chnjinlei/hive
1
0
Fork 0
Code Issues Pull Requests Actions 41 Packages Projects Releases Wiki Activity

docs: update the latest features from recent changes

Browse Source
This commit is contained in:
Richard Tang
2026-03-03 10:12:43 -08:00
parent a370403b16
commit f921846879
1 changed files with 4 additions and 15 deletions
Download Patch File Download Diff File Expand all files Collapse all files
README.md
+4 -15
View File
@@ -126,13 +126,14 @@ Click "Try a sample agent" and check the templates. You can run a templates dire
## Features
- **[Goal-Driven Development](docs/key_concepts/goals_outcome.md)** - Define objectives in natural language; the coding agent generates the agent graph and connection code to achieve them
- **Browser-Use** - Control the browser on your computer to achieve hard tasks
- **Parallel Execution** - Execute the generated graph in parallel. This way you can have multiple agent compelteing the jobs for you
- **[Goal-Driven Generation](docs/key_concepts/goals_outcome.md)** - Define objectives in natural language; the coding agent generates the agent graph and connection code to achieve them
- **[Adaptiveness](docs/key_concepts/evolution.md)** - Framework captures failures, calibrates according to the objectives, and evolves the agent graph
- **[Dynamic Node Connections](docs/key_concepts/graph.md)** - No predefined edges; connection code is generated by any capable LLM based on your goals
- **SDK-Wrapped Nodes** - Every node gets shared memory, local RLM memory, monitoring, tools, and LLM access out of the box
- **[Human-in-the-Loop](docs/key_concepts/graph.md#human-in-the-loop)** - Intervention nodes that pause execution for human input with configurable timeouts and escalation
- **Real-time Observability** - WebSocket streaming for live monitoring of agent execution, decisions, and node-to-node communication
- **Cost & Budget Control** - Set spending limits, throttles, and automatic model degradation policies
- **Production-Ready** - Self-hostable, built for scale and reliability
## Integration
@@ -200,19 +201,7 @@ flowchart LR
## Run Agents
The `hive` CLI is the primary interface for running agents.
```bash
# Run a specific agent
hive run exports/my_agent --input '{"task": "Your input here"}'
# Interactive REPL
hive shell
```
> **Using Python directly (alternative):** You can also run agents with `PYTHONPATH=exports uv run python -m agent_name run --input '{...}'`
See [environment-setup.md](docs/environment-setup.md) for complete setup instructions.
Now you can run an agent by selectiing the agent (either an existing agent or example agent). You can click the Run button on the top left, or talk to the queen agent and it can run the agent for you.
## Documentation