From c12dc2b7e0b6d3aa6dda1c29245df4a72f039067 Mon Sep 17 00:00:00 2001 From: Andreas Motl Date: Mon, 16 Sep 2024 12:28:18 +0200 Subject: [PATCH] Chore: Fix broken links --- docs/_include/links.md | 2 +- docs/domain/ml/index.md | 8 ++++---- docs/feature/search/vector/index.md | 2 +- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/docs/_include/links.md b/docs/_include/links.md index b6572e7..6ffedcd 100644 --- a/docs/_include/links.md +++ b/docs/_include/links.md @@ -13,7 +13,7 @@ [Geospatial Data Model]: https://cratedb.com/data-model/geospatial [Geospatial Database]: https://cratedb.com/geospatial-spatial-database [HNSW]: https://en.wikipedia.org/wiki/Hierarchical_navigable_small_world -[HNSW paper]: https://arxiv.org/pdf/1603.09320.pdf +[HNSW paper]: https://arxiv.org/pdf/1603.09320 [HoloViews]: https://www.holoviews.org/ [Indexing, Columnar Storage, and Aggregations]: https://cratedb.com/product/features/indexing-columnar-storage-aggregations [inverted index]: https://en.wikipedia.org/wiki/Inverted_index diff --git a/docs/domain/ml/index.md b/docs/domain/ml/index.md index 768ac05..24bdee1 100644 --- a/docs/domain/ml/index.md +++ b/docs/domain/ml/index.md @@ -366,10 +366,10 @@ tensorflow [How to Use Private Data in Generative AI]: https://youtu.be/icquKckM4o0?feature=shared [Jupyter Notebook]: https://jupyter.org/ [LangChain]: https://python.langchain.com/ -[LangChain: Analyzing structured data]: https://python.langchain.com/docs/use_cases/extraction/ -[LangChain: Chatbots]: https://python.langchain.com/docs/use_cases/chatbots -[LangChain: Q&A with SQL]: https://python.langchain.com/docs/use_cases/sql/ -[LangChain: Retrieval augmented generation]: https://python.langchain.com/docs/use_cases/question_answering/ +[LangChain: Analyzing structured data]: https://python.langchain.com/docs/how_to/#extraction +[LangChain: Chatbots]: https://python.langchain.com/docs/how_to/#chatbots +[LangChain: Q&A with SQL]: https://python.langchain.com/docs/how_to/#qa-over-sql--csv +[LangChain: Retrieval augmented generation]: https://python.langchain.com/docs/tutorials/sql_qa/ [langchain-conversational-history-binder]: https://mybinder.org/v2/gh/crate/cratedb-examples/main?labpath=topic%2Fmachine-learning%2Fllm-langchain%2Fconversational_memory.ipynb [langchain-conversational-history-colab]: https://colab.research.google.com/github/crate/cratedb-examples/blob/main/topic/machine-learning/llm-langchain/conversational_memory.ipynb [langchain-conversational-history-github]: https://github.com/crate/cratedb-examples/blob/main/topic/machine-learning/llm-langchain/conversational_memory.ipynb diff --git a/docs/feature/search/vector/index.md b/docs/feature/search/vector/index.md index ff1e51b..287b359 100644 --- a/docs/feature/search/vector/index.md +++ b/docs/feature/search/vector/index.md @@ -274,7 +274,7 @@ features of Lucene 9, and about the journey of implementing HNSW from -[Lucene Is All You Need]: https://arxiv.org/pdf/2308.14963.pdf +[Lucene Is All You Need]: https://arxiv.org/pdf/2308.14963 [making of Lucene vector search]: https://www.apachecon.com/acna2022/slides/04_lucene_vector_search_sokolov.pdf [Time series data in manufacturing]: https://github.com/crate/cratedb-datasets/raw/main/machine-learning/fulltext/White%20paper%20-%20Time-series%20data%20in%20manufacturing.pdf [Uwe Schindler - What's coming next with Apache Lucene?]: https://youtu.be/EHJjSYWjIF0?t=330s&feature=shared