Observation and developer tooling companion package for Agently
Project description
agently-devtools
agently-devtools is the local observation, evaluation, and playground companion package for agently.
Install
pip install -U agently agently-devtools
Compatible with agently >=4.1.0.2,<4.2.0.
Compatibility resolution uses the current Agently offline manifest first, then the Agently release registry, then a bounded legacy fallback for 4.1.0.2 through 4.1.1.
Python >=3.10
Start
agently-devtools start
Default local address:
- Console:
http://127.0.0.1:15596/ - Ingest:
http://127.0.0.1:15596/observation/ingest
Explicit listener options:
agently-devtools start --host 0.0.0.0 --port 15596 --path /observation/ingest --no-open
Observation Bridge
from agently import Agently
from agently_devtools import ObservationBridge
bridge = ObservationBridge(
Agently,
app_id="your_app_id",
group_id="your_group_id",
)
bridge.watch(Agently)
Explicit endpoint styles are also supported:
ObservationBridge(Agently, host="127.0.0.1", port=15596, path="/observation/ingest")
ObservationBridge(Agently, endpoint="https://devtools.example.com/observation/ingest")
Use selective watch when you do not want to upload every observation event:
bridge = ObservationBridge(
Agently,
app_id="your_app_id",
)
bridge.watch(agent, flow, lookup_reference)
The older bridge = ObservationBridge(...); bridge.register(Agently) style remains compatible and emits a deprecation warning. Prefer binding the Agently object or event center in the constructor, then selecting global or scoped observation with bridge.watch(...).
The bridge uses a background queue and coalesces high-frequency streaming events before upload, so passive observation does not block normal request output. For short-lived scripts, call await bridge.flush() before exit when you need all buffered events delivered.
TriggerFlow executions automatically publish their flow definition, so the execution graph can show the full static structure, including branches that have not been hit yet.
Scenario Evaluations
from agently_devtools import EvaluationBridge, EvaluationCase, EvaluationRunner
bridge = EvaluationBridge(
base_url="http://127.0.0.1:15596",
app_id="your_app_id",
group_id="your_eval_group",
)
runner = EvaluationRunner(bridge=bridge)
binding = bridge.bind_agent_factory(
lambda: build_agent(),
suite_id="support-suite",
target_name="support-agent",
)
report = runner.run(
binding,
cases=[
EvaluationCase(case_id="refund", input="Need a refund for a duplicate payment."),
EvaluationCase(case_id="shipping", input="Where is my shipment now?"),
],
rules=[
lambda record: bool(record.output),
lambda record: record.error is None,
],
rounds=2,
)
Use the binding helper that matches your target:
bind_agent(...)/bind_agent_factory(...)bind_request(...)/bind_request_factory(...)bind_triggerflow(...)/bind_triggerflow_factory(...)
EvaluationBridge already records rounds into DevTools and keeps observed run linkage automatically. You do not need an extra ObservationBridge just for Scenario Evaluations.
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