forked from Archives/langchain
load prompt
Harrison Chase
2 years ago
parent
0d0d3f122a
commit
7df74a4d52
@ -0,0 +1,579 @@
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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": "43fb16cb",
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"metadata": {},
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"source": [
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"# Prompt Walkthrough\n",
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"\n",
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"An overview of the different types of prompts in LangChain and how to use them"
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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": 53,
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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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"import yaml\n",
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"\n",
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"with open(\"simple_prompt.yaml\", \"r\") as stream:\n",
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" config = yaml.safe_load(stream)"
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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": 54,
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"id": "1ab11b59",
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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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"{'input_variables': ['adjective', 'content'],\n",
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" 'template': 'Tell me a {adjective} joke about {content}.\\nLike what does it mean?'}"
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]
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},
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"execution_count": 54,
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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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"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": 55,
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"id": "78a2cf84",
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"metadata": {},
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"outputs": [],
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"source": [
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"from pathlib import Path\n",
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"from typing import Union\n",
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"import yaml\n",
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"def load_file(file: Union[str, Path]):\n",
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" if isinstance(file, str):\n",
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" file_path = Path(file)\n",
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" else:\n",
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" file_path = file\n",
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" if file_path.suffix == \".json\":\n",
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" with open(file_path) as f:\n",
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" config = json.load(f)\n",
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" elif file_path.suffix == \".yaml\":\n",
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" with open(file_path, \"r\") as f:\n",
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" config = yaml.safe_load(f)\n",
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" else:\n",
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" raise ValueError\n",
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" return load_prompt_from_config(config)\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": 42,
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"id": "6e1f9bcd",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain.prompts import Prompt, DynamicPrompt\n",
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"import json\n",
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"def load_prompt_from_config(config):\n",
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" if \"type\" in config:\n",
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" prompt_type = config.pop(\"type\")\n",
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" else:\n",
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" prompt_type = \"prompt\"\n",
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" if prompt_type == \"prompt\":\n",
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" return _load_prompt(config)\n",
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" elif prompt_type == \"dynamic_prompt\":\n",
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" return _load_dynamic_prompt(config)\n",
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" else:\n",
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" raise ValueError\n",
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" \n",
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"def _load_template(var_name: str, config: dict) -> dict:\n",
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" if f\"{var_name}_path\" in config:\n",
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" if var_name in config:\n",
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" raise ValueError(f\"Both `{var_name}_path` and `{var_name}` cannot be provided.\")\n",
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" template_path = Path(config.pop(f\"{var_name}_path\"))\n",
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" if template_path.suffix == \".txt\":\n",
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" with open(template_path) as f:\n",
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" template = f.read()\n",
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" else:\n",
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" raise ValueError\n",
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" config[var_name] = template\n",
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" return config\n",
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" \n",
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" \n",
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"def _load_dynamic_prompt(config):\n",
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" if \"loader\" in config:\n",
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" prompt_type = config.pop(\"loader\")\n",
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" else:\n",
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" prompt_type = \"init\"\n",
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" if prompt_type == \"init\":\n",
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" config = _load_template(\"suffix\", config)\n",
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" config = _load_template(\"prefix\", config)\n",
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" return DynamicPrompt(**config)\n",
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" elif prompt_type == \"from_structured_examples\":\n",
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" config = _load_template(\"suffix\", config)\n",
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" config = _load_template(\"prefix\", config)\n",
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" config[\"example_prompt\"] = _load_prompt(config[\"example_prompt\"])\n",
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" if isinstance(config[\"examples\"], list):\n",
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" pass\n",
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" elif isinstance(config[\"examples\"], str):\n",
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" with open(config[\"examples\"]) as f:\n",
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" examples = json.load(f)\n",
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" config[\"examples\"] = examples\n",
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" else:\n",
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" raise ValueError\n",
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" return DynamicPrompt.from_structured_examples(**config)\n",
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" else:\n",
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" raise ValueError\n",
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"\n",
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"def _load_prompt(config):\n",
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" if \"loader\" in config:\n",
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" prompt_type = config.pop(\"loader\")\n",
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" else:\n",
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" prompt_type = \"init\"\n",
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" if prompt_type == \"init\":\n",
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" config = _load_template(\"template\", config)\n",
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" return Prompt(**config)\n",
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" elif prompt_type == \"from_examples\":\n",
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" config = _load_template(\"suffix\", config)\n",
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" config = _load_template(\"prefix\", config)\n",
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" if isinstance(config[\"examples\"], list):\n",
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" pass\n",
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" elif isinstance(config[\"examples\"], str):\n",
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" with open(config[\"examples\"]) as f:\n",
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" examples = json.load(f)\n",
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" config[\"examples\"] = examples\n",
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" else:\n",
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" raise ValueError\n",
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" return Prompt.from_examples(**config)\n",
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" elif prompt_type == \"from_structured_examples\":\n",
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" config = _load_template(\"suffix\", config)\n",
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" config = _load_template(\"prefix\", config)\n",
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" config[\"example_prompt\"] = _load_prompt(config[\"example_prompt\"])\n",
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" if isinstance(config[\"examples\"], list):\n",
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" pass\n",
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" elif isinstance(config[\"examples\"], str):\n",
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" with open(config[\"examples\"]) as f:\n",
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" examples = json.load(f)\n",
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" config[\"examples\"] = examples\n",
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" else:\n",
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" raise ValueError\n",
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" return Prompt.from_structured_examples(**config)\n",
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" else:\n",
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" raise ValueError"
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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": "b045da0f",
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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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"cell_type": "markdown",
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"id": "cddb465e",
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"metadata": {},
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"source": [
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"### Basic Prompt\n",
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"\n",
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"The most simple type of prompt - a string template that takes any number of input variables. The template should be formatted as a Python f-string."
