SMU Library Chatbot

.env.example

@@ -86,7 +86,7 @@ CHUNCK_SIZE=1024
 CHUNK_OVERLAP=64
 SOURCE_PATH="data/pdfs/smu_lib_html/"
 
-# Index for SMU LibBot PDF files - chunk_size=1024 chunk_overlap=512
+# Index for SMU Library Chatbot PDF files - chunk_size=1024 chunk_overlap=512
 FAISS_INDEX_PATH="data/smu_lib_index/"
 
 # telegram bot

README.md

@@ -1,5 +1,5 @@
 ---
-title: Chat with SMU LibBot
+title: Chat with SMU Library Chatbot
 emoji: 👀
 colorFrom: indigo
 colorTo: blue
@@ -87,7 +87,7 @@ Check out the configuration reference at https://huggingface.co/docs/hub/spaces-
 
 ## Talk to Your Own PDF Files
 
-- The sample PDF books & documents are downloaded from the internet (for SMU LibBot) and [PCI DSS official website](https://www.pcisecuritystandards.org/document_library/?category=pcidss) and the corresponding embeddings are stored in folders `data/ai_books` and `data/pci_dss_v4` respectively, which allows you to run locally without any additional effort.
+- The sample PDF books & documents are downloaded from the internet (for SMU Library Chatbot) and [PCI DSS official website](https://www.pcisecuritystandards.org/document_library/?category=pcidss) and the corresponding embeddings are stored in folders `data/ai_books` and `data/pci_dss_v4` respectively, which allows you to run locally without any additional effort.
 
 - You can also put your own PDF files into any folder specified in `SOURCE_PDFS_PATH` and run the command below to generate embeddings which will be stored in folder `FAISS_INDEX_PATH` or `CHROMADB_INDEX_PATH`. If both `*_INDEX_PATH` env vars are set, `FAISS_INDEX_PATH` takes precedence. Make sure the folder specified by `*_INDEX_PATH` doesn't exist; other wise the command will simply try to load index from the folder and do a simple similarity search, as a way to verify if embeddings are generated and stored properly. Please note the HuggingFace Embedding model specified by `HF_EMBEDDINGS_MODEL_NAME` will be used to generate the embeddings.
 

app.py

@@ -44,7 +44,7 @@ if chat_with_llama_2:
     qa_chain = ChatChain(llm_loader)
     name = "Llama-2"
 else:
-    name = "SMU LibBot"
+    name = "SMU Library Chatbot"
 
 title = f"""<h1 align="left" style="min-width:200px; margin-top:0;"> Chat with {name} </h1>"""
 
@@ -216,5 +216,7 @@ with gr.Blocks(css=customCSS) as demo:
         api_name="reset",
     )
 
-demo.title = "Chat with SMU LibBot" if chat_with_llama_2 else "Chat with Llama-2"
+demo.title = (
+    "Chat with SMU Library Chatbot" if chat_with_llama_2 else "Chat with Llama-2"
+)
 demo.queue(concurrency_count=CONCURRENT_COUNT).launch(share=share_gradio_app)