diff --git a/README.md b/README.md index 344939f40..fbcc215ef 100644 --- a/README.md +++ b/README.md @@ -22,19 +22,6 @@ The key features of the Intelligence Layer are: 4. [Use-case index](#use-case-index) 5. [How to make your own use-case](#how-to-make-your-own-use-case) -To give you a starting point for using the Intelligence Layer, we provide some pre-configured `Task`s that are ready to use out-of-the-box, as well as an accompanying "Getting started" guide in the form of Jupyter Notebooks. - -| Type | Task | Description | -| --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | -| Classify | [EmbeddingBasedClassify](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.use_cases.html#intelligence_layer.use_cases.EmbeddingBasedClassify) | Classify a short text by computing its similarity with example texts for each class. | -| Classify | [SingleLabelClassify](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.use_cases.html#intelligence_layer.use_cases.SingleLabelClassify) | Classify a short text by assessing each class' probability using zero-shot prompting. | -| QA | [LongContextQa](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.use_cases.html#intelligence_layer.use_cases.LongContextQa) | Answer a question based on one document of any length. | -| QA | [MultipleChunkQa](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.use_cases.html#intelligence_layer.use_cases.MultipleChunkQa) | Answer a question based on a list of short texts. | -| QA | [RetrieverBasedQa](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.use_cases.html#intelligence_layer.use_cases.RetrieverBasedQa) | Answer a question based on a document base using a [BaseRetriever](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.connectors.html#intelligence_layer.connectors.BaseRetriever) implementation. | -| QA | [SingleChunkQa](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.use_cases.html#intelligence_layer.use_cases.SingleChunkQa) | Answer a question based on a short text. | -| Search | [Search](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.use_cases.html#intelligence_layer.use_cases.Search) | Search for texts in a document base using a [BaseRetriever](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.connectors.html#intelligence_layer.connectors.BaseRetriever) implementation. | -| Summarize | [ShortBodySummarize](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.use_cases.html#intelligence_layer.use_cases.ShortBodySummarize) | Condense a short text into a brief summary. | - ### How to make your own Note that we do not expect the above use cases to solve all of your issues. @@ -108,17 +95,16 @@ from intelligence_layer.core.task import Task To give you a starting point for using the Intelligence Layer, we provide some pre-configured `Task`s that are ready to use out-of-the-box, as well as an accompanying "Getting started" guide in the form of Jupyter Notebooks. -| Type | Task | Description | -| --------- | ------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------- | -| Classify | [EmbeddingBasedClassify](./src/intelligence_layer/use_cases/classify/embedding_based_classify.py) | Classify a text using the cosine similarity of its embeddings to examples | -| Classify | [SingleLabelClassify](./src/intelligence_layer/use_cases/classify/single_label_classify.py) | Classify a text given labels using zero-shot prompting | -| QA | [LongContextQa](./src/intelligence_layer/use_cases/qa/long_context_qa.py) | Answer a question based on one document of any length | -| QA | [MultipleChunkQa](./src/intelligence_layer/use_cases/qa/multiple_chunk_qa.py) | Answer a question based a list of text chunks | -| QA | [RetrieverBasedQa](./src/intelligence_layer/use_cases/qa/retriever_based_qa.py) | Answer a question based on a document base | -| QA | [SingleChunkQa](./src/intelligence_layer/use_cases/qa/single_chunk_qa.py) | Answer a question based on a single text chunk | -| Search | [QdrantSearch](./src/intelligence_layer/use_cases/search/qdrant_search.py) | Search through texts given a query and some filters | -| Search | [Search](./src/intelligence_layer/use_cases/search/search.py) | Search through texts given a query | -| Summarize | [ShortBodySummarize](./src/intelligence_layer/use_cases/summarize/summarize.py) | Summarize a single text chunk into a short body text | +| Type | Task | Description | +| --------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ | +| Classify | [EmbeddingBasedClassify](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.use_cases.html#intelligence_layer.use_cases.EmbeddingBasedClassify) | Classify a short text by computing its similarity with example texts for each class. | +| Classify | [SingleLabelClassify](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.use_cases.html#intelligence_layer.use_cases.SingleLabelClassify) | Classify a short text by assessing each class' probability using zero-shot prompting. | +| QA | [LongContextQa](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.use_cases.html#intelligence_layer.use_cases.LongContextQa) | Answer a question based on one document of any length. | +| QA | [MultipleChunkQa](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.use_cases.html#intelligence_layer.use_cases.MultipleChunkQa) | Answer a question based on a list of short texts. | +| QA | [RetrieverBasedQa](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.use_cases.html#intelligence_layer.use_cases.RetrieverBasedQa) | Answer a question based on a document base using a [BaseRetriever](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.connectors.html#intelligence_layer.connectors.BaseRetriever) implementation. | +| QA | [SingleChunkQa](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.use_cases.html#intelligence_layer.use_cases.SingleChunkQa) | Answer a question based on a short text. | +| Search | [Search](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.use_cases.html#intelligence_layer.use_cases.Search) | Search for texts in a document base using a [BaseRetriever](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.connectors.html#intelligence_layer.connectors.BaseRetriever) implementation. | +| Summarize | [ShortBodySummarize](https://glowing-tribble-223446r.pages.github.io/intelligence_layer.use_cases.html#intelligence_layer.use_cases.ShortBodySummarize) | Condense a short text into a brief summary. | ## How to make your own use-case