Talk to Your Graph (TTYG) Evaluation is a Python module for evaluating whether LLM agents correctly orchestrate and invoke available tools to answer user questions, based on a gold-standard corpus of tool call expectations.
Project description
Talk to Your Graph (TTYG) Evaluation
TTYG Evaluation is a Python module for evaluating whether LLM agents correctly orchestrate and invoke available tools to answer user questions, based on a gold-standard corpus of tool call expectations.
License
Apache-2.0 License. See LICENSE file for details.
Installation
pip install ttyg-evaluation
Maintainers
Developed and maintained by Graphwise. For issues or feature requests, please open a GitHub issue.
Usage
To use this module you must provide a gold standard corpus that defines questions and expected tool calls for each question.
Gold Standard Format
A gold standard corpus is a list of templates. Each template contains:
id– Unique template identifierqaSet– A list of questions derived from this template, where each includes:question_id– Unique question identifierquestion– The natural language query passed to the LLMtools_calls– A list of tool calls grouped by level. The assumption is that the final answer to the question is derived from the outputs of the tools, which are called last (last level).
Each tool call includes:
name– The tool being called (e.g.,sparql_query)args– Arguments passed to the tool (e.g., SPARQL query)output– The expected output from the tooloutput_media_type– (optional, missing or one ofapplication/sparql-results+json,application/json) - Indicates how the output of a tool must be processedordered– (optional, defaults tofalse) - only applicable for SPARQL query results, whether the order of the results matters.falsemeans that the results are not ordered, hence for comparison we can re-order them.truemeans the results order matters and in order to match the order must be preserved.optional_vars– (optional, defaults to an empty list) - only applicable for SPARQL query results, list of binding names, which can be ignored when comparing SPARQL results
Example Corpus
The example corpus below illustrates a minimal but realistic gold standard, showing two templates with associated questions and tool calls.
[
{
"id": "list_all_transformers_within_Substation_SUBSTATION",
"qaSet": [
{
"question_id": "c10bbc8dce98a4b8832d125134a16153",
"question": "List all transformers within Substation OSLO",
"tools_calls": [
[
{
"name": "sparql_query",
"args": {
"query": "\nPREFIX cimex: <https://rawgit2.com/statnett/Talk2PowerSystem/main/demo1/cimex/>\nPREFIX cim: <https://cim.ucaiug.io/ns#>\nPREFIX rank: <http://www.ontotext.com/owlim/RDFRank#>\nPREFIX xsd: <http://www.w3.org/2001/XMLSchema#>\nselect distinct ?transformer ?transformerName\nwhere {\n bind(<urn:uuid:f176963c-9aeb-11e5-91da-b8763fd99c5f> as ?substation)\n\n ?transformer a cim:PowerTransformer ;\n cim:Equipment.EquipmentContainer ?substation ;\n cim:IdentifiedObject.name ?transformerName .\n}\n"
},
"output": "{\"head\": {\"vars\": [\"transformer\", \"transformerName\"]}, \"results\": {\"bindings\": [{\"transformer\": {\"type\": \"uri\", \"value\": \"urn:uuid:f1769de8-9aeb-11e5-91da-b8763fd99c5f\"}, \"transformerName\": {\"type\": \"literal\", \"value\": \"OSLO T2\"}}, {\"transformer\": {\"type\": \"uri\", \"value\": \"urn:uuid:f1769dd6-9aeb-11e5-91da-b8763fd99c5f\"}, \"transformerName\": {\"type\": \"literal\", \"value\": \"OSLO T1\"}}]}}",
"output_media_type": "application/sparql-results+json",
"optional_vars": ["transformerName"]
}
]
]
},
{
