From 833f6c033dc8aab059287f8f9c8773066c0655b2 Mon Sep 17 00:00:00 2001 From: Victoria Slocum Date: Tue, 18 Jul 2023 13:22:25 +0200 Subject: [PATCH] fix links --- website/docs/api/large-language-models.mdx | 104 +++++++++---------- website/docs/usage/large-language-models.mdx | 12 ++- 2 files changed, 59 insertions(+), 57 deletions(-) diff --git a/website/docs/api/large-language-models.mdx b/website/docs/api/large-language-models.mdx index 6deea336a..85bca7e60 100644 --- a/website/docs/api/large-language-models.mdx +++ b/website/docs/api/large-language-models.mdx @@ -163,16 +163,16 @@ descriptions. > examples = null > ``` -| Argument | Description | -| ------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `labels` | List of labels or str of comma-separated list of labels. ~~Union[List[str], str]~~ | -| `template` | Custom prompt template to send to LLM model. Default templates for each task are located in the `spacy_llm/tasks/templates` directory. Defaults to [ner.v2.jinja](https://github.com/spacy-llm/spacy_llm/tasks/templates/ner.v2.jinja). ~~str~~ | -| `label_definitions` | Optional dict mapping a label to a description of that label. These descriptions are added to the prompt to help instruct the LLM on what to extract. Defaults to `None`. ~~Optional[Dict[str, str]]~~ | -| `examples` | Optional function that generates examples for few-shot learning. Defaults to `None`. ~~Optional[Callable[[], Iterable[Any]]]~~ | -| `normalizer` | Function that normalizes the labels as returned by the LLM. If `None`, defaults to `spacy.LowercaseNormalizer.v1`. Defaults to `None`. ~~Optional[Callable[[str], str]]~~ | -| `alignment_mode` | Alignment mode in case the LLM returns entities that do not align with token boundaries. Options are `"strict"`, `"contract"` or `"expand"`. Defaults to `"contract"`. ~~str~~ | -| `case_sensitive_matching` | Whether to search without case sensitivity. Defaults to `False`. ~~bool~~ | -| `single_match` | Whether to match an entity in the LLM's response only once (the first hit) or multiple times. Defaults to `False`. ~~bool~~ | +| Argument | Description | +| ------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `labels` | List of labels or str of comma-separated list of labels. ~~Union[List[str], str]~~ | +| `template` | Custom prompt template to send to LLM model. Default templates for each task are located in the `spacy_llm/tasks/templates` directory. Defaults to [ner.v2.jinja](https://github.com/explosion/spacy-llm/blob/main/spacy_llm/tasks/templates/ner.v2.jinja). ~~str~~ | +| `label_definitions` | Optional dict mapping a label to a description of that label. These descriptions are added to the prompt to help instruct the LLM on what to extract. Defaults to `None`. ~~Optional[Dict[str, str]]~~ | +| `examples` | Optional function that generates examples for few-shot learning. Defaults to `None`. ~~Optional[Callable[[], Iterable[Any]]]~~ | +| `normalizer` | Function that normalizes the labels as returned by the LLM. If `None`, defaults to `spacy.LowercaseNormalizer.v1`. Defaults to `None`. ~~Optional[Callable[[str], str]]~~ | +| `alignment_mode` | Alignment mode in case the LLM returns entities that do not align with token boundaries. Options are `"strict"`, `"contract"` or `"expand"`. Defaults to `"contract"`. ~~str~~ | +| `case_sensitive_matching` | Whether to search without case sensitivity. Defaults to `False`. ~~bool~~ | +| `single_match` | Whether to match an entity in the LLM's response only once (the first hit) or multiple times. Defaults to `False`. ~~bool~~ | The NER task implementation doesn't currently ask the LLM for specific offsets, but simply expects a list of strings that represent the enties in the document. @@ -326,17 +326,17 @@ overlapping entities and store its annotations in `doc.spans`. > examples = null > ``` -| Argument | Description | -| ------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `labels` | List of labels or str of comma-separated list of labels. ~~Union[List[str], str]~~ | -| `template` | Custom prompt template to send to LLM model. Default templates for each task are located in the `spacy_llm/tasks/templates` directory. Defaults to [`spancat.v2.jinja`](https://github.com/spacy-llm/spacy_llm/tasks/templates/spancat.v2.jinja). ~~str~~ | -| `label_definitions` | Optional dict mapping a label to a description of that label. These descriptions are added to the prompt to help instruct the LLM on what to extract. Defaults to `None`. ~~Optional[Dict[str, str]]~~ | -| `spans_key` | Key of the `Doc.spans` dict to save the spans under. Defaults to `"sc"`. ~~str~~ | -| `examples` | Optional function that generates