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feat: create HTTP DELETE API endpoints to unregister ScoringFn and Benchmark resources in Llama Stack (#3371)
# What does this PR do? <!-- Provide a short summary of what this PR does and why. Link to relevant issues if applicable. --> This PR provides functionality for users to unregister ScoringFn and Benchmark resources for `scoring` and `eval` APIs. <!-- If resolving an issue, uncomment and update the line below --> <!-- Closes #[issue-number] --> Closes #3051 ## Test Plan <!-- Describe the tests you ran to verify your changes with result summaries. *Provide clear instructions so the plan can be easily re-executed.* --> Updated integration and unit tests via CI workflow
This commit is contained in:
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01bdcce4d2
commit
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13 changed files with 241 additions and 3 deletions
68
docs/_static/llama-stack-spec.html
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68
docs/_static/llama-stack-spec.html
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@ -1380,6 +1380,40 @@
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}
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}
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]
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},
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"delete": {
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"responses": {
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"200": {
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"description": "OK"
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},
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"400": {
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"$ref": "#/components/responses/BadRequest400"
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},
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"429": {
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"$ref": "#/components/responses/TooManyRequests429"
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},
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"500": {
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"$ref": "#/components/responses/InternalServerError500"
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},
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"default": {
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"$ref": "#/components/responses/DefaultError"
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}
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},
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"tags": [
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"Benchmarks"
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],
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"description": "Unregister a benchmark.",
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"parameters": [
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{
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"name": "benchmark_id",
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"in": "path",
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"description": "The ID of the benchmark to unregister.",
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"required": true,
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"schema": {
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"type": "string"
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}
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}
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]
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}
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},
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"/v1/openai/v1/chat/completions/{completion_id}": {
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@ -1620,6 +1654,40 @@
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}
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}
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]
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},
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"delete": {
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"responses": {
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"200": {
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"description": "OK"
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},
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"400": {
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"$ref": "#/components/responses/BadRequest400"
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},
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"429": {
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"$ref": "#/components/responses/TooManyRequests429"
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},
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"500": {
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"$ref": "#/components/responses/InternalServerError500"
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},
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"default": {
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"$ref": "#/components/responses/DefaultError"
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}
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},
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"tags": [
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"ScoringFunctions"
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],
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"description": "Unregister a scoring function.",
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"parameters": [
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{
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"name": "scoring_fn_id",
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"in": "path",
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"description": "The ID of the scoring function to unregister.",
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"required": true,
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"schema": {
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"type": "string"
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}
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}
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]
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}
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},
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"/v1/shields/{identifier}": {
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49
docs/_static/llama-stack-spec.yaml
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49
docs/_static/llama-stack-spec.yaml
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@ -954,6 +954,30 @@ paths:
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required: true
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schema:
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type: string
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delete:
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responses:
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'200':
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description: OK
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'400':
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$ref: '#/components/responses/BadRequest400'
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'429':
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$ref: >-
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#/components/responses/TooManyRequests429
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'500':
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$ref: >-
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#/components/responses/InternalServerError500
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default:
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$ref: '#/components/responses/DefaultError'
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tags:
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- Benchmarks
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description: Unregister a benchmark.
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parameters:
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- name: benchmark_id
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in: path
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description: The ID of the benchmark to unregister.
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required: true
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schema:
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type: string
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/v1/openai/v1/chat/completions/{completion_id}:
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get:
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responses:
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@ -1119,6 +1143,31 @@ paths:
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required: true
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schema:
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type: string
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delete:
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responses:
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'200':
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description: OK
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'400':
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$ref: '#/components/responses/BadRequest400'
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'429':
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$ref: >-
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#/components/responses/TooManyRequests429
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'500':
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$ref: >-
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#/components/responses/InternalServerError500
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default:
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$ref: '#/components/responses/DefaultError'
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tags:
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- ScoringFunctions
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description: Unregister a scoring function.
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parameters:
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- name: scoring_fn_id
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in: path
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description: >-
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The ID of the scoring function to unregister.
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required: true
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schema:
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type: string
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/v1/shields/{identifier}:
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get:
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responses:
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@ -93,3 +93,11 @@ class Benchmarks(Protocol):
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:param metadata: The metadata to use for the benchmark.
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"""
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...
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@webmethod(route="/eval/benchmarks/{benchmark_id}", method="DELETE")
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async def unregister_benchmark(self, benchmark_id: str) -> None:
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"""Unregister a benchmark.
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:param benchmark_id: The ID of the benchmark to unregister.
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"""
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...
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@ -197,3 +197,11 @@ class ScoringFunctions(Protocol):
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:param params: The parameters for the scoring function for benchmark eval, these can be overridden for app eval.
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"""
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...