"question_id": "8bbea9a10876a04ad77a82fd2aedee40",
"question": "List all transformers within Substation STAVANGER",
"tools_calls": [
[
{
"name": "sparql_query",
"args": {
"query": "\nPREFIX cimex: <https://rawgit2.com/statnett/Talk2PowerSystem/main/demo1/cimex/>\nPREFIX cim: <https://cim.ucaiug.io/ns#>\nPREFIX rank: <http://www.ontotext.com/owlim/RDFRank#>\nPREFIX xsd: <http://www.w3.org/2001/XMLSchema#>\nselect distinct ?transformer ?transformerName\nwhere {\n bind(<urn:uuid:f1769664-9aeb-11e5-91da-b8763fd99c5f> as ?substation)\n\n ?transformer a cim:PowerTransformer ;\n cim:Equipment.EquipmentContainer ?substation ;\n cim:IdentifiedObject.name ?transformerName .\n}\n"
},
"output": "{\"head\": {\"vars\": [\"transformer\", \"transformerName\"]}, \"results\": {\"bindings\": [{\"transformer\": {\"type\": \"uri\", \"value\": \"urn:uuid:f1769e0c-9aeb-11e5-91da-b8763fd99c5f\"}, \"transformerName\": {\"type\": \"literal\", \"value\": \"STAVANGET1\"}}]}}",
"output_media_type": "application/sparql-results+json",
"optional_vars": ["transformerName"]
}
]
]
}
]
},
{
"id": "list_all_substations_within_bidding_zone_REGION",
"qaSet": [
{
"question_id": "d566b1e9da418ac83e520a66cc7af4d7",
"question": "List all substations within bidding zone NO2 SGR",
"tools_calls": [
[
{
"name": "sparql_query",
"args": {
"query": "\nPREFIX cimex: <https://rawgit2.com/statnett/Talk2PowerSystem/main/demo1/cimex/>\nPREFIX cim: <https://cim.ucaiug.io/ns#>\nPREFIX rank: <http://www.ontotext.com/owlim/RDFRank#>\nPREFIX xsd: <http://www.w3.org/2001/XMLSchema#>\nselect distinct ?substation ?substationName\nwhere {\n bind(<urn:uuid:f176965f-9aeb-11e5-91da-b8763fd99c5f> as ?region)\n\n ?substation a cim:Substation ;\n cim:Substation.Region ?region ;\n cim:IdentifiedObject.name ?substationName .\n}\n"
},
"output": "{\"head\": {\"vars\": [\"substation\", \"substationName\"]}, \"results\": {\"bindings\": [{\"substation\": {\"type\": \"uri\", \"value\": \"urn:uuid:f1769670-9aeb-11e5-91da-b8763fd99c5f\"}, \"substationName\": {\"type\": \"literal\", \"value\": \"ARENDAL\"}}, {\"substation\": {\"type\": \"uri\", \"value\": \"urn:uuid:f176968e-9aeb-11e5-91da-b8763fd99c5f\"}, \"substationName\": {\"type\": \"literal\", \"value\": \"BLAFALLI\"}}, {\"substation\": {\"type\": \"uri\", \"value\": \"urn:uuid:f1769664-9aeb-11e5-91da-b8763fd99c5f\"}, \"substationName\": {\"type\": \"literal\", \"value\": \"STAVANGER\"}}, {\"substation\": {\"type\": \"uri\", \"value\": \"urn:uuid:f1769676-9aeb-11e5-91da-b8763fd99c5f\"}, \"substationName\": {\"type\": \"literal\", \"value\": \"KRISTIA_HVDC\"}}, {\"substation\": {\"type\": \"uri\", \"value\": \"urn:uuid:f1769682-9aeb-11e5-91da-b8763fd99c5f\"}, \"substationName\": {\"type\": \"literal\", \"value\": \"KVILLDAL\"}}, {\"substation\": {\"type\": \"uri\", \"value\": \"urn:uuid:f176966a-9aeb-11e5-91da-b8763fd99c5f\"}, \"substationName\": {\"type\": \"literal\", \"value\": \"SANDEFJORD\"}}, {\"substation\": {\"type\": \"uri\", \"value\": \"urn:uuid:f176965a-9aeb-11e5-91da-b8763fd99c5f\"}, \"substationName\": {\"type\": \"literal\", \"value\": \"KRISTIANSAND\"}}, {\"substation\": {\"type\": \"uri\", \"value\": \"urn:uuid:f176967c-9aeb-11e5-91da-b8763fd99c5f\"}, \"substationName\": {\"type\": \"literal\", \"value\": \"FEDA_HVDC\"}}]}}",
"output_media_type": "application/sparql-results+json",
"ordered": true
}
]
]
}
]
}
]
The module is agnostic to the specific LLM agent implementation and model; it depends solely on the format of the response. Below is a sample response from the LLM agent for a single question:
{
