-
001.ipynb
(10 mins)- Boto3 Client
- Zero-Shot
- Single Turn Conversation
- Bedrock Runtime and InvokeModel
- Comparing Models
- Amazon Titan Text Express V1
- Claude Haiku 3
- Load Local Files
- Use Amazon Q Developer to generate function
-
002.ipynb
(10 mins)- Few-Shot
- In-Context Learning
- Packaging Function
-
003.ipynb
(30 mins)- Multi-turn Conversation
- Multi-turn with Invoke Model
- Multi-turn with Converse API
- Session or Chat History Management (Knowledgebase)
- NOTES:
- Message History (how is the conversation being chained)
- Summarization (what happens if hte message history gets too long?)
-
004.ipynb
(30 mins)- reAct Reasoning
- Tool Use
- Gaurd Rails
-
005.ipynb
(10 mins)- Generate a frontend using Gradio
- Generate a frontend using Streamlit
- Generate a frontend using v0
We don't directly need the AWS CLI but its useful to have around for debugging or quickly creating on off resources like an S3 Bucket
chmod u+x ./bin/install_aws_cli
./bin/install_aws_cli
SageMaker StudioLabs JuypterLabs Workspace will have AWS CLI preinstalled
You can set your AWS Credentials two ways:
- Env Vars
- AWS Credentials Profile
Cloud developer enviroments will require you set env vars since they can't persist or store an ~/.aws/credentaisls
file:
export AWS_ACCESS_KEY_ID=""
export AWS_SECRET_ACCESS_KEY=""
export AWS_DEFAULT_REGION="ca-central-1"
Local developer enviroments you can use AWS configure which will persist or store credentials in a ~/.aws/credentaisls
file:
aws configure
Please consider there can be limitations of models or features based on selected region. In worst-case we will fallback to nearest best suppported region>
SageMaker StudioLabs JuypterLabs Workspace will use your user roll for permissions so you don't need to set credentinals
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