fix(evals): Add agent evaluators to made by traceloop #3505
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Note Other AI code review bot(s) detectedCodeRabbit has detected other AI code review bot(s) in this pull request and will avoid duplicating their findings in the review comments. This may lead to a less comprehensive review. WalkthroughAdds synonym-based field mapping and normalization used before evaluator validation, renames validator to return normalized output, adds many new "made by traceloop" evaluator factories, introduces a sample agents experiment demo and a travel-agent example, and updates tests to cover mappings and validator behavior. Changes
Sequence Diagram(s)sequenceDiagram
autonumber
participant AgentDemo as AgentDemo (sample_app)
participant OpenAI as AsyncOpenAI
participant Normalizer as FieldMapping.normalize_task_output
participant Traceloop as Traceloop Client
participant Evaluators as EvaluatorMadeByTraceloop
participant Experiment as Experiment.run
AgentDemo->>OpenAI: generate_agent_trace(task_description)
OpenAI-->>AgentDemo: trace (prompt, completion, tools, etc.)
AgentDemo->>Normalizer: normalize_task_output(trace, required_fields)
Normalizer-->>AgentDemo: normalized_task_output
AgentDemo->>Traceloop: build experiment payload (evaluators list)
Traceloop->>Evaluators: instantiate evaluators (required_input_fields)
AgentDemo->>Experiment: client.experiment.run(dataset_slug, payload)
Experiment-->>Traceloop: dispatch to evaluators
Evaluators-->>Experiment: evaluations/results
Experiment-->>AgentDemo: aggregated results & errors
Estimated code review effort🎯 4 (Complex) | ⏱️ ~45 minutes
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Pre-merge checks and finishing touches❌ Failed checks (1 warning)
✅ Passed checks (4 passed)
✨ Finishing touches
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1. packages/sample-app/sample_app/experiment/made_by_traceloop/agents_exp.py:29
- Draft comment:
Consider verifying that OPENAI_API_KEY is set to avoid runtime errors. - Reason this comment was not posted:
Comment did not seem useful. Confidence is useful =20%<= threshold50%The comment suggests verifying that an environment variable is set, which is a general suggestion to avoid runtime errors. It doesn't provide a specific code suggestion or ask for a specific test to be written. It falls under the category of asking the author to ensure something is done, which is against the rules.
2. packages/sample-app/sample_app/experiment/made_by_traceloop/agents_exp.py:32
- Draft comment:
Consider adding error handling around the OpenAI API call to handle potential failures. - Reason this comment was not posted:
Decided after close inspection that this draft comment was likely wrong and/or not actionable: usefulness confidence = 20% vs. threshold = 50% This comment is suggesting a code quality improvement (adding error handling) rather than identifying a specific bug. While error handling is generally good practice, the rules state that I should not comment on things that are "obvious" and that comments should only be made when "there is clearly a code change required." This is more of a suggestion for defensive programming. Additionally, this is sample/example code in an experimental file, where error handling might be intentionally omitted for clarity. The comment doesn't point to a specific failure case or bug - it's generic advice. According to the rules, "Comments that suggest code quality refactors are good! But only if they are actionable and clear" - while this is actionable, it's also quite generic and could apply to almost any API call. The rules emphasize that I should only keep comments with "STRONG EVIDENCE that the comment is correct" and by default assume comments are incorrect or not useful. This could be legitimate advice since API calls can fail for various reasons (network issues, rate limits, authentication failures, etc.), and the lack of error handling could cause the entire experiment to crash. In production code, this would definitely be important. The comment is actionable and clear about what needs to be done. While error handling is important in production code, this is explicitly sample/example code in an experimental file. The rules state not to make comments that are "obvious" - and adding error handling to API calls is fairly obvious best practice. More importantly, the experiment framework itself hasstop_on_error=Falseat line 159, suggesting the framework handles errors at a higher level. The comment is generic advice rather than identifying a specific problem with the code change. This comment should be deleted. It's generic advice about error handling that could apply to any API call, rather than identifying a specific issue with the code. This is sample/example code where such details might be intentionally simplified, and the suggestion falls under "obvious" best practices rather than a clear code change requirement.
