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jamescalam committed Feb 1, 2023
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18 changes: 13 additions & 5 deletions generation/langchain/handbook/01-langchain-prompt-templates.ipynb
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{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/generation/langchain/handbook/01-langchain-prompt-templates.ipynb) [![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg)](https://nbviewer.org/github/pinecone-io/examples/blob/master/generation/langchain/handbook/01-langchain-prompt-templates.ipynb)\n",
"\n",
"# Prompt Engineering\n",
"\n",
"In this notebook we'll explore the fundamentals of prompt engineering. We'll start by installing library prerequisites."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"!pip install langchain openai cohere"
"!pip install langchain openai"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# Prompt Engineering\n",
"\n",
"In this notebook we'll explore the fundamentals of prompt engineering.\n",
"\n",
"## Structure of a Prompt\n",
"\n",
"A prompt can consist of multiple components:\n",
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16 changes: 12 additions & 4 deletions generation/prompt-engineering.ipynb
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@@ -1,5 +1,17 @@
{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/pinecone-io/examples/blob/master/generation/prompt-engineering.ipynb) [![Open nbviewer](https://raw.githubusercontent.com/pinecone-io/examples/master/assets/nbviewer-shield.svg)](https://nbviewer.org/github/pinecone-io/examples/blob/master/generation/prompt-engineering.ipynb)\n",
"\n",
"# Prompt Engineering\n",
"\n",
"In this notebook we'll explore the fundamentals of prompt engineering. We'll start by installing the `openai` library, which we'll be using throughout these examples. However, note that we can use other LLMs here, like those offered by Cohere or open source alternatives available via Hugging Face."
]
},
{
"cell_type": "code",
"execution_count": null,
Expand All @@ -14,10 +26,6 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"# Prompt Engineering\n",
"\n",
"In this notebook we'll explore the fundamentals of prompt engineering.\n",
"\n",
"## Structure of a Prompt\n",
"\n",
"A prompt can consist of multiple components:\n",
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