Update app.py

app.py

@@ -10,7 +10,7 @@ def save_docs(docs):
     import shutil
     import os
 
-    output_dir="/content/docs/"
+    output_dir="/home/user/app/docs/"
 
     if os.path.exists(output_dir):
         shutil.rmtree(output_dir)
@@ -35,19 +35,19 @@ def process_docs():
     from langchain.embeddings.openai import OpenAIEmbeddings
     from langchain.text_splitter import RecursiveCharacterTextSplitter
 
-    loader1 = DirectoryLoader('/content/docs/', glob="./*.pdf", loader_cls=PyPDFLoader)
+    loader1 = DirectoryLoader('/home/user/app/docs/', glob="./*.pdf", loader_cls=PyPDFLoader)
     document1 = loader1.load()
 
-    loader2 = DirectoryLoader('/content/docs/', glob="./*.txt", loader_cls=TextLoader)
+    loader2 = DirectoryLoader('/home/user/app/docs/', glob="./*.txt", loader_cls=TextLoader)
     document2 = loader2.load()
 
-    loader3 = DirectoryLoader('/content/docs/', glob="./*.docx", loader_cls=Docx2txtLoader)
+    loader3 = DirectoryLoader('/home/user/app/docs/', glob="./*.docx", loader_cls=Docx2txtLoader)
     document3 = loader3.load()
 
-    loader4 = DirectoryLoader('/content/docs/', glob="./*.csv", loader_cls=CSVLoader)
+    loader4 = DirectoryLoader('/home/user/app/docs/', glob="./*.csv", loader_cls=CSVLoader)
     document4 = loader4.load()
 
-    loader5 = DirectoryLoader('/content/docs/', glob="./*.xlsx", loader_cls=UnstructuredExcelLoader)
+    loader5 = DirectoryLoader('/home/user/app/docs/', glob="./*.xlsx", loader_cls=UnstructuredExcelLoader)
     document5 = loader5.load()
 
     document1.extend(document2)
@@ -65,7 +65,7 @@ def process_docs():
     embeddings = OpenAIEmbeddings()
 
     docs_db = FAISS.from_documents(docs, embeddings)
-    docs_db.save_local("/content/docs_db/")
+    docs_db.save_local("/home/user/app/docs_db/")
 
     return "Successful!"
 
@@ -113,7 +113,7 @@ def search_docs(prompt, question, state):
     state = state or []
 
     embeddings = OpenAIEmbeddings()
-    docs_db = FAISS.load_local("/content/docs_db/", embeddings)
+    docs_db = FAISS.load_local("/home/user/app/docs_db/", embeddings)
     docs = docs_db.similarity_search(question)
 
     prompt += "\n\n"