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Describe translation task.
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@ -236,6 +236,57 @@ objects. This depends on the return type of the [model](#models).
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| `responses` | The generated prompts. ~~Iterable[Any]~~ |
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| `responses` | The generated prompts. ~~Iterable[Any]~~ |
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| **RETURNS** | The annotated documents. ~~Iterable[Doc]~~ |
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| **RETURNS** | The annotated documents. ~~Iterable[Doc]~~ |
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### Translation {id="translation"}
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The translation task translates texts from a defined or inferred source to a
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defined target language.
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#### spacy.Translation.v1 {id="translation-v1"}
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`spacy.Translation.v1` supports both zero-shot and few-shot prompting.
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> #### Example config
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>
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> ```ini
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> [components.llm.task]
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> @llm_tasks = "spacy.Translation.v1"
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> examples = null
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> target_lang = "Spanish"
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> ```
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| Argument | Description |
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| --------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `template` | Custom prompt template to send to LLM model. Defaults to [summarization.v1.jinja](https://github.com/explosion/spacy-llm/blob/main/spacy_llm/tasks/templates/summarization.v1.jinja). ~~str~~ |
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| `examples` | Optional function that generates examples for few-shot learning. Defaults to `None`. ~~Optional[Callable[[], Iterable[Any]]]~~ |
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| `parse_responses` (NEW) | Callable for parsing LLM responses for this task. Defaults to the internal parsing method for this task. ~~Optional[TaskResponseParser[SummarizationTask]]~~ |
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| `prompt_example_type` (NEW) | Type to use for fewshot examples. Defaults to `SummarizationExample`. ~~Optional[Type[FewshotExample]]~~ |
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| `source_lang` | Language to translate from. Doesn't have to be set. ~~Optional[str]~~ |
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| `target_lang` | Language to translate to. No default value, has to be set. ~~str~~ |
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| `field` | Name of extension attribute to store translation in (i. e. the translation will be available in `doc._.{field}`). Defaults to `translation`. ~~str~~ |
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To perform [few-shot learning](/usage/large-language-models#few-shot-prompts),
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you can write down a few examples in a separate file, and provide these to be
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injected into the prompt to the LLM. The default reader `spacy.FewShotReader.v1`
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supports `.yml`, `.yaml`, `.json` and `.jsonl`.
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```yaml
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- text: 'Top of the morning to you!'
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translation: '¡Muy buenos días!'
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- text: 'The weather is great today.'
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translation: 'El clima está fantástico hoy.'
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- text: 'Do you know what will happen tomorrow?'
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translation: '¿Sabes qué pasará mañana?'
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```
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```ini
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[components.llm.task]
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@llm_tasks = "spacy.Translation.v1"
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target_lang = "Spanish"
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[components.llm.task.examples]
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@misc = "spacy.FewShotReader.v1"
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path = "translation_examples.yml"
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```
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### Summarization {id="summarization"}
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### Summarization {id="summarization"}
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A summarization task takes a document as input and generates a summary that is
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A summarization task takes a document as input and generates a summary that is
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