{ "cells": [ { "cell_type": "markdown", "id": "5371a9bb", "metadata": {}, "source": [ "# WandB Tracing\n", "\n", "There are two recommended ways to trace your LangChains:\n", "\n", "1. Setting the `LANGCHAIN_WANDB_TRACING` environment variable to \"true\".\n", "1. Using a context manager with tracing_enabled() to trace a particular block of code.\n", "\n", "**Note** if the environment variable is set, all code will be traced, regardless of whether or not it's within the context manager." ] }, { "cell_type": "code", "execution_count": 1, "id": "17c04cc6-c93d-4b6c-a033-e897577f4ed1", "metadata": { "ExecuteTime": { "end_time": "2023-05-18T12:47:46.580776Z", "start_time": "2023-05-18T12:47:46.577833Z" }, "tags": [] }, "outputs": [], "source": [ "import os\n", "\n", "os.environ[\"LANGCHAIN_WANDB_TRACING\"] = \"true\"\n", "\n", "# wandb documentation to configure wandb using env variables\n", "# https://docs.wandb.ai/guides/track/advanced/environment-variables\n", "# here we are configuring the wandb project name\n", "os.environ[\"WANDB_PROJECT\"] = \"langchain-tracing\"\n", "\n", "from langchain.agents import initialize_agent, load_tools\n", "from langchain.agents import AgentType\n", "from langchain.llms import OpenAI\n", "from langchain.callbacks import wandb_tracing_enabled" ] }, { "cell_type": "code", "execution_count": 2, "id": "1b62cd48", "metadata": { "ExecuteTime": { "end_time": "2023-05-18T12:47:47.445229Z", "start_time": "2023-05-18T12:47:47.436424Z" }, "tags": [] }, "outputs": [], "source": [ "# Agent run with tracing. Ensure that OPENAI_API_KEY is set appropriately to run this example.\n", "\n", "llm = OpenAI(temperature=0)\n", "tools = load_tools([\"llm-math\"], llm=llm)" ] }, { "cell_type": "code", "execution_count": null, "id": "bfa16b79-aa4b-4d41-a067-70d1f593f667", "metadata": { "ExecuteTime": { "end_time": "2023-05-18T12:48:01.816137Z", "start_time": "2023-05-18T12:47:49.109574Z" }, "tags": [] }, "outputs": [], "source": [ "agent = initialize_agent(\n", " tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True\n", ")\n", "\n", "agent.run(\"What is 2 raised to .123243 power?\") # this should be traced\n", "# A url with for the trace sesion like the following should print in your console:\n", "# https://wandb.ai///runs/\n", "# The url can be used to view the trace session in wandb." ] }, { "cell_type": "code", "execution_count": 4, "id": "fe833c33-033f-4806-be0c-cc3d147db13d", "metadata": { "ExecuteTime": { "end_time": "2023-05-18T12:48:25.909223Z", "start_time": "2023-05-18T12:48:09.657895Z" }, "tags": [] }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "\n", "\n", "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", "\u001b[32;1m\u001b[1;3m I need to use a calculator to solve this.\n", "Action: Calculator\n", "Action Input: 5^.123243\u001b[0m\n", "Observation: \u001b[36;1m\u001b[1;3mAnswer: 1.2193914912400514\u001b[0m\n", "Thought:\u001b[32;1m\u001b[1;3m I now know the final answer.\n", "Final Answer: 1.2193914912400514\u001b[0m\n", "\n", "\u001b[1m> Finished chain.\u001b[0m\n", "\n", "\n", "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", "\u001b[32;1m\u001b[1;3m I need to use a calculator to solve this.\n", "Action: Calculator\n", "Action Input: 2^.123243\u001b[0m\n", "Observation: \u001b[36;1m\u001b[1;3mAnswer: 1.0891804557407723\u001b[0m\n", "Thought:\u001b[32;1m\u001b[1;3m I now know the final answer.\n", "Final Answer: 1.0891804557407723\u001b[0m\n", "\n", "\u001b[1m> Finished chain.\u001b[0m\n" ] }, { "data": { "text/plain": [ "'1.0891804557407723'" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "# Now, we unset the environment variable and use a context manager.\n", "if \"LANGCHAIN_WANDB_TRACING\" in os.environ:\n", " del os.environ[\"LANGCHAIN_WANDB_TRACING\"]\n", "\n", "# enable tracing using a context manager\n", "with wandb_tracing_enabled():\n", " agent.run(\"What is 5 raised to .123243 power?\") # this should be traced\n", "\n", "agent.run(\"What is 2 raised to .123243 power?\") # this should not be traced" ] } ], "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": "3.11.3" } }, "nbformat": 4, "nbformat_minor": 5 }