { "output_tables_as_markdown": True } } }, expand=["markdown"] ) print(f"Created parsing job with ID: {job.id}") # You would typically poll the job status and retrieve results here # For example, using client.parsing.get_job_result(job.id) except Exception as e: print(f"An error occurred: {e}")