"question_id": "f91fc938d606e5f6089912bebfaf114b",
"input_tokens": 298028,
"output_tokens": 725,
"total_tokens": 298753,
"elapsed_sec": 46.48961806297302,
"tools_calls": [
{
"name": "autocomplete_search",
"args": {
"query": "STAVANGER",
"result_class": "cim:Substation"
},
"id": "call_7amIsfEGelOnVZ1DWtgtc0hc",
"status": "success",
"output": "{\n \"head\": {\n \"vars\": [\n \"iri\",\n \"name\",\n \"rank\"\n ]\n },\n \"results\": {\n \"bindings\": [\n {\n \"iri\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f1769664-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"name\": {\n \"type\": \"literal\",\n \"value\": \"STAVANGER\"\n },\n \"rank\": {\n \"datatype\": \"http://www.w3.org/2001/XMLSchema#float\",\n \"type\": \"literal\",\n \"value\": \"0.00976\"\n }\n }\n ]\n }\n}"
},
{
"name": "sparql_query",
"args": {
"query": "SELECT DISTINCT ?substation2 ?substation2Name ?line ?lineName WHERE {\n # Substation STAVANGER\n BIND(urn:uuid:f1769664-9aeb-11e5-91da-b8763fd99c5f AS ?substation1) .\n\n # Find lines connected to STAVANGER\n ?line a cim:Line ;\n cimex:connectedThroughPart ?substation1, ?substation2 ;\n cim:IdentifiedObject.name ?lineName .\n\n # Ensure the connected substation is different from STAVANGER\n ?substation2 a cim:Substation ;\n cim:IdentifiedObject.name ?substation2Name .\n FILTER(?substation1 != ?substation2)\n}"
},
"id": "call_DbMkZ8kv3qkf49wNNdREkpRN",
"status": "error",
"output": "Error: ValueError('The following prefixes are undefined: urn')\n Please fix your mistakes."
},
{
"name": "sparql_query",
"args": {
"query": "SELECT DISTINCT ?substation2 ?substation2Name ?line ?lineName WHERE {\n # Substation STAVANGER\n BIND(<urn:uuid:f1769664-9aeb-11e5-91da-b8763fd99c5f> AS ?substation1) .\n\n # Find lines connected to STAVANGER\n ?line a cim:Line ;\n cimex:connectedThroughPart ?substation1, ?substation2 ;\n cim:IdentifiedObject.name ?lineName .\n\n # Ensure the connected substation is different from STAVANGER\n ?substation2 a cim:Substation ;\n cim:IdentifiedObject.name ?substation2Name .\n FILTER(?substation1 != ?substation2)\n}"
},
"id": "call_Qm1mzX7g5q9SVPrR2QzEMTp3",
"status": "success",
"output": "{\n \"head\": {\n \"vars\": [\n \"substation2\",\n \"substation2Name\",\n \"line\",\n \"lineName\"\n ]\n },\n \"results\": {\n \"bindings\": [\n {\n \"substation2\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f176965a-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"substation2Name\": {\n \"type\": \"literal\",\n \"value\": \"KRISTIANSAND\"\n },\n \"line\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:47332c85-17a4-7a41-abd5-2b92e4b800ed\"\n },\n \"lineName\": {\n \"type\": \"literal\",\n \"value\": \"LC 300KRISTIAN-STAVANGE\"\n }\n },\n {\n \"substation2\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f1769614-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"substation2Name\": {\n \"type\": \"literal\",\n \"value\": \"DAGALI\"\n },\n \"line\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:c5f535a5-f053-a948-9cee-f6a7b07c7d4f\"\n },\n \"lineName\": {\n \"type\": \"literal\",\n \"value\": \"LC 420DAGALI-HAGAFOSS\"\n }\n },\n {\n \"substation2\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f1769682-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"substation2Name\": {\n \"type\": \"literal\",\n \"value\": \"KVILLDAL\"\n },\n \"line\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:c5f535a5-f053-a948-9cee-f6a7b07c7d4f\"\n },\n \"lineName\": {\n \"type\": \"literal\",\n \"value\": \"LC 420DAGALI-HAGAFOSS\"\n }\n },\n {\n \"substation2\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f1769688-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"substation2Name\": {\n \"type\": \"literal\",\n \"value\": \"HAGAFOSS\"\n },\n \"line\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:c5f535a5-f053-a948-9cee-f6a7b07c7d4f\"\n },\n \"lineName\": {\n \"type\": \"literal\",\n \"value\": \"LC 420DAGALI-HAGAFOSS\"\n }\n },\n {\n \"substation2\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f176963c-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"substation2Name\": {\n \"type\": \"literal\",\n \"value\": \"OSLO\"\n },\n \"line\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:a93b83d7-8a39-ef48-8c29-36de1ac0eaf5\"\n },\n \"lineName\": {\n \"type\": \"literal\",\n \"value\": \"LC 420SYSLE-HAGAFOSS\"\n }\n },\n {\n \"substation2\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f1769648-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"substation2Name\": {\n \"type\": \"literal\",\n \"value\": \"SYSLE\"\n },\n \"line\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:a93b83d7-8a39-ef48-8c29-36de1ac0eaf5\"\n },\n \"lineName\": {\n \"type\": \"literal\",\n \"value\": \"LC 420SYSLE-HAGAFOSS\"\n }\n },\n {\n \"substation2\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f1769682-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"substation2Name\": {\n \"type\": \"literal\",\n \"value\": \"KVILLDAL\"\n },\n \"line\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:a93b83d7-8a39-ef48-8c29-36de1ac0eaf5\"\n },\n \"lineName\": {\n \"type\": \"literal\",\n \"value\": \"LC 420SYSLE-HAGAFOSS\"\n }\n },\n {\n \"substation2\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f1769688-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"substation2Name\": {\n \"type\": \"literal\",\n \"value\": \"HAGAFOSS\"\n },\n \"line\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:a93b83d7-8a39-ef48-8c29-36de1ac0eaf5\"\n },\n \"lineName\": {\n \"type\": \"literal\",\n \"value\": \"LC 420SYSLE-HAGAFOSS\"\n }\n },\n {\n \"substation2\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f176962a-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"substation2Name\": {\n \"type\": \"literal\",\n \"value\": \"AURLAND\"\n },\n \"line\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:293e49bc-c995-fc46-a69c-380876b317a1\"\n },\n \"lineName\": {\n \"type\": \"literal\",\n \"value\": \"LC 420AURLAND-HAGAFOSS\"\n }\n },\n {\n \"substation2\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f1769682-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"substation2Name\": {\n \"type\": \"literal\",\n \"value\": \"KVILLDAL\"\n },\n \"line\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:293e49bc-c995-fc46-a69c-380876b317a1\"\n },\n \"lineName\": {\n \"type\": \"literal\",\n \"value\": \"LC 420AURLAND-HAGAFOSS\"\n }\n },\n {\n \"substation2\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f1769688-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"substation2Name\": {\n \"type\": \"literal\",\n \"value\": \"HAGAFOSS\"\n },\n \"line\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:293e49bc-c995-fc46-a69c-380876b317a1\"\n },\n \"lineName\": {\n \"type\": \"literal\",\n \"value\": \"LC 420AURLAND-HAGAFOSS\"\n }\n },\n {\n \"substation2\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f1769624-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"substation2Name\": {\n \"type\": \"literal\",\n \"value\": \"SIMA\"\n },\n \"line\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:293e49bc-c995-fc46-a69c-380876b317a1\"\n },\n \"lineName\": {\n \"type\": \"literal\",\n \"value\": \"LC 420AURLAND-HAGAFOSS\"\n }\n },\n {\n \"substation2\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f1769642-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"substation2Name\": {\n \"type\": \"literal\",\n \"value\": \"SYLLING\"\n },\n \"line\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:163037f6-cf93-054e-8a6d-3f58de83b6a3\"\n },\n \"lineName\": {\n \"type\": \"literal\",\n \"value\": \"LC 420SYLLING-HAGAFOSS\"\n }\n },\n {\n \"substation2\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f176963c-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"substation2Name\": {\n \"type\": \"literal\",\n \"value\": \"OSLO\"\n },\n \"line\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:163037f6-cf93-054e-8a6d-3f58de83b6a3\"\n },\n \"lineName\": {\n \"type\": \"literal\",\n \"value\": \"LC 420SYLLING-HAGAFOSS\"\n }\n },\n {\n \"substation2\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f1769682-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"substation2Name\": {\n \"type\": \"literal\",\n \"value\": \"KVILLDAL\"\n },\n \"line\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:163037f6-cf93-054e-8a6d-3f58de83b6a3\"\n },\n \"lineName\": {\n \"type\": \"literal\",\n \"value\": \"LC 420SYLLING-HAGAFOSS\"\n }\n },\n {\n \"substation2\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f1769688-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"substation2Name\": {\n \"type\": \"literal\",\n \"value\": \"HAGAFOSS\"\n },\n \"line\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:163037f6-cf93-054e-8a6d-3f58de83b6a3\"\n },\n \"lineName\": {\n \"type\": \"literal\",\n \"value\": \"LC 420SYLLING-HAGAFOSS\"\n }\n }\n ]\n }\n}"
}
],
"answer": "The substations connected to the substation \"STAVANGER\" via AC or DC lines are:\n\n1. **KRISTIANSAND** via line \"LC 300KRISTIAN-STAVANGE\"\n2. **DAGALI** via line \"LC 420DAGALI-HAGAFOSS\"\n3. **KVILLDAL** via lines:\n - \"LC 420DAGALI-HAGAFOSS\"\n - \"LC 420SYSLE-HAGAFOSS\"\n - \"LC 420AURLAND-HAGAFOSS\"\n - \"LC 420SYLLING-HAGAFOSS\"\n4. **HAGAFOSS** via lines:\n - \"LC 420DAGALI-HAGAFOSS\"\n - \"LC 420SYSLE-HAGAFOSS\"\n - \"LC 420AURLAND-HAGAFOSS\"\n - \"LC 420SYLLING-HAGAFOSS\"\n5. **OSLO** via lines:\n - \"LC 420SYSLE-HAGAFOSS\"\n - \"LC 420SYLLING-HAGAFOSS\"\n6. **SYSLE** via line \"LC 420SYSLE-HAGAFOSS\"\n7. **AURLAND** via line \"LC 420AURLAND-HAGAFOSS\"\n8. **SIMA** via line \"LC 420AURLAND-HAGAFOSS\"\n9. **SYLLING** via line \"LC 420SYLLING-HAGAFOSS\""
}
If an error occurs, the expected response format is:
{
"question_id": "a8daaf98b84b4f6b0e0052fb942bf6b6",
"error": "Error message"
}
Sample code:
from ttyg_evaluation import run_evaluation, compute_aggregations
sample_gold_standard: list[dict] = [] # read your corpus
chat_responses: dict = {} # call your implementation to get the response
evaluation_results = run_evaluation(sample_gold_standard, chat_responses)
aggregates = compute_aggregations(evaluation_results)
evaluation_results is a list in which for each question from the gold standard corpus we have for example
{
"template_id": "list_all_transformers_within_Substation_SUBSTATION",
"question_id": "c10bbc8dce98a4b8832d125134a16153",
"question": "List all transformers within Substation OSLO",
"expected_tools_calls": [
[
{
"name": "sparql_query",
"args": {
