From a42ad4a73977ffe17938d85dd93ec3913d782515 Mon Sep 17 00:00:00 2001 From: Cell Date: Wed, 25 Sep 2024 07:00:33 -0400 Subject: [PATCH] AB#3538: issue: 'https://docs.trychroma.com/embeddings' hyperlink is not working. Fix: update with using 'https://docs.trychroma.com/guides/embeddings' (#3539) Co-authored-by: CellCS Co-authored-by: Li Jiang --- autogen/agentchat/contrib/retrieve_user_proxy_agent.py | 2 +- autogen/retrieve_utils.py | 4 ++-- website/blog/2023-10-18-RetrieveChat/index.mdx | 2 +- 3 files changed, 4 insertions(+), 4 deletions(-) diff --git a/autogen/agentchat/contrib/retrieve_user_proxy_agent.py b/autogen/agentchat/contrib/retrieve_user_proxy_agent.py index 10b70e0e9720..b247d7a158f6 100644 --- a/autogen/agentchat/contrib/retrieve_user_proxy_agent.py +++ b/autogen/agentchat/contrib/retrieve_user_proxy_agent.py @@ -178,7 +178,7 @@ def __init__( vector db. Default is None, SentenceTransformer with the given `embedding_model` will be used. If you want to use OpenAI, Cohere, HuggingFace or other embedding functions, you can pass it here, - follow the examples in `https://docs.trychroma.com/embeddings`. + follow the examples in `https://docs.trychroma.com/guides/embeddings`. - `customized_prompt` (Optional, str) - the customized prompt for the retrieve chat. Default is None. - `customized_answer_prefix` (Optional, str) - the customized answer prefix for the diff --git a/autogen/retrieve_utils.py b/autogen/retrieve_utils.py index 9393903ec86c..4fb53c7c9600 100644 --- a/autogen/retrieve_utils.py +++ b/autogen/retrieve_utils.py @@ -365,7 +365,7 @@ def create_vector_db_from_dir( embedding_function is not None. embedding_function (Optional, Callable): the embedding function to use. Default is None, SentenceTransformer with the given `embedding_model` will be used. If you want to use OpenAI, Cohere, HuggingFace or other embedding - functions, you can pass it here, follow the examples in `https://docs.trychroma.com/embeddings`. + functions, you can pass it here, follow the examples in `https://docs.trychroma.com/guides/embeddings`. custom_text_split_function (Optional, Callable): a custom function to split a string into a list of strings. Default is None, will use the default function in `autogen.retrieve_utils.split_text_to_chunks`. custom_text_types (Optional, List[str]): a list of file types to be processed. Default is TEXT_FORMATS. @@ -448,7 +448,7 @@ def query_vector_db( embedding_function is not None. embedding_function (Optional, Callable): the embedding function to use. Default is None, SentenceTransformer with the given `embedding_model` will be used. If you want to use OpenAI, Cohere, HuggingFace or other embedding - functions, you can pass it here, follow the examples in `https://docs.trychroma.com/embeddings`. + functions, you can pass it here, follow the examples in `https://docs.trychroma.com/guides/embeddings`. Returns: diff --git a/website/blog/2023-10-18-RetrieveChat/index.mdx b/website/blog/2023-10-18-RetrieveChat/index.mdx index d3ad6aff3287..10fcd8f0ed4e 100644 --- a/website/blog/2023-10-18-RetrieveChat/index.mdx +++ b/website/blog/2023-10-18-RetrieveChat/index.mdx @@ -176,7 +176,7 @@ huggingface_ef = embedding_functions.HuggingFaceEmbeddingFunction( ) ``` -More examples can be found [here](https://docs.trychroma.com/embeddings). +More examples can be found [here](https://docs.trychroma.com/guides/embeddings). ### Customizing Text Split Function Before we can store the documents into a vector database, we need to split the texts into chunks. Although