mirror of
https://github.com/hwchase17/langchain.git
synced 2025-09-05 21:12:48 +00:00
Callbacks Refactor [base] (#3256)
Co-authored-by: Nuno Campos <nuno@boringbits.io> Co-authored-by: Davis Chase <130488702+dev2049@users.noreply.github.com> Co-authored-by: Zander Chase <130414180+vowelparrot@users.noreply.github.com> Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
This commit is contained in:
Ankush Gola
GitHub
@@ -5,7 +5,14 @@
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"id": "5371a9bb",
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"metadata": {},
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"source": [
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"# Tracing Walkthrough"
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"# Tracing Walkthrough\n",
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"\n",
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"There are two recommended ways to trace your LangChains:\n",
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"\n",
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"1. Setting the `LANGCHAIN_TRACING` environment variable to \"true\".\n",
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"1. Using a context manager with tracing_enabled() to trace a particular block of code.\n",
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"\n",
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"**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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]
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},
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{
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@@ -18,24 +25,22 @@
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"outputs": [],
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"source": [
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"import os\n",
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"os.environ[\"LANGCHAIN_HANDLER\"] = \"langchain\"\n",
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"\n",
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"## Uncomment this if using hosted setup.\n",
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"os.environ[\"LANGCHAIN_TRACING\"] = \"true\"\n",
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"\n",
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"## Uncomment below if using hosted setup.\n",
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"# os.environ[\"LANGCHAIN_ENDPOINT\"] = \"https://langchain-api-gateway-57eoxz8z.uc.gateway.dev\" \n",
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"\n",
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"## Uncomment this if you want traces to be recorded to \"my_session\" instead of default.\n",
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"\n",
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"## Uncomment below if you want traces to be recorded to \"my_session\" instead of \"default\".\n",
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"# os.environ[\"LANGCHAIN_SESSION\"] = \"my_session\" \n",
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"\n",
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"## Better to set this environment variable in the terminal\n",
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"## Uncomment this if using hosted version. Replace \"my_api_key\" with your actual API Key.\n",
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"\n",
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"## Uncomment below if using hosted version. Replace \"my_api_key\" with your actual API Key.\n",
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"# os.environ[\"LANGCHAIN_API_KEY\"] = \"my_api_key\" \n",
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"\n",
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"import langchain\n",
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"from langchain.agents import Tool, initialize_agent, load_tools\n",
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"from langchain.agents import AgentType\n",
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"from langchain.callbacks import tracing_enabled\n",
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"from langchain.chat_models import ChatOpenAI\n",
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"from langchain.llms import OpenAI"
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]
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@@ -73,8 +78,7 @@
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"\u001b[32;1m\u001b[1;3m I need to use a calculator to solve this.\n",
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"Action: Calculator\n",
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"Action Input: 2^.123243\u001b[0m\n",
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"Observation: \u001b[36;1m\u001b[1;3mAnswer: 1.0891804557407723\n",
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"\u001b[0m\n",
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"Observation: \u001b[36;1m\u001b[1;3mAnswer: 1.0891804557407723\u001b[0m\n",
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"Thought:\u001b[32;1m\u001b[1;3m I now know the final answer.\n",
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"Final Answer: 1.0891804557407723\u001b[0m\n",
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"\n",
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@@ -104,7 +108,9 @@
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"cell_type": "code",
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"execution_count": 4,
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"id": "4829eb1d",
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"metadata": {},
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"name": "stdout",
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@@ -113,52 +119,11 @@
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"\n",
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"\n",
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"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
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"\u001b[32;1m\u001b[1;3mQuestion: What is 2 raised to .123243 power?\n",
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"Thought: I need a calculator to solve this problem.\n",
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"Action:\n",
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"```\n",
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"{\n",
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" \"action\": \"calculator\",\n",
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" \"action_input\": \"2^0.123243\"\n",
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"}\n",
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"```\n",
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"\u001b[0m\n",
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"Observation: calculator is not a valid tool, try another one.\n",
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"\u001b[32;1m\u001b[1;3mI made a mistake, I need to use the correct tool for this question.\n",
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"Action:\n",
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"```\n",
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"{\n",
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" \"action\": \"calculator\",\n",
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" \"action_input\": \"2^0.123243\"\n",
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"}\n",
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"```\n",
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"\n",
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"\u001b[0m\n",
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"Observation: calculator is not a valid tool, try another one.\n",
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"\u001b[32;1m\u001b[1;3mI made a mistake, the tool name is actually \"calc\" instead of \"calculator\".\n",
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"Action:\n",
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"```\n",
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"{\n",
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" \"action\": \"calc\",\n",
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" \"action_input\": \"2^0.123243\"\n",
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"}\n",
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"```\n",
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"\n",
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"\u001b[0m\n",
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"Observation: calc is not a valid tool, try another one.\n",
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"\u001b[32;1m\u001b[1;3mI made another mistake, the tool name is actually \"Calculator\" instead of \"calc\".\n",
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"Action:\n",
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"```\n",
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"{\n",
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" \"action\": \"Calculator\",\n",
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" \"action_input\": \"2^0.123243\"\n",
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"}\n",
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"```\n",
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"\n",
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"\u001b[0m\n",
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"Observation: \u001b[36;1m\u001b[1;3mAnswer: 1.0891804557407723\n",
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"\u001b[0m\n",
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"Thought:\u001b[32;1m\u001b[1;3mThe final answer is 1.0891804557407723.\n",
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"\u001b[32;1m\u001b[1;3mI need to use a calculator to solve this.\n",
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"Action: Calculator\n",
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"Action Input: 2 ^ .123243\u001b[0m\n",
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"Observation: \u001b[36;1m\u001b[1;3mAnswer: 1.0891804557407723\u001b[0m\n",
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"Thought:\u001b[32;1m\u001b[1;3mI now know the answer to the question. \n",
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"Final Answer: 1.0891804557407723\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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@@ -186,8 +151,182 @@
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"execution_count": 5,
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"id": "76abfd82",
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"metadata": {
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"tags": []
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},
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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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"\n",