"query": "\nPREFIX cimex: <https://rawgit2.com/statnett/Talk2PowerSystem/main/demo1/cimex/>\nPREFIX cim: <https://cim.ucaiug.io/ns#>\nPREFIX rank: <http://www.ontotext.com/owlim/RDFRank#>\nPREFIX xsd: <http://www.w3.org/2001/XMLSchema#>\nselect distinct ?transformer ?transformerName\nwhere {\n bind(<urn:uuid:f176963c-9aeb-11e5-91da-b8763fd99c5f> as ?substation)\n\n ?transformer a cim:PowerTransformer ;\n cim:Equipment.EquipmentContainer ?substation ;\n cim:IdentifiedObject.name ?transformerName .\n}\n"
},
"output": "{\"head\": {\"vars\": [\"transformer\", \"transformerName\"]}, \"results\": {\"bindings\": [{\"transformer\": {\"type\": \"uri\", \"value\": \"urn:uuid:f1769de8-9aeb-11e5-91da-b8763fd99c5f\"}, \"transformerName\": {\"type\": \"literal\", \"value\": \"OSLO T2\"}}, {\"transformer\": {\"type\": \"uri\", \"value\": \"urn:uuid:f1769dd6-9aeb-11e5-91da-b8763fd99c5f\"}, \"transformerName\": {\"type\": \"literal\", \"value\": \"OSLO T1\"}}]}}",
"output_media_type": "application/sparql-results+json",
"ordered": false,
"matches": "call_3b3zHJnBXwYYSg04BiFGAAgO"
}
]
],
"answer": "The following transformers are located within the Substation OSLO:\n\n1. **OSLO T2** (IRI: `urn:uuid:f1769de8-9aeb-11e5-91da-b8763fd99c5f`)\n2. **OSLO T1** (IRI: `urn:uuid:f1769dd6-9aeb-11e5-91da-b8763fd99c5f`)",
"agent_tools_calls": [
{
"name": "autocomplete_search",
"args": {
"query": "OSLO",
"result_class": "cim:Substation"
},
"id": "call_3wIrBHIsInzAWzo8qwwYAkDD",
"status": "success",
"output": "{\n \"head\": {\n \"vars\": [\n \"iri\",\n \"name\",\n \"rank\"\n ]\n },\n \"results\": {\n \"bindings\": [\n {\n \"iri\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f176963c-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"name\": {\n \"type\": \"literal\",\n \"value\": \"OSLO\"\n },\n \"rank\": {\n \"datatype\": \"http://www.w3.org/2001/XMLSchema#float\",\n \"type\": \"literal\",\n \"value\": \"0.01185\"\n }\n }\n ]\n }\n}"
},
{
"name": "sparql_query",
"args": {
"query": "SELECT ?transformer ?transformerName WHERE {\n ?transformer a cim:PowerTransformer ;\n cim:Equipment.EquipmentContainer <urn:uuid:f176963c-9aeb-11e5-91da-b8763fd99c5f> ;\n cim:IdentifiedObject.name ?transformerName .\n}"
},
"id": "call_3b3zHJnBXwYYSg04BiFGAAgO",
"status": "success",
"output": "{\n \"head\": {\n \"vars\": [\n \"transformer\",\n \"transformerName\"\n ]\n },\n \"results\": {\n \"bindings\": [\n {\n \"transformer\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f1769de8-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"transformerName\": {\n \"type\": \"literal\",\n \"value\": \"OSLO T2\"\n }\n },\n {\n \"transformer\": {\n \"type\": \"uri\",\n \"value\": \"urn:uuid:f1769dd6-9aeb-11e5-91da-b8763fd99c5f\"\n },\n \"transformerName\": {\n \"type\": \"literal\",\n \"value\": \"OSLO T1\"\n }\n }\n ]\n }\n}"
}
],
"answer_score": 1,
"input_tokens": 221339,
"output_tokens": 212,
"total_tokens": 221551,
"elapsed_sec": 6.601679801940918
}
template_id- the template idquestion_id- the question idquestion- the natural language queryexpected_tools_calls- the expected tools calls as in the gold standardanswer- the LLM natural language answeragent_tools_calls- the actual tools calls by the LLM agentanswer_score- a real number between 0 and 1. It's calculated by comparing the results of the last tools calls, which are expected. If there is no match in the actual tools calls, then the score will be0. Otherwise, it's calculated as the number of the matched tools calls on the last step divided by the total tools calls from the last step.input_tokens- input tokens usageoutput_tokens- output tokens usagetotal_tokens- total tokens usageelapsed_sec- elapsed seconds
The aggregates object provides aggregated evaluation metrics.
