forked from Archives/langchain
985496f4be
Big docs refactor! Motivation is to make it easier for people to find resources they are looking for. To accomplish this, there are now three main sections: - Getting Started: steps for getting started, walking through most core functionality - Modules: these are different modules of functionality that langchain provides. Each part here has a "getting started", "how to", "key concepts" and "reference" section (except in a few select cases where it didnt easily fit). - Use Cases: this is to separate use cases (like summarization, question answering, evaluation, etc) from the modules, and provide a different entry point to the code base. There is also a full reference section, as well as extra resources (glossary, gallery, etc) Co-authored-by: Shreya Rajpal <ShreyaR@users.noreply.github.com>
540 lines
13 KiB
Plaintext
540 lines
13 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "43fb16cb",
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"metadata": {},
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"source": [
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"# Prompt Serialization\n",
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"\n",
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"It is often preferrable to store prompts not as python code but as files. This can make it easy to share, store, and version prompts. This notebook covers how to do that in LangChain, walking through all the different types of prompts and the different serialization options.\n",
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"\n",
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"At a high level, the following design principles are applied to serialization:\n",
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"\n",
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"1. Both JSON and YAML are supported. We want to support serialization methods that are human readable on disk, and YAML and JSON are two of the most popular methods for that. Note that this rule applies to prompts. For other assets, like Examples, different serialization methods may be supported.\n",
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"\n",
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"2. We support specifying everything in one file, or storing different components (templates, examples, etc) in different files and referencing them. For some cases, storing everything in file makes the most sense, but for others it is preferrable to split up some of the assets (long templates, large examples, reusable components). LangChain supports both.\n",
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"\n",
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"There is also a single entry point to load prompts from disk, making it easy to load any type of 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": 1,
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"id": "2c8d7587",
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"metadata": {},
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"outputs": [],
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"source": [
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"# All prompts are loaded through the `load_prompt` function.\n",
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"from langchain.prompts import load_prompt"
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]
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},
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{
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"cell_type": "markdown",
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"id": "cddb465e",
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"metadata": {},
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"source": [
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"## PromptTemplate\n",
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"\n",
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"This section covers examples for loading a PromptTemplate."
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]
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},
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{
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"cell_type": "markdown",
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"id": "4d4b40f2",
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"metadata": {},
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"source": [
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"### Loading from YAML\n",
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"This shows an example of loading a PromptTemplate from YAML."
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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": "2d6e5117",
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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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"input_variables:\r\n",
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" [\"adjective\", \"content\"]\r\n",
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"template: \r\n",
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" Tell me a {adjective} joke about {content}.\r\n"
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]
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}
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],
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"source": [
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"!cat simple_prompt.yaml"
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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": "4f4ca686",
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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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"Tell me a funny joke about chickens.\n"
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]
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}
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],
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"source": [
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"prompt = load_prompt(\"simple_prompt.yaml\")\n",
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"print(prompt.format(adjective=\"funny\", content=\"chickens\"))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "362eadb2",
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"metadata": {},
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"source": [
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"### Loading from JSON\n",
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"This shows an example of loading a PromptTemplate from JSON."
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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": "510def23",
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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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"{\r\n",
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" \"input_variables\": [\"adjective\", \"content\"],\r\n",
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" \"template\": \"Tell me a {adjective} joke about {content}.\"\r\n",
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"}\r\n"
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]
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}
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],
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"source": [
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"!cat simple_prompt.json"
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]
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},
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{
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"cell_type": "markdown",
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"id": "d788a83c",
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"metadata": {},
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"source": [
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"### Loading Template from a File\n",
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"This shows an example of storing the template in a separate file and then referencing it in the config. Notice that the key changes from `template` to `template_path`."
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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": "5547760d",
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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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"Tell me a {adjective} joke about {content}."
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]
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}
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],
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"source": [
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"!cat simple_template.txt"
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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": "9cb13ac5",
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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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"{\r\n",
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" \"input_variables\": [\"adjective\", \"content\"],\r\n",
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" \"template_path\": \"simple_template.txt\"\r\n",
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"}\r\n"
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]
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}
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],
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"source": [
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"!cat simple_prompt_with_template_file.json"
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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": "762cb4bf",
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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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"Tell me a funny joke about chickens.\n"
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]
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}
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],
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"source": [
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"prompt = load_prompt(\"simple_prompt_with_template_file.json\")\n",
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"print(prompt.format(adjective=\"funny\", content=\"chickens\"))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "2ae191cc",
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"metadata": {},
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"source": [
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"## FewShotPromptTemplate\n",
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"\n",
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"This section covers examples for loading few shot prompt templates."
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]
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},
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{
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"cell_type": "markdown",
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"id": "9828f94c",
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"metadata": {},
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"source": [
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"### Examples\n",
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"This shows an example of what examples stored as json might look like."
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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": "b21f5b95",
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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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"[\r\n",
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" {\"input\": \"happy\", \"output\": \"sad\"},\r\n",
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" {\"input\": \"tall\", \"output\": \"short\"}\r\n",
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"]\r\n"
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]
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}
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],
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"source": [
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"!cat examples.json"
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]
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},
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{
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"cell_type": "markdown",
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"id": "8e300335",
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"metadata": {},
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"source": [
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"### Loading from YAML\n",
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"This shows an example of loading a few shot example from YAML."