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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": "ab46bd2a",
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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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"'Tellme a joke.'"
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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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"# An example prompt with no input variables\n",
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"_config = {\n",
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" \"input_variables\": [],\n",
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" \"template\": \"Tell me a joke.\"\n",
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"}\n",
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"no_input_prompt = load_prompt_from_config(_config)\n",
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"no_input_prompt.format()"
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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": "c3ad0fa8",
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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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"'Tell me a funny joke.'"
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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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"# An example prompt with one input variable\n",
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"_config = {\n",
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" \"input_variables\": [\"adjective\"],\n",
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" \"template\": \"Tell me a {adjective} joke.\"\n",
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"}\n",
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"one_input_prompt = load_prompt_from_config(_config)\n",
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"one_input_prompt.format(adjective=\"funny\")"
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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": "ba577dcf",
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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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"'Tell me a funny joke about chickens.'"
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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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"# An example prompt with multiple input variables\n",
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"_config = {\n",
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" \"input_variables\": [\"adjective\", \"content\"],\n",
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" \"template\": \"Tell me a {adjective} joke about {content}.\"\n",
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"}\n",
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"multiple_input_prompt = load_prompt_from_config(_config)\n",
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"multiple_input_prompt.format(adjective=\"funny\", content=\"chickens\")"
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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": 43,
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"id": "e0ad7fb8",
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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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"'Tell me a funny joke about chickens.'"
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]
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},
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"execution_count": 43,
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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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"multiple_input_prompt = load_file(\"simple_prompt_with_template_file.json\")\n",
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"multiple_input_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": "d27b1824",
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"metadata": {},
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"source": [
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"### Examples\n",
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"Examples are datapoints that can be used to show the model how to produce results. They can be either strings, or dictionaries that are then turned into strings by an example prompt itself."
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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": "2c00e965",
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"metadata": {},
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"outputs": [],
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"source": [
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"string_examples = [\"Input: happy\\nOutput: sad\", \"Input: tall\\nOutput: short\"]\n",
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"dict_examples = [{\"input\": \"happy\", \"output\": \"sad\"}, {\"input\": \"tall\", \"output\": \"short\"}]\n",
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"example_prompt_config = {\"input_variables\": [\"input\",\"output\"], \"template\": \"Input: {input}\\nOutput: {output}\"}"
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]
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},
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{
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"cell_type": "markdown",
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"id": "1492b49d",
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"metadata": {},
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"source": [
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"### Simple Prompt with examples\n",
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"\n",
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"We can then use these examples to construct prompts."
