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Release: 2023-06 June Bootcamp.
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![Georgian](assets/georgian-logo.png)
⛔ [DEPRECATED] ⛔

IMPORTANT: This code is provided as-is from June 2023. Please note that all code provided here is for illustrative purposes only. Dependent libraries have since been updated and current versions may contain vulnerabilities. We do NOT recommend running this code.

# Georgian GenAI Boot Camp
![Georgian](assets/georgian-logo.png)

Welcome to the Georgian GenAI boot camp repository. This repository contains all the demos we used during our bootcamps. Content for the latest boot camp can be found under the [notebooks](https://github.com/georgian-io/genai-bootcamp/tree/main/notebooks) directory. A copy of the content from previous boot camps can be found in the [archive](https://github.com/georgian-io/genai-bootcamp/tree/main/archive).
# Georgian GenAI Boot Camp - June 2023

IMPORTANT: In the archive folder, the code provided as-is from the dates of the respective bootcamps. Please note that all code provided here is for illustrative purposes only. Dependent libraries have since been updated and current versions may contain vulnerabilities. We do NOT recommend running the code in the archive.
Welcome to the Georgian GenAI boot camp repository. This repository contains all the demos we used during the bootcamp.

## Table of Contents
- [Georgian GenAI Boot Camp](#georgian-genai-boot-camp)
- [Table of Contents](#table-of-contents)
- [Goals](#goals)
- [Setup \& Installation](#setup--installation)
- [Agenda](#agenda)
- [API Access](#api-access)
- [Bootcamp Participants:](#bootcamp-participants)
- [Non-Bootcamp Participants:](#non-bootcamp-participants)
- [Repository Info](#repository-info)
- [Resources](#resources)

* [Goals](#goals)
* [Agenda](#agenda)
* [API Access](#api-access)
* [Setup & Installation](#setup--installation)
* [Repository Info](#repository-info)
* [Resources](#resources)

---
## Goals
Our bootcamps usually consist of a few days of tutorials followed by a hackathon. At the end of the hackathon our goal was for participants to have:
At the end of the hackathon our goal was for participants to have:
- A deeper understanding of the opportunities GenAI unlocks.
- A theoretical understanding of the latest GenAI technologies.
- A practical understanding of the latest GenAI technologies.
- Implemented at least one end-to-end application using GenAI.

[[Back to top]](#)

## Setup & Installation

0. This repository requires you to have installed poetry as a dependency manager. Please follow the instructions to install poetry from [here](https://python-poetry.org/docs/#installation).

1. Clone this repository and `cd genai-bootcamp`

2. Environment management options

a) Poetry: ```poetry shell```

b) Conda: create and activate a conda env for this project:
```bash
conda create -n genai-bootcamp python=3.10
conda activate genai-bootcamp
```

3. Install package
```
poetry install
```

4. Setup private environment files

Paste the `.env` file and `google-api.json` file provided to you into root directory of this repository.

Note: DO NOT COMMIT THIS FILE OR SHARE IT ANYWHERE!

Note: If you have trouble setting up Poetry, you should be able to skip it and just run `pip install -r requirements.txt` instead. Please reach out to us or create an issue if this does not work.

Note: Some operating systems might rename `.env` to `env`. The period at the front is important as all the notebooks expect this. Please rename the file if you run into this issue.

[[Back to top]](#)

---
## Agenda

Below you can see the agenda we followed for our boot camp in October 2023.
Below you can see the agenda we followed for our boot camp in June 2023.

<!-- omit in toc -->
### Day 1:

<!-- omit in toc -->
#### Introduction to LLMs & Prompt Engineering (Georgian & Vector Institute)
* [Azin Asgarian](https://www.linkedin.com/in/azin-asgarian/), AI Technical Lead at Georgian
* [David Emerson](https://www.linkedin.com/in/david-emerson-1b9b2225/), Applied Machine Learning Scientist at Vector Institute
* [Akash Saravanan](https://www.linkedin.com/in/akashsara/), Applied Research at Georgian
#### Introduction to LLMs (David Emerson from Vector)
* LLM Trends
* Foundation models
* Working with LLMs
* Intro to Prompt Engineering

<!-- omit in toc -->
#### Prompt Engineering & Evaluation (Georgian)
* [Akash Saravanan](https://www.linkedin.com/in/akashsara/), Applied Research at Georgian
* [Pashootan Vaezipoor](https://www.linkedin.com/in/pashootan-vaezipoor-7353212a/), Machine Learning Researcher at Georgian
#### Customizing LLMs (David Emerson from Vector)
* Prompt Engineering
* Fine-tuning Approaches

<!-- omit in toc -->
#### [Guest Speakers] Google & Microsoft
* [Erik Saarenvirta](https://www.linkedin.com/in/erik-saarenvirta/?originalSubdomain=ca), Sr. Customer Engineer, Data & AI at Google
* [Asmita Usturge](https://www.linkedin.com/in/asmitausturge/), Senior Data Scientist and Azure Cloud Lead at Microsoft
#### Hands-on Session (Georgian & Google)
* Setup and example notebooks - Akash Saravanan (Georgian)
* Prompt engineering best practices - Royal Sequeira (Georgian)
* Google demo - Erik Saarenvirta (Google)

