mirror of
https://github.com/hwchase17/langchain
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b1fa726377
Updates docs and cookbooks to import ChatOpenAI, OpenAI, and OpenAI Embeddings from `langchain_openai` There are likely more --------- Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
293 lines
7.2 KiB
Plaintext
293 lines
7.2 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "32e022a2",
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"metadata": {},
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"source": [
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"# Program-aided language model (PAL) chain\n",
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"\n",
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"Implements Program-Aided Language Models, as in https://arxiv.org/pdf/2211.10435.pdf.\n"
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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": 1,
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"id": "1370e40f",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain_experimental.pal_chain import PALChain\n",
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"from langchain_openai import OpenAI"
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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": "9a58e15e",
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"metadata": {},
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"outputs": [],
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"source": [
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"llm = OpenAI(temperature=0, max_tokens=512)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "095adc76",
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"metadata": {},
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"source": [
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"## Math Prompt"
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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": 2,
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"id": "beddcac7",
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"metadata": {},
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"outputs": [],
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"source": [
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"pal_chain = PALChain.from_math_prompt(llm, verbose=True)"
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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": 3,
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"id": "e2eab9d4",
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"metadata": {},
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"outputs": [],
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"source": [
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"question = \"Jan has three times the number of pets as Marcia. Marcia has two more pets than Cindy. If Cindy has four pets, how many total pets do the three have?\""
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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": 4,
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"id": "3ef64b27",
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"metadata": {
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"scrolled": true
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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 PALChain chain...\u001b[0m\n",
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"\u001b[32;1m\u001b[1;3mdef solution():\n",
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" \"\"\"Jan has three times the number of pets as Marcia. Marcia has two more pets than Cindy. If Cindy has four pets, how many total pets do the three have?\"\"\"\n",
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" cindy_pets = 4\n",
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" marcia_pets = cindy_pets + 2\n",
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" jan_pets = marcia_pets * 3\n",
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" total_pets = cindy_pets + marcia_pets + jan_pets\n",
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" result = total_pets\n",
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" return result\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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"'28'"
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]
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},
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"execution_count": 4,
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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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"pal_chain.run(question)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "0269d20a",
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"metadata": {},
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"source": [
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"## Colored Objects"
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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": 5,
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"id": "e524f81f",
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"metadata": {},
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"outputs": [],
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"source": [
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"pal_chain = PALChain.from_colored_object_prompt(llm, verbose=True)"
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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": "03a237b8",
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"metadata": {},
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"outputs": [],
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"source": [
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"question = \"On the desk, you see two blue booklets, two purple booklets, and two yellow pairs of sunglasses. If I remove all the pairs of sunglasses from the desk, how many purple items remain on it?\""
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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": 7,
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"id": "a84a4352",
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"metadata": {},
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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 PALChain chain...\u001b[0m\n",
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"\u001b[32;1m\u001b[1;3m# Put objects into a list to record ordering\n",
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"objects = []\n",
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"objects += [('booklet', 'blue')] * 2\n",
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"objects += [('booklet', 'purple')] * 2\n",
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"objects += [('sunglasses', 'yellow')] * 2\n",
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"\n",
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"# Remove all pairs of sunglasses\n",
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"objects = [object for object in objects if object[0] != 'sunglasses']\n",
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"\n",
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"# Count number of purple objects\n",
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"num_purple = len([object for object in objects if object[1] == 'purple'])\n",
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"answer = num_purple\u001b[0m\n",
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"\n",
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"\u001b[1m> Finished PALChain 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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"'2'"
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]
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},
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"execution_count": 7,
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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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"pal_chain.run(question)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "fc3d7f10",
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"metadata": {},
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"source": [
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"## Intermediate Steps\n",
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"You can also use the intermediate steps flag to return the code executed that generates the answer."
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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": 5,
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"id": "9d2d9c61",
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"metadata": {},
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"outputs": [],
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"source": [
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"pal_chain = PALChain.from_colored_object_prompt(\n",
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" llm, verbose=True, return_intermediate_steps=True\n",
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")"
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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": "b29b971b",
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"metadata": {},
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"outputs": [],
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"source": [
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"question = \"On the desk, you see two blue booklets, two purple booklets, and two yellow pairs of sunglasses. If I remove all the pairs of sunglasses from the desk, how many purple items remain on it?\""
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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": 8,
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"id": "a2c40c28",
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"metadata": {},
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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 PALChain chain...\u001b[0m\n",
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"\u001b[32;1m\u001b[1;3m# Put objects into a list to record ordering\n",
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"objects = []\n",
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"objects += [('booklet', 'blue')] * 2\n",
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"objects += [('booklet', 'purple')] * 2\n",
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"objects += [('sunglasses', 'yellow')] * 2\n",
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"\n",
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"# Remove all pairs of sunglasses\n",
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"objects = [object for object in objects if object[0] != 'sunglasses']\n",
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"\n",
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"# Count number of purple objects\n",
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"num_purple = len([object for object in objects if object[1] == 'purple'])\n",
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"answer = num_purple\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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"result = pal_chain({\"question\": question})"
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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": 11,
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"id": "efddd033",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"\"# Put objects into a list to record ordering\\nobjects = []\\nobjects += [('booklet', 'blue')] * 2\\nobjects += [('booklet', 'purple')] * 2\\nobjects += [('sunglasses', 'yellow')] * 2\\n\\n# Remove all pairs of sunglasses\\nobjects = [object for object in objects if object[0] != 'sunglasses']\\n\\n# Count number of purple objects\\nnum_purple = len([object for object in objects if object[1] == 'purple'])\\nanswer = num_purple\""
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]
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},
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"execution_count": 11,
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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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"result[\"intermediate_steps\"]"
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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": "dfd88594",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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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": "3.11.3"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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