Update app.py

app.py

@@ -5,14 +5,21 @@ import csv
 import os
 import langchain
 import chromadb
-#import faiss
+import glob
+
+from langchain.embeddings.openai import OpenAIEmbeddings
+from langchain.vectorstores import Chroma
+from langchain.text_splitter import TokenTextSplitter
+from langchain.llms import OpenAI
+from langchain.chains import ChatVectorDBChain
+from langchain.document_loaders import PyPDFLoader
 
 # Use Chroma in Colab to create vector embeddings, I then saved them to HuggingFace so now I have to set it use them here.
-from chromadb.config import Settings
-client = chromadb.Client(Settings(
-    chroma_db_impl="duckdb+parquet",
-    persist_directory="./embeddings" # Optional, defaults to .chromadb/ in the current directory
-))
+#from chromadb.config import Settings
+#client = chromadb.Client(Settings(
+#    chroma_db_impl="duckdb+parquet",
+#    persist_directory="./embeddings" # Optional, defaults to .chromadb/ in the current directory
+#))
 
 
 def get_empty_state():
@@ -143,7 +150,7 @@ with gr.Blocks(css=css) as demo:
     btn_submit.click(submit_message, [ input_message, prompt_template, temperature, max_tokens, context_length, state], [input_message, chatbot, total_tokens_str, state])
     input_message.submit(submit_message, [ input_message, prompt_template, temperature, max_tokens, context_length, state], [input_message, chatbot, total_tokens_str, state])
     btn_clear_conversation.click(clear_conversation, [], [input_message, chatbot, total_tokens_str, state])
-    prompt_template.change(on_prompt_template_change, inputs=[prompt_template], outputs=[description])
+    prompt_template.change(on_prompt_template_change, inputs=[prompt_template], outputs=[prompt_template_preview])