resolver_params Reference

resolver_params is a dict passed to lx.extract() to fine-tune how the model's output is parsed and aligned to source text. Keys may change across versions — check the current extract() docstring if in doubt.

Full example

result = lx.extract(
    text_or_documents=text,
    examples=examples,
    prompt_description=prompt,
    model_id="gemini-2.5-flash",
    resolver_params={
        "suppress_parse_errors": True,
        "extraction_index_suffix": "_index",
        "enable_fuzzy_alignment": True,
        "fuzzy_alignment_threshold": 0.75,
        "fuzzy_alignment_algorithm": "lcs",
        "fuzzy_alignment_min_density": 1 / 3,
        "accept_match_lesser": True,
    },
)

Key descriptions

• suppress_parse_errors (default True in extract()): on parse or schema errors for a chunk, log a warning and return [] for that chunk rather than raising. The chunk is effectively dropped; no partial output is recovered from the malformed response.
• extraction_index_suffix: attribute name suffix used to preserve extraction ordering (e.g. "_index" looks for attributes like medication_index and sorts extractions by that value).
• enable_fuzzy_alignment (default True): attempt fuzzy alignment when exact substring match fails.
• fuzzy_alignment_threshold (default 0.75): minimum fraction of extraction tokens that must be matched in the source span.
• fuzzy_alignment_algorithm (default "lcs"): algorithm for fuzzy alignment. "lcs" uses longest-common-subsequence DP (O(n*m²)); "legacy" uses the older difflib-based approach and is deprecated.
• fuzzy_alignment_min_density (default 1/3): minimum ratio of matched tokens to the span length. Filters out sparse matches where only a few tokens align across a very long source span.
• accept_match_lesser: accept MATCH_LESSER alignments — partial exact matches where the model's extraction_text is longer than the span that exactly matched in the source (e.g. the model returned a few extra tokens at the edges). This is distinct from fuzzy alignment: the matched portion is still an exact substring. Use it for truncation or extra-token cases, not as a substitute for lowering fuzzy_alignment_threshold.

When to tune these

• Too many char_interval=None extractions: lower fuzzy_alignment_threshold (e.g. 0.6). Enable accept_match_lesser only if the model is returning extraction_text that contains an exact source substring plus extra tokens.
• Fuzzy alignment matching the wrong span: raise fuzzy_alignment_min_density (e.g. 0.5) so matches must be denser.
• Performance-sensitive pipelines on long documents: stick with "lcs" and consider lowering max_char_buffer rather than disabling fuzzy alignment entirely.