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580 lines
16 KiB
Plaintext
580 lines
16 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 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",
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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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" \"max_length\": 20,\n",
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"}\n",
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"dynamic_prompt = load_prompt_from_config(_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": 30,
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"id": "d00b4385",
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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"
|
|
]
|
|
}
|
|
],
|
|
"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
|
|
}
|