Update app.py (#4)

- Update app.py (e7f77a8622e201f6165a1d1100dcd7ffc1543125)


Co-authored-by: Shivansh Mathur <ShivanshMathur007@users.noreply.huggingface.co>

app.py

@@ -1,5 +1,4 @@
 from langchain.vectorstores import FAISS
-# from langchain.chains import ConversationalRetrievalChain
 from langchain.chains import RetrievalQA
 from langchain.llms import HuggingFaceHub
 import gradio as gr
@@ -9,36 +8,19 @@ from langchain_experimental.agents.agent_toolkits.csv.base import create_csv_age
 from langchain.document_loaders import PyPDFDirectoryLoader
 from langchain.document_loaders.csv_loader import CSVLoader
 from langchain.text_splitter import RecursiveCharacterTextSplitter
-from langchain.memory import ConversationSummaryBufferMemory
 import io
 import contextlib
 
 
-embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L12-v2")
+embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")
 vector_store= FAISS.load_local("vector_db/", embeddings)
 
 repo_id="mistralai/Mixtral-8x7B-Instruct-v0.1"
 llm = HuggingFaceHub(repo_id=repo_id, model_kwargs={"temperature": 0.01, "max_new_tokens": 2048})
 
-# memory = ConversationSummaryBufferMemory(
-#     llm=llm,
-#     output_key='answer',
-#     memory_key='chat_history',
-#     max_token_limit=300,
-#     return_messages=True)
-
-# retriever = vector_store.as_retriever(
-#     search_type="similarity",
-#     search_kwargs={"k": 10, "include_metadata": True})
-
-# qa = ConversationalRetrievalChain.from_llm(
-#     llm=llm,
-#     memory=memory,
-#     chain_type="stuff",
-#     retriever=retriever,
-#     return_source_documents=True,
-#     get_chat_history=lambda h : h,
-#     verbose=True)
+retriever = vector_store.as_retriever(
+    search_type="similarity",
+    search_kwargs={"k":3, "include_metadata": True})
 
 agent=create_csv_agent(llm,['data/Gretel_Data.csv','data/RAN_Data _T.csv'],verbose=True)
 
@@ -98,4 +80,5 @@ demo1=gr.ChatInterface(
         stop_btn="Stop",
     )
 demo2=gr.TabbedInterface([demo,demo1],["RAG","AGENT"], title='INCEDO', theme=gr.themes.Soft())
-demo2.launch(auth=("admin", "Sam&Clara"))
+demo2.launch(share=True,debug=True,auth=("admin", "Sam&Clara"))
+