Fixed pdf file save error

app.py

@@ -5,20 +5,21 @@ from langchain.embeddings import HuggingFaceEmbeddings
 from langchain.prompts import PromptTemplate
 from langchain.vectorstores import FAISS
 from langchain.llms import CTransformers
-import os
+import tempfile
 import torch
 
 
+
 def model_response(query,docs_page_content):
 
 ### Check if GPU is available run the model on GPU
     if torch.cuda.is_available():
         config={'max_new_tokens':1024,
                               'context_length': 4096,
-                              'temperature':0.5,
+                              'temperature':0.0,
                               'gpu_layers': 10}
     else:
-        config={'max_new_tokens':1028,
+        config={'max_new_tokens':1024,
                               'context_length': 4096,
                               'temperature':0.5}
 
@@ -28,7 +29,7 @@ def model_response(query,docs_page_content):
                       config=config)
     
     template= """
-                You are a helpful assistant that that can answer questions about documents using the provided transcripts. Answer the following question: "{query}" by searching the following transcript: "{docs_page_content}"
+                You are a helpful assistant that that can answer questions about documents using the provided transcripts. Answer the following question: "{query}" by searching the following transcript: {docs_page_content}
                 Only use the factual information from the transcript to answer the question. If you feel like you don't have enough information to answer the question, say "I don't know". Your answers should be verbose and detailed.
                 """
     prompt=PromptTemplate(input_variables=["query","docs_page_content"],
@@ -37,11 +38,6 @@ def model_response(query,docs_page_content):
     ## Generate the response from the LLama 2 model
     response=llm(prompt.format(query=query,docs_page_content=docs_page_content))
 
-    ## Remove the pdf file after the response is generated
-    if response:
-        if doc_type == 'PDF File':
-            os.remove("files/pdf_file.pdf")
-
     container = st.container(border=True)
     container.write(response) 
 
@@ -90,16 +86,19 @@ elif doc_type == 'PDF File':
     query = st.text_area('What is your question?','', placeholder='Ask question from the uploaded pdf')
     with st.sidebar:
         pdf_file = st.file_uploader("Choose a PDF file:", accept_multiple_files=False, type=['pdf'])
-        if pdf_file is not None:
-            with open('files/pdf_file.pdf', "wb") as f:
-                f.write(pdf_file.read())
+        # if pdf_file is not None:
+        #     with open('files/pdf_file.pdf', "wb") as f:
+        #         f.write(pdf_file.read())
         if st.button('Submit'):
             if pdf_file is not None:
                 if query != '':
-                    loader = PyPDFLoader("files/pdf_file.pdf")
-                    data = loader.load()
+                    temp_file = tempfile.NamedTemporaryFile(delete=False)
+                    temp_file.write(pdf_file.read())
+                    temp_file.close()
+                    pdf_loader = PyPDFLoader(temp_file.name)
+                    data = pdf_loader.load()
+                    print(data)
                     docs_page_content = similarity_finder(data)
-                    print(docs_page_content)
     if pdf_file is not None:
         if query != '':
             model_response(query,docs_page_content)