Update README.md

README.md

@@ -16,7 +16,9 @@ tags:
 - books
 - LLM
 ---
-# Vector store of embeddings for the book "1984" by George Orwell
+# Vector store of embeddings for books 
+- **"1984" by George Orwell**
+- **"The Almanac of Naval Ravikant" by Eric Jorgenson**
 
 This is a [faiss](https://github.com/facebookresearch/faiss) vector store created with [instructor embeddings](https://github.com/HKUNLP/instructor-embedding) using [LangChain](https://langchain.readthedocs.io/en/latest/modules/indexes/examples/embeddings.html#instructembeddings) . Use it for similarity search, question answering or anything else that leverages embeddings! 😃
 
@@ -25,8 +27,11 @@ Creating these embeddings can take a while so here's a convenient, downloadable
 
 ## How to use
 
-1. Download data
-2. Load to use with LangChain
+1. Specify the book
+   - `1984`
+   - `The Almanac of Naval Ravikant`
+3. Download data
+4. Load to use with LangChain
 
 pip install -qqq langchain InstructorEmbedding sentence_transformers faiss-cpu huggingface_hub
 
@@ -36,12 +41,13 @@ from langchain.embeddings import HuggingFaceInstructEmbeddings
 from langchain.vectorstores.faiss import FAISS
 from huggingface_hub import snapshot_download
 
-# download the `vectorstore` folder
+# download the vectorstore for the book you want
+book="1984"
 cache_dir="orwell_faiss"
 vectorstore = snapshot_download(repo_id="calmgoose/orwell-1984_faiss-instructembeddings",
                                 repo_type="dataset",
                                 revision="main",
-                                allow_patterns="vectorstore/*",
+                                allow_patterns=f"books/{book}/*",
                                 cache_dir=cache_dir,
                                 )