https://github.com/dynatrace/obslab-llm-observability
Search for a holiday and get destination advice from an LLM. Observability by Dynatrace.
https://github.com/dynatrace/obslab-llm-observability
ai-observability application-observability demo dynatrace genai llm obslab ollama openai pinecone rag-pipeline
Last synced: 3 months ago
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Search for a holiday and get destination advice from an LLM. Observability by Dynatrace.
- Host: GitHub
- URL: https://github.com/dynatrace/obslab-llm-observability
- Owner: Dynatrace
- License: apache-2.0
- Created: 2024-05-22T01:28:13.000Z (about 1 year ago)
- Default Branch: amazon-bedrock
- Last Pushed: 2025-02-13T00:40:35.000Z (5 months ago)
- Last Synced: 2025-04-05T13:04:27.207Z (3 months ago)
- Topics: ai-observability, application-observability, demo, dynatrace, genai, llm, obslab, ollama, openai, pinecone, rag-pipeline
- Language: HTML
- Homepage: https://dynatrace.github.io/obslab-llm-observability/
- Size: 8.12 MB
- Stars: 6
- Watchers: 1
- Forks: 140
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# EasyTravel Bedrock - Travel Advisor
Demo application for giving travel advice written in Python. Observability signals by [OpenTelemetry](https://opentelemetry.io).
Uses [Amazon Bedrock](https://aws.amazon.com/bedrock/) to generate advice for a given destination.
> **Note**
> This product is not officially supported by Dynatrace!
### Try it yourself
* Explore our sample dashboards on the [Dynatrace Playground](https://dt-url.net/v203wj2).
* Implement AI observability in your environments with our detailed [Dynatrace Documentation](https://dt-url.net/oi23w9x).
## Configure Bedrock
You can follow the [Amazon Getting Started guide](https://docs.aws.amazon.com/bedrock/latest/userguide/getting-started.html)
to get access to an Amazon Bedrock foundation model, or deploy your own custom model.
## Try it out yourself
[](https://github.com/codespaces/new/Dynatrace/obslab-llm-observability?ref=amazon-bedrock)
## Developer Information Below
### Run Locally
You can start the application locally by running the following command.
```bash
export AWS_EMBEDDING_MODEL=
export AWS_MODEL=
export AWS_GUARDRAIL_ID=
export AWS_DEFAULT_REGION=
export AWS_ACCESS_KEY_ID=
export AWS_SECRET_ACCESS_KEY=
export OTEL_ENDPOINT=https://.live.dynatrace.com/api/v2/otlp
export API_TOKEN=
python app.py
```
--------------------------
### Deploy on a Local K8S Cluster
You will need [Docker](https://docs.docker.com/engine/install/) or [Podman](https://podman.io/docs/installation) installed.
Create a cluster if you do not already have one:
```bash
kind create cluster --config .devcontainer/kind-cluster.yml --wait 300s
```
Customise and set some environment variables
```bash
export AWS_EMBEDDING_MODEL=
export AWS_MODEL=
export AWS_GUARDRAIL_ID=
export AWS_DEFAULT_REGION=
export AWS_ACCESS_KEY_ID=
export AWS_SECRET_ACCESS_KEY=
export DT_ENDPOINT=https://.live.dynatrace.com
export DT_TOKEN=
```
Run the deployment script:
```bash
.devcontainer/deployment.sh
```