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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": "1a5a686d",
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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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"Give the antonym of every input\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: big\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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"_config = {\n",
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" \"loader\": \"from_examples\",\n",
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" \"examples\": string_examples,\n",
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" \"prefix\": \"Give the antonym of every input\",\n",
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" \"suffix\": \"Input: {adjective}\\nOutput:\", \n",
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" \"input_variables\": [\"adjective\"],\n",
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"}\n",
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"prompt_from_string_examples = load_prompt_from_config(_config)\n",
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"print(prompt_from_string_examples.format(adjective=\"big\"))"
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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": 22,
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"id": "08d43717",
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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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"Give the antonym of every input\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: big\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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"_config = {\n",
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" \"loader\": \"from_examples\",\n",
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" \"examples\": \"string_examples.json\",\n",
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" \"prefix\": \"Give the antonym of every input\",\n",
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" \"suffix\": \"Input: {adjective}\\nOutput:\", \n",
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" \"input_variables\": [\"adjective\"],\n",
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"}\n",
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"prompt_from_string_examples = load_prompt_from_config(_config)\n",
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"print(prompt_from_string_examples.format(adjective=\"big\"))"
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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": "7931e5f2",
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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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"Give the antonym of every input\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: big\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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"_config = {\n",
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" \"loader\": \"from_structured_examples\",\n",
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" \"examples\": dict_examples,\n",
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" \"example_prompt\": example_prompt_config,\n",
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" \"prefix\": \"Give the antonym of every input\",\n",
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" \"suffix\": \"Input: {adjective}\\nOutput:\", \n",
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" \"input_variables\": [\"adjective\"],\n",
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"}\n",
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"prompt_from_structured_examples = load_prompt_from_config(_config)\n",
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"print(prompt_from_structured_examples.format(adjective=\"big\"))"
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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": 23,
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"id": "738ff0a8",
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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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"Give the antonym of every input\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: big\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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"_config = {\n",
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" \"loader\": \"from_structured_examples\",\n",
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" \"examples\": \"structured_examples.json\",\n",
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" \"example_prompt\": example_prompt_config,\n",
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" \"prefix\": \"Give the antonym of every input\",\n",
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" \"suffix\": \"Input: {adjective}\\nOutput:\", \n",
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" \"input_variables\": [\"adjective\"],\n",
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"}\n",
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"prompt_from_structured_examples = load_prompt_from_config(_config)\n",
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"print(prompt_from_structured_examples.format(adjective=\"big\"))"
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]
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},
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{
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"cell_type": "markdown",
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"id": "861a4d1f",
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"metadata": {},
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"source": [
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"### Dynamic Prompt\n",
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"\n",
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"We also do more clever things with prompts - for example, only select a certain number of examples in order to limit the size of the text passed in. This will vary with the input text size."
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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": 29,
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"id": "207e55f7",
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"metadata": {},
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"outputs": [],
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"source": [
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"_config = {\n",
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" \"type\": \"dynamic_prompt\",\n",
|
||||
" \"loader\": \"from_structured_examples\",\n",
|
||||
" \"examples\": \"structured_examples.json\",\n",
|
||||
" \"example_prompt\": example_prompt_config,\n",
|
||||
" \"prefix\": \"Give the antonym of every input\",\n",
|
||||
" \"suffix\": \"Input: {adjective}\\nOutput:\", \n",
|
||||
" \"input_variables\": [\"adjective\"],\n",
|
||||
" \"max_length\": 20,\n",
|
||||
"}\n",
|
||||
"dynamic_prompt = load_prompt_from_config(_config)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 30,
|
||||
"id": "d00b4385",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Give the antonym of every input\n",
|
||||
"\n",
|
||||
"Input: happy\n",
|
||||
"Output: sad\n",
|
||||
"\n",
|
||||
"Input: tall\n",
|
||||
"Output: short\n",
|
||||
"\n",
|
||||
"Input: big\n",
|
||||
"Output:\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# An example with small input, so it selects both examples.\n",
|
||||
"print(dynamic_prompt.format(adjective=\"big\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 31,
|
||||
"id": "878bcde9",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Give the antonym of every input\n",
|
||||
"\n",
|
||||
"Input: happy\n",
|
||||
"Output: sad\n",
|
||||
"\n",
|
||||
"Input: big and huge and massive\n",
|
||||
"Output:\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# An example with long input, so it selects only one example.\n",
|
||||
"print(dynamic_prompt.format(adjective=\"big and huge and massive\"))"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "76a1065d",
|
||||
"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": "3.7.6"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
@ -0,0 +1,4 @@
|
||||
{
|
||||
"input_variables": ["adjective", "content"],
|
||||
"template": "Tell me a {adjective} joke about {content}."
|
||||
}
|
||||
@ -0,0 +1,5 @@
|
||||
input_variables:
|
||||
["adjective", "content"]
|
||||
template: |
|
||||
Tell me a {adjective} joke about {content}.
|
||||
Like what does it mean?
|
||||
@ -0,0 +1,4 @@
|
||||
{
|
||||
"input_variables": ["adjective", "content"],
|
||||
"template_path": "simple_template.txt"
|
||||
}
|
||||
@ -0,0 +1 @@
|
||||
Tell me a {adjective} joke about {content}.
|
||||
@ -0,0 +1 @@
|
||||
["Input: happy\nOutput: sad", "Input: tall\nOutput: short"]
|
||||
@ -0,0 +1 @@
|
||||
[{"input": "happy", "output": "sad"}, {"input": "tall", "output": "short"}]
|
||||
@ -0,0 +1,131 @@
|
||||
from pathlib import Path
|
||||
from typing import Union
|
||||
import yaml
|
||||
|
||||
from langchain.prompts import Prompt, DynamicPrompt
|
||||
import json
|
||||
|
||||
|
||||
def load_prompt_from_config(config):
|
||||
"""Get the right type from the config and load it accordingly."""
