langgraph-example/examples/python/notebooks/same-thread.ipynb

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    "# How to run multiple agents on the same thread\n",
    "\n",
    "In LangGraph API, a thread is not explicitly associated with a particular agent.\n",
    "This means that you can run multiple agents on the same thread.\n",
    "In this example, we will create two agents and then call them both on the same thread."
   ]
  },
  {
   "cell_type": "code",
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   "id": "e06be1f6-07a5-4e93-8497-02473fc65d4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "from langgraph_sdk import get_client\n",
    "\n",
    "client = get_client()\n",
    "\n",
    "openai_assistant = await client.assistants.create(graph_id=\"agent\", config={\"configurable\": {\"model_name\": \"openai\"}})\n",
    "\n",
    "# There should always be a default assistant with no configuration\n",
    "assistants = await client.assistants.search()\n",
    "default_assistant = [a for a in assistants if not a['config']][0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4f10d346-69e6-44f4-8ff0-ef539ba938df",
   "metadata": {},
   "source": [
    "We can see that these agents are different"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "3898ca35-eb2c-4b12-97ea-e0cc6a7c6a2e",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'assistant_id': '13ecc353-a9a9-474b-a824-b6a343cd74b1',\n",
       " 'graph_id': 'agent',\n",
       " 'config': {'configurable': {'model_name': 'openai'}},\n",
       " 'created_at': '2024-05-21T16:22:59.258447+00:00',\n",
       " 'updated_at': '2024-05-21T16:22:59.258447+00:00',\n",
       " 'metadata': {}}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "openai_assistant"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a8fa67b2-cb4f-43d3-a1fc-f8b3936c16b6",
   "metadata": {},
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    {
     "data": {
      "text/plain": [
       "{'assistant_id': 'fe096781-5601-53d2-b2f6-0d3403f7e9ca',\n",
       " 'graph_id': 'agent',\n",
       " 'config': {},\n",
       " 'created_at': '2024-05-18T00:19:39.688822+00:00',\n",
       " 'updated_at': '2024-05-18T00:19:39.688822+00:00',\n",
       " 'metadata': {'created_by': 'system'}}"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "default_assistant"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5e655e61-c2ee-488a-90f6-6189c84841da",
   "metadata": {},
   "source": [
    "We can now run it on the OpenAI assistant first."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "68ed7a1b-74be-4560-8c55-c76d49d3d348",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "StreamPart(event='metadata', data={'run_id': 'f90b3029-8669-4d70-976c-b70368e355d8'})\n",
      "StreamPart(event='updates', data={'agent': {'messages': [{'content': 'I was created by OpenAI, a research organization focused on developing and advancing artificial intelligence technology.', 'additional_kwargs': {}, 'response_metadata': {'finish_reason': 'stop'}, 'type': 'ai', 'name': None, 'id': 'run-9801a5ba-2f3c-43de-89cf-c740debf36fc', 'example': False, 'tool_calls': [], 'invalid_tool_calls': []}]}})\n",
      "StreamPart(event='end', data=None)\n"
     ]
    }
   ],
   "source": [
    "thread = await client.threads.create()\n",
    "input = {\"messages\": [{\"role\": \"user\", \"content\": \"who made you?\"}]}\n",
    "async for event in client.runs.stream(thread['thread_id'], openai_assistant['assistant_id'], input=input, stream_mode='updates'):\n",
    "    print(event)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c53709e9-ddb2-4429-9042-456eb6c91244",
   "metadata": {},
   "source": [
    "Now, we can run it on a different Anthropic-based assistant."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "666d78f1-019a-433e-839e-52d2ebb3d9c8",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "StreamPart(event='metadata', data={'run_id': 'c3521302-48ae-4c29-a0f2-5eb865cbc6d7'})\n",
      "StreamPart(event='updates', data={'agent': {'messages': [{'content': \"I am an AI assistant created by Anthropic to be helpful, harmless, and honest. I don't actually have a physical form or visual representation - I exist as a language model trained to have natural conversations.\", 'additional_kwargs': {}, 'response_metadata': {}, 'type': 'ai', 'name': None, 'id': 'run-4d05ffd7-0505-43e1-a068-0207c56b7665', 'example': False, 'tool_calls': [], 'invalid_tool_calls': []}]}})\n",
      "StreamPart(event='end', data=None)\n"
     ]
    }
   ],
   "source": [
    "input = {\"messages\": [{\"role\": \"user\", \"content\": \"and you?\"}]}\n",
    "async for event in client.runs.stream(thread['thread_id'], default_assistant['assistant_id'], input=input, stream_mode='updates'):\n",
    "    print(event)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4c26df68-c447-4a88-bc94-59df42b117b5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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