https://github.com/whiteducksoftware/ai-community-demo
Demo Application for the AI-Community event.
https://github.com/whiteducksoftware/ai-community-demo
Last synced: 19 days ago
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Demo Application for the AI-Community event.
- Host: GitHub
- URL: https://github.com/whiteducksoftware/ai-community-demo
- Owner: whiteducksoftware
- Created: 2025-06-13T17:13:02.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-06-17T09:22:23.000Z (about 1 year ago)
- Last Synced: 2025-07-02T16:10:03.365Z (about 1 year ago)
- Language: Python
- Size: 223 KB
- Stars: 2
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Demo for Agents with Flock:
## Dependencies:
- `python` >= 3.11.x
- `uv` - package manager
- `docker`
## Environment Variables:
In order for the application to have everything it needs,
a few Environment Variables will need to be set in
a `.env`-file at the root of this project (`./.env`):
```
# --- LLM Settings ---
AZURE_API_KEY="YOUR_API_KEY_FOR_AZURE_OPENAI"
AZURE_API_BASE="https://yourdeploymentregion.api.cognitive.microsoft.com/"
AZURE_API_VERSION="2024-12-01-preview"
DEFAULT_MODEL="azure/"
DEFAULT_MODEL_TEMPERATURE=1.0
DEFAULT_MODEL_MAX_TOKENS=8000
# --- Logging ---
LOG_LEVEL="WARNING"
LOGGING_DIR="log"
GITHUB_PERSONAL_ACCESS_TOKEN="YOUR PERSONAL GITHUB ACCESS TOKEN WITH PERMISSIONS TO MANAGE YOUR REPOSITORIES."
```
## Setup:
run: `uv sync` to install the necessary python dependencies.
### Services:
This project depends on two services:
1. `docker`
2. `Kernel-Memory` by Microsoft for RAG-Features
Setting up docker should be straightforward.
However, the application expects a `Kernel-Memory` instance
to listen at `http://localhost:9001/`.
For that, we need to start a dedicated docker-container.
### Setting up Kernel-Memory:
In [`./kernel-memory-config/appsettings.Development.json`](./kernel-memory-configs/appsettings.Development.json)
you can find the configuration for the kernel-memory service.
Here, you will need to adjust two sections:
```json
"AzureOpenAIEmbedding": {
"Auth": "ApiKey",
"AzureIdentityAudience": null,
"Endpoint": "https://YOUR_DEPLOYMENT_ENDPOINT.api.cognitive.microsoft.com/",
"APIKey": "YOUR_API_KEY",
"Deployment": "YOUR_EMBEDDING_MODEL_DEPLOYMENT_NAME",
"MaxTokenTotal": 8191,
"Tokenizer": "cl100k",
"EmbeddingDimensions": null,
"MaxEmbeddingBatchSize": 1,
"MaxRetries": 10,
"TrustedCertificateThumbprints": [],
"APIType": "EmbeddingGeneration"
},
"AzureOpenAIText": {
"Auth": "ApiKey",
"AzureIdentityAudience": null,
"Endpoint": "https://YOUR_DEPLOYMENT_ENDPOINT.api.cognitive.microsoft.com/",
"APIKey": "YOUR_API_KEY",
"Deployment": "YOUR_TEXT_GENERATION_MODEL_DEPLOYMENT_NAME (e.g. gpt-4.1-nano)",
"MaxTokenTotal": 16384,
"Tokenizer": "o200k",
"APIType": "ChatCompletion",
"MaxRetries": 10,
"TrustedCertificateThumbprints": []
},
```
Once you have that sorted out, you can start the docker-container for `Kernel-Memory` with:
```bash
docker run --volume ./kernel-memory-configs/appsettings.Development.json:/app/appsettings.Production.json -it --rm -p 9001:9001 kernelmemory/service
```
### Running the Application:
After you have performed the necessary setup steps, just run:
```bash
uv run main.py
```
### Demo Prompt:
You can find a demo-prompt in [`./demo_prompt.txt`](./demo_prompt.txt) that
will instruct your agents to implement the Task Management Application that is specified
in [`./files_for_memory`](./files_for_memory/)