mirror of
https://github.com/langchain-ai/langgraph.git
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Add collab
This commit is contained in:
William Fu-Hinthorn
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "a3e3ebc4-57af-4fe4-bdd3-36aff67bf276",
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"metadata": {},
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"source": [
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"## Example 2: Agent Team Supervisor\n",
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"\n",
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"The prevoius example routed messages automatically based on the output of the initial researcher agent.\n",
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"\n",
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"We can also choose to use an LLM to orchestrate the different agents.\n",
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"\n",
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"Below, we will create an agent group, with an agent supervisor to help delegate tasks.\n",
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"\n",
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"To simplify each agent node, we will use the AgentExecutor class from LangChain."
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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": "0d30b6f7-3bec-4d9f-af50-43dfdc81ae6c",
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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 langchain langchain_openai langchain_experimental langsmith pandas"
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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": "30c2f3de-c730-4aec-85a6-af2c2f058803",
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"metadata": {},
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"outputs": [],
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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_if_undefined(var: str):\n",
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" if not os.environ.get(var):\n",
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" os.environ[var] = getpass(f\"Please provide your {var}\")\n",
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"\n",
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"\n",
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"_set_if_undefined(\"OPENAI_API_KEY\")\n",
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"_set_if_undefined(\"LANGCHAIN_API_KEY\")\n",
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"_set_if_undefined(\"TAVILY_API_KEY\")\n",
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"\n",
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"# Optional, add tracing in LangSmith\n",
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"os.environ[\"LANGCHAIN_TRACING_V2\"] = \"true\"\n",
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"os.environ[\"LANGCHAIN_PROJECT\"] = \"Multi-agent Collaboration\""
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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": "f04c6778-403b-4b49-9b93-678e910d5cec",
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"metadata": {},
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"outputs": [],
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"source": [
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"from typing import List, Tuple, Union\n",
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"\n",
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"import matplotlib.pyplot as plt\n",
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"from langchain_community.tools.tavily_search import TavilySearchResults\n",
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"from langchain_core.tools import tool\n",
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"\n",
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"tavily_tool = TavilySearchResults(max_results=5)\n",
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"\n",
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"\n",
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"@tool\n",
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"def create_plot(\n",
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" data: Union[List[float], List[int]],\n",
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" labels: Union[List[str], None] = None,\n",
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" title: str = \"Plot\",\n",
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" xlabel: str = \"X\",\n",
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" ylabel: str = \"Y\",\n",
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" color: Union[str, List[str]] = \"blue\",\n",
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" plot_type: str = \"bar\",\n",
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") -> Tuple[plt.Figure, plt.Axes]:\n",
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" \"\"\"\n",
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" Generates a bar or line plot from the provided data and returns the figure and axis objects.\n",
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"\n",
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" :param data: A list of numerical values for the bar heights or line points.\n",
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" :param labels: A list of strings for the bar or point labels. Default is None.\n",
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" :param title: Title of the plot. Default is 'Plot'.\n",
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" :param xlabel: Label for the X-axis. Default is 'X'.\n",
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" :param ylabel: Label for the Y-axis. Default is 'Y'.\n",
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" :param color: Color of the bars or line. Can be a single color or a list of colors. Default is 'blue'.\n",
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" :param figsize: Size of the figure as a tuple (width, height). Default is (10, 6).\n",
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" :param plot_type: Type of plot ('bar' or 'line'). Default is 'bar'.\n",
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" :return: Tuple containing the figure and axes objects.\n",
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" \"\"\"\n",
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" if plot_type not in [\"bar\", \"line\"]:\n",
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" raise ValueError(\"Invalid plot_type. Expected 'bar' or 'line'.\")\n",
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"\n",
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" fig, ax = plt.subplots(figsize=(10, 6))\n",
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" x_positions = range(len(data))\n",
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"\n",
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" if labels and len(labels) == len(data):\n",
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" plt.xticks(x_positions, labels)\n",
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"\n",
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" if plot_type == \"bar\":\n",
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" ax.bar(x_positions, data, color=color)\n",
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" elif plot_type == \"line\":\n",
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" ax.plot(x_positions, data, color=color, marker=\"o\") # 'o' for circular markers\n",
