Update app.py

app.py

@@ -1,3 +1,174 @@
+# import openai
+# import streamlit as st
+# from openai import OpenAI
+# import io
+# import time
+# import os
+# from dotenv import load_dotenv
+
+# # Initialize the OpenAI client with your API key
+# # Load environment variables from the .env file
+# load_dotenv()
+
+# # Get the OpenAI API key
+# OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+
+# client = OpenAI(api_key=OPENAI_API_KEY)
+# vector_store_id = "vs_sHLBqA88ng66RDZYMgaBmDuX"  # Vector Store ID to use
+
+# # all_files = list(client.beta.vector_stores.files.list(vector_store_id))
+# # for file in all_files:
+# #   # print(file)
+# #   file_id = file.id
+# #   st.write(file_id)
+
+# # Set the assistant ID
+# assistant_id = "asst_UeIHpkpVejAgrIz3RnisxSLm"  # Replace with your own assistant ID
+
+# def ensure_single_thread_id():
+#     if "thread_id" not in st.session_state:
+#         thread = client.beta.threads.create()
+#         st.session_state.thread_id = thread.id
+#     return st.session_state.thread_id
+
+# def safe_message_send(prompt, thread_id):
+#     try:
+#         message = client.beta.threads.messages.create(
+#             thread_id=thread_id,
+#             role="user",
+#             content=prompt
+#         )
+#         return message
+#     except Exception as e:
+#         if "active" in str(e):
+#             print("Waiting for the current run to finish...")
+#             time.sleep(1)  # wait a bit before retrying
+#             return safe_message_send(prompt, thread_id)  # retry sending the message
+#         else:
+#             raise e
+
+# def stream_generator(prompt, thread_id):
+#     # print(f'First time thread in the function {thread_id}')
+#     message = safe_message_send(prompt, thread_id)  # use the new safe send function
+    
+#     with st.spinner("Wait... Generating response..."):
+#         try:
+#             stream = client.beta.threads.runs.create(
+#                 thread_id=thread_id,
+#                 assistant_id=assistant_id,
+#                 stream=True
+#             )
+
+#             for event in stream:
+#                 if event.data.object == "thread.message.delta":
+#                     for content in event.data.delta.content:
+#                         if content.type == 'text':
+#                             yield content.text.value
+#                             time.sleep(0.01)
+#                 elif event.data.object == "thread.run.stop":
+#                     break  # Break if the run stops
+#         except Exception as e:
+#             print(f"Error during streaming: {str(e)}")
+
+# def upload_and_add_to_vector_store(uploaded_file):
+#     """Upload a file to OpenAI and add it to the specified vector store."""
+#     try:
+#         # Convert the uploaded file to a BytesIO stream for uploading
+#         file_stream = io.BytesIO(uploaded_file.getvalue())
+#         file_stream.name = uploaded_file.name  # Preserve the file name    
+#         # Upload the file to the vector store
+#         file_batch = client.beta.vector_stores.file_batches.upload_and_poll(
+#             vector_store_id=vector_store_id,
+#             files=[file_stream]
+#         )
+
+
+#         st.success(f"File '{uploaded_file.name}' processed and added to vector store. Status: {file_batch.status}")
+#     except Exception as e:
+#         st.error(f"Failed to process file: {str(e)}")