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@webmethod(route="/scoring-functions/{scoring_fn_id:path}", method="DELETE")
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async def unregister_scoring_function(self, scoring_fn_id: str) -> None:
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"""Unregister a scoring function.
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:param scoring_fn_id: The ID of the scoring function to unregister.
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"""
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...
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@ -56,3 +56,7 @@ class BenchmarksRoutingTable(CommonRoutingTableImpl, Benchmarks):
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provider_resource_id=provider_benchmark_id,
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)
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await self.register_object(benchmark)
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async def unregister_benchmark(self, benchmark_id: str) -> None:
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existing_benchmark = await self.get_benchmark(benchmark_id)
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await self.unregister_object(existing_benchmark)
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@ -64,6 +64,10 @@ async def unregister_object_from_provider(obj: RoutableObject, p: Any) -> None:
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return await p.unregister_shield(obj.identifier)
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elif api == Api.datasetio:
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return await p.unregister_dataset(obj.identifier)
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elif api == Api.eval:
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return await p.unregister_benchmark(obj.identifier)
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elif api == Api.scoring:
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return await p.unregister_scoring_function(obj.identifier)
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elif api == Api.tool_runtime:
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return await p.unregister_toolgroup(obj.identifier)
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else:
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@ -60,3 +60,7 @@ class ScoringFunctionsRoutingTable(CommonRoutingTableImpl, ScoringFunctions):
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)
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scoring_fn.provider_id = provider_id
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await self.register_object(scoring_fn)
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async def unregister_scoring_function(self, scoring_fn_id: str) -> None:
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existing_scoring_fn = await self.get_scoring_function(scoring_fn_id)
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await self.unregister_object(existing_scoring_fn)
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@ -75,6 +75,13 @@ class MetaReferenceEvalImpl(
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)
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self.benchmarks[task_def.identifier] = task_def
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async def unregister_benchmark(self, benchmark_id: str) -> None:
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if benchmark_id in self.benchmarks:
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del self.benchmarks[benchmark_id]
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key = f"{EVAL_TASKS_PREFIX}{benchmark_id}"
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await self.kvstore.delete(key)
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async def run_eval(
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self,
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benchmark_id: str,
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@ -63,6 +63,9 @@ class LlmAsJudgeScoringImpl(
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async def register_scoring_function(self, function_def: ScoringFn) -> None:
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self.llm_as_judge_fn.register_scoring_fn_def(function_def)
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async def unregister_scoring_function(self, scoring_fn_id: str) -> None:
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self.llm_as_judge_fn.unregister_scoring_fn_def(scoring_fn_id)
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async def score_batch(
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self,
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dataset_id: str,
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@ -51,18 +51,23 @@ class NVIDIAEvalImpl(
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async def shutdown(self) -> None: ...
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async def _evaluator_get(self, path):
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async def _evaluator_get(self, path: str):
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"""Helper for making GET requests to the evaluator service."""
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response = requests.get(url=f"{self.config.evaluator_url}{path}")
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response.raise_for_status()
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return response.json()
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async def _evaluator_post(self, path, data):
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async def _evaluator_post(self, path: str, data: dict[str, Any]):
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"""Helper for making POST requests to the evaluator service."""
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response = requests.post(url=f"{self.config.evaluator_url}{path}", json=data)
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response.raise_for_status()
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return response.json()
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async def _evaluator_delete(self, path: str) -> None:
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"""Helper for making DELETE requests to the evaluator service."""
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response = requests.delete(url=f"{self.config.evaluator_url}{path}")
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response.raise_for_status()
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async def register_benchmark(self, task_def: Benchmark) -> None:
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"""Register a benchmark as an evaluation configuration."""
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await self._evaluator_post(
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},
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)
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async def unregister_benchmark(self, benchmark_id: str) -> None:
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"""Unregister a benchmark evaluation configuration from NeMo Evaluator."""