3. packages/traceloop-sdk/tests/evaluator/test_evaluator.py:50
- Draft comment:
Great tests! The error messages properly include required field names and synonym suggestions. - Reason this comment was not posted:
Comment did not seem useful. Confidence is useful =0%<= threshold50%This comment is purely informative and does not provide any actionable feedback or suggestions for improvement. It simply states that the error messages include required field names and synonym suggestions, which does not align with the rules for useful comments.
4. packages/traceloop-sdk/tests/evaluator/test_field_mapping.py:10
- Draft comment:
Comprehensive test coverage for synonym mapping and normalization. Consider adding additional edge cases if necessary. - Reason this comment was not posted:
Comment looked like it was already resolved.
5. packages/traceloop-sdk/experiment/experiment.py:447
- Draft comment:
Consider logging a warning when skipping invalid JSON lines in _parse_jsonl_to_rows to help diagnose data issues. - Reason this comment was not posted:
Comment was not on a location in the diff, so it can't be submitted as a review comment.
6. packages/traceloop-sdk/traceloop/sdk/evaluator/evaluator.py:149
- Draft comment:
The validate_and_normalize_task_output function effectively integrates synonym mapping and provides detailed error messages. Nice work! - Reason this comment was not posted:
Comment did not seem useful. Confidence is useful =0%<= threshold50%This comment is purely informative and does not provide any actionable feedback or suggestions for improvement. It simply praises the function without offering any specific guidance or questions.
7. packages/traceloop-sdk/traceloop/sdk/evaluator/evaluators_made_by_traceloop.py:243
- Draft comment:
Docstring update for word_count_ratio improves clarity. The configuration details are well documented. - Reason this comment was not posted:
Comment was not on a location in the diff, so it can't be submitted as a review comment.
8. packages/traceloop-sdk/traceloop/sdk/evaluator/field_mapping.py:162
- Draft comment:
The normalization logic is clear; consider documenting that an exact match is prioritized over synonyms. - Reason this comment was not posted:
Comment looked like it was already resolved.
9. packages/traceloop-sdk/traceloop/sdk/experiment/experiment.py:230
- Draft comment:
Using asyncio.Semaphore(50) is good for concurrency control; consider making the concurrency limit configurable for scalability. - Reason this comment was not posted:
Comment was not on a location in the diff, so it can't be submitted as a review comment.
10. packages/traceloop-sdk/traceloop/sdk/experiment/experiment.py:169
- Draft comment:
Integrating task output normalization using validate_and_normalize_task_output enhances consistency. Good design choice. - Reason this comment was not posted:
Comment did not seem useful. Confidence is useful =0%<= threshold50%This comment is purely informative and does not provide any actionable feedback or suggestions for improvement. It simply states that a change enhances consistency, which is not useful for the PR author.
