Show HN: Dhenara Agent DSL– Framework for Complex Agents with Free Observability
GitHub: https://github.com/dhenara/dhenara-agent
Documentation: https://docs.dhenara.com/dhenara-agent/introduction
Key Features:
- Agent Lifecycle Management: Create, run, resume, and manage agents
- Run Controls: Resume execution from any point to save on API costs
- Built-in Observability: OpenTelemetry tracing with Jaeger and Zipkin support
- Event System: Fine-grained flow control
- Open Development: Build using standard tools (Git, VS Code)
- No Platform Lock-in: Build powerful command-line agents similar to Claude Code using just Git and VS Code
Simple Architecture:
DAD uses three main components:
1. Nodes: Basic execution units (API calls, file operations) 2. Flows: Collections of nodes with execution logic 3. Agents: High-level coordinators
Sample:
outer_loop_flow = FlowDefinition()
# Outer loop
outer_loop_flow.for_each(
id="category_processor",
statement=ObjectTemplate(expression="$expr{$hier{categories}.outcome.structured.categories}"),
item_var="category",
index_var="category_index",
max_iterations=10,
body=FlowDefinition().for_each(
# Inner loop
id="item_processor",
statement=ObjectTemplate(expression="$expr{category.items}"),
item_var="item",
index_var="item_index",
max_iterations=20,
body=item_processing_flow
)
)
While still in alpha, we've designed it to handle complex agent behaviors with robust control flow. We're Working On:- Budget control with pause/resume capabilities
- Additional node types and integrations
- Parallel execution for complex workflows
- Enhanced visualization tools
Try it out: `pip install dhenara-agent`
We welcome your feedback on what would make this more useful for your AI agent projects!
Thanks.
How?
https://docs.dhenara.com/dhenara-agent/guides/tutorials/comm...
This example is not a full-fledged code generator, but it can handle various coding tasks and make updates directly to repositories. It provides a command-line interface for code modifications or additions.
This can be extended further for more complex CLI agent creations.