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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": 9,
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"id": "e2bec0fc",
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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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"_type: few_shot\r\n",
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"input_variables:\r\n",
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" [\"adjective\"]\r\n",
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"prefix: \r\n",
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" Write antonyms for the following words.\r\n",
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"example_prompt:\r\n",
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" input_variables:\r\n",
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" [\"input\", \"output\"]\r\n",
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" template:\r\n",
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" \"Input: {input}\\nOutput: {output}\"\r\n",
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"examples:\r\n",
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" examples.json\r\n",
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"suffix:\r\n",
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" \"Input: {adjective}\\nOutput:\"\r\n"
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]
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}
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],
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"source": [
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"!cat few_shot_prompt.yaml"
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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": 10,
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"id": "98c8f356",
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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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"Write antonyms for the following words.\n",
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"\n",
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"Input: happy\n",
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"Output: sad\n",
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"\n",
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"Input: tall\n",
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"Output: short\n",
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"\n",
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"Input: funny\n",
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"Output:\n"
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]
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}
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],
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"source": [
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"prompt = load_prompt(\"few_shot_prompt.yaml\")\n",
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"print(prompt.format(adjective=\"funny\"))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "4870aa9d",
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"metadata": {},
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"source": [
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"### Loading from JSON\n",
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"This shows an example of loading a few shot example from JSON."
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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": "9d996a86",
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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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"{\r\n",
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" \"_type\": \"few_shot\",\r\n",
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" \"input_variables\": [\"adjective\"],\r\n",
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" \"prefix\": \"Write antonyms for the following words.\",\r\n",
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" \"example_prompt\": {\r\n",
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" \"input_variables\": [\"input\", \"output\"],\r\n",
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" \"template\": \"Input: {input}\\nOutput: {output}\"\r\n",
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" },\r\n",
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" \"examples\": \"examples.json\",\r\n",
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" \"suffix\": \"Input: {adjective}\\nOutput:\"\r\n",
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"} \r\n"
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]
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}
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],
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"source": [
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"!cat few_shot_prompt.json"
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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": 12,
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"id": "dd2c10bb",
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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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"Write antonyms for the following words.\n",
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"\n",
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"Input: happy\n",
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"Output: sad\n",
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"\n",
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"Input: tall\n",
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"Output: short\n",
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"\n",
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"Input: funny\n",
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"Output:\n"
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]
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}
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],
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"source": [
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"prompt = load_prompt(\"few_shot_prompt.json\")\n",
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"print(prompt.format(adjective=\"funny\"))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9d23faf4",
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"metadata": {},
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"source": [
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"### Examples in the Config\n",
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"This shows an example of referencing the examples directly in the config."
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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": 13,
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"id": "6cd781ef",
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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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"{\r\n",
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" \"_type\": \"few_shot\",\r\n",
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" \"input_variables\": [\"adjective\"],\r\n",
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" \"prefix\": \"Write antonyms for the following words.\",\r\n",
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" \"example_prompt\": {\r\n",
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" \"input_variables\": [\"input\", \"output\"],\r\n",
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" \"template\": \"Input: {input}\\nOutput: {output}\"\r\n",
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" },\r\n",
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" \"examples\": [\r\n",
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" {\"input\": \"happy\", \"output\": \"sad\"},\r\n",
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" {\"input\": \"tall\", \"output\": \"short\"}\r\n",
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" ],\r\n",
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" \"suffix\": \"Input: {adjective}\\nOutput:\"\r\n",
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"} \r\n"
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]
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}
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],
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"source": [
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"!cat few_shot_prompt_examples_in.json"
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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": "533ab8a7",
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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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"Write antonyms for the following words.\n",
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"\n",
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"Input: happy\n",
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"Output: sad\n",
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"\n",
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"Input: tall\n",
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"Output: short\n",
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"\n",
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"Input: funny\n",
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"Output:\n"
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]
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}
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],
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"source": [
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"prompt = load_prompt(\"few_shot_prompt_examples_in.json\")\n",
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"print(prompt.format(adjective=\"funny\"))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "2e86139e",
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"metadata": {},
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"source": [
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"### Example Prompt from a File\n",
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"This shows an example of loading the PromptTemplate that is used to format the examples from a separate file. Note that the key changes from `example_prompt` to `example_prompt_path`."
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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": 15,
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"id": "0b6dd7b8",
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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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"{\r\n",
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" \"input_variables\": [\"input\", \"output\"],\r\n",
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" \"template\": \"Input: {input}\\nOutput: {output}\" \r\n",
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"}\r\n"
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]
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}
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],
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"source": [
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"!cat example_prompt.json"
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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": 16,
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"id": "76a1065d",
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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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"{\r\n",
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" \"_type\": \"few_shot\",\r\n",
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" \"input_variables\": [\"adjective\"],\r\n",
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" \"prefix\": \"Write antonyms for the following words.\",\r\n",
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" \"example_prompt_path\": \"example_prompt.json\",\r\n",
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" \"examples\": \"examples.json\",\r\n",
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" \"suffix\": \"Input: {adjective}\\nOutput:\"\r\n",
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"} \r\n"
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]
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}
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],
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"source": [
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"!cat few_shot_prompt_example_prompt.json "
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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": 17,
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"id": "744d275d",
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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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"Write antonyms for the following words.\n",
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"\n",
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"Input: happy\n",
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"Output: sad\n",
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"\n",
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"Input: tall\n",
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"Output: short\n",
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"\n",
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"Input: funny\n",
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"Output:\n"
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]
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}
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],
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"source": [
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"prompt = load_prompt(\"few_shot_prompt_example_prompt.json\")\n",
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"print(prompt.format(adjective=\"funny\"))"
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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": "3.10.9"
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},
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"vscode": {
|
|
"interpreter": {
|
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"hash": "b1677b440931f40d89ef8be7bf03acb108ce003de0ac9b18e8d43753ea2e7103"
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}
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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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}
|