Update app.py

app.py

@@ -49,26 +49,24 @@ def get_file_size(file):
     file.seek(0)
     return file_size
 
-# Add a sidebar for model selection
+# Add a sidebar for model selection and user details
 st.sidebar.write("Settings")
 st.sidebar.write("-----------")
 model_options = ["MBZUAI/LaMini-T5-738M", "google/flan-t5-base", "google/flan-t5-small"]
 selected_model = st.sidebar.radio("Choose Model", model_options)
 st.sidebar.write("-----------")
-
 uploaded_file = st.sidebar.file_uploader("Upload file", type=["pdf"])
-
 st.sidebar.write("-----------")
 st.sidebar.write("About Me")
 st.sidebar.write("Name: Deepak Yadav")
 st.sidebar.write("Bio: Passionate about AI and machine learning. Enjoys working on innovative projects and sharing knowledge with the community.")
-st.sidebar.write("[GitHub](https://github.com//deepak7376)")
-st.sidebar.write("[LinkedIn](https://www.linkedin.com/in/dky7376)")
+st.sidebar.write("[GitHub](https://github.com/deepak7376)")
+st.sidebar.write("[LinkedIn](https://www.linkedin.com/in/dky7376/)")
 st.sidebar.write("-----------")
 
 @st.cache_resource
-def initialize_qa_chain(FILEPATH, CHECKPOINT):
-    loader = PDFMinerLoader(FILEPATH)
+def initialize_qa_chain(filepath, CHECKPOINT):
+    loader = PDFMinerLoader(filepath)
     documents = loader.load()
     text_splitter = RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap=500)
     splits = text_splitter.split_documents(documents)
@@ -105,15 +103,14 @@ def process_answer(instruction, qa_chain):
     return generated_text
 
 if uploaded_file is not None:
-    file_details = {
-        "Filename": uploaded_file.name,
-        "File size": get_file_size(uploaded_file)
-    }
     os.makedirs("docs", exist_ok=True)
     filepath = os.path.join("docs", uploaded_file.name)
-    print(filepath)
+    with open(filepath, "wb") as temp_file:
+        temp_file.write(uploaded_file.read())
+        temp_filepath = temp_file.name
+
     with st.spinner('Embeddings are in process...'):
-       qa_chain = initialize_qa_chain(filepath, selected_model)
+        qa_chain = initialize_qa_chain(temp_filepath, selected_model)
 else:
     qa_chain = None