Skip to content

feat(gooddata-eval): add the agentic anomaly-detection evaluator #1801

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
Tomkess wants to merge 1 commit into
base: master
Choose a base branch
from
Open

feat(gooddata-eval): add the agentic anomaly-detection evaluator #1801

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
13 changes: 13 additions & 0 deletions packages/gooddata-eval/src/gooddata_eval/cli/agentic_runner.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,7 @@
from gooddata_eval.core.agentic._langfuse import make_langfuse_client
from gooddata_eval.core.agentic._trace_linker import BackgroundTraceLinker, SubmitTraceLink, run_trace_link_inline
from gooddata_eval.core.agentic.alert_skill import evaluate_agentic_alert_skill
from gooddata_eval.core.agentic.anomaly_detection import evaluate_agentic_anomaly_detection
from gooddata_eval.core.agentic.conversation import ConversationFixture, evaluate_agentic_conversation
from gooddata_eval.core.agentic.general_question import evaluate_agentic_general_question
from gooddata_eval.core.agentic.guardrail import evaluate_agentic_guardrail
Expand Down Expand Up @@ -44,6 +45,7 @@ class _LfKw(TypedDict, total=False):
"agentic_guardrail",
"agentic_conversation",
"agentic_kda_skill",
"agentic_anomaly_detection",
}
)

Expand Down Expand Up @@ -228,6 +230,17 @@ def _dispatch_agentic(
agent_id=agent_id,
**lf_kw,
)
elif kind == "agentic_anomaly_detection":
return evaluate_agentic_anomaly_detection(
host=host,
token=token,
workspace_id=workspace_id,
question=item.question,
expected_output=eo if isinstance(eo, dict) else {},
k=k,
agent_id=agent_id,
**lf_kw,
)
elif kind == "agentic_conversation":
fixture_data = eo.get("fixture") or eo if isinstance(eo, dict) else {}
return evaluate_agentic_conversation(
Expand Down
Loading
Loading