arcade-mcp/toolkits/mongodb/evals/eval_mongodb.py
2025-09-12 18:41:23 -07:00

190 lines
5.9 KiB
Python

# RUN ME WITH `uv run arcade evals evals --host api.arcade.dev`
import arcade_mongodb
from arcade_evals import (
BinaryCritic,
EvalRubric,
EvalSuite,
ExpectedToolCall,
SimilarityCritic,
tool_eval,
)
from arcade_mongodb.tools.mongodb import (
aggregate_documents,
count_documents,
discover_collections,
discover_databases,
find_documents,
get_collection_schema,
)
from arcade_tdk import ToolCatalog
# Evaluation rubric
rubric = EvalRubric(
fail_threshold=0.85,
warn_threshold=0.95,
)
catalog = ToolCatalog()
catalog.add_module(arcade_mongodb)
@tool_eval()
def mongodb_eval_suite() -> EvalSuite:
suite = EvalSuite(
name="MongoDB Tools Evaluation",
system_message=(
"You are an AI assistant with access to MongoDB tools. "
"Use them to help the user with their tasks."
),
catalog=catalog,
rubric=rubric,
)
suite.add_case(
name="Discover databases",
user_message="What databases are available in my MongoDB instance?",
expected_tool_calls=[
ExpectedToolCall(func=discover_databases, args={}),
],
rubric=rubric,
)
suite.add_case(
name="Discover collections",
user_message="What collections are in the 'admin' database?",
expected_tool_calls=[
ExpectedToolCall(func=discover_collections, args={"database_name": "admin"}),
],
rubric=rubric,
critics=[
BinaryCritic(critic_field="database_name", weight=1.0),
],
)
suite.add_case(
name="Get collection schema (single tool call)",
user_message="Get the schema of the 'system.users' collection in the 'admin' database.",
expected_tool_calls=[
ExpectedToolCall(
func=get_collection_schema,
args={"database_name": "admin", "collection_name": "system.users"},
),
],
rubric=rubric,
critics=[
BinaryCritic(critic_field="database_name", weight=0.5),
BinaryCritic(critic_field="collection_name", weight=0.5),
],
)
suite.add_case(
name="Find documents (direct call)",
user_message="Find documents in the 'startup_log' collection of the 'local' database, limited to 5 results.",
additional_messages=[
{
"role": "user",
"content": "You can call find_documents directly without discovering collections first for this test.",
}
],
expected_tool_calls=[
ExpectedToolCall(
func=find_documents,
args={
"database_name": "local",
"collection_name": "startup_log",
"limit": 5,
},
),
],
rubric=rubric,
critics=[
BinaryCritic(critic_field="database_name", weight=0.33),
BinaryCritic(critic_field="collection_name", weight=0.33),
BinaryCritic(critic_field="limit", weight=0.34),
],
)
suite.add_case(
name="Count documents",
user_message="Count all documents in the 'startup_log' collection of the 'local' database.",
additional_messages=[
{
"role": "user",
"content": "You can call count_documents directly without discovering collections first for this test.",
}
],
expected_tool_calls=[
ExpectedToolCall(
func=count_documents,
args={
"database_name": "local",
"collection_name": "startup_log",
},
),
],
rubric=rubric,
critics=[
BinaryCritic(critic_field="database_name", weight=0.5),
BinaryCritic(critic_field="collection_name", weight=0.5),
],
)
suite.add_case(
name="Count documents with filter",
user_message="Count documents in the 'startup_log' collection of the 'local' database where the level is 'INFO'.",
additional_messages=[
{
"role": "user",
"content": "You can call count_documents directly without discovering collections first for this test.",
}
],
expected_tool_calls=[
ExpectedToolCall(
func=count_documents,
args={
"database_name": "local",
"collection_name": "startup_log",
"filter_dict": '{"level": "INFO"}',
},
),
],
rubric=rubric,
critics=[
BinaryCritic(critic_field="database_name", weight=0.25),
BinaryCritic(critic_field="collection_name", weight=0.25),
SimilarityCritic(critic_field="filter_dict", weight=0.5),
],
)
suite.add_case(
name="Aggregate documents",
user_message="Group documents in the 'startup_log' collection of the 'local' database by level and count them.",
additional_messages=[
{
"role": "user",
"content": "You can call aggregate_documents directly without discovering collections first for this test.",
}
],
expected_tool_calls=[
ExpectedToolCall(
func=aggregate_documents,
args={
"database_name": "local",
"collection_name": "startup_log",
"pipeline": [
'{"$group": {"_id": "$level", "count": {"$sum": 1}}}',
],
},
),
],
rubric=rubric,
critics=[
BinaryCritic(critic_field="database_name", weight=0.2),
BinaryCritic(critic_field="collection_name", weight=0.2),
SimilarityCritic(critic_field="pipeline", weight=0.6),
],
)
return suite