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Actionable comments posted: 2
🧹 Nitpick comments (2)
packages/traceloop-sdk/tests/evaluator/test_evaluator.py (1)
6-7: Minor: Class docstring still references old function name.The docstring says "Tests for validate_task_output function" but the tests now use
validate_and_normalize_task_output.class TestValidateTaskOutput: - """Tests for validate_task_output function""" + """Tests for validate_and_normalize_task_output function"""packages/sample-app/sample_app/experiment/made_by_traceloop/agents_exp.py (1)
20-21: Consider deferringTraceloop.init()to avoid side effects on import.Module-level initialization can cause unintended side effects when the module is imported but not executed. Consider moving the initialization inside
run_agents_experiment().-# Initialize Traceloop -client = Traceloop.init() +# Client will be initialized when running the experiment +client = None async def generate_agent_trace(task_description: str) -> dict:Then in
run_agents_experiment():async def run_agents_experiment(): global client if client is None: client = Traceloop.init() # ... rest of function
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packages/sample-app/sample_app/experiment/made_by_traceloop/agents_exp.py(1 hunks)packages/traceloop-sdk/tests/evaluator/test_evaluator.py(14 hunks)packages/traceloop-sdk/tests/evaluator/test_field_mapping.py(1 hunks)packages/traceloop-sdk/tests/experiment/test_experiment.py(3 hunks)packages/traceloop-sdk/traceloop/sdk/evaluator/evaluator.py(4 hunks)packages/traceloop-sdk/traceloop/sdk/evaluator/evaluators_made_by_traceloop.py(1 hunks)packages/traceloop-sdk/traceloop/sdk/evaluator/field_mapping.py(1 hunks)packages/traceloop-sdk/traceloop/sdk/experiment/experiment.py(3 hunks)
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packages/traceloop-sdk/tests/evaluator/test_field_mapping.py (3)
packages/traceloop-sdk/traceloop/sdk/evaluator/field_mapping.py (4)
get_synonyms(52-63)normalize_task_output(66-126)get_field_suggestions(129-149)format_field_help(152-167)packages/traceloop-sdk/traceloop/sdk/evaluator/evaluator.py (1)
validate_and_normalize_task_output(149-218)packages/traceloop-sdk/traceloop/sdk/evaluator/config.py (1)
EvaluatorDetails(5-23)
packages/traceloop-sdk/traceloop/sdk/evaluator/evaluator.py (2)
packages/traceloop-sdk/traceloop/sdk/evaluator/field_mapping.py (3)
normalize_task_output(66-126)get_field_suggestions(129-149)format_field_help(152-167)packages/traceloop-sdk/traceloop/sdk/evaluator/config.py (1)
EvaluatorDetails(5-23)
packages/traceloop-sdk/tests/evaluator/test_evaluator.py (1)
packages/traceloop-sdk/traceloop/sdk/evaluator/evaluator.py (1)
validate_and_normalize_task_output(149-218)
packages/traceloop-sdk/traceloop/sdk/experiment/experiment.py (1)
packages/traceloop-sdk/traceloop/sdk/evaluator/evaluator.py (2)
Evaluator(16-146)validate_and_normalize_task_output(149-218)
packages/traceloop-sdk/traceloop/sdk/evaluator/evaluators_made_by_traceloop.py (1)
packages/traceloop-sdk/traceloop/sdk/evaluator/config.py (1)
EvaluatorDetails(5-23)
🔇 Additional comments (41)
packages/traceloop-sdk/traceloop/sdk/evaluator/evaluators_made_by_traceloop.py (13)
243-243: Minor docstring fix looks good.The docstring now correctly documents both required fields (
numerator_textanddenominator_text) for theword_count_ratioevaluator.
456-478: Newanswer_completenessevaluator looks good.The implementation follows the established pattern with appropriate required fields (
question,completion,context).
480-499: Newprompt_perplexityevaluator looks good.Follows the established pattern with the required
promptfield.
501-522: Newanswer_correctnessevaluator looks good.Implementation is consistent with the required fields (
question,completion,ground_truth).
524-543: Newuncertainty_detectorevaluator looks good.Appropriately requires only the
promptfield.
545-565: Newagent_tool_error_detectorevaluator looks good.Required fields (
tool_input,tool_output) are appropriate for detecting tool execution errors.
567-587: Newagent_flow_qualityevaluator looks good.Uses trajectory fields (
trajectory_prompts,trajectory_completions) as documented.
589-609: Newagent_efficiencyevaluator looks good.Consistent with other trajectory-based evaluators using the same required fields.
611-631: Newagent_goal_completenessevaluator looks good.Uses trajectory fields consistently with other agent evaluators.
633-653: Newinstruction_adherenceevaluator looks good.Required fields (
instructions,response) are appropriate for evaluating instruction following.
655-676: Newconversation_qualityevaluator looks good.Required fields (
prompts,completions) are appropriate for conversation evaluation.
