synapt-extract 0.3.2

SynaptExtraction IL v1 -- schema, validation, and finalization

synapt-extract

SynaptExtraction is the intermediate language (IL) for synapt's product stack. It is the universal exchange format between text extraction and intelligence operations.

Any text + Any LLM  ->  SynaptExtraction (IL)  ->  @synapt/memory (intelligence)

Install

pip install synapt-extract

Quick start

from synapt_extract import (
    build_extraction_prompt,
    finalize_extraction,
    FinalizeContext,
)

# 1. Build a prompt
prompt = build_extraction_prompt(text, profile="standard")

# 2. Send to any LLM, parse JSON response
llm_output = json.loads(llm.complete(prompt))

# 3. Finalize
result = finalize_extraction(llm_output, FinalizeContext(
    produced_by="openai://gpt-4o-mini",
    user_id=user_id,
    kind="conversa/prayer",
))

assert result.validation.valid

Prompt profiles

Profile	Model class	Capabilities
minimal	3B-7B local	entities, entity_state, goals, themes, summary
standard	GPT-4o-mini, Haiku	+ entity_context, goal_timing, facts, temporal_refs, sentiment, evidence_anchoring
full	GPT-4o, Sonnet, Opus	+ entity_ids, goal_entity_refs, relations, relation_origin, assertion_signals, temporal_classes

Prompt and schema builder

Use the builder when the model API supports structured output. It resolves capabilities once, then builds the matching prompt, Stage 1 JSON schema, OpenAI response format, finalized packet schema, and optional finalization context.

from synapt_extract import create_extraction_builder

builder = (
    create_extraction_builder(text, profile="standard")
    .add_capabilities(["entity_ids", "goal_entity_refs"])
    .with_extracted_at("2026-05-11T18:00:00Z")
    .with_produced_by({
        "model": "openai://gpt-5.5",
        "model_version": "gpt-5.5-2026-04-23",
        "configuration": {"reasoning_effort": "medium"},
        "operator": "synapt-dev",
    })
    .with_source(source_id="note-1", source_type="note")
)

built = builder.build(name="synapt_extract_stage1")

# Send built["prompt"] and built["response_format"] to the model.
# Then call builder.finalize(stage1_json) or finalize_extraction(stage1_json, builder.finalize_context()).

build_extraction_schema() returns the semantic Stage 1 schema. build_extraction_response_format() returns an OpenAI-compatible json_schema response format; strict mode requires every object property as OpenAI expects and represents semantic optional fields as nullable. build_finalized_extraction_schema() returns the finalized packet shape, including produced_by, source context, capabilities, embeddings, and extensions.

Links

• Repository
• JSON Schema
• TypeScript package

License

MIT