Aggregations are computed both per-template and overall, using micro and macro averaging strategies.
These aggregations support analysis of agent quality, token efficiency, and execution performance.
Aggregations include:
per_template- a dictionary where each key is a template identifier. For each template, the following statistics are reported:number_of_error_samples- number of questions for this template, which resulted in error responsenumber_of_success_samples- number of questions for this template, which resulted in successful responseinput_tokens-sum,mean,median,minandmaxstatistics forinput_tokensof all successful questions for this templateoutput_tokens-sum,mean,median,minandmaxstatistics foroutput_tokensof all successful questions for this templatetotal_tokens-sum,mean,median,minandmaxstatistics fortotal_tokensof all successful questions for this templateelapsed_sec-sum,mean,median,minandmaxstatistics forelapsed_secof all successful questions for this templateanswer_score-sum,mean,median,minandmaxstatistics foranswer_scoreof all successful questions for this templatetools_calls- statistics for thetools_callsfor of all successful questions for this template. Includes:total_calls- for each tool how many times it was calledonce_per_sample- how many times each tool was called, but counted only once per questionempty_results- how many times the tool was called, but it returned empty resultserror_calls- how many times the tool was called and this resulted in error
micro- micro gives overall aggregate statistics across questions, treating each equally. It includes:number_of_error_samples- total number of questions, which resulted in error responsenumber_of_success_samples- total number of questions, which resulted in successful responseinput_tokens-sum,mean,median,minandmaxstatistics forinput_tokensof all successful questionsoutput_tokens-sum,mean,median,minandmaxstatistics foroutput_tokensof all successful questionstotal_tokens-sum,mean,median,minandmaxstatistics fortotal_tokensof all successful questionselapsed_sec-sum,mean,median,minandmaxstatistics forelapsed_secof all successful questionsanswer_score-sum,mean,median,minandmaxstatistics foranswer_scoreof all successful questions
macro- macro gives averages across templates, i.e., it computes the mean of each metric per template, then averages those means. It includes:input_tokens-meanforinput_tokensoutput_tokens-meanforoutput_tokenstotal_tokens-meanfortotal_tokenselapsed_sec-meanforelapsed_secanswer_score-meanforanswer_score
Example aggregations:
{
"per_template": {
"list_all_transformers_within_Substation_SUBSTATION": {
"number_of_error_samples": 0,
"number_of_success_samples": 10,
"tools_calls": {
"total_calls": {
"autocomplete_search": 10,
"sparql_query": 8
},
"once_per_sample": {
"autocomplete_search": 10,
"sparql_query": 8
},
"empty_results": {
"autocomplete_search": 2
}
},
"answer_score": {
"sum": 8.0,
"mean": 0.8,
"median": 1.0,
"min": 0.0,
"max": 1.0
},
"input_tokens": {
"sum": 2064559,
"mean": 206455.9,
"median": 221263.5,
"min": 147171,
"max": 221339
},
"output_tokens": {
"sum": 1555,
"mean": 155.5,
"median": 177.0,
"min": 46,
"max": 212
},
"total_tokens": {
"sum": 2066114,
"mean": 206611.4,
"median": 221439.5,
"min": 147217,
"max": 221551
},
"elapsed_sec": {
"sum": 259.2278094291687,
"mean": 25.92278094291687,
"median": 9.677194952964783,
"min": 5.529741525650024,
"max": 55.4010910987854
}
},
"list_all_substations_within_bidding_zone_REGION": {
