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Ivan
64 lines
2.3 KiB
Markdown
64 lines
2.3 KiB
Markdown
# Introduction
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This section includes a list of notebooks that walk you through some simple concepts in Instructor. We start small and then work our way up to more complex and tricky implementations using the library.
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## Overview
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Currently we have the following notebooks avaliable
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1. `Introduction` - This is a quick walkthrough some of the benefits of Pydantic and how the Instructor Library integrates nicely with Pydantic with `instructor.patch()`
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2. `Tips` - Quick demonstration of how to use enums, `Pydantic` models and structured prompting to get specific output formats
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3. `Applications Rag`: Learn how to generate nested models with `Pydantic` by rewriting user queries
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4. `Knowledge Graphs`: Dive deep into the use of LLMs to break down complex topics into simple knowledge graphs
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5. `Validation` : Learn how to use Pydantic's inbuilt validators to perform more complex validation and checks on the outputs of your functions
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6. `Chain Of Density` : Learn how to produce high quality summaries that consistently beat out human-generated ones using `Chain of Density` summarization.
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## Installation
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We utilise the Graphviz package in this tutorial series. If you don't have it on hand, you should download it. Mac users can do so by running `brew install graphviz` while Linux users can try `sudo apt install graphviz` ( modify to your system specific package manager). Here is a link to their official [documentation](https://graphviz.org/download/)
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If you're encountering an error like the following when trying to run graphviz after installing it, just restart the notebook and verify you've got graphviz installed by running `dot -v` in your shell.
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```
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Command '[PosixPath('dot'), '-Kdot', '-Tsvg']' died with <Signals.SIGKILL: 9>.
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```
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Here are the steps to start running the notebooks
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1. Create a virtual environment
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```
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python3 -m venv .venv
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source .venv .venv/bin/activate
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```
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2. Install the dependencies
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```
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pip3 install -r requirements.txt
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```
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3. Add the virtual environment to Jupyter notebook
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```
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python -m ipykernel install --user --name=instructor-env
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```
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4. Add OpenAI API Key into your shell by running the following command. This will be set for as long as the shell is open.
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```
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export OPENAI_API_KEY=<api key goes here>
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```
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5. Start Jupyter Notebook
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```
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jupyter notebook
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``` |