+    
+
+
+# def list_all_files_in_vector_store():
+#     """List all files in the specified vector store."""
+#     try:
+#         all_files = list(client.beta.vector_stores.files.list(vector_store_id=vector_store_id))
+#         # st.write(all_files)
+#         for file in all_files:
+#             file_id = file.id
+#             st.write(file_id)   
+#     except Exception as e:
+#         st.error(f"Failed to list files: {str(e)}")
+#         return {}
+
+# def delete_file_from_vector_store(vector_store_id, file_id):
+#     """Delete a file from the specified vector store."""
+#     try:
+#         client.beta.vector_stores.files.delete(
+#             vector_store_id=vector_store_id,
+#             file_id=file_id
+#         )
+#         st.success(f"File with ID '{file_id}' deleted from vector store '{vector_store_id}'.")
+#     except Exception as e:
+#         st.error(f"Failed to delete file. File id is not Found.")
+
+# # Interface to delete files from vector store
+# st.sidebar.subheader("Delete File from Vector Store")
+# file_id_to_delete = st.sidebar.text_input("Enter File ID to Delete", "")
+# if st.sidebar.button("Delete File"):
+#     delete_file_from_vector_store(vector_store_id, file_id_to_delete)
+
+# # Streamlit interface setup
+# st.title("💬Chatbot")
+# st.caption("🚀 A Streamlit Custom Chatbot")
+
+
+# with st.sidebar:
+#     st.write("Upload PDF File")
+#     uploaded_file = st.file_uploader("Choose a file", type=['pdf', 'docx'], key='file_uploader')
+
+#     if st.button('Upload File', key='process_file'):
+#         if uploaded_file is not None:
+#             upload_and_add_to_vector_store(uploaded_file)
+#             st.success("File successfully uploaded and processed.")
+#         else:
+#             st.error("Please upload a file to process.")
+
+#     # List all uploaded files
+#     st.write("### Uploaded Files")
+#     if 'uploaded_files' in st.session_state and st.session_state.uploaded_files:
+#         for file_name, file_id in st.session_state.uploaded_files.items():
+#             st.write(f"{file_name}: {file_id}")
+    
+#     # List all files in the vector store
+#     st.write("## All Files in Vector Store")
+#     all_files = list_all_files_in_vector_store() 
+
+# # Initialize session state for chat
+# st.session_state.start_chat = True
+# if 'start_chat' not in st.session_state:
+#     st.session_state.start_chat = False
+
+# # Main chat interface
+# if st.session_state.start_chat:
+#     if "messages" not in st.session_state:
+#         st.session_state.messages = []
+
+#     for message in st.session_state.messages:
+#         with st.chat_message(message["role"]):
+#             st.markdown(message["content"])
+
+#     prompt = st.chat_input("Enter your message")
+#     if prompt:
+#         thread_id = ensure_single_thread_id()
+#         with st.chat_message("user"):
+#             st.markdown(prompt)
+#         st.session_state.messages.append({"role": "user", "content": prompt})
+        
+#         with st.chat_message("assistant"):
+#             response = st.write_stream(stream_generator(prompt, thread_id))
+#         st.session_state.messages.append({"role": "assistant", "content": response})
+
 import openai
 import streamlit as st
 from openai import OpenAI
@@ -6,166 +177,120 @@ import time
 import os
 from dotenv import load_dotenv
 
