mirror of
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36c4d6aa3e
* add assistant config * add test * change notebook to use assistant config * use assistant config in testing * code refinement --------- Co-authored-by: Eric Zhu <ekzhu@users.noreply.github.com>
209 lines
7.1 KiB
Plaintext
209 lines
7.1 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## OpenAI Assistants in AutoGen\n",
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"\n",
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"This notebook shows a very basic example of the [`GPTAssistantAgent`](https://github.com/microsoft/autogen/blob/main/autogen/agentchat/contrib/gpt_assistant_agent.py#L16C43-L16C43), which is an experimental AutoGen agent class that leverages the [OpenAI Assistant API](https://platform.openai.com/docs/assistants/overview) for conversational capabilities, working with\n",
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"`UserProxyAgent` in AutoGen."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"OpenAI client config of GPTAssistantAgent(assistant) - model: gpt-4-turbo-preview\n",
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"GPT Assistant only supports one OpenAI client. Using the first client in the list.\n",
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"No matching assistant found, creating a new assistant\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\u001b[33muser_proxy\u001b[0m (to assistant):\n",
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"\n",
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"Print hello world\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33massistant\u001b[0m (to user_proxy):\n",
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"\n",
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"```python\n",
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"print(\"Hello, world!\")\n",
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"```\n",
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"\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[31m\n",
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">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...\u001b[0m\n",
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"\u001b[33muser_proxy\u001b[0m (to assistant):\n",
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"\n",
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"exitcode: 0 (execution succeeded)\n",
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"Code output: \n",
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"Hello, world!\n",
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"\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33massistant\u001b[0m (to user_proxy):\n",
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"\n",
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"TERMINATE\n",
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"\n",
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"\n",
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"--------------------------------------------------------------------------------\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"ChatResult(chat_id=None, chat_history=[{'content': 'Print hello world', 'role': 'assistant'}, {'content': '```python\\nprint(\"Hello, world!\")\\n```\\n', 'role': 'user'}, {'content': 'exitcode: 0 (execution succeeded)\\nCode output: \\nHello, world!\\n', 'role': 'assistant'}, {'content': 'TERMINATE\\n', 'role': 'user'}], summary='\\n', cost=({'total_cost': 0}, {'total_cost': 0}), human_input=[])"
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]
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},
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"execution_count": 1,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"import logging\n",
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"import os\n",
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"\n",
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"from autogen import AssistantAgent, UserProxyAgent, config_list_from_json\n",
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"from autogen.agentchat.contrib.gpt_assistant_agent import GPTAssistantAgent\n",
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"\n",
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"logger = logging.getLogger(__name__)\n",
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"logger.setLevel(logging.WARNING)\n",
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"\n",
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"assistant_id = os.environ.get(\"ASSISTANT_ID\", None)\n",
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"\n",
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"config_list = config_list_from_json(\"OAI_CONFIG_LIST\")\n",
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"llm_config = {\"config_list\": config_list}\n",
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"\n",
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"assistant_config = {\"assistant_id\": assistant_id}\n",
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"\n",
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"gpt_assistant = GPTAssistantAgent(\n",
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" name=\"assistant\",\n",
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" instructions=AssistantAgent.DEFAULT_SYSTEM_MESSAGE,\n",
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" llm_config=llm_config,\n",
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" assistant_config=assistant_config,\n",
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")\n",
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"\n",
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"user_proxy = UserProxyAgent(\n",
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" name=\"user_proxy\",\n",
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" code_execution_config={\n",
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" \"work_dir\": \"coding\",\n",
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" \"use_docker\": False,\n",
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" }, # Please set use_docker=True if docker is available to run the generated code. Using docker is safer than running the generated code directly.\n",
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" is_termination_msg=lambda msg: \"TERMINATE\" in msg[\"content\"],\n",
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" human_input_mode=\"NEVER\",\n",
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" max_consecutive_auto_reply=1,\n",
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")\n",
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"user_proxy.initiate_chat(gpt_assistant, message=\"Print hello world\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\u001b[33muser_proxy\u001b[0m (to assistant):\n",
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"\n",
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"Write py code to eval 2 + 2\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33massistant\u001b[0m (to user_proxy):\n",
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"\n",
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"```python\n",
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"# Calculate 2+2 and print the result\n",
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"result = 2 + 2\n",
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"print(result)\n",
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"```\n",
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"\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[31m\n",
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">>>>>>>> EXECUTING CODE BLOCK 0 (inferred language is python)...\u001b[0m\n",
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"\u001b[33muser_proxy\u001b[0m (to assistant):\n",
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"\n",
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"exitcode: 0 (execution succeeded)\n",
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"Code output: \n",
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"4\n",
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"\n",
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"\n",
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"--------------------------------------------------------------------------------\n",
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"\u001b[33massistant\u001b[0m (to user_proxy):\n",
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"\n",
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"The Python code successfully calculated \\(2 + 2\\) and printed the result, which is \\(4\\).\n",
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"\n",
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"TERMINATE\n",
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"\n",
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"\n",
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"--------------------------------------------------------------------------------\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"ChatResult(chat_id=None, chat_history=[{'content': 'Write py code to eval 2 + 2', 'role': 'assistant'}, {'content': '```python\\n# Calculate 2+2 and print the result\\nresult = 2 + 2\\nprint(result)\\n```\\n', 'role': 'user'}, {'content': 'exitcode: 0 (execution succeeded)\\nCode output: \\n4\\n', 'role': 'assistant'}, {'content': 'The Python code successfully calculated \\\\(2 + 2\\\\) and printed the result, which is \\\\(4\\\\).\\n\\nTERMINATE\\n', 'role': 'user'}], summary='The Python code successfully calculated \\\\(2 + 2\\\\) and printed the result, which is \\\\(4\\\\).\\n\\n\\n', cost=({'total_cost': 0}, {'total_cost': 0}), human_input=[])"
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]
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},
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"execution_count": 2,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"user_proxy.initiate_chat(gpt_assistant, message=\"Write py code to eval 2 + 2\", clear_history=True)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Permanently deleting assistant...\n"
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]
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}
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],
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"source": [
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"gpt_assistant.delete_assistant()"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.13"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 2
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}
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