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"\n",
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" ax.set_title(title)\n",
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" ax.set_xlabel(xlabel)\n",
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" ax.set_ylabel(ylabel)\n",
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"\n",
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" return fig, ax"
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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": "6a430af7-8fce-4e66-ba9e-d940c1bc48e8",
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"metadata": {},
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"outputs": [],
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"source": [
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"import operator\n",
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"from typing import Annotated, Any, Dict, List, Optional, Sequence, TypedDict\n",
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"\n",
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"from langchain.agents import AgentExecutor, create_openai_functions_agent\n",
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"from langchain_core.messages import BaseMessage, HumanMessage\n",
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"from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder\n",
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"from langchain_core.tools import BaseTool\n",
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"from langchain_experimental.tools import PythonREPLTool\n",
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"from langchain_openai import ChatOpenAI\n",
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"\n",
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"from langgraph.graph import END, StateGraph\n",
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"\n",
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"\n",
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"class AgentState(TypedDict):\n",
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" messages: Annotated[Sequence[BaseMessage], operator.add]\n",
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" next: str\n",
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"\n",
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"\n",
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"workflow = StateGraph(AgentState)\n",
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"\n",
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"\n",
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"def create_agent_node(name: str, llm: ChatOpenAI, tools: list, system_prompt: str):\n",
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" prompt = ChatPromptTemplate.from_messages(\n",
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" [\n",
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" (\n",
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" \"system\",\n",
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" system_prompt,\n",
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" ),\n",
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" MessagesPlaceholder(variable_name=\"messages\"),\n",
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" MessagesPlaceholder(variable_name=\"agent_scratchpad\"),\n",
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" ]\n",
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" )\n",
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" agent = create_openai_functions_agent(llm, tools, prompt)\n",
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" executor = AgentExecutor(agent=agent, tools=tools, verbose=True)\n",
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"\n",
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" def _update_state(ai_message) -> dict:\n",
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" if isinstance(ai_message, FunctionMessage):\n",
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" result = ai_message\n",
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" else:\n",
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" message = ai_message.dict(exclude={\"type\"})\n",
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" message[\"name\"] = name\n",
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" result = HumanMessage(**message)\n",
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" return {\n",
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" \"messages\": [result],\n",
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" \"sender\": name,\n",
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" }\n",
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"\n",
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" chain = executor | _update_state\n",
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" workflow.add_node(name, chain)\n",
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"\n",
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"\n",
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"llm = ChatOpenAI(model=\"gpt-4\")\n",
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"\n",
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"create_agent_node(\"Researcher\", llm, [tavily_tool], \"You are a web researcher.\")\n",
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"create_agent_node(\"Chart Generator\", llm, [create_plot], \"You are a chart generator.\")\n",
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"# NOTE: THIS PERFORMS ARBITRARY CODE EXECUTION. PROCEED WITH CAUTION\n",
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"create_agent_node(\n",
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" \"Data Analyst\",\n",
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" llm,\n",
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" [PythonREPLTool()],\n",
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" \"You may generate safe python code to analyze data.\",\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d6374825-912f-40c9-910d-afa267b401bf",
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"metadata": {},
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"source": [
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"Almost done, now we need to create the team supervisor."
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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": "17c108a0-6dc3-46fd-a5e6-a1fcfad5458a",
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"metadata": {},
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"outputs": [],
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"source": [
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"# So the team supervisor is an LLM node. It just picks the next t\n",
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"from langchain.output_parsers.openai_functions import JsonOutputFunctionsParser\n",
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"\n",
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"\n",
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"def create_agent_supervisor(members: List[str], llm: ChatOpenAI, system_prompt: str):\n",
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" options = [\"FINISH\"] + members\n",
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" function_def = {\n",
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" \"name\": \"route\",\n",
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" \"description\": \"Select the next role.\",\n",
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" \"parameters\": {\n",
