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tutorials/jigsawstack-prompt-engine/jigsawstack-prompt-engine.ipynb
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| { | ||
| "cells": [ | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "# JigsawStack Prompt Engine" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "[JigsawStack](https://jigsawstack.com) is an AI SDK that is easy to plug and play into any backend to automate a lot of the heavy lifting away for tasks like scraping, OCR, translation, and using LLMs.\n", | ||
| "\n", | ||
| "The JigsawStack Prompt Engine allows you to run the best LLM on every prompt at the fastest speed powered by Groq!" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Features" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "🌐**Prompt caching**: Stores prompts and responses for quick reuse, significantly reducing latency for repeated queries.\n", | ||
| "\n", | ||
| "💬**Automatic prompt optimization**: Automatically refines prompts to enhance response accuracy and efficiency from the language model.\n", | ||
| "\n", | ||
| "📄**Response schema validation**: Ensures that responses adhere to a predefined format or structure, providing consistency in output.\n", | ||
| "\n", | ||
| "🔁**Reusable prompts**: Allows prompts to be reused across different sessions and workflows, saving time in repetitive tasks.\n", | ||
| "\n", | ||
| "🧠**Multi-agent LLM from 50+ models**: Automatically selects the best model suitable for the task from the poll of models.\n", | ||
| "\n", | ||
| "🚫 **No virtual rate limits, tokens, and GPU management**\n" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Prerequisite " | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "- Create a JigsawStack [account](https://jigsawstack.com) (Get started for free)\n", | ||
| "- Retrieve your api [key](https://jigsawstack.com/dashboard)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "### Setup" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "Install the JigsawStack SDK" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": 1, | ||
| "metadata": { | ||
| "trusted": true | ||
| }, | ||
| "outputs": [ | ||
| { | ||
| "name": "stdout", | ||
| "output_type": "stream", | ||
| "text": [ | ||
| "Requirement already satisfied: jigsawstack in /opt/anaconda3/envs/openvoice/lib/python3.9/site-packages (0.1.14)\n", | ||
| "Requirement already satisfied: requests>=2.31.0 in /opt/anaconda3/envs/openvoice/lib/python3.9/site-packages (from jigsawstack) (2.32.2)\n", | ||
| "Requirement already satisfied: typing-extensions in /opt/anaconda3/envs/openvoice/lib/python3.9/site-packages (from jigsawstack) (4.11.0)\n", | ||
| "Requirement already satisfied: charset-normalizer<4,>=2 in /opt/anaconda3/envs/openvoice/lib/python3.9/site-packages (from requests>=2.31.0->jigsawstack) (2.0.4)\n", | ||
| "Requirement already satisfied: idna<4,>=2.5 in /opt/anaconda3/envs/openvoice/lib/python3.9/site-packages (from requests>=2.31.0->jigsawstack) (3.7)\n", | ||
| "Requirement already satisfied: urllib3<3,>=1.21.1 in /opt/anaconda3/envs/openvoice/lib/python3.9/site-packages (from requests>=2.31.0->jigsawstack) (2.2.2)\n", | ||
| "Requirement already satisfied: certifi>=2017.4.17 in /opt/anaconda3/envs/openvoice/lib/python3.9/site-packages (from requests>=2.31.0->jigsawstack) (2024.7.4)\n", | ||
| "Note: you may need to restart the kernel to use updated packages.\n" | ||
| ] | ||
| } | ||
| ], | ||
| "source": [ | ||
| "%pip install jigsawstack" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "Import and Initialize the SDK" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "trusted": true | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "from jigsawstack import JigsawStack\n", | ||
| "\n", | ||
| "jigsaw = JigsawStack(api_key=\"your-api-key\")" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Usage" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "### Example 1: Create and run a prompt" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "- #### Create prompt" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "trusted": true | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "params = {\n", | ||
