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langchain/docs/extras/integrations/providers/wandb_tracing.ipynb

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"# 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."
]
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"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"
]
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"# 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)"
]
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"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/<wandb_entity>/<wandb_project>/runs/<run_id>\n",
"# The url can be used to view the trace session in wandb."
]
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"\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"
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"# 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"
]
}
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