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await self._evaluator_delete(f"/v1/evaluation/configs/{DEFAULT_NAMESPACE}/{benchmark_id}")
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async def run_eval(
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self,
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benchmark_id: str,
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@ -9,6 +9,7 @@ from pathlib import Path
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import pandas as pd
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import pytest
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import requests
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@pytest.fixture
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assert len(list_response) > 0
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assert any(x.identifier == sample_scoring_fn_id for x in list_response)
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# TODO: add unregister api for scoring functions
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def test_scoring_functions_unregister(
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llama_stack_client,
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sample_scoring_fn_id,
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judge_model_id,
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sample_judge_prompt_template,
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):
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llm_as_judge_provider = [
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x
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for x in llama_stack_client.providers.list()
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if x.api == "scoring" and x.provider_type == "inline::llm-as-judge"
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]
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if len(llm_as_judge_provider) == 0:
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pytest.skip("No llm-as-judge provider found, cannot test unregister")
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llm_as_judge_provider_id = llm_as_judge_provider[0].provider_id
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# Register first
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register_scoring_function(
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llama_stack_client,
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llm_as_judge_provider_id,
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sample_scoring_fn_id,
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judge_model_id,
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sample_judge_prompt_template,
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)
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# Ensure it is present
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list_response = llama_stack_client.scoring_functions.list()
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assert any(x.identifier == sample_scoring_fn_id for x in list_response)
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# Unregister scoring fn
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try:
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base_url = llama_stack_client.base_url
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except AttributeError:
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pytest.skip("No server base_url available; cannot test HTTP unregister in library mode")
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resp = requests.delete(f"{base_url}/v1/scoring-functions/{sample_scoring_fn_id}", timeout=30)
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assert resp.status_code in (200, 204)
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list_after = llama_stack_client.scoring_functions.list()
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assert all(x.identifier != sample_scoring_fn_id for x in list_after)
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@pytest.mark.parametrize("scoring_fn_id", ["basic::equality"])
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@ -105,6 +105,9 @@ class ScoringFunctionsImpl(Impl):
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async def register_scoring_function(self, scoring_fn):
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return scoring_fn
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async def unregister_scoring_function(self, scoring_fn_id: str):
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return scoring_fn_id
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class BenchmarksImpl(Impl):
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def __init__(self):
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async def register_benchmark(self, benchmark):
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return benchmark
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async def unregister_benchmark(self, benchmark_id: str):
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return benchmark_id
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class ToolGroupsImpl(Impl):
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def __init__(self):
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@ -330,6 +336,13 @@ async def test_scoring_functions_routing_table(cached_disk_dist_registry):
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assert "test-scoring-fn" in scoring_fn_ids
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assert "test-scoring-fn-2" in scoring_fn_ids
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# Unregister scoring functions and verify listing
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for i in range(len(scoring_functions.data)):
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await table.unregister_scoring_function(scoring_functions.data[i].scoring_fn_id)
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scoring_functions_list_after_deletion = await table.list_scoring_functions()
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assert len(scoring_functions_list_after_deletion.data) == 0
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async def test_benchmarks_routing_table(cached_disk_dist_registry):
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table = BenchmarksRoutingTable({"test_provider": BenchmarksImpl()}, cached_disk_dist_registry, {})
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benchmark_ids = {b.identifier for b in benchmarks.data}
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assert "test-benchmark" in benchmark_ids
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# Unregister the benchmark and verify removal
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await table.unregister_benchmark(benchmark_id="test-benchmark")
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benchmarks_after = await table.list_benchmarks()
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assert len(benchmarks_after.data) == 0
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# Unregistering a non-existent benchmark should raise a clear error
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with pytest.raises(ValueError, match="Benchmark 'dummy_benchmark' not found"):
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await table.unregister_benchmark(benchmark_id="dummy_benchmark")
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async def test_tool_groups_routing_table(cached_disk_dist_registry):
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table = ToolGroupsRoutingTable({"test_provider": ToolGroupsImpl()}, cached_disk_dist_registry, {})
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@ -52,14 +52,19 @@ class TestNVIDIAEvalImpl(unittest.TestCase):
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self.evaluator_post_patcher = patch(
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"llama_stack.providers.remote.eval.nvidia.eval.NVIDIAEvalImpl._evaluator_post"
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)
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self.evaluator_delete_patcher = patch(
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"llama_stack.providers.remote.eval.nvidia.eval.NVIDIAEvalImpl._evaluator_delete"
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)
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self.mock_evaluator_get = self.evaluator_get_patcher.start()
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self.mock_evaluator_post = self.evaluator_post_patcher.start()
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self.mock_evaluator_delete = self.evaluator_delete_patcher.start()
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def tearDown(self):
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"""Clean up after each test."""
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self.evaluator_get_patcher.stop()
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self.evaluator_post_patcher.stop()
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self.evaluator_delete_patcher.stop()
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def _assert_request_body(self, expected_json):
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"""Helper method to verify request body in Evaluator POST request is correct"""
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@ -115,6 +120,13 @@ class TestNVIDIAEvalImpl(unittest.TestCase):
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self.mock_evaluator_post.assert_called_once()
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self._assert_request_body({"namespace": benchmark.provider_id, "name": benchmark.identifier, **eval_config})
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def test_unregister_benchmark(self):
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# Unregister the benchmark
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self.run_async(self.eval_impl.unregister_benchmark(benchmark_id=MOCK_BENCHMARK_ID))
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# Verify the Evaluator API was called correctly
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self.mock_evaluator_delete.assert_called_once_with(f"/v1/evaluation/configs/nvidia/{MOCK_BENCHMARK_ID}")
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def test_run_eval(self):
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benchmark_config = BenchmarkConfig(
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eval_candidate=ModelCandidate(
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