diff --git a/docs/extras/modules/data_connection/retrievers/how_to/self_query/chroma_self_query.ipynb b/docs/extras/modules/data_connection/retrievers/how_to/self_query/chroma_self_query.ipynb index 2814e3c1..e1b8f096 100644 --- a/docs/extras/modules/data_connection/retrievers/how_to/self_query/chroma_self_query.ipynb +++ b/docs/extras/modules/data_connection/retrievers/how_to/self_query/chroma_self_query.ipynb @@ -5,7 +5,7 @@ "id": "13afcae7", "metadata": {}, "source": [ - "# Self-querying with Chroma\n", + "# Chroma self-querying \n", "\n", ">[Chroma](https://docs.trychroma.com/getting-started) is a database for building AI applications with embeddings.\n", "\n", diff --git a/docs/extras/modules/data_connection/retrievers/how_to/self_query/qdrant_self_query.ipynb b/docs/extras/modules/data_connection/retrievers/how_to/self_query/qdrant_self_query.ipynb index b26e4786..a2390813 100644 --- a/docs/extras/modules/data_connection/retrievers/how_to/self_query/qdrant_self_query.ipynb +++ b/docs/extras/modules/data_connection/retrievers/how_to/self_query/qdrant_self_query.ipynb @@ -6,7 +6,7 @@ "id": "13afcae7", "metadata": {}, "source": [ - "# Self-querying with Qdrant\n", + "# Qdrant self-querying \n", "\n", ">[Qdrant](https://qdrant.tech/documentation/) (read: quadrant ) is a vector similarity search engine. It provides a production-ready service with a convenient API to store, search, and manage points - vectors with an additional payload. `Qdrant` is tailored to extended filtering support. It makes it useful \n", "\n", @@ -222,9 +222,7 @@ "cell_type": "code", "execution_count": 7, "id": "fc3f1e6e", - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -422,7 +420,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.3" + "version": "3.10.6" } }, "nbformat": 4, diff --git a/docs/extras/modules/data_connection/retrievers/how_to/self_query/weaviate_self_query.ipynb b/docs/extras/modules/data_connection/retrievers/how_to/self_query/weaviate_self_query.ipynb index bbb05a0e..372c1249 100644 --- a/docs/extras/modules/data_connection/retrievers/how_to/self_query/weaviate_self_query.ipynb +++ b/docs/extras/modules/data_connection/retrievers/how_to/self_query/weaviate_self_query.ipynb @@ -5,7 +5,7 @@ "id": "13afcae7", "metadata": {}, "source": [ - "# Self-querying with Weaviate" + "# Weaviate self-querying " ] }, { @@ -293,7 +293,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.10" + "version": "3.10.6" } }, "nbformat": 4, diff --git a/docs/extras/modules/data_connection/retrievers/integrations/merger_retriever.ipynb b/docs/extras/modules/data_connection/retrievers/integrations/merger_retriever.ipynb index 00217414..14e0b3ab 100644 --- a/docs/extras/modules/data_connection/retrievers/integrations/merger_retriever.ipynb +++ b/docs/extras/modules/data_connection/retrievers/integrations/merger_retriever.ipynb @@ -1,16 +1,15 @@ { "cells": [ { - "attachments": {}, "cell_type": "markdown", "id": "fc0db1bc", "metadata": {}, "source": [ "# LOTR (Merger Retriever)\n", "\n", - "Lord of the Retrievers, also known as MergerRetriever, takes a list of retrievers as input and merges the results of their get_relevant_documents() methods into a single list. The merged results will be a list of documents that are relevant to the query and that have been ranked by the different retrievers.\n", + "`Lord of the Retrievers`, also known as `MergerRetriever`, takes a list of retrievers as input and merges the results of their get_relevant_documents() methods into a single list. The merged results will be a list of documents that are relevant to the query and that have been ranked by the different retrievers.\n", "\n", - "The MergerRetriever class can be used to improve the accuracy of document retrieval in a number of ways. First, it can combine the results of multiple retrievers, which can help to reduce the risk of bias in the results. Second, it can rank the results of the different retrievers, which can help to ensure that the most relevant documents are returned first." + "The `MergerRetriever` class can be used to improve the accuracy of document retrieval in a number of ways. First, it can combine the results of multiple retrievers, which can help to reduce the risk of bias in the results. Second, it can rank the results of the different retrievers, which can help to ensure that the most relevant documents are returned first." ] }, { @@ -71,7 +70,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "c152339d", "metadata": {}, diff --git a/docs/extras/modules/data_connection/retrievers/integrations/pubmed.ipynb b/docs/extras/modules/data_connection/retrievers/integrations/pubmed.ipynb index fd711fc7..6e0ce8a7 100644 --- a/docs/extras/modules/data_connection/retrievers/integrations/pubmed.ipynb +++ b/docs/extras/modules/data_connection/retrievers/integrations/pubmed.ipynb @@ -5,11 +5,11 @@ "id": "3df0dcf8", "metadata": {}, "source": [ - "# PubMed Retriever\n", + "# PubMed\n", "\n", - "This notebook goes over how to use PubMed as a retriever\n", + "This notebook goes over how to use `PubMed` as a retriever\n", "\n", - "PubMed® comprises more than 35 million citations for biomedical literature from MEDLINE, life science journals, and online books. Citations may include links to full text content from PubMed Central and publisher web sites." + "`PubMed®` comprises more than 35 million citations for biomedical literature from `MEDLINE`, life science journals, and online books. Citations may include links to full text content from `PubMed Central` and publisher web sites." ] }, { @@ -72,7 +72,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.1" + "version": "3.10.6" } }, "nbformat": 4,