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"\n",
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"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
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"\u001b[32;1m\u001b[1;3mI need to use a calculator to solve this.\n",
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"Action: Calculator\n",
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"Action Input: 2 ^ .123243\u001b[0m\n",
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"Observation: \u001b[36;1m\u001b[1;3mAnswer: 1.0891804557407723\u001b[0m\n",
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"Thought:\u001b[32;1m\u001b[1;3mI now know the answer to the question. \n",
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"Final Answer: 1.0891804557407723\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n",
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"\n",
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"\n",
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"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
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"\u001b[32;1m\u001b[1;3mI need to use a calculator to solve this.\n",
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"Action: Calculator\n",
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"Action Input: 5 ^ .123243\u001b[0m\n",
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"Observation: \u001b[36;1m\u001b[1;3mAnswer: 1.2193914912400514\u001b[0m\n",
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"Thought:\u001b[32;1m\u001b[1;3mI now know the answer to the question. \n",
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"Final Answer: 1.2193914912400514\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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}
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],
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"source": [
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"# Both of the agent runs will be traced because the environment variable is set\n",
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"agent.run(\"What is 2 raised to .123243 power?\")\n",
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"with tracing_enabled() as session:\n",
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" agent.run(\"What is 5 raised to .123243 power?\")"
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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": "fe833c33-033f-4806-be0c-cc3d147db13d",
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"metadata": {
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"tags": []
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},
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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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"\n",
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"\n",
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"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
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"\u001b[32;1m\u001b[1;3mI need to use a calculator to solve this.\n",
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"Action: Calculator\n",
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"Action Input: 5 ^ .123243\u001b[0m\n",
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"Observation: \u001b[36;1m\u001b[1;3mAnswer: 1.2193914912400514\u001b[0m\n",
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"Thought:\u001b[32;1m\u001b[1;3mI now know the answer to the question. \n",
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"Final Answer: 1.2193914912400514\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n",
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"\n",
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"\n",
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"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
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"\u001b[32;1m\u001b[1;3mI need to use a calculator to solve this.\n",
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"Action: Calculator\n",
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"Action Input: 2 ^ .123243\u001b[0m\n",
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"Observation: \u001b[36;1m\u001b[1;3mAnswer: 1.0891804557407723\u001b[0m\n",
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"Thought:\u001b[32;1m\u001b[1;3mI now know the answer to the question. \n",
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"Final Answer: 1.0891804557407723\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"'1.0891804557407723'"
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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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"# Now, we unset the environment variable and use a context manager.\n",
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"if \"LANGCHAIN_TRACING\" in os.environ:\n",
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" del os.environ[\"LANGCHAIN_TRACING\"]\n",
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"\n",
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"# here, we are writing traces to \"my_test_session\"\n",
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"with tracing_enabled(\"my_session\") as session:\n",
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" assert session\n",
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" agent.run(\"What is 5 raised to .123243 power?\") # this should be traced\n",
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"\n",
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"agent.run(\"What is 2 raised to .123243 power?\") # this should not be traced"
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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": 14,
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"id": "b34105a4-be8e-46e4-8abe-01adba3ba727",
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"metadata": {
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"tags": []
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},
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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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"\n",
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"\n",
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"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
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"\n",
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"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
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"\n",
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"\n",
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"\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
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"\n",
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"\u001b[32;1m\u001b[1;3mI need to use a calculator to solve this.\n",
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"Action: Calculator\n",
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"Action Input: 3^0.123\u001b[0m\u001b[32;1m\u001b[1;3mI need to use a calculator to solve this.\n",
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"Action: Calculator\n",
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"Action Input: 2^0.123\u001b[0m\u001b[32;1m\u001b[1;3mAny number raised to the power of 0 is 1, but I'm not sure about a decimal power.\n",
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"Action: Calculator\n",
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"Action Input: 1^.123\u001b[0m\n",
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"Observation: \u001b[36;1m\u001b[1;3mAnswer: 1.1446847956963533\u001b[0m\n",
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"Thought:\n",
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"Observation: \u001b[36;1m\u001b[1;3mAnswer: 1.0889970153361064\u001b[0m\n",
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"Thought:\n",
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"Observation: \u001b[36;1m\u001b[1;3mAnswer: 1.0\u001b[0m\n",
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"Thought:\n",
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"\u001b[1m> Finished chain.\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished chain.\u001b[0m\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"'1.0'"
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]
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},
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"execution_count": 14,
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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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"# The context manager is concurrency safe:\n",
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"import asyncio \n",
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"if \"LANGCHAIN_TRACING\" in os.environ:\n",
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" del os.environ[\"LANGCHAIN_TRACING\"]\n",
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" \n",
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"questions = [f\"What is {i} raised to .123 power?\" for i in range(1,4)]\n",
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"\n",
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"# start a background task\n",
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"task = asyncio.create_task(agent.arun(questions[0])) # this should not be traced\n",
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"with tracing_enabled() as session:\n",
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" assert session\n",
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" tasks = [agent.arun(q) for q in questions[1:3]] # these should be traced\n",
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" await asyncio.gather(*tasks)\n",
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"\n",
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"await task"
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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": null,
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"id": "4e46c85b-2ac0-4661-abed-9c2bf3036820",
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"metadata": {},
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"outputs": [],
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"source": []
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@@ -209,7 +348,7 @@
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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": "3.9.1"
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"version": "3.10.9"
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}
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},
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"nbformat": 4,
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