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" \"title\": \"routeSchema\",\n",
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" \"type\": \"object\",\n",
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" \"properties\": {\n",
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" \"next\": {\n",
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" \"title\": \"Next\",\n",
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" \"anyOf\": [\n",
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" {\"enum\": options},\n",
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" ],\n",
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" }\n",
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" },\n",
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" \"required\": [\"next\"],\n",
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" },\n",
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" }\n",
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" prompt = ChatPromptTemplate.from_messages(\n",
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" [\n",
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" (\"system\", system_prompt),\n",
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" MessagesPlaceholder(variable_name=\"messages\"),\n",
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" (\n",
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" \"system\",\n",
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" \"Given the conversation above, who should act next?\"\n",
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" \" Or should we FINISH? Select one of: {options}\",\n",
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" ),\n",
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" ]\n",
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" ).partial(options=str(options))\n",
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" chain = (\n",
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" prompt\n",
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" | llm.bind_functions(functions=[function_def], function_call=\"route\")\n",
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" | JsonOutputFunctionsParser()\n",
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" )\n",
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" workflow.add_node(\"supervisor\", chain)\n",
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" conditional_map = {k: k for k in members}\n",
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" conditional_map[\"FINISH\"] = END\n",
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"\n",
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" for member in members:\n",
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" workflow.add_edge(member, \"supervisor\")\n",
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" workflow.add_conditional_edges(\n",
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" \"supervisor\", lambda x: x[\"next\"], conditional_map\n",
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" )"
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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": "14778e86-077b-4e6a-893c-400e59b0cdbf",
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"metadata": {},
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"outputs": [],
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"source": [
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"create_agent_supervisor(\n",
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" [\"Researcher\", \"Chart Generator\", \"Data Analyst\"],\n",
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" llm,\n",
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" \"You are an agent supervisor tasked with managing work order.\"\n",
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" \" Respond with only the role will optimally help us accomplish the user's task or question.\"\n",
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" \" When finished, respond with FINISH.\",\n",
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")\n",
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"\n",
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"# Finally, add entrypoint\n",
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"workflow.set_entry_point(\"supervisor\")\n",
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"\n",
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"\n",
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"def enter(text: str) -> dict:\n",
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" return {\"messages\": [HumanMessage(content=text)]}\n",
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"\n",
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"\n",
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"graph = enter | workflow.compile()"
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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": "56ba78e9-d9c1-457c-a073-d606d5d3e013",
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"metadata": {},
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"outputs": [
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{
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"ename": "InvalidUpdateError",
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"evalue": "",
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"output_type": "error",
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"traceback": [
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"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
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"\u001b[0;31mInvalidUpdateError\u001b[0m Traceback (most recent call last)",
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"Cell \u001b[0;32mIn[7], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mgraph\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mCode hello world and print it to the terminal\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n",
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"File \u001b[0;32m~/code/lc/langchain/libs/core/langchain_core/runnables/base.py:1780\u001b[0m, in \u001b[0;36mRunnableSequence.invoke\u001b[0;34m(self, input, config)\u001b[0m\n\u001b[1;32m 1778\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1779\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m i, step \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28menumerate\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39msteps):\n\u001b[0;32m-> 1780\u001b[0m \u001b[38;5;28minput\u001b[39m \u001b[38;5;241m=\u001b[39m \u001b[43mstep\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1781\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1782\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;66;43;03m# mark each step as a child run\u001b[39;49;00m\n\u001b[1;32m 1783\u001b[0m \u001b[43m \u001b[49m\u001b[43mpatch_config\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1784\u001b[0m \u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrun_manager\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_child\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mseq:step:\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mi\u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1785\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 1786\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1787\u001b[0m \u001b[38;5;66;03m# finish the root run\u001b[39;00m\n\u001b[1;32m 1788\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n",