| " \"prompt\": \"How to cook {dish}\", #The prompt for your use case\n", | ||
| " \"inputs\": [{ \"key\": \"dish\" }], #dynamic vars that are in the brackets {}\n", | ||
| " \"return_prompt\": [{\n", | ||
| " \"step\": \"name of this step\",\n", | ||
| " \"details\": \"details of this step\",\n", | ||
| " }], #The structure of the JSON, in this case, an array of objects\n", | ||
| "}\n", | ||
| "result = jigsaw.prompt_engine.create(params)\n", | ||
| "\n", | ||
| "print(result.prompt_engine_id) # prompt engine ID" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "- #### Run the prompt" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "trusted": true | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "resp = jigsaw.prompt_engine.run(\n", | ||
| " {\n", | ||
| " \"id\": result.prompt_engine_id, #The ID you got after creating the engine\n", | ||
| " \"input_values\": {\n", | ||
| " \"dish\": \"Singaporean chicken rice\", #They value for your dynamic field\n", | ||
| " },\n", | ||
| " }\n", | ||
| ")\n", | ||
| "\n", | ||
| "print(resp)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "### Example 2: Execute the prompt directly" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "trusted": true | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "params = {\n", | ||
| " \"prompt\":\"How to cook {dish}\",\n", | ||
| " \"inputs\": [\n", | ||
| " {\n", | ||
| " \"key\": \"dish\"\n", | ||
| " },\n", | ||
| " ],\n", | ||
| " \"input_values\": {\n", | ||
| " \"dish\": \"Nigerian Jollof Rice\"\n", | ||
| " },\n", | ||
| " \"return_prompt\": [{\n", | ||
| " \"step\": \"name of this step\",\n", | ||
| " \"details\": \"details of this step\",\n", | ||
| " }],\n", | ||
| "}\n", | ||
| "\n", | ||
| "result = jigsaw.prompt_engine.run_prompt_direct(params)\n", | ||
| "\n", | ||
| "print(result)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Prompt Guard - Llama Guard 3 by Groq" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "The prompt engine comes with prompt guards to prevent prompt injection from user inputs and a wide range of unsafe use cases. This can be turned on automatically using the `prompt_guard` field." | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "code", | ||
| "execution_count": null, | ||
| "metadata": { | ||
| "trusted": true | ||
| }, | ||
| "outputs": [], | ||
| "source": [ | ||
| "params = {\n", | ||
| " \"prompt\": \"Tell me a story about {about}\",\n", | ||
| " \"inputs\": [\n", | ||
| " {\n", | ||
| " \"key\": \"about\",\n", | ||
| " },\n", | ||
| " ],\n", | ||
| " \"input_values\": {\n", | ||
| " \"about\": \"The Leaning Tower of Pisa\"\n", | ||
| " },\n", | ||
| " \"return_prompt\": \"Return the result in a markdown format\",\n", | ||
| " \"prompt_guard\": [\"sexual_content\", \"defamation\"] #Add this to use llama-guard\n", | ||
| "}\n", | ||
| "result = jigsaw.prompt_engine.run_prompt_direct(params)\n", | ||
| "\n", | ||
| "print(result)" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "## Recommendation" | ||
| ] | ||
| }, | ||
| { | ||
| "cell_type": "markdown", | ||
| "metadata": {}, | ||
| "source": [ | ||
| "\n", | ||
| "- For prompts that are used repeatedly, it is recommended to first create the prompt, then run it using its prompt ID to enable optimization.\n", | ||
| "\n", | ||
| "- Run Prompt Direct is ideal for one-time use.\n", | ||
| "\n", | ||
| "For more information on the Prompt Engine engine see [documentation](https://docs.jigsawstack.com/examples/ai/prompt-engine)" | ||
| ] | ||
| } | ||
| ], | ||
| "metadata": { | ||
| "kernelspec": { | ||
| "display_name": "Python env", | ||
| "language": "python", | ||
| "name": "openvoice" | ||
| }, | ||
| "language_info": { | ||
| "codemirror_mode": { | ||
| "name": "ipython", | ||
| "version": 3 | ||
| }, | ||
| "file_extension": ".py", | ||
| "mimetype": "text/x-python", | ||
| "name": "python", | ||
| "nbconvert_exporter": "python", | ||
| "pygments_lexer": "ipython3", | ||
| "version": "3.9.19" | ||
| } | ||
| }, | ||
| "nbformat": 4, | ||
| "nbformat_minor": 4 | ||
| } |
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