Create app.py

app.py

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+import openai
+import streamlit as st
+from openai import OpenAI
+import io
+import time
+import os
+from dotenv import load_dotenv
+
+# OpenAI keys
+OPENAI_API_KEY = st.secrets["OPENAI_API_KEY"]
+VECTOR_STORE_ID = os.getenv("VECTOR_STORE_ID")
+
+client = OpenAI(api_key=OPENAI_API_KEY)
+vector_store_id = VECTOR_STORE_ID  # 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})