-# Initialize the OpenAI client with your API key
-# Load environment variables from the .env file
+# Initialize the OpenAI client
 load_dotenv()
-
-# Get the OpenAI API key
 OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
-
+VECTOR_STORE_ID = "vs_sHLBqA88ng66RDZYMgaBmDuX"
+ASSISTANT_ID = "asst_UeIHpkpVejAgrIz3RnisxSLm"
 client = OpenAI(api_key=OPENAI_API_KEY)
-vector_store_id = "vs_sHLBqA88ng66RDZYMgaBmDuX"  # Vector Store ID to use
-
-# all_files = list(client.beta.vector_stores.files.list(vector_store_id))
-# for file in all_files:
-#   # print(file)
-#   file_id = file.id
-#   st.write(file_id)
-
-# Set the assistant ID
-assistant_id = "asst_UeIHpkpVejAgrIz3RnisxSLm"  # Replace with your own assistant ID
 
+# Ensure a single OpenAI thread per session
 def ensure_single_thread_id():
     if "thread_id" not in st.session_state:
         thread = client.beta.threads.create()
         st.session_state.thread_id = thread.id
     return st.session_state.thread_id
 
+# Send a user message safely
 def safe_message_send(prompt, thread_id):
     try:
-        message = client.beta.threads.messages.create(
+        return client.beta.threads.messages.create(
             thread_id=thread_id,
             role="user",
             content=prompt
         )
-        return message
     except Exception as e:
         if "active" in str(e):
-            print("Waiting for the current run to finish...")
-            time.sleep(1)  # wait a bit before retrying
-            return safe_message_send(prompt, thread_id)  # retry sending the message
-        else:
-            raise e
+            time.sleep(1)
+            return safe_message_send(prompt, thread_id)
+        raise e
 
+# Generator for streaming assistant response
 def stream_generator(prompt, thread_id):
-    # print(f'First time thread in the function {thread_id}')
-    message = safe_message_send(prompt, thread_id)  # use the new safe send function
-    
-    with st.spinner("Wait... Generating response..."):
-        try:
-            stream = client.beta.threads.runs.create(
-                thread_id=thread_id,
-                assistant_id=assistant_id,
-                stream=True
-            )
-
-            for event in stream:
-                if event.data.object == "thread.message.delta":
-                    for content in event.data.delta.content:
-                        if content.type == 'text':
-                            yield content.text.value
-                            time.sleep(0.01)
-                elif event.data.object == "thread.run.stop":
-                    break  # Break if the run stops
-        except Exception as e:
-            print(f"Error during streaming: {str(e)}")
+    safe_message_send(prompt, thread_id)
+    stream = client.beta.threads.runs.create(
+        thread_id=thread_id,
+        assistant_id=ASSISTANT_ID,
+        stream=True
+    )
+    for event in stream:
+        if event.data.object == "thread.message.delta":
+            for content in event.data.delta.content:
+                if content.type == 'text':
+                    yield content.text.value
+        elif event.data.object == "thread.run.stop":
+            break
 
+# Upload file to vector store
 def upload_and_add_to_vector_store(uploaded_file):
-    """Upload a file to OpenAI and add it to the specified vector store."""
     try:
-        # Convert the uploaded file to a BytesIO stream for uploading
         file_stream = io.BytesIO(uploaded_file.getvalue())
-        file_stream.name = uploaded_file.name  # Preserve the file name    
-        # Upload the file to the vector store
-        file_batch = client.beta.vector_stores.file_batches.upload_and_poll(
-            vector_store_id=vector_store_id,
+        file_stream.name = uploaded_file.name
+        client.vector_stores.file_batches.upload_and_poll(
+            vector_store_id=VECTOR_STORE_ID,
             files=[file_stream]
         )
-
-
-        st.success(f"File '{uploaded_file.name}' processed and added to vector store. Status: {file_batch.status}")
+        st.success(f"Uploaded '{uploaded_file.name}' to vector store.")
     except Exception as e:
-        st.error(f"Failed to process file: {str(e)}")
-    
-
+        st.error(f"Upload failed: {e}")
 
+# List files in vector store
 def list_all_files_in_vector_store():
-    """List all files in the specified vector store."""
     try:
-        all_files = list(client.beta.vector_stores.files.list(vector_store_id=vector_store_id))
-        # st.write(all_files)
-        for file in all_files:
-            file_id = file.id
-            st.write(file_id)   
+        all_files = client.vector_stores.files.list(vector_store_id=VECTOR_STORE_ID)
+        for f in all_files.data:
+            st.write(f.id)
     except Exception as e:
-        st.error(f"Failed to list files: {str(e)}")
-        return {}
+        st.error(f"List files failed: {e}")
 
