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big docs refactor (#1978)
Co-authored-by: Ankush Gola <ankush.gola@gmail.com>
This commit is contained in:
Harrison Chase
GitHub
166
docs/modules/models/chat/examples/few_shot_examples.ipynb
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166
docs/modules/models/chat/examples/few_shot_examples.ipynb
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "bb0735c0",
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"metadata": {},
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"source": [
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"# How to use few shot examples\n",
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"\n",
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"This notebook covers how to use few shot examples in chat models.\n",
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"\n",
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"There does not appear to be solid consensus on how best to do few shot prompting. As a result, we are not solidifying any abstractions around this yet but rather using existing abstractions."
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]
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},
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{
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"cell_type": "markdown",
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"id": "c6e9664c",
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"metadata": {},
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"source": [
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"## Alternating Human/AI messages\n",
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"The first way of doing few shot prompting relies on using alternating human/ai messages. See an example of this below."
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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": "62156fe4",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.chat_models import ChatOpenAI\n",
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"from langchain import PromptTemplate, LLMChain\n",
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"from langchain.prompts.chat import (\n",
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" ChatPromptTemplate,\n",
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" SystemMessagePromptTemplate,\n",
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" AIMessagePromptTemplate,\n",
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" HumanMessagePromptTemplate,\n",
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")\n",
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"from langchain.schema import (\n",
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" AIMessage,\n",
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" HumanMessage,\n",
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" SystemMessage\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": 2,
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"id": "ed7ac3c6",
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"metadata": {},
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"outputs": [],
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"source": [
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"chat = ChatOpenAI(temperature=0)"
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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": "98791aa9",
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"metadata": {},
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"outputs": [],
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"source": [
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"template=\"You are a helpful assistant that translates english to pirate.\"\n",
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"system_message_prompt = SystemMessagePromptTemplate.from_template(template)\n",
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"example_human = HumanMessagePromptTemplate.from_template(\"Hi\")\n",
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"example_ai = AIMessagePromptTemplate.from_template(\"Argh me mateys\")\n",
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"human_template=\"{text}\"\n",
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"human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)"
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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": "4eebdcd7",
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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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"\"I be lovin' programmin', me hearty!\""
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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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"chat_prompt = ChatPromptTemplate.from_messages([system_message_prompt, example_human, example_ai, human_message_prompt])\n",
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"chain = LLMChain(llm=chat, prompt=chat_prompt)\n",
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"# get a chat completion from the formatted messages\n",
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"chain.run(\"I love programming.\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "5c4135d7",
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"metadata": {},
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"source": [
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"## System Messages\n",
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"\n",
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"OpenAI provides an optional `name` parameter that they also recommend using in conjunction with system messages to do few shot prompting. Here is an example of how to do that below."
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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": "1ba92d59",
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"metadata": {},
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"outputs": [],
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"source": [
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"template=\"You are a helpful assistant that translates english to pirate.\"\n",
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"system_message_prompt = SystemMessagePromptTemplate.from_template(template)\n",
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"example_human = SystemMessagePromptTemplate.from_template(\"Hi\", additional_kwargs={\"name\": \"example_user\"})\n",
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"example_ai = SystemMessagePromptTemplate.from_template(\"Argh me mateys\", additional_kwargs={\"name\": \"example_assistant\"})\n",
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"human_template=\"{text}\"\n",
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"human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)"
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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": "56e488a7",
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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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"\"I be lovin' programmin', me hearty.\""
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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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"chat_prompt = ChatPromptTemplate.from_messages([system_message_prompt, example_human, example_ai, human_message_prompt])\n",
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"chain = LLMChain(llm=chat, prompt=chat_prompt)\n",
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"# get a chat completion from the formatted messages\n",
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"chain.run(\"I love programming.\")"
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]
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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": "3.9.1"
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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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