<!-- omit in toc -->
### Day 2:
#### Tools & platforms (Rodrigo Ceballos from Georgian)
* Concepts with Langchain
* Memory and Search
* Interfaces with Streamlit
* Evaluation with LabelStudio
* Deployment with HuggingFace

#### Fine-tuning, RLHF, and Deployment
* Fine-tuning - Rohit Saha (Georgian)
* RLHF - Akash Saravanan (Georgian)
* Deploying LLMs - Rodrigo Ceballos (Georgian)

#### LLM Privacy and Security
* Introduction - Alex Manea (Georgian)
* Robustness and Mitigating Bias - Angeline Yasodhara (Georgian)
* PrivateGPT - Michael Young and Kory Fong (PrivateAI)

<!-- omit in toc -->
#### LLM Fine-Tuning & Alignment (Georgian)
* [Rohit Saha](https://www.linkedin.com/in/rohit-saha-ai/), Applied Research Scientist at Georgian
* [Akash Saravanan](https://www.linkedin.com/in/akashsara/), Applied Research at Georgian
[[Back to top]](#)

<!-- omit in toc -->
#### Tools, Platforms, & Deployment (Georgian)
* [Rodrigo Ceballos](https://www.linkedin.com/in/rodrigo-ceballos-lentini/), Machine Learning Engineer at Georgian
* [Kyryl Truskovskyi](https://www.linkedin.com/in/kyryl-truskovskyi-275b7967/), Machine Learning Engineer at Georgian
* [Maria Ponomarenko](https://www.linkedin.com/in/maria-ponomarenko-71b465179/), MLOps Intern at Georgian
---
## API Access
To be able to run the notebooks here, you'll need access to API keys for all these services. Read on for instructions on how to set up each of the APIs that you need. Note that the OpenAI and Google APIs will charge you based on usage, so you will need to set up billing.

<!-- omit in toc -->
#### Privacy, Trust & Responsible AI (Georgian & PrivateAI)
* [Angeline Yasodhara](https://www.linkedin.com/in/angelineyasodhara/), Applied Research Scientist at Georgian
* [Mike Brosseau](https://www.linkedin.com/in/mikebrosseau/), Director, Product Management at Private AI
* [Rodrigo Ceballos](https://www.linkedin.com/in/rodrigo-ceballos-lentini/), Machine Learning Engineer at Georgian
Note that to run the examples, you only need to have one API key setup. So if you already have access to an OpenAI key, you could run all the notebooks with it (excluding the Google/HuggingFace examples). The PrivateAI API key is used only for the PrivateAI demos (in `notebooks/day-1/04-example-summarization.ipynb` and `notebooks/extra_resources/PrivateAI Demo.ipynb`).

1. Create a `.env` file. In the root directory of this repo (I.E., the same directory this readme is in), create a `.env` file. Ensure that the period is present at the start of the filename. Within this file, place the following text:
```
OPENAI_API_KEY=""
GOOGLE_APPLICATION_CREDENTIALS="../../google-api.json"
HUGGINGFACEHUB_API_TOKEN=""
HUGGINGFACEHUB_ENDPOINT="https://api-inference.huggingface.co/models/tiiuae/falcon-7b-instruct"
PRIVATE_AI_API_KEY = ""
```

<!-- omit in toc -->
### Day 3:
2. OpenAI: Create an OpenAI account (or login) and visit the [API Keys](https://platform.openai.com/account/api-keys) page. Generate an API key here and place it in the `.env` file you created above. These examples were designed with GPT-4. If you do not have access to it, please request access through the [waitlist](https://openai.com/waitlist/gpt-4-api). Or alternatively, you can use `gpt-3.5-turbo` instead.

<!-- omit in toc -->
#### [Guest Speakers] Meta & Qdrant
* [Kacper Lukawski](https://www.linkedin.com/in/kacperlukawski/), Developer Advocate at Qdrant
* [Vedanuj Goswami](https://www.linkedin.com/in/vedanuj/), Research Engineer at Meta AI
3. Google: Follow steps 1 through 4 detailed in this [link](https://cloud.google.com/vertex-ai/docs/start/client-libraries). Once you have downloaded the service account key from step 4, place it in the root directory of this repository and rename it to `google-api.json`.

<!-- omit in toc -->
### Day 4:
4. HuggingFace: Create a HuggingFace account (or login) and visit the [Access Tokens](https://huggingface.co/settings/tokens) page in the settings menu. Generate an token (read access is sufficient) and place it in the `.env` file.

<!-- omit in toc -->
#### [Guest Speaker] LLM Observability with Arize AI
* [Amber Roberts](https://www.linkedin.com/in/amber-roberts42/), ML Growth Lead at Arize AI
* [Claire Longo](https://www.linkedin.com/in/claire-longo/), Head of ML Solutions Engineering at Arize AI
5. PrivateAI: Request an API key through [this form](https://www.private-ai.com/api-key/). Add it to the `.env` file above.