-def delete_file_from_vector_store(vector_store_id, file_id):
-    """Delete a file from the specified vector store."""
+# Delete a file
+def delete_file_from_vector_store(file_id):
     try:
-        client.beta.vector_stores.files.delete(
-            vector_store_id=vector_store_id,
+        client.vector_stores.files.delete(
+            vector_store_id=VECTOR_STORE_ID,
             file_id=file_id
         )
-        st.success(f"File with ID '{file_id}' deleted from vector store '{vector_store_id}'.")
+        st.success(f"Deleted file {file_id}")
     except Exception as e:
-        st.error(f"Failed to delete file. File id is not Found.")
+        st.error(f"Delete failed: {e}")
 
-# Interface to delete files from vector store
-st.sidebar.subheader("Delete File from Vector Store")
-file_id_to_delete = st.sidebar.text_input("Enter File ID to Delete", "")
+# Sidebar UI
+st.sidebar.header("File Management")
+file_id = st.sidebar.text_input("File ID to delete")
 if st.sidebar.button("Delete File"):
-    delete_file_from_vector_store(vector_store_id, file_id_to_delete)
+    delete_file_from_vector_store(file_id)
+uploaded = st.sidebar.file_uploader("Upload PDF/DOCX", type=['pdf','docx'])
+if st.sidebar.button("Upload File") and uploaded:
+    upload_and_add_to_vector_store(uploaded)
+st.sidebar.markdown("---")
+st.sidebar.subheader("All Files in Vector Store")
+list_all_files_in_vector_store()
 
-# Streamlit interface setup
-st.title("💬Chatbot")
-st.caption("🚀 A Streamlit Custom Chatbot")
+# Initialize session state for chat
+if "messages" not in st.session_state:
+    st.session_state.messages = []
 
+st.title("💬 Chatbot")
 
-with st.sidebar:
-    st.write("Upload PDF File")
-    uploaded_file = st.file_uploader("Choose a file", type=['pdf', 'docx'], key='file_uploader')
+# Display chat history
+for msg in st.session_state.messages:
+    with st.chat_message(msg["role"]):
+        st.markdown(msg["content"])
 
-    if st.button('Upload File', key='process_file'):
-        if uploaded_file is not None:
-            upload_and_add_to_vector_store(uploaded_file)
-            st.success("File successfully uploaded and processed.")
-        else:
-            st.error("Please upload a file to process.")
+# Chat input and streaming
+prompt = st.chat_input("Your question...")
+if prompt:
+    thread_id = ensure_single_thread_id()
+    # display user message
+    with st.chat_message("user"):
+        st.markdown(prompt)
+    st.session_state.messages.append({"role": "user", "content": prompt})
 
-    # List all uploaded files
-    st.write("### Uploaded Files")
-    if 'uploaded_files' in st.session_state and st.session_state.uploaded_files:
-        for file_name, file_id in st.session_state.uploaded_files.items():
-            st.write(f"{file_name}: {file_id}")
-    
-    # List all files in the vector store
-    st.write("## All Files in Vector Store")
-    all_files = list_all_files_in_vector_store() 
+    # stream assistant message
+    full_response = ""
+    with st.chat_message("assistant"):
+        for chunk in stream_generator(prompt, thread_id):
+            full_response += chunk
+            st.markdown(full_response)
+    st.session_state.messages.append({"role": "assistant", "content": full_response})
 
-# Initialize session state for chat
-st.session_state.start_chat = True
-if 'start_chat' not in st.session_state:
-    st.session_state.start_chat = False
-
-# Main chat interface
-if st.session_state.start_chat:
-    # if "messages" not in st.session_state:
-    #     st.session_state.messages = []
-
-    for message in st.session_state.messages:
-        with st.chat_message(message["role"]):
-            st.markdown(message["content"])
-
-    prompt = st.chat_input("Enter your message")
-    if prompt:
-        thread_id = ensure_single_thread_id()
-        with st.chat_message("user"):
-            st.markdown(prompt)
-        st.session_state.messages.append({"role": "user", "content": prompt})
-        
-        with st.chat_message("assistant"):
-            response = st.write_stream(stream_generator(prompt, thread_id))
-        st.session_state.messages.append({"role": "assistant", "content": response})
-