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"File \u001b[0;32m~/code/lc/langgraph/langgraph/pregel/__init__.py:521\u001b[0m, in \u001b[0;36mPregel.invoke\u001b[0;34m(self, input, config, output_keys, input_keys, **kwargs)\u001b[0m\n\u001b[1;32m 511\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21minvoke\u001b[39m(\n\u001b[1;32m 512\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 513\u001b[0m \u001b[38;5;28minput\u001b[39m: Union[\u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, Any], Any],\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 518\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Any,\n\u001b[1;32m 519\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Union[\u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, Any], Any]:\n\u001b[1;32m 520\u001b[0m latest: Union[\u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, Any], Any] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[0;32m--> 521\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstream\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 522\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 523\u001b[0m \u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 524\u001b[0m \u001b[43m \u001b[49m\u001b[43moutput_keys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moutput_keys\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43moutput_keys\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mis\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;129;43;01mnot\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moutput\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 525\u001b[0m \u001b[43m \u001b[49m\u001b[43minput_keys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minput_keys\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 526\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 527\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[1;32m 528\u001b[0m \u001b[43m \u001b[49m\u001b[43mlatest\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\n\u001b[1;32m 529\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m latest\n",
|
||||
"File \u001b[0;32m~/code/lc/langgraph/langgraph/pregel/__init__.py:557\u001b[0m, in \u001b[0;36mPregel.transform\u001b[0;34m(self, input, config, output_keys, input_keys, **kwargs)\u001b[0m\n\u001b[1;32m 548\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mtransform\u001b[39m(\n\u001b[1;32m 549\u001b[0m \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m 550\u001b[0m \u001b[38;5;28minput\u001b[39m: Iterator[Union[\u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, Any], Any]],\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 555\u001b[0m \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Any,\n\u001b[1;32m 556\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Iterator[Union[\u001b[38;5;28mdict\u001b[39m[\u001b[38;5;28mstr\u001b[39m, Any], Any]]:\n\u001b[0;32m--> 557\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_transform_stream_with_config\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 558\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43minput\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m 559\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_transform\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 560\u001b[0m \u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 561\u001b[0m \u001b[43m \u001b[49m\u001b[43moutput_keys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43moutput_keys\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 562\u001b[0m \u001b[43m \u001b[49m\u001b[43minput_keys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43minput_keys\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 563\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m 564\u001b[0m \u001b[43m \u001b[49m\u001b[43m)\u001b[49m\u001b[43m:\u001b[49m\n\u001b[1;32m 565\u001b[0m \u001b[43m \u001b[49m\u001b[38;5;28;43;01myield\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mchunk\u001b[49m\n",
|
||||
"File \u001b[0;32m~/code/lc/langchain/libs/core/langchain_core/runnables/base.py:1232\u001b[0m, in \u001b[0;36mRunnable._transform_stream_with_config\u001b[0;34m(self, input, transformer, config, run_type, **kwargs)\u001b[0m\n\u001b[1;32m 1230\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m 1231\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[0;32m-> 1232\u001b[0m chunk: Output \u001b[38;5;241m=\u001b[39m \u001b[43mcontext\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mnext\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43miterator\u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n\u001b[1;32m 1233\u001b[0m \u001b[38;5;28;01myield\u001b[39;00m chunk\n\u001b[1;32m 1234\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m final_output_supported:\n",
|
||||
"File \u001b[0;32m~/code/lc/langgraph/langgraph/pregel/__init__.py:335\u001b[0m, in \u001b[0;36mPregel._transform\u001b[0;34m(self, input, run_manager, config, input_keys, output_keys)\u001b[0m\n\u001b[1;32m 332\u001b[0m _interrupt_or_proceed(done, inflight, step)\n\u001b[1;32m 334\u001b[0m \u001b[38;5;66;03m# apply writes to channels\u001b[39;00m\n\u001b[0;32m--> 335\u001b[0m \u001b[43m_apply_writes\u001b[49m\u001b[43m(\u001b[49m\u001b[43mcheckpoint\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mchannels\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mpending_writes\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mconfig\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mstep\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m 337\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mdebug:\n\u001b[1;32m 338\u001b[0m print_checkpoint(step, channels)\n",
|
||||
"File \u001b[0;32m~/code/lc/langgraph/langgraph/pregel/__init__.py:687\u001b[0m, in \u001b[0;36m_apply_writes\u001b[0;34m(checkpoint, channels, pending_writes, config, for_step)\u001b[0m\n\u001b[1;32m 685\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m chan, vals \u001b[38;5;129;01min\u001b[39;00m pending_writes_by_channel\u001b[38;5;241m.\u001b[39mitems():\n\u001b[1;32m 686\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m chan \u001b[38;5;129;01min\u001b[39;00m channels:\n\u001b[0;32m--> 687\u001b[0m \u001b[43mchannels\u001b[49m\u001b[43m[\u001b[49m\u001b[43mchan\u001b[49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mupdate\u001b[49m\u001b[43m(\u001b[49m\u001b[43mvals\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 688\u001b[0m checkpoint[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mchannel_versions\u001b[39m\u001b[38;5;124m\"\u001b[39m][chan] \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n\u001b[1;32m 689\u001b[0m updated_channels\u001b[38;5;241m.\u001b[39madd(chan)\n",
|
||||
"File \u001b[0;32m~/code/lc/langgraph/langgraph/channels/last_value.py:47\u001b[0m, in \u001b[0;36mLastValue.update\u001b[0;34m(self, values)\u001b[0m\n\u001b[1;32m 45\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m\n\u001b[1;32m 46\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(values) \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[0;32m---> 47\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m InvalidUpdateError()\n\u001b[1;32m 49\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mvalue \u001b[38;5;241m=\u001b[39m values[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m]\n",
|
||||
"\u001b[0;31mInvalidUpdateError\u001b[0m: "
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"graph.invoke(\"Code hello world and print it to the terminal\")"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.11.2"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
File diff suppressed because one or more lines are too long
Reference in New Issue
Block a user