langchain/docs/extras/modules/callbacks/filecallbackhandler.ipynb
2023-07-23 23:23:16 -07:00

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"# Logging to file\n",
"This example shows how to print logs to file. It shows how to use the `FileCallbackHandler`, which does the same thing as [`StdOutCallbackHandler`](https://python.langchain.com/en/latest/modules/callbacks/getting_started.html#using-an-existing-handler), but instead writes the output to file. It also uses the `loguru` library to log other outputs that are not captured by the handler."
]
},
{
"cell_type": "code",
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"id": "6cb156cc",
"metadata": {},
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{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"\u001b[1m> Entering new LLMChain chain...\u001b[0m\n",
"Prompt after formatting:\n",
"\u001b[32;1m\u001b[1;3m1 + 2 = \u001b[0m\n"
]
},
{
"name": "stderr",
"output_type": "stream",
"text": [
"\u001b[32m2023-06-01 18:36:38.929\u001b[0m | \u001b[1mINFO \u001b[0m | \u001b[36m__main__\u001b[0m:\u001b[36m<module>\u001b[0m:\u001b[36m20\u001b[0m - \u001b[1m\n",
"\n",
"3\u001b[0m\n"
]
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\u001b[1m> Finished chain.\u001b[0m\n"
]
}
],
"source": [
"from loguru import logger\n",
"\n",
"from langchain.callbacks import FileCallbackHandler\n",
"from langchain.chains import LLMChain\n",
"from langchain.llms import OpenAI\n",
"from langchain.prompts import PromptTemplate\n",
"\n",
"logfile = \"output.log\"\n",
"\n",
"logger.add(logfile, colorize=True, enqueue=True)\n",
"handler = FileCallbackHandler(logfile)\n",
"\n",
"llm = OpenAI()\n",
"prompt = PromptTemplate.from_template(\"1 + {number} = \")\n",
"\n",
"# this chain will both print to stdout (because verbose=True) and write to 'output.log'\n",
"# if verbose=False, the FileCallbackHandler will still write to 'output.log'\n",
"chain = LLMChain(llm=llm, prompt=prompt, callbacks=[handler], verbose=True)\n",
"answer = chain.run(number=2)\n",
"logger.info(answer)"
]
},
{
"cell_type": "markdown",
"id": "9c50d54f",
"metadata": {},
"source": [
"Now we can open the file `output.log` to see that the output has been captured."
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "aa32dc0a",
"metadata": {},
"outputs": [],
"source": [
"!pip install ansi2html > /dev/null"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "4af00719",
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"<!DOCTYPE HTML PUBLIC \"-//W3C//DTD HTML 4.01 Transitional//EN\" \"http://www.w3.org/TR/html4/loose.dtd\">\n",
"<html>\n",
"<head>\n",
"<meta http-equiv=\"Content-Type\" content=\"text/html; charset=utf-8\">\n",
"<title></title>\n",
"<style type=\"text/css\">\n",
".ansi2html-content { display: inline; white-space: pre-wrap; word-wrap: break-word; }\n",
".body_foreground { color: #AAAAAA; }\n",
".body_background { background-color: #000000; }\n",
".inv_foreground { color: #000000; }\n",
".inv_background { background-color: #AAAAAA; }\n",
".ansi1 { font-weight: bold; }\n",
".ansi3 { font-style: italic; }\n",
".ansi32 { color: #00aa00; }\n",
".ansi36 { color: #00aaaa; }\n",
"</style>\n",
"</head>\n",
"<body class=\"body_foreground body_background\" style=\"font-size: normal;\" >\n",
"<pre class=\"ansi2html-content\">\n",
"\n",
"\n",
"<span class=\"ansi1\">&gt; Entering new LLMChain chain...</span>\n",
"Prompt after formatting:\n",
"<span class=\"ansi1 ansi32\"></span><span class=\"ansi1 ansi3 ansi32\">1 + 2 = </span>\n",
"\n",
"<span class=\"ansi1\">&gt; Finished chain.</span>\n",
"<span class=\"ansi32\">2023-06-01 18:36:38.929</span> | <span class=\"ansi1\">INFO </span> | <span class=\"ansi36\">__main__</span>:<span class=\"ansi36\">&lt;module&gt;</span>:<span class=\"ansi36\">20</span> - <span class=\"ansi1\">\n",
"\n",
"3</span>\n",
"\n",
"</pre>\n",
"</body>\n",
"\n",
"</html>\n"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from IPython.display import display, HTML\n",
"from ansi2html import Ansi2HTMLConverter\n",
"\n",
"with open(\"output.log\", \"r\") as f:\n",
" content = f.read()\n",
"\n",
"conv = Ansi2HTMLConverter()\n",
"html = conv.convert(content, full=True)\n",
"\n",
"display(HTML(html))"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
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"language_info": {
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"file_extension": ".py",
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