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Agents

Agents are autonomous AI entities that can execute tasks and use tools. Each agent belongs to an organization and, optionally, to an AgentTemplate that seeds its initial configuration.

Agent Properties

FieldDescription
nameHuman-readable name
organizationOwning org (auto-filled from the caller’s API key / token)
templateThe AgentTemplate this agent was stamped from (nullable for ad-hoc agents)
purposeproduction / eval / dev. Only production agents are woken by the wake_agents cron.
tagsFree-form string labels (e.g. scenario:group-lunch-memory, git-ref:feature/x)
modelLLM model (e.g., claude-sonnet-4-5, gpt-4o). Copied from the template’s default_model at creation if blank.
reasoning_effort'' (model default) / minimal / low / medium / high / xhigh / max
system_promptInstructions (copied from template’s system_prompt at creation if blank)
timezoneAgent’s timezone for time-aware operations
max_turnsMaximum iterations per run (default: 50)
statusCurrent state: running / sleeping / archived
sleep_untilWhen the agent will wake up (if sleeping)
adaptersTools available to this agent (seeded from the template’s adapter set)

Creating an Agent

Usually you create an agent from a template — the agent snapshots the template’s system_prompt, default_model, adapter set, and per-adapter config at creation.
curl -X POST https://api.bedrock.orinlabs.org/api/cloud/agents/ \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "name": "Support Agent",
    "template": "TEMPLATE_ID",
    "timezone": "America/New_York"
  }'
You can override any field at creation time (e.g., specify a custom model, system_prompt, or adapters array). Ad-hoc agents without a template are allowed too — pass template: null and provide model + system_prompt + adapters explicitly.
If model or system_prompt are blank at creation and a template is attached, the template’s values are copied in. Template edits after that don’t retroactively change the agent.

Tagging Agents

Tags are free-form string labels. Useful for filtering in the portal — e.g., git-ref:feature/x on eval agents, or cohort:beta on production agents.
curl -X POST https://api.bedrock.orinlabs.org/api/cloud/agents/AGENT_ID/tags/ \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"tag": "cohort:beta"}'
curl -X DELETE https://api.bedrock.orinlabs.org/api/cloud/agents/AGENT_ID/tags/cohort:beta/ \
  -H "Authorization: Bearer YOUR_API_KEY"
Both endpoints are idempotent — the POST returns 200 if the tag already existed, 201 if it was created.

Running an Agent

Wake an agent to start execution:
curl -X POST https://api.bedrock.orinlabs.org/api/cloud/agents/AGENT_ID/run/ \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"wakeup": true}'

What Happens During a Run

Every run_agent invocation spawns an isolated bedrock-harness subprocess (pinned to the template’s harness_git_ref, or latest main if unset). The harness drives the loop and streams spans back to Bedrock over HTTP; a HarnessRun row links the subprocess to the resulting Trace.
  1. Status Change: Agent transitions to RUNNING
  2. Runtime Loop (up to max_turns iterations):
    • Build prompt with system instructions and adapter state
    • Call LLM with available tools
    • Process any tool calls
  3. Sleep: Agent calls sleep tool or hits max turns

The Runtime Loop

  1. Build prompt with tools and adapter state
  2. Call LLM
  3. Process tool calls
  4. Check if should continue — if yes, go back to step 1; if no (sleep called), exit

Built-in Default Tools

Every agent has access to these tools regardless of adapters:
ToolDescription
sleepSleep until a specified datetime (with checklist verification)
waitPause briefly (max 30 seconds)
set_timezoneUpdate the agent’s timezone

Sleep Tool

Agents must call sleep to end their run gracefully. Before sleeping, the agent must verify a checklist of conditions:
{
  "name": "sleep",
  "arguments": {
    "all_tasks_completed": true,
    "no_pending_background_tasks": true,
    "until": "2024-01-15T14:00:00Z"
  }
}
ParameterDescription
all_tasks_completedConfirm you’ve done everything you can on your tasks right now. True if tasks are complete OR you MUST wait on something external with nothing more to do. False if there’s still work you could be doing.
no_pending_background_tasksConfirm there’s nothing else you could be working on. False if you could improve your work, make it more comprehensive, or handle other responsibilities.
untilISO 8601 datetime to sleep until
Sleeping to wait on the user is usually an indication that more work should be done. Agents should only sleep when they MUST wait on something external, not when they simply need user input.
If any checklist item is false, the sleep will be rejected and the agent must address the issue before sleeping. If an agent doesn’t call sleep and hits max_turns, it’s automatically put to sleep for 1 hour.

Stopping an Agent

Force-stop a running agent:
curl -X POST https://api.bedrock.orinlabs.org/api/cloud/agents/AGENT_ID/stop/ \
  -H "Authorization: Bearer YOUR_API_KEY"
This immediately transitions the agent to SLEEPING status.

Agent State

Agents using built-in adapters have persistent state:
StateDescription
ContactsPhone book of people the agent knows
DocumentsText documents for reference. Each document has a kind: note (ephemeral scratchpad) or skill (curated knowledge — facts or SOPs — that can be promoted into template adapter config for future agents).
ProjectsHierarchical project tracking
NotificationsPending notifications and reminders
MessagesSMS/Email/MMS conversation history
This state persists across runs and is private to each agent.

Supported Models

Bedrock supports models from: Anthropic (Claude):
  • claude-sonnet-4-5
  • claude-opus-4
  • claude-haiku-4-5
OpenAI:
  • gpt-4o
  • gpt-4o-mini
  • gpt-4-turbo
Claude models get automatic access to web search capabilities.

Usage Tracking

Get usage statistics for an agent:
curl -X GET "https://api.bedrock.orinlabs.org/api/cloud/agents/AGENT_ID/usage/?start_date=2024-01-01T00:00:00Z" \
  -H "Authorization: Bearer YOUR_API_KEY"
Response:
{
  "agent_id": "agent-uuid",
  "agent_name": "Support Agent",
  "input_tokens": 45000,
  "output_tokens": 12000,
  "cached_tokens": 30000,
  "total_cost_usd": 0.85,
  "llm_calls": 150,
  "model_breakdown": {
    "claude-sonnet-4": {
      "input_tokens": 45000,
      "output_tokens": 12000,
      "total_cost_usd": 0.85,
      "llm_calls": 150
    }
  }
}

Wakeup Message

When an agent wakes up, it receives this instruction:
You are being woken up from sleep. Gather information from your tools to determine what to do next. Check every tool that stores information (like any tool with ‘list’ in the name) to re-ground yourself.
This prompts agents to check for new messages, tasks, etc. before taking action.

Example: Complete Agent Lifecycle

import requests

API_KEY = "your-api-key"
BASE_URL = "https://api.bedrock.orinlabs.org"
headers = {"Authorization": f"Bearer {API_KEY}"}

# 1. Create an agent from a template
agent = requests.post(
    f"{BASE_URL}/api/cloud/agents/",
    headers=headers,
    json={
        "name": "Task Manager",
        "template": "TEMPLATE_ID",
    }
).json()

# 2. Run the agent
requests.post(
    f"{BASE_URL}/api/cloud/agents/{agent['id']}/run/",
    headers=headers,
    json={"wakeup": True}
)

# 3. Check status
status = requests.get(
    f"{BASE_URL}/api/cloud/agents/{agent['id']}/",
    headers=headers
).json()
print(f"Agent status: {status['status']}")

# 4. View execution traces
traces = requests.get(
    f"{BASE_URL}/api/tracing/traces/list/",
    headers=headers,
    params={"agent": agent["id"]},
).json()