6. You should now have all fields in the `.env` file setup and ready to go! You can now proceed with the installation steps below.

[[Back to top]](#)

---
## API Access

### Bootcamp Participants:
## Setup & Installation

To be able to run the notebooks here, you'll need access to API keys for all the different services. Fear not, we've provided you with all the API keys you need. Just download the files we've sent to you and place them in the root of this directory.
0. This repository requires you to have installed poetry as a dependency manager. Please follow the instructions to install poetry from [here](https://python-poetry.org/docs/#installation).

### Non-Bootcamp Participants:
1. Environment management options

a) Poetry: ```poetry shell```

b) Conda: create and activate a conda env for this project:
```bash
conda create -n genai-bootcamp python=3.10
conda activate genai-bootcamp
```

To be able to run the notebooks here, you'll need access to API keys for all these services. Read on for instructions on how to set up each of the APIs that you need. Many of these APIs (such as OpenAI) will charge you based on usage, so you will need to set up billing.
2. Install `fiddler-auditor` (we need to install this separately as it sometimes breaks).
```
pip install fiddler-auditor==0.0.1
```

Note that to run the examples, you only need to have one LLM set up. So if you already have access to an OpenAI key, you could run all the notebooks with it (excluding the Google/HuggingFace examples). The PrivateAI API key is used only for the PrivateAI demo (`notebooks/extra_resources/PrivateAI Demo.ipynb`). We use AnyScale to set up LLaMa 2 access.
3. Install package
```
poetry install
```

1. Create a `.env` file. In the root directory of this repo (I.E., the same directory this readme is in), create a `.env` file. Ensure that the period is present at the start of the filename. Within this file, place the following text:
4. Check installation worked by running
```
OPENAI_API_KEY=""
GOOGLE_APPLICATION_CREDENTIALS="../../google-api.json"
ANYSCALE_API_BASE="https://api.endpoints.anyscale.com/v1"
ANYSCALE_API_KEY = ""
PRIVATE_AI_API_KEY = ""
AWS_ACCESS_KEY_ID=""
AWS_SECRET_ACCESS_KEY=""
AWS_DEFAULT_REGION="us-east-1"
pytest .
```

1. OpenAI: Create an OpenAI account (or login) and visit the [API Keys](https://platform.openai.com/account/api-keys) page. Generate an API key here and place it in the `.env` file you created above. These examples were designed with GPT-4. If you do not have access to it, please request access through the [waitlist](https://openai.com/waitlist/gpt-4-api). Or alternatively, you can use `gpt-3.5-turbo` instead.
2. Google: Follow steps 1 through 4 detailed in this [link](https://cloud.google.com/vertex-ai/docs/start/client-libraries). Once you have downloaded the service account key from step 4, place it in the root directory of this repository and rename it to `google-api.json`.
3. AnyScale: Once you have billing setup, you can get your API keys from the [credentials](https://app.endpoints.anyscale.com/credentials) page.
4. PrivateAI: Request an API key through [this form](https://www.private-ai.com/api-key/). Add it to the `.env` file above.
5. AWS Bedrock (for Claude): Follow the instructions on [this page](https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_access-keys.html#Using_CreateAccessKey) to obtain your AWS keys. Alternatively, you can authenticate via boto3 if you have AWS Bedrock access within your organization.
6. You should now have all fields in the `.env` file setup and ready to go! You can now proceed with the installation steps below.
5. Setup private environment files

[[Back to top]](#)
Paste the `.env` file and `google-api.json` file provided to you into root directory of this repository.

---
Note: DO NOT COMMIT THIS FILE OR SHARE IT ANYWHERE!

## Repository Info
[[Back to top]](#)

<!-- omit in toc -->
## Repository Info
### Poetry
We use [poetry](https://python-poetry.org/) as our dependency manager.
The link above has great documentation but there is a TL;DR.

- Install the package: `poetry install`
- Add a dependency: `poetry add <python-lib>`
- Where are dependencies specified? `pyproject.toml` include the high level requirements. The latests exact versions installed are in `poetry.lock`.
- Where are dependencies specified? `pyproject.toml` include the high level requirements. The latest exact versions installed are in `poetry.lock`.

<!-- omit in toc -->
### Debugging
- If for some reason `poetry install` fails to install a library try to `pip install <lib>` and then run `poetry install` again. This solves 95% of these errors.

Expand All @@ -183,4 +153,4 @@ The link above has great documentation but there is a TL;DR.
* [GenAI Interface Cookiecutter](https://github.com/rodrigo-georgian/genai-interface-cookiecutter): A cookie cutter template for you to start off with a basic UI using streamlit.
* [Georgian AI Library (GAL)](https://github.com/georgian-io/GAL): Our library containing overviews of AI techniques.

[[Back to top]](#)
[[Back to top]](#)# t-cot
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