Metadata-Version: 2.3
Name: pragmatiks-agno-provider
Version: 0.49.0
Summary: Agno agent provider for Pragmatiks
Author: Pragmatiks
Author-email: Pragmatiks <team@pragmatiks.io>
Requires-Dist: pragmatiks-sdk>=0.6.0
Requires-Dist: pragmatiks-gcp-provider>=0.77.0
Requires-Dist: pragmatiks-kubernetes-provider>=0.100.0
Requires-Dist: agno[anthropic,openai,postgres,qdrant]>=2.4.0
Requires-Dist: sqlalchemy>=2.0.0
Requires-Dist: mcp>=1.26.0
Requires-Dist: ddgs>=8.0.0
Requires-Python: >=3.13
Description-Content-Type: text/markdown

# Agno Provider for Pragmatiks

Deploys Agno AI agents to Kubernetes clusters with reactive dependency management.

## Resources

### `agno/agent`

Deploys an Agno agent as a Kubernetes Deployment with a Service.

**Config:**
- `cluster` - GKE cluster dependency (required)
- `model` - Model dependency for LLM (required)
- `embeddings` - Embeddings dependency for RAG (optional)
- `vector_store` - Vector store dependency for RAG (optional)
- `instructions` - System instructions for the agent (optional)
- `image` - Container image (default: `ghcr.io/agno-ai/agno:latest`)
- `replicas` - Number of replicas (default: 1)

**Outputs:**
- `url` - In-cluster URL for agent API
- `ready` - Whether the deployment is ready

## Usage

```yaml
apiVersion: agno/v1
kind: agent
metadata:
  name: company-assistant
  namespace: demo
spec:
  cluster: $ref{ai-cluster}
  model: $ref{claude}
  embeddings: $ref{my-embeddings}
  vector_store: $ref{qdrant-collection}
  instructions: |
    You are a helpful assistant.
```