"number_of_error_samples": 0,
"number_of_success_samples": 10,
"tools_calls": {
"total_calls": {
"autocomplete_search": 10
},
"once_per_sample": {
"autocomplete_search": 10
},
"empty_results": {
"autocomplete_search": 10
}
},
"answer_score": {
"sum": 0.0,
"mean": 0.0,
"median": 0.0,
"min": 0.0,
"max": 0.0
},
"input_tokens": {
"sum": 1471880,
"mean": 147188,
"median": 147188.0,
"min": 147188,
"max": 147188
},
"output_tokens": {
"sum": 571,
"mean": 57.1,
"median": 57.0,
"min": 56,
"max": 61
},
"total_tokens": {
"sum": 1472451,
"mean": 147245.1,
"median": 147245.0,
"min": 147244,
"max": 147249
},
"elapsed_sec": {
"sum": 185.5483124256134,
"mean": 18.55483124256134,
"median": 8.886059165000916,
"min": 2.8653159141540527,
"max": 47.51542258262634
}
},
"list_all_substations_that_are_connected_via_an_ac_line_or_a_dc_line_to_substation_named_SUBSTATION": {
"number_of_error_samples": 1,
"number_of_success_samples": 9,
"tools_calls": {
"total_calls": {
"autocomplete_search": 9,
"sparql_query": 17
},
"once_per_sample": {
"autocomplete_search": 9,
"sparql_query": 9
},
"error_calls": {
"sparql_query": 8
}
},
"answer_score": {
"sum": 9.0,
"mean": 1.0,
"median": 1.0,
"min": 1.0,
"max": 1.0
},
"input_tokens": {
"sum": 2601595,
"mean": 289066.1111111111,
"median": 297059,
"min": 222528,
"max": 298028
},
"output_tokens": {
"sum": 6066,
"mean": 674,
"median": 700,
"min": 363,
"max": 805
},
"total_tokens": {
"sum": 2607661,
"mean": 289740.1111111111,
"median": 297759,
"min": 222891,
"max": 298787
},
"elapsed_sec": {
"sum": 354.82168316841125,
"mean": 39.42463146315681,
"median": 41.88556528091431,
"min": 26.418761014938354,
"max": 52.42662525177002
}
},
"list_all_ac_lines_that_traverse_bidding_zones_REGION1_and_REGION2": {
"number_of_error_samples": 0,
"number_of_success_samples": 10,
"tools_calls": {
"total_calls": {
"autocomplete_search": 20
},
"once_per_sample": {
"autocomplete_search": 10
},
"empty_results": {
"autocomplete_search": 20
}
},
"answer_score": {
"sum": 0.0,
"mean": 0.0,
"median": 0.0,
"min": 0.0,
"max": 0.0
},
"input_tokens": {
"sum": 1472540,
"mean": 147254,
"median": 147254.0,
"min": 147254,
"max": 147254
},
"output_tokens": {
"sum": 1052,
"mean": 105.2,
"median": 105.0,
"min": 105,
"max": 107
},
"total_tokens": {
"sum": 1473592,
"mean": 147359.2,
"median": 147359.0,
"min": 147359,
"max": 147361
},
"elapsed_sec": {
"sum": 197.44370341300964,
"mean": 19.744370341300964,
"median": 18.030158162117004,
"min": 15.56333041191101,
"max": 26.422670125961304
}
}
},
"micro": {
"number_of_error_samples": 1,
"number_of_success_samples": 39,
"answer_score": {
"sum": 17.0,
"mean": 0.4358974358974359,
"median": 0.0,
"min": 0.0,
"max": 1.0
},
"input_tokens": {
"sum": 7610574,
"mean": 195142.92307692306,
"median": 147254,
"min": 147171,
"max": 298028
},
"output_tokens": {
"sum": 9244,
"mean": 237.02564102564102,
"median": 105,
"min": 46,
"max": 805
},
"total_tokens": {
"sum": 7619818,
"mean": 195379.94871794872,
"median": 147359,
"min": 147217,
"max": 298787
},
"elapsed_sec": {
"sum": 997.041508436203,
"mean": 25.565166882979565,
"median": 18.32871961593628,
"min": 2.8653159141540527,
"max": 55.4010910987854
}
},
"macro": {
"answer_score": {
"mean": 0.45
},
"input_tokens": {
"mean": 197491.0027777778
},
"output_tokens": {
"mean": 247.95
},
"total_tokens": {
"mean": 197738.9527777778
},
"elapsed_sec": {
"mean": 25.911653497483996
}
}
}
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