From 027f1c94f97ff468f9fb33edb31cb3eade474d2e Mon Sep 17 00:00:00 2001 From: Erika Pham Date: Wed, 17 Apr 2024 16:03:28 -0400 Subject: [PATCH] Update basic-rag readme & sphinx documentations --- cookbook/Basic-RAG/README.md | 2 +- src/docs/get_started.installation.rst | 4 ++-- src/docs/get_started.vectordb.rst | 19 +++++++++++++------ 3 files changed, 16 insertions(+), 9 deletions(-) diff --git a/cookbook/Basic-RAG/README.md b/cookbook/Basic-RAG/README.md index dd8f74c..be1807a 100644 --- a/cookbook/Basic-RAG/README.md +++ b/cookbook/Basic-RAG/README.md @@ -3,7 +3,7 @@ Welcome to the Basic RAG Cookbook! This repository is dedicated to showcasing how to utilize the Retrieval-Augmented Generation (RAG) model for various applications using custom and few-shot prompts. For in depth understanding of RAG pipelines, chains, and prompts -check [RAG-Piplines.md](https://github.com/arjbingly/Capstone_5/blob/main/projects/Basic-RAG/RAG-Piplines.md) +check [RAG-Pipelines.md](https://github.com/arjbingly/Capstone_5/blob/main/cookbook/Basic-RAG/RAG-PIPELINES.md) ### Contents: diff --git a/src/docs/get_started.installation.rst b/src/docs/get_started.installation.rst index 642b298..27ce014 100644 --- a/src/docs/get_started.installation.rst +++ b/src/docs/get_started.installation.rst @@ -1,9 +1,9 @@ Installation =============== -*Since we are just in the development phase we have not published to pypi yet.* +*Since we are under the development phase, we have not published to pypi yet.* * ``git clone`` the repository * ``pip install .`` from the repository * *For Developers*: ``pip install -e .`` -Moreover, further customization can be made on the config file, `src/config.ini`. +Further customization can be made on the config file, `src/config.ini`. diff --git a/src/docs/get_started.vectordb.rst b/src/docs/get_started.vectordb.rst index cf158b0..ff96e80 100644 --- a/src/docs/get_started.vectordb.rst +++ b/src/docs/get_started.vectordb.rst @@ -1,7 +1,8 @@ Vector Stores =============== -# Explain what a vector store is... +Vector store or vector database is a type of database that stores data in high-dimensional vectors. +This is a crucial component of RAG, storing embeddings for both retrieval and generation processes. Supported Vector Stores ######################## @@ -9,28 +10,33 @@ Supported Vector Stores Currently supported vectorstores are: 1. Chroma -2. Deeplake +2. DeepLake Chroma ******* Since Chroma is a server-client based vector database, make sure to run the server. -* To run Chroma locally, either use move to `src/scripts` then run `source run_chroma.sh` or refer to - `Running Chroma in ClientServer `_. +* To run Chroma locally, either: + 1. Move to `src/scripts` then run ``source run_chroma.sh`` OR + 2. Refer to `Running Chroma in ClientServer `_. This by default runs on port 8000. -* If Chroma is not run locally, change `host` and `port` under `chroma` in `src/config.ini`, or provide the arguments +* If Chroma is not run locally, change ``host`` and ``port`` under ``chroma`` in `src/config.ini`, or provide the arguments explicitly. +For non-supported vectorstores, (...) Embeddings ########### -* By default, the embedding model is `instructor-xl`. Can be changed by changing `embedding_type` and `embedding_model` +* By default, the embedding model is `instructor-xl`. Can be changed by changing ``embedding_type`` and ``embedding_model`` in `src/config.ini` or providing the arguments explicitly. * Any huggingface embeddings can be used. Data Ingestion ############### + +For more details on data ingestion, refer to our `cookbook`_. + :: client = DeepLakeClient() # Any vectordb client @@ -41,3 +47,4 @@ Data Ingestion retriever.ingest(dir_path) +