ó ±oi\ãó•Srg)aÈ # Master configuration file for Synthetic Data Kit # Global paths configuration paths: # Input data locations input: pdf: "{data_output_location}/pdf" html: "{data_output_location}/html" youtube: "{data_output_location}/youtube" docx: "{data_output_location}/docx" ppt: "{data_output_location}/ppt" txt: "{data_output_location}/txt" # Output locations output: parsed: "{data_output_location}/output" # Where parsed text files are saved generated: "{data_output_location}/generated" # Where generated content is saved cleaned: "{data_output_location}/cleaned" # Where cleaned content is saved final: "{data_output_location}/final" # Where final formatted content is saved # VLLM server configuration vllm: api_base: "http://localhost:8000/v1" # Base URL for VLLM API port: 8000 # Port for VLLM server model: "{model_name}" # Default model to use max_retries: 3 # Number of retries for API calls retry_delay: 1.0 # Initial delay between retries (seconds) # Ingest configuration ingest: default_format: "txt" # Default output format for parsed files youtube_captions: "auto" # Options: "auto", "manual" - caption preference # LLM generation parameters generation: temperature: {temperature} # Higher = more creative, lower = more deterministic top_p: {top_p} # Nucleus sampling parameter chunk_size: {chunk_size} # Size of text chunks for processing overlap: {overlap} # Overlap between chunks to maintain context max_tokens: {max_tokens} # Maximum tokens in LLM responses num_pairs: {default_num_pairs} # Default number of QA pairs to generate # Content cleanup parameters cleanup: threshold: {cleanup_threshold} # Default quality threshold (1-10) batch_size: {cleanup_batch_size} # Number of items per batch for rating temperature: {cleanup_temperature} # Temperature for rating (lower = more consistent) # Format conversion parameters format: default: "jsonl" # Default output format include_metadata: true # Include metadata in output files pretty_json: true # Use indentation in JSON output # Prompts for different tasks prompts: # Summary generation prompt summary: | Summarize this document in 3-5 sentences, focusing on the main topic and key concepts. # QA pair generation prompt qa_generation: | Create {num_pairs} question-answer pairs from this text for LLM training. Rules: 1. Questions must be about important facts in the text 2. Answers must be directly supported by the text 3. Return JSON format only: [ {{ "question": "Question 1?", "answer": "Answer 1." }}, {{ "question": "Question 2?", "answer": "Answer 2." }} ] Text: {text} # QA pair rating prompt qa_rating: | Rate each of these question-answer pairs for quality and return exactly this JSON format: [ {{"question": "same question text", "answer": "same answer text", "rating": n}} ] Where n is a number from 1-10. DO NOT include any text outside of the JSON array, just return valid JSON: {pairs}N)Úsynthetic_qa_config©óÚ\/home/james-whalen/.local/lib/python3.13/site-packages/unsloth/dataprep/synthetic_configs.pyÚrsðð`Ñr