From c3726092fdf5331bd7d7683f9444768af983d876 Mon Sep 17 00:00:00 2001 From: Vidit Ostwal <110953813+Vidit-Ostwal@users.noreply.github.com> Date: Tue, 6 May 2025 18:37:52 +0530 Subject: [PATCH] Added Advance Configuration Docs for Rag Tool (#2713) * Added Advance Configuration Docs for Rag Tool * Re-run test cases * Change doc * prepping new version (#2733) --------- Co-authored-by: Lucas Gomide Co-authored-by: Lorenze Jay <63378463+lorenzejay@users.noreply.github.com> --- docs/tools/ragtool.mdx | 20 +++++++++++++++++++- 1 file changed, 19 insertions(+), 1 deletion(-) diff --git a/docs/tools/ragtool.mdx b/docs/tools/ragtool.mdx index b03059152..b4c074fca 100644 --- a/docs/tools/ragtool.mdx +++ b/docs/tools/ragtool.mdx @@ -143,12 +143,30 @@ config = { "config": { "model": "text-embedding-ada-002" } + }, + "vectordb": { + "provider": "elasticsearch", + "config": { + "collection_name": "my-collection", + "cloud_id": "deployment-name:xxxx", + "api_key": "your-key", + "verify_certs": False + } + }, + "chunker": { + "chunk_size": 400, + "chunk_overlap": 100, + "length_function": "len", + "min_chunk_size": 0 } } rag_tool = RagTool(config=config, summarize=True) ``` -## Conclusion +The internal RAG tool utilizes the Embedchain adapter, allowing you to pass any configuration options that are supported by Embedchain. +You can refer to the [Embedchain documentation](https://docs.embedchain.ai/components/introduction) for details. +Make sure to review the configuration options available in the .yaml file. +## Conclusion The `RagTool` provides a powerful way to create and query knowledge bases from various data sources. By leveraging Retrieval-Augmented Generation, it enables agents to access and retrieve relevant information efficiently, enhancing their ability to provide accurate and contextually appropriate responses.