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.gitignore

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+.streamlit

app.py

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+import openai
+import time
+import logging
+import streamlit as st
+
+openai_api_key = st.secrets["openai_api_key"]
+client = openai.OpenAI(api_key = openai_api_key)
+model = "gpt-3.5-turbo-16k"
+
+# === Thread an empty thread
+thread = client.beta.threads.create()
+thread_id = thread.id
+
+def wait_for_run_completion(client, thread_id, run_id, sleep_interval=5):
+    """
+    Waits for a run to complete and prints the elapsed time.:param client: The OpenAI client object.
+    :param thread_id: The ID of the thread.
+    :param run_id: The ID of the run.
+    :param sleep_interval: Time in seconds to wait between checks.
+    """
+    while True:
+        try:
+            run = client.beta.threads.runs.retrieve(thread_id = thread_id, run_id = run_id)
+            if run.completed_at:
+                elapsed_time = run.completed_at - run.created_at
+                formatted_elapsed_time = time.strftime(
+                    "%H:%M:%S", time.gmtime(elapsed_time)
+                )
+                print(f"Run completed in {formatted_elapsed_time}")
+                logging.info(f"Run completed in {formatted_elapsed_time}")
+                # Get messages here once Run is completed!
+                messages = client.beta.threads.messages.list(thread_id=thread_id)
+                last_message = messages.data[0]
+                response = last_message.content[0].text.value
+                st.write(response)
+                break
+        except Exception as e:
+            logging.error(f"An error occurred while retrieving the run: {e}")
+            break
+        logging.info("Waiting for run to complete...")
+        time.sleep(sleep_interval)
+
+def create_new_assistant():
+    personal_trainer_assis = client.beta.assistants.create(
+        name="Data Analyst",
+        instructions="""You are great at creating beautiful data visualizations. You analyze data present in .csv files, understand trends, and come up with data visualizations relevant to those trends. You also share a brief text summary of the trends observed.""",
+        model=model
+    )
+    print(f"Created new assistant with ID: {personal_trainer_assis.id}")
+    return personal_trainer_assis.id
+
+def main():
+    # Streamlit interface
+    st.title("Data Analyst")
+
+    # Note that API key's running out of budget
+    contact_url = "https://www.linkedin.com/in/linhvuu"
+    st.write("If no result returns, it means I am running out of energy. Please contact [Linh Vuu](%s) to wake me up." % contact_url)
+    
+    uploaded_file = st.file_uploader("Upload a CSV file for analysis", type=['csv'])
+
+    if uploaded_file is not None:
+
+        file_content = uploaded_file.read()
+
+        # Upload a file with an "assistants" purpose
+        file_array = [file_content]
+        file_id_array = []
+        for file in file_array:
+            file = client.files.create(
+                file = file_content,
+                purpose="assistants"
+            )
+            file_id_array.append(file.id)
+
+        print(file_id_array)
+
+    with st.form(key="user_input_form"):
+
+        question = st.text_input("Enter question:")
+        submit_button = st.form_submit_button(label="Response to my question above")
+
+        if submit_button:
+
+            # ==== Create a Message ====
+            message = question
+            message = client.beta.threads.messages.create(
+                thread_id = thread_id, role = "user", content = message, file_ids = file_id_array
+            )
+
+            # Define assistant_id before the try-except block
+            assistant_id = "asst_IY1VCWqTnQ2Uvj9zWHLXmblg"
+            run = None
+
+            # === Run our Assistant ===
+            try:
+                if assistant_id is None:
+                    # If assistant_id is None, create a new assistant
+                    assistant_id = create_new_assistant()
+
+                run = client.beta.threads.runs.create(
+                    thread_id = thread_id,
+                    assistant_id = assistant_id
+                )
+            except openai.NotFoundError:
+                # If assistant_id does not exist, create a new assistant and retry
+                assistant_id = create_new_assistant()
+                run = client.beta.threads.runs.create(
+                    thread_id = thread_id,
+                    assistant_id = assistant_id
+                )
+
+            # === Run ===
+            wait_for_run_completion(client=client, thread_id=thread_id, run_id=run.id)
+
+if __name__ == "__main__":
+    main()

requirements.txt

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+openai