|
||||
if "type" in config:
|
||||
prompt_type = config.pop("type")
|
||||
else:
|
||||
# Default to base prompt type.
|
||||
prompt_type = "prompt"
|
||||
if prompt_type == "prompt":
|
||||
return _load_prompt(config)
|
||||
elif prompt_type == "dynamic_prompt":
|
||||
return _load_dynamic_prompt(config)
|
||||
else:
|
||||
raise ValueError
|
||||
|
||||
|
||||
def _load_template(var_name: str, config: dict) -> dict:
|
||||
"""Load template from disk if applicable."""
|
||||
# Check if template_path exists in config.
|
||||
if f"{var_name}_path" in config:
|
||||
# If it does, make sure template variable doesn't also exist.
|
||||
if var_name in config:
|
||||
raise ValueError(f"Both `{var_name}_path` and `{var_name}` cannot be provided.")
|
||||
# Pop the template path from the config.
|
||||
template_path = Path(config.pop(f"{var_name}_path"))
|
||||
# Load the template.
|
||||
if template_path.suffix == ".txt":
|
||||
with open(template_path) as f:
|
||||
template = f.read()
|
||||
else:
|
||||
raise ValueError
|
||||
# Set the template variable to the extracted variable.
|
||||
config[var_name] = template
|
||||
return config
|
||||
|
||||
|
||||
def _load_examples(config):
|
||||
"""Load examples if necessary."""
|
||||
if isinstance(config["examples"], list):
|
||||
pass
|
||||
elif isinstance(config["examples"], str):
|
||||
with open(config["examples"]) as f:
|
||||
examples = json.load(f)
|
||||
config["examples"] = examples
|
||||
else:
|
||||
raise ValueError
|
||||
return config
|
||||
|
||||
|
||||
def _load_dynamic_prompt(config):
|
||||
"""Load the dynamic prompt from the config."""
|
||||
# Get the loader type (init, from_examples, etc)
|
||||
if "loader" in config:
|
||||
prompt_type = config.pop("loader")
|
||||
else:
|
||||
prompt_type = "init"
|
||||
# Call loading logic depending on what loader to use.
|
||||
if prompt_type == "init":
|
||||
# Load the suffix and prefix templates.
|
||||
config = _load_template("suffix", config)
|
||||
config = _load_template("prefix", config)
|
||||
return DynamicPrompt(**config)
|
||||
elif prompt_type == "from_structured_examples":
|
||||
# Load the suffix and prefix templates.
|
||||
config = _load_template("suffix", config)
|
||||
config = _load_template("prefix", config)
|
||||
# Load the example prompt.
|
||||
config["example_prompt"] = _load_prompt(config["example_prompt"])
|
||||
# Load the examples.
|
||||
config = _load_examples(config)
|
||||
return DynamicPrompt.from_structured_examples(**config)
|
||||
else:
|
||||
raise ValueError
|
||||
|
||||
|
||||
def _load_prompt(config):
|
||||
"""Load the base prompt type from config."""
|
||||
# Get the loader type (init, from_examples, etc)
|
||||
if "loader" in config:
|
||||
prompt_type = config.pop("loader")
|
||||
else:
|
||||
prompt_type = "init"
|
||||
# Call loading logic depending on what loader to use.
|
||||
if prompt_type == "init":
|
||||
# Load the template from disk.
|
||||
config = _load_template("template", config)
|
||||
return Prompt(**config)
|
||||
elif prompt_type == "from_examples":
|
||||
# Load the suffix and prefix templates.
|
||||
config = _load_template("suffix", config)
|
||||
config = _load_template("prefix", config)
|
||||
# Load the examples.
|
||||
config = _load_examples(config)
|
||||
return Prompt.from_examples(**config)
|
||||
elif prompt_type == "from_structured_examples":
|
||||
# Load the suffix and prefix templates.
|
||||
config = _load_template("suffix", config)
|
||||
config = _load_template("prefix", config)
|
||||
config["example_prompt"] = _load_prompt(config["example_prompt"])
|
||||
# Load the examples.
|
||||
config = _load_examples(config)
|
||||
return Prompt.from_structured_examples(**config)
|
||||
else:
|
||||
raise ValueError
|
||||
|
||||
|
||||
def load_prompt(file: Union[str, Path]):
|
||||
"""Load prompt from file."""
|
||||
# Convert file to Path object.
|
||||
if isinstance(file, str):
|
||||
file_path = Path(file)
|
||||
else:
|
||||
file_path = file
|
||||
# Load from either json or yaml.
|
||||
if file_path.suffix == ".json":
|
||||
with open(file_path) as f:
|
||||
config = json.load(f)
|
||||
elif file_path.suffix == ".yaml":
|
||||
with open(file_path, "r") as f:
|
||||
config = yaml.safe_load(f)
|
||||
else:
|
||||
raise ValueError
|
||||
# Load the prompt from the config now.
|
||||
return load_prompt_from_config(config)
|
||||
Loading…
Reference in New Issue