Update app.py

app.py

@@ -1,174 +1,3 @@
-# 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
@@ -177,120 +6,165 @@ import time
 import os
 from dotenv import load_dotenv
 
-# Initialize the OpenAI client
+# 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")
-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:
-        return client.beta.threads.messages.create(
+        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):
-            time.sleep(1)
-            return safe_message_send(prompt, thread_id)
-        raise 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
 
-# Generator for streaming assistant response
 def stream_generator(prompt, thread_id):
-    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
+    # 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)}")
 
-# 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
-        client.vector_stores.file_batches.upload_and_poll(
-            vector_store_id=VECTOR_STORE_ID,
+        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"Uploaded '{uploaded_file.name}' to vector store.")
+
+
+        st.success(f"File '{uploaded_file.name}' processed and added to vector store. Status: {file_batch.status}")
     except Exception as e:
-        st.error(f"Upload failed: {e}")
+        st.error(f"Failed to process file: {str(e)}")
+    
+
 
-# List files in vector store
 def list_all_files_in_vector_store():
+    """List all files in the specified vector store."""
     try:
-        all_files = client.vector_stores.files.list(vector_store_id=VECTOR_STORE_ID)
-        for f in all_files.data:
-            st.write(f.id)
+        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"List files failed: {e}")
+        st.error(f"Failed to list files: {str(e)}")
+        return {}
 
-# Delete a file
-def delete_file_from_vector_store(file_id):
+def delete_file_from_vector_store(vector_store_id, file_id):
+    """Delete a file from the specified vector store."""
     try:
-        client.vector_stores.files.delete(
-            vector_store_id=VECTOR_STORE_ID,
+        client.beta.vector_stores.files.delete(
+            vector_store_id=vector_store_id,
             file_id=file_id
         )
-        st.success(f"Deleted file {file_id}")
+        st.success(f"File with ID '{file_id}' deleted from vector store '{vector_store_id}'.")
     except Exception as e:
-        st.error(f"Delete failed: {e}")
+        st.error(f"Failed to delete file. File id is not Found.")
 
-# Sidebar UI
-st.sidebar.header("File Management")
-file_id = st.sidebar.text_input("File ID to delete")
+# 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(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()
+    delete_file_from_vector_store(vector_store_id, file_id_to_delete)
 
-# Initialize session state for chat
-if "messages" not in st.session_state:
-    st.session_state.messages = []
+# Streamlit interface setup
+st.title("💬Chatbot")
+st.caption("🚀 A Streamlit Custom Chatbot")
 
-st.title("💬 Chatbot")
 
-# Display chat history
-for msg in st.session_state.messages:
-    with st.chat_message(msg["role"]):
-        st.markdown(msg["content"])
+with st.sidebar:
+    st.write("Upload PDF File")
+    uploaded_file = st.file_uploader("Choose a file", type=['pdf', 'docx'], key='file_uploader')
 
-# 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})
+    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.")
 
-    # 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})
+    # 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})