mirror of
https://github.com/langchain-ai/langgraph.git
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240 lines
7.5 KiB
Plaintext
240 lines
7.5 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "3631f2b9-aa79-472e-a9d6-9125a90ee704",
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"metadata": {},
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"source": [
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"# How to stream full state of your graph"
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]
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},
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{
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"cell_type": "markdown",
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"id": "858c7499-0c92-40a9-bd95-e5a5a5817e92",
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"metadata": {},
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"source": [
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"LangGraph supports multiple streaming modes. The main ones are:\n",
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"\n",
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"- `values`: This streaming mode streams back values of the graph. This is the **full state of the graph** after each node is called.\n",
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"- `updates`: This streaming mode streams back updates to the graph. This is the **update to the state of the graph** after each node is called.\n",
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"\n",
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"This guide covers `stream_mode=\"values\"`."
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]
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},
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{
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"cell_type": "markdown",
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"id": "7c2f84f1-0751-4779-97d4-5cbb286093b7",
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"metadata": {},
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"source": [
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"## Setup"
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]
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},
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{
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"cell_type": "markdown",
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"id": "323db423-b644-40bd-9c2d-976a53f602f7",
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"metadata": {},
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"source": [
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"We'll be using a simple ReAct agent for this guide."
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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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"id": "6b4285e4-7434-4971-bde0-aabceef8ee7e",
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"metadata": {},
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"outputs": [],
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"source": [
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"%%capture --no-stderr\n",
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"%pip install -U langgraph langchain-openai"
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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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"id": "f7f9f24a-e3d0-422b-8924-47950b2facd6",
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"metadata": {},
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"outputs": [
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{
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"name": "stdin",
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"output_type": "stream",
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"text": [
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"OPENAI_API_KEY: ········\n"
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]
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}
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],
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"source": [
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"import getpass\n",
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"import os\n",
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"\n",
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"\n",
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"def _set_env(var: str):\n",
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" if not os.environ.get(var):\n",
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" os.environ[var] = getpass.getpass(f\"{var}: \")\n",
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"\n",
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"\n",
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"_set_env(\"OPENAI_API_KEY\")"
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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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"id": "ef5a3ec6-0cd0-4541-ab1b-d63ede22720e",
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"metadata": {},
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"outputs": [],
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"source": [
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"from typing import Literal\n",
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"from langchain_community.tools.tavily_search import TavilySearchResults\n",
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"from langchain_core.runnables import ConfigurableField\n",
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"from langchain_core.tools import tool\n",
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"from langchain_openai import ChatOpenAI\n",
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"from langgraph.prebuilt import create_react_agent\n",
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"\n",
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"\n",
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"@tool\n",
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"def get_weather(city: Literal[\"nyc\", \"sf\"]):\n",
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" \"\"\"Use this to get weather information.\"\"\"\n",
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" if city == \"nyc\":\n",
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" return \"It might be cloudy in nyc\"\n",
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" elif city == \"sf\":\n",
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" return \"It's always sunny in sf\"\n",
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" else:\n",
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" raise AssertionError(\"Unknown city\")\n",
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"\n",
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"\n",
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"tools = [get_weather]\n",
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"\n",
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"model = ChatOpenAI(model_name=\"gpt-4o\", temperature=0)\n",
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"graph = create_react_agent(model, tools)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "002a715b-e0be-4e89-8d42-f0098882586b",
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"metadata": {},
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"source": [
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"## Stream values"
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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": 4,
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"id": "e9e9ffb0-2cd5-466f-b70b-b6ed51b852d1",
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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[1m Human Message \u001b[0m=================================\n",
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"\n",
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"what's the weather in sf\n",
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"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
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"Tool Calls:\n",
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" get_weather (call_61VvIzqVGtyxcXi0z6knZkjZ)\n",
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" Call ID: call_61VvIzqVGtyxcXi0z6knZkjZ\n",
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" Args:\n",
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" city: sf\n",
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"=================================\u001b[1m Tool Message \u001b[0m=================================\n",
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"Name: get_weather\n",
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"\n",
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"It's always sunny in sf\n",
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"==================================\u001b[1m Ai Message \u001b[0m==================================\n",
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"\n",
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"The weather in San Francisco is currently sunny.\n"
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]
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}
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],
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"source": [
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"inputs = {\"messages\": [(\"human\", \"what's the weather in sf\")]}\n",
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"async for chunk in graph.astream(inputs, stream_mode=\"values\"):\n",
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" chunk[\"messages\"][-1].pretty_print()"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d73de237-bf45-4fa7-93ef-6dae7eacffc0",
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"metadata": {},
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"source": [
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"If we want to just get the final result, we can use the same method and just keep track of the last value we received"
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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": 5,
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"id": "c122bf15-a489-47bf-b482-a744a54e2cc4",
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"metadata": {},
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"outputs": [],
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"source": [
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"inputs = {\"messages\": [(\"human\", \"what's the weather in sf\")]}\n",
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"async for chunk in graph.astream(inputs, stream_mode=\"values\"):\n",
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" final_result = chunk"
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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": 6,
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"id": "316022e5-4c65-48e4-9878-8d94a2425ed4",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"{'messages': [HumanMessage(content=\"what's the weather in sf\", id='54b39b6f-054b-4306-980b-86905e48a6bc'),\n",
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" AIMessage(content='', additional_kwargs={'tool_calls': [{'id': 'call_avoKnK8reERzTUSxrN9cgFxY', 'function': {'arguments': '{\"city\":\"sf\"}', 'name': 'get_weather'}, 'type': 'function'}]}, response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 57, 'total_tokens': 71}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_5e6c71d4a8', 'finish_reason': 'tool_calls', 'logprobs': None}, id='run-f2f43c89-2c96-45f4-975c-2d0f22d0d2d1-0', tool_calls=[{'name': 'get_weather', 'args': {'city': 'sf'}, 'id': 'call_avoKnK8reERzTUSxrN9cgFxY'}], usage_metadata={'input_tokens': 57, 'output_tokens': 14, 'total_tokens': 71}),\n",
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" ToolMessage(content=\"It's always sunny in sf\", name='get_weather', id='fc18a798-c7b2-4f73-84fa-8ffdffb6ddcb', tool_call_id='call_avoKnK8reERzTUSxrN9cgFxY'),\n",
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" AIMessage(content='The weather in San Francisco is currently sunny. Enjoy the sunshine!', response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 84, 'total_tokens': 98}, 'model_name': 'gpt-4o-2024-05-13', 'system_fingerprint': 'fp_5e6c71d4a8', 'finish_reason': 'stop', 'logprobs': None}, id='run-21418147-da8e-4738-a076-239377397c40-0', usage_metadata={'input_tokens': 84, 'output_tokens': 14, 'total_tokens': 98})]}"
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]
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},
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"execution_count": 6,
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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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"final_result"
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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": 7,
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"id": "0f64ebbe-535c-4b35-a95f-0a7490cfed90",
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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[1m Ai Message \u001b[0m==================================\n",
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"\n",
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"The weather in San Francisco is currently sunny. Enjoy the sunshine!\n"
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]
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}
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],
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"source": [
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"final_result[\"messages\"][-1].pretty_print()"
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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": "langgraph",
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"language": "python",
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"name": "langgraph"
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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": "3.12.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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