[llm unify 5a/n] Add JinjaPompt and re-convert extract entities #1161
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Signed-off-by: Henry Lindeman <hmlindeman@yahoo.com>
Signed-off-by: Henry Lindeman <hmlindeman@yahoo.com>
Signed-off-by: Henry Lindeman <hmlindeman@yahoo.com>
Signed-off-by: Henry Lindeman <hmlindeman@yahoo.com>
Signed-off-by: Henry Lindeman <hmlindeman@yahoo.com>
Signed-off-by: Henry Lindeman <hmlindeman@yahoo.com>
baitsguy
reviewed
Feb 7, 2025
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| def validate(d: Document) -> bool: | ||
| if self._tokenizer is not None: | ||
| return d.properties.get(self._entity_name, "None") != "None" |
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self._entity_name in d.properties?
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discussed offline, we need to check for "None" because that's what the llm returns if no val
| if self._tokenizer is not None: | ||
| return d.properties.get(self._entity_name, "None") != "None" | ||
| else: | ||
| return True |
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can just combine the if else
| return d | ||
| batches.append(curr_club) | ||
| else: | ||
| batches = [[i for e, i in elements[: self._num_of_elements]]] |
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mind adding a comment saying if no tokenizer we process each element separately because we don't know how many we can combine?
| from sycamore.data import Element, Document | ||
| from sycamore.llms import LLM | ||
| from sycamore.llms.prompts.default_prompts import ( | ||
| EntityExtractorZeroShotGuidancePrompt, |
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can we start deleting these if we're not using? the set of prompts is growing
Signed-off-by: Henry Lindeman <hmlindeman@yahoo.com>
baitsguy
approved these changes
Feb 7, 2025
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Also refactors entity extractor to break up the megafunction