Update basic-rag readme & sphinx documentations

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:
 

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`.

src/docs/get_started.vectordb.rst

@@ -1,36 +1,42 @@
 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
 ########################
 
 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 <https://docs.trychroma.com/usage-guide#running-chroma-in-clientserver-mode>`_.
+* To run Chroma locally, either:
+  1. Move to `src/scripts` then run ``source run_chroma.sh`` OR
+  2. Refer to `Running Chroma in ClientServer <https://docs.trychroma.com/usage-guide#running-chroma-in-clientserver-mode>`_.
   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<https://github.com/arjbingly/Capstone_5/blob/main/cookbook/Basic-RAG/README.md>`_.
+
 ::
 
     client = DeepLakeClient() # Any vectordb client
@@ -41,3 +47,4 @@ Data Ingestion
 
 
     retriever.ingest(dir_path)
+