examples for few-shot learning. Defaults to `None`. ~~Optional[Callable[[], Iterable[Any]]]~~ | -| `normalizer` | Function that normalizes the labels as returned by the LLM. If `None`, defaults to `spacy.LowercaseNormalizer.v1`. ~~Optional[Callable[[str], str]]~~ | -| `alignment_mode` | Alignment mode in case the LLM returns entities that do not align with token boundaries. Options are `"strict"`, `"contract"` or `"expand"`. Defaults to `"contract"`. ~~str~~ | -| `case_sensitive_matching` | Whether to search without case sensitivity. Defaults to `False`. ~~bool~~ | -| `single_match` | Whether to match an entity in the LLM's response only once (the first hit) or multiple times. Defaults to `False`. ~~bool~~ | +| Argument | Description | +| ------------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `labels` | List of labels or str of comma-separated list of labels. ~~Union[List[str], str]~~ | +| `template` | Custom prompt template to send to LLM model. Default templates for each task are located in the `spacy_llm/tasks/templates` directory. Defaults to [`spancat.v2.jinja`](https://github.com/explosion/spacy-llm/blob/main/spacy_llm/tasks/templates/spancat.v2.jinja). ~~str~~ | +| `label_definitions` | Optional dict mapping a label to a description of that label. These descriptions are added to the prompt to help instruct the LLM on what to extract. Defaults to `None`. ~~Optional[Dict[str, str]]~~ | +| `spans_key` | Key of the `Doc.spans` dict to save the spans under. Defaults to `"sc"`. ~~str~~ | +| `examples` | Optional function that generates examples for few-shot learning. Defaults to `None`. ~~Optional[Callable[[], Iterable[Any]]]~~ | +| `normalizer` | Function that normalizes the labels as returned by the LLM. If `None`, defaults to `spacy.LowercaseNormalizer.v1`. ~~Optional[Callable[[str], str]]~~ | +| `alignment_mode` | Alignment mode in case the LLM returns entities that do not align with token boundaries. Options are `"strict"`, `"contract"` or `"expand"`. Defaults to `"contract"`. ~~str~~ | +| `case_sensitive_matching` | Whether to search without case sensitivity. Defaults to `False`. ~~bool~~ | +| `single_match` | Whether to match an entity in the LLM's response only once (the first hit) or multiple times. Defaults to `False`. ~~bool~~ | Except for the `spans_key` parameter, the SpanCat task reuses the configuration from the NER task. Refer to [its documentation](#ner-v2) for more insight. @@ -388,16 +388,16 @@ definitions are included in the prompt. > examples = null > ``` -| Argument | Description | -| ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `labels` | List of labels or str of comma-separated list of labels. ~~Union[List[str], str]~~ | -| `label_definitions` | Dictionary of label definitions. Included in the prompt, if set. Defaults to `None`. ~~Optional[Dict[str, str]]~~ | -| `template` | Custom prompt template to send to LLM model. Default templates for each task are located in the `spacy_llm/tasks/templates` directory. Defaults to [`textcat.jinja`](https://github.com/spacy-llm/spacy_llm/tasks/templates/textcat.jinja). ~~str~~ | -| `examples` | Optional function that generates examples for few-shot learning. Defaults to `None`. ~~Optional[Callable[[], Iterable[Any]]]~~ | -| `normalizer` | Function that normalizes the labels as returned by the LLM. If `None`, falls back to `spacy.LowercaseNormalizer.v1`. Defaults to `None`. ~~Optional[Callable[[str], str]]~~ | -| `exclusive_classes` | If set to `True`, only one label per document should be valid. If set to `False`, one document can have multiple labels. Defaults to `False`. ~~bool~~ | -| `allow_none` | When set to `True`, allows the LLM to not return any of the given label. The resulting dict in `doc.cats` will have `0.0` scores for all labels. Defaults to `True`. ~~bool~~ | -| `verbose` | If set to `True`, warnings will be generated when the LLM returns invalid responses. Defaults to `False`. ~~bool~~ | +| Argument | Description | +| ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `labels` | List of labels or str of comma-separated list of labels. ~~Union[List[str], str]~~ | +| `label_definitions` | Dictionary of label definitions. Included in the prompt, if set. Defaults to `None`. ~~Optional[Dict[str, str]]~~ | +| `template` | Custom prompt template to send to LLM model. Default templates for each task are located in the `spacy_llm/tasks/templates` directory. Defaults to [`textcat.jinja`](https://github.com/explosion/spacy-llm/blob/main/spacy_llm/tasks/templates/textcat.jinja). ~~str~~ | +| `examples` | Optional function that generates examples for few-shot learning. Defaults to `None`. ~~Optional[Callable[[], Iterable[Any]]]~~ | +| `normalizer` | Function that normalizes the labels as returned by the LLM. If `None`, falls back to `spacy.LowercaseNormalizer.v1`. Defaults to `None`. ~~Optional[Callable[[str], str]]~~ | +| `exclusive_classes` | If set to `True`, only one label per document should be valid. If set to `False`, one document can have multiple labels. Defaults to `False`. ~~bool~~ | +| `allow_none` | When set to `True`, allows the LLM to not return any of the given label. The resulting dict in `doc.cats` will have `0.0` scores for all labels. Defaults to `True`. ~~bool~~ | +| `verbose` | If set to `True`, warnings will be generated when the LLM returns invalid responses. Defaults to `False`. ~~bool~~ | To perform [few-shot learning](/usage/large-langauge-models#few-shot-prompts), you can write down a few examples in a separate file, and provide these to be @@ -444,15 +444,15 @@ prompting and includes an improved prompt template. > examples = null > ``` -| Argument | Description | -| ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `labels` | List of labels or str of comma-separated list of labels. ~~Union[List[str], str]~~ | -| `template` | Custom prompt template to send to LLM model. Default templates for each task are located in the `spacy_llm/tasks/templates` directory. Defaults to [`textcat.jinja`](https://github.com/spacy-llm/spacy_llm/tasks/templates/textcat.jinja). ~~str~~ | -| `examples` | Optional function that generates examples for few-shot learning. Defaults to `None`. ~~Optional[Callable[[], Iterable[Any]]]~~ | -| `normalizer` | Function that normalizes the labels as returned by the LLM. If `None`, falls back to `spacy.LowercaseNormalizer.v1`. ~~Optional[Callable[[str], str]]~~ | -| `exclusive_classes` | If set to `True`, only one label per document should be valid. If set to `False`, one document can have multiple labels. Defaults to `False`. ~~bool~~ | -| `allow_none` | When set to `True`, allows the LLM to not return any of the given label. The resulting dict in `doc.cats` will have `0.0` scores for all labels. Defaults to `True`. ~~bool~~ | -| `verbose` | If set to `True`, warnings will be generated when the LLM returns invalid responses. Defaults to `False`. ~~bool~~ | +| Argument | Description | +| ------------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `labels` | List of labels or str of comma-separated list of labels. ~~Union[List[str], str]~~ | +| `template` | Custom prompt template to send to LLM model. Default templates for each task are located in the `spacy_llm/tasks/templates` directory. Defaults to [`textcat.jinja`](https://github.com/explosion/spacy-llm/blob/main/spacy_llm/tasks/templates/textcat.jinja). ~~str~~ | +| `examples` | Optional function that generates examples for few-shot learning. Defaults to `None`. ~~Optional[Callable[[], Iterable[Any]]]~~ | +| `normalizer` | Function that normalizes the labels as returned by the LLM. If `None`, falls back to `spacy.LowercaseNormalizer.v1`. ~~Optional[Callable[[str], str]]~~ | +| `exclusive_classes` | If set to `True`, only one label per document should be valid. If set to `False`, one document can have multiple labels. Defaults to `False`. ~~bool~~ | +| `allow_none` | When set to `True`, allows the LLM to not return any of the given label. The resulting dict in `doc.cats` will have `0.0` scores for all labels. Defaults to `True`. ~~bool~~ | +| `verbose` | If set to `True`, warnings will be generated when the LLM returns invalid responses. Defaults to `False`. ~~bool~~ | To perform [few-shot learning](/usage/large-langauge-models#few-shot-prompts), you can write down a few examples in a separate file, and provide these to be @@ -544,14 +544,14 @@ on an upstream NER component for entities extraction. > labels = ["LivesIn", "Visits"] > ``` -| Argument | Description | -| ------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `labels` | List of labels or str of comma-separated list of labels. ~~Union[List[str], str]~~ | -| `template` | Custom prompt template to send to LLM model. Default templates for each task are located in the `spacy_llm/tasks/templates` directory. Defaults to [`rel.jinja`](https://github.com/spacy-llm/spacy_llm/tasks/templates/rel.jinja). ~~str~~ | -| `label_description` | Dictionary providing a description for each relation label. Defaults to `None`. ~~Optional[Dict[str, str]]~~ | -| `examples` | Optional function that generates examples for few-shot learning. Defaults to `None`. ~~Optional[Callable[[], Iterable[Any]]]~~ | -| `normalizer` | Function that normalizes the labels as returned by the LLM. If `None`, falls back to `spacy.LowercaseNormalizer.v1`. Defaults to `None`. ~~Optional[Callable[[str], str]]~~ | -| `verbose` | If set to `True`, warnings will be generated when the LLM returns invalid responses. Defaults to `False`. ~~bool~~ | +| Argument | Description | +| ------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `labels` | List of labels or str of comma-separated list of labels. ~~Union[List[str], str]~~ | +| `template` | Custom prompt template to send to LLM model. Default templates for each task are located in the `spacy_llm/tasks/templates` directory. Defaults to [`rel.jinja`](https://github.com/explosion/spacy-llm/blob/main/spacy_llm/tasks/templates/rel.jinja). ~~str~~ | +| `label_description` | Dictionary providing a description for each relation label. Defaults to `None`. ~~Optional[Dict[str, str]]~~ | +| `examples` | Optional function that generates examples for few-shot learning. Defaults to `None`. ~~Optional[Callable[[], Iterable[Any]]]~~ | +| `normalizer` | Function that normalizes the labels as returned by the LLM. If `None`, falls back to `spacy.LowercaseNormalizer.v1`. Defaults to `None`. ~~Optional[Callable[[str], str]]~~ | +| `verbose` | If set to `True`, warnings will be generated when the LLM returns invalid responses. Defaults to `False`. ~~bool~~ | To perform [few-shot learning](/usage/large-langauge-models#few-shot-prompts), you can write down a few examples in a separate file, and provide these to be @@ -589,10 +589,10 @@ attribute in the doc's tokens accordingly. > examples = null > ``` -| Argument | Description | -| ---------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| `template` | Custom prompt template to send to LLM model. Default templates for each task are located in the `spacy_llm/tasks/templates` directory. Defaults to [lemma.jinja](https://github.com/spacy-llm/spacy_llm/tasks/templates/lemma.jinja). ~~str~~ | -| `examples` | Optional function that generates examples for few-shot learning. Defaults to `None`. ~~Optional[Callable[[], Iterable[Any]]]~~ | +| Argument | Description | +| ---------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| `template` | Custom prompt template to send to LLM model. Default templates for each task are located in the `spacy_llm/tasks/templates` directory. Defaults to [lemma.jinja](https://github.com/explosion/spacy-llm/blob/main/spacy_llm/tasks/templates/lemma.jinja). ~~str~~ | +| `examples` | Optional function that generates examples for few-shot learning. Defaults to `None`. ~~Optional[Callable[[], Iterable[Any]]]~~ | `Lemma.v1` prompts the LLM to lemmatize the passed text and return the lemmatized version as a list of tokens and their corresponding lemma. E. g. the diff --git a/website/docs/usage/large-language-models.mdx b/website/docs/usage/large-language-models.mdx index 8ec3907f8..18c7791e4 100644 --- a/website/docs/usage/large-language-models.mdx +++ b/website/docs/usage/large-language-models.mdx @@ -95,7 +95,7 @@ the [OpenAI](#openai) section. Create a config file `config.cfg` containing at least the following (or see the full example -[here](https://github.com/spacy-llm/usage_examples/textcat_openai)): +[here](https://github.com/explosion/spacy-llm/tree/main/usage_examples/textcat_openai)): ```ini [nlp] @@ -133,7 +133,8 @@ To run this example, ensure that you have a GPU enabled, and `transformers`, [DollyHF](#dollyhf-v1) section. Create a config file `config.cfg` containing at least the following (or see the -full example [here](https://github.com/spacy-llm/usage_examples/ner_dolly)): +full example +[here](https://github.com/explosion/spacy-llm/tree/main/usage_examples/ner_dolly)): ```ini [nlp] @@ -214,7 +215,7 @@ To register your custom task with spaCy, decorate a factory function using the to in your config. > 📖 For more details, see the -> [**usage example on writing your own task**](https://github.com/spacy-llm/usage_examples/README.md#writing-your-own-task) +> [**usage example on writing your own task**](https://github.com/explosion/spacy-llm/tree/main/usage_examples#writing-your-own-task) ```python from typing import Iterable, List @@ -354,8 +355,9 @@ structured information. All tasks are registered in spaCy's `llm_tasks` registry. Practically speaking, a task should adhere to the `Protocol` `LLMTask` defined -in [`ty.py`](https://github.com/spacy-llm/spacy_llm/ty.py). It needs to define a -`generate_prompts` function and a `parse_responses` function. +in [`ty.py`](https://github.com/explosion/spacy-llm/blob/main/spacy_llm/ty.py). +It needs to define a `generate_prompts` function and a `parse_responses` +function. | Task | Description | | --------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------ |