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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# LLMCheckerChain\n",
"This notebook showcases how to use LLMCheckerChain."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"\n",
"\u001b[1m> Entering new LLMCheckerChain chain...\u001b[0m\n",
"\n",
"\n",
"\u001b[1m> Entering new SequentialChain chain...\u001b[0m\n",
"\u001b[1mChain 0\u001b[0m:\n",
"{'statement': '\\nNone. Mammals do not lay eggs.'}\n",
"\n",
"\u001b[1mChain 1\u001b[0m:\n",
"{'assertions': '\\n• Mammals reproduce using live birth\\n• Mammals do not lay eggs\\n• Animals that lay eggs are not mammals'}\n",
"\n",
"\u001b[1mChain 2\u001b[0m:\n",
"{'checked_assertions': '\\n1. True\\n\\n2. True\\n\\n3. False - Mammals are a class of animals that includes animals that lay eggs, such as monotremes (platypus and echidna).'}\n",
"\n",
"\u001b[1mChain 3\u001b[0m:\n",
"{'revised_statement': ' Monotremes, such as the platypus and echidna, lay the biggest eggs of any mammal.'}\n",
"\n",
"\n",
"\u001b[1m> Finished SequentialChain chain.\u001b[0m\n",
"\n",
"\u001b[1m> Finished LLMCheckerChain chain.\u001b[0m\n"
]
},
{
"data": {
"text/plain": [
"' Monotremes, such as the platypus and echidna, lay the biggest eggs of any mammal.'"
]
},
"execution_count": 1,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from langchain.chains import LLMCheckerChain\n",
"from langchain.llms import OpenAI\n",
"\n",
"llm = OpenAI(temperature=0.7)\n",
"\n",
"text = \"What type of mammal lays the biggest eggs?\"\n",
"\n",
"checker_chain = LLMCheckerChain(llm=llm, verbose=True)\n",
"\n",
"checker_chain.run(text)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": []
}
],
"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": "3.10.9"
}
},
"nbformat": 4,
"nbformat_minor": 4
}
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