> For the complete documentation index, see [llms.txt](https://docs.amesa.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.amesa.com/reference/sdk-reference/core/agent-api.md).

# Agent API

### Agent API

The `Agent` class is the central orchestrator that combines skills, sensors, and perceptors.

#### Creating an Agent

```python
from composabl import Agent

# Create a new agent
agent = Agent()

# Create with ID
agent = Agent(id="temperature-controller-v1")
```

#### Agent Methods

**Adding Components**

```python
# Add single sensor
agent.add_sensor(sensor)

# Add multiple sensors
agent.add_sensors([sensor1, sensor2, sensor3])

# Add skill
agent.add_skill(skill)

# Add multiple skills
agent.add_skills([skill1, skill2])

# Add perceptor
agent.add_perceptor(perceptor)

# Add scenario
agent.add_scenario(scenario)
```

**Serialization**

```python
# Export to file
agent.export("path/to/agent.json")

# Load from file
agent = Agent.load("path/to/agent.json")
```

**Visualization**

```python
# Display agent structure
agent.draw()

# Get structure as string
structure = agent.get_structure()
```

#### Complete Agent Example

```python
from composabl import Agent, Sensor, Skill, Scenario, Perceptor
from composabl import MaintainGoal

# Create agent
agent = Agent(id="reactor-controller")

# Add sensors
agent.add_sensors([
    Sensor("temp", "Temperature in Celsius", lambda obs: obs["temperature"]),
    Sensor("pressure", "Pressure in bar", lambda obs: obs["pressure_reading"]),
    Sensor("flow", "Flow rate L/min", lambda obs: obs["flow_rate"])
])

# Add perceptor
class RateCalculator(PerceptorImpl):
    def __init__(self):
        self.last_temp = None
        
    async def compute(self, obs_spec, obs):
        rate = 0
        if self.last_temp is not None:
            rate = obs["temperature"] - self.last_temp
        self.last_temp = obs["temperature"]
        return {"temp_rate": rate}
    
    def filtered_sensor_space(self, obs):
        return ["temperature"]

agent.add_perceptor(Perceptor("rate-calc", RateCalculator))

# Add skills
temp_skill = Skill("maintain-temp", 
                  MaintainGoal("temp", "Keep temperature stable", 
                              target=75.0, stop_distance=2.0))
agent.add_skill(temp_skill)

# Add scenarios
agent.add_scenario(Scenario({
    "temperature": {"min": 70, "max": 80},
    "pressure": {"min": 5, "max": 7}
}))

# Visualize
agent.draw()
```


---

# Agent Instructions
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