Design System: https://github.com/ArcadeAI/Design-System/pull/31 Docs: https://github.com/ArcadeAI/docs/pull/439 <img width="832" height="797" alt="Screenshot 2025-09-11 at 2 35 36 PM" src="https://github.com/user-attachments/assets/198f194f-d41c-41a0-bedf-b77bccd70dfa" />
190 lines
5.9 KiB
Python
190 lines
5.9 KiB
Python
# RUN ME WITH `uv run arcade evals evals --host api.arcade.dev`
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import arcade_mongodb
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from arcade_evals import (
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BinaryCritic,
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EvalRubric,
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EvalSuite,
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ExpectedToolCall,
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SimilarityCritic,
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tool_eval,
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)
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from arcade_mongodb.tools.mongodb import (
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aggregate_documents,
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count_documents,
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discover_collections,
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discover_databases,
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find_documents,
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get_collection_schema,
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)
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from arcade_tdk import ToolCatalog
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# Evaluation rubric
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rubric = EvalRubric(
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fail_threshold=0.85,
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warn_threshold=0.95,
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)
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catalog = ToolCatalog()
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catalog.add_module(arcade_mongodb)
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@tool_eval()
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def mongodb_eval_suite() -> EvalSuite:
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suite = EvalSuite(
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name="MongoDB Tools Evaluation",
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system_message=(
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"You are an AI assistant with access to MongoDB tools. "
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"Use them to help the user with their tasks."
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),
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catalog=catalog,
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rubric=rubric,
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)
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suite.add_case(
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name="Discover databases",
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user_message="What databases are available in my MongoDB instance?",
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expected_tool_calls=[
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ExpectedToolCall(func=discover_databases, args={}),
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],
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rubric=rubric,
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)
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suite.add_case(
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name="Discover collections",
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user_message="What collections are in the 'admin' database?",
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expected_tool_calls=[
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ExpectedToolCall(func=discover_collections, args={"database_name": "admin"}),
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],
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rubric=rubric,
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critics=[
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BinaryCritic(critic_field="database_name", weight=1.0),
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],
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)
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suite.add_case(
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name="Get collection schema (single tool call)",
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user_message="Get the schema of the 'system.users' collection in the 'admin' database.",
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expected_tool_calls=[
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ExpectedToolCall(
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func=get_collection_schema,
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args={"database_name": "admin", "collection_name": "system.users"},
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),
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],
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rubric=rubric,
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critics=[
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BinaryCritic(critic_field="database_name", weight=0.5),
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BinaryCritic(critic_field="collection_name", weight=0.5),
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],
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)
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suite.add_case(
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name="Find documents (direct call)",
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user_message="Find documents in the 'startup_log' collection of the 'local' database, limited to 5 results.",
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additional_messages=[
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{
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"role": "user",
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"content": "You can call find_documents directly without discovering collections first for this test.",
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}
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],
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expected_tool_calls=[
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ExpectedToolCall(
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func=find_documents,
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args={
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"database_name": "local",
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"collection_name": "startup_log",
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"limit": 5,
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},
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),
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],
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rubric=rubric,
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critics=[
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BinaryCritic(critic_field="database_name", weight=0.33),
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BinaryCritic(critic_field="collection_name", weight=0.33),
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BinaryCritic(critic_field="limit", weight=0.34),
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],
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)
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suite.add_case(
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name="Count documents",
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user_message="Count all documents in the 'startup_log' collection of the 'local' database.",
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additional_messages=[
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{
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"role": "user",
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"content": "You can call count_documents directly without discovering collections first for this test.",
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}
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],
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expected_tool_calls=[
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ExpectedToolCall(
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func=count_documents,
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args={
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"database_name": "local",
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"collection_name": "startup_log",
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},
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),
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],
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rubric=rubric,
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critics=[
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BinaryCritic(critic_field="database_name", weight=0.5),
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BinaryCritic(critic_field="collection_name", weight=0.5),
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],
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)
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suite.add_case(
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name="Count documents with filter",
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user_message="Count documents in the 'startup_log' collection of the 'local' database where the level is 'INFO'.",
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additional_messages=[
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{
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"role": "user",
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"content": "You can call count_documents directly without discovering collections first for this test.",
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}
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],
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expected_tool_calls=[
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ExpectedToolCall(
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func=count_documents,
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args={
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"database_name": "local",
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"collection_name": "startup_log",
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"filter_dict": '{"level": "INFO"}',
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},
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),
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],
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rubric=rubric,
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critics=[
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BinaryCritic(critic_field="database_name", weight=0.25),
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BinaryCritic(critic_field="collection_name", weight=0.25),
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SimilarityCritic(critic_field="filter_dict", weight=0.5),
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],
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)
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suite.add_case(
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name="Aggregate documents",
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user_message="Group documents in the 'startup_log' collection of the 'local' database by level and count them.",
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additional_messages=[
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{
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"role": "user",
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"content": "You can call aggregate_documents directly without discovering collections first for this test.",
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}
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],
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expected_tool_calls=[
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ExpectedToolCall(
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func=aggregate_documents,
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args={
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"database_name": "local",
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"collection_name": "startup_log",
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"pipeline": [
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'{"$group": {"_id": "$level", "count": {"$sum": 1}}}',
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],
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},
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),
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],
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rubric=rubric,
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critics=[
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BinaryCritic(critic_field="database_name", weight=0.2),
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BinaryCritic(critic_field="collection_name", weight=0.2),
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SimilarityCritic(critic_field="pipeline", weight=0.6),
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],
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)
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return suite
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