678-699: Newintent_changeevaluator looks good.Uses the same conversation fields (
prompts,completions) consistently.
701-720: Newtone_detectionevaluator looks good.Requires only
textfield, consistent with other text-analysis evaluators.packages/traceloop-sdk/tests/experiment/test_experiment.py (3)
168-169: Test assertions updated correctly for new error message format.The split assertions (
"pii-detector requires:"and"'text'"separately) correctly accommodate the new multi-line error format fromvalidate_and_normalize_task_output.
215-216: Consistent with the assertion pattern change above.
315-320: Helpful inline comment explaining synonym mapping behavior.The comment clarifies that
'text'maps to'response'via synonym mapping, so only'prompt'remains missing. This makes the test's expected behavior clear for future maintainers.packages/traceloop-sdk/tests/evaluator/test_evaluator.py (3)
2-2: Import correctly updated tovalidate_and_normalize_task_output.
15-15: All function calls correctly updated.All invocations of the validation function have been updated to use
validate_and_normalize_task_output.Also applies to: 26-26, 40-40, 50-50, 73-73, 94-94, 116-116, 131-131, 150-150, 160-160, 180-180, 196-196, 218-218
54-55: Assertions correctly adapted for new multi-line error format.The split assertions properly verify both the evaluator slug and the missing field name are present in the error message.
Also applies to: 163-164, 200-201
packages/traceloop-sdk/traceloop/sdk/experiment/experiment.py (3)
8-8: Import correctly updated tovalidate_and_normalize_task_output.
169-171: Correct usage of normalized task output.The normalized
task_resultis now properly assigned and used downstream for task creation and evaluator execution. The comment accurately describes the behavior.
484-487: Consistent normalization in_execute_tasks.The same normalization pattern is correctly applied in the GitHub execution path, ensuring consistent behavior across both local and GitHub execution modes.
packages/traceloop-sdk/tests/evaluator/test_field_mapping.py (6)
1-7: Well-organized test imports and structure.Clean imports of the field mapping functions under test.
10-75: Comprehensive tests forget_synonyms.Good coverage including:
- Different field categories (text, question, reference, trajectory)
- Non-synonym and unknown fields returning single-element sets
- Symmetry verification ensuring all synonyms in a group map to the same set
77-239: Thorough tests fornormalize_task_output.Excellent coverage of normalization scenarios:
- Various synonym mappings (text→completion, prompt→question, etc.)
- Multiple fields normalization
- Preservation of extra fields
- Empty input handling
- Priority of exact matches over synonyms
- Mixed synonym and non-synonym fields
242-296: Good tests forget_field_suggestions.Covers key scenarios: single suggestions, multiple synonyms available, no suggestions, and empty available fields.
299-323: Tests forformat_field_helplook good.Verifies both fields with and without synonyms are formatted correctly.
326-411: Valuable integration tests withvalidate_and_normalize_task_output.End-to-end tests verify the complete flow including:
- Synonym mapping during validation
- Helpful error messages with synonym information
- Context→reference mapping
- Trajectory field mappings for agent evaluators
packages/traceloop-sdk/traceloop/sdk/evaluator/evaluator.py (5)
3-3: Clean import of field mapping utilities.The imports are appropriately scoped to only the needed functions.
149-168: Well-documented function signature and docstring.The renamed function clearly communicates its dual purpose (validation and normalization). The docstring accurately describes the return value and exception behavior.
170-177: Clean normalization flow.Collecting all required fields and normalizing in a single pass is efficient. The normalized output is then used for validation, ensuring synonyms are properly resolved before checking for missing fields.
179-195: Validation logic correctly checks normalized output.The validation now operates on
normalized_outputinstead of the rawtask_output, ensuring that synonym-mapped fields are recognized as present.
197-218: Enhanced error reporting with helpful suggestions.The error messages now include:
- Per-evaluator breakdown of missing fields
- Synonym information via
format_field_help- Suggestions via
get_field_suggestions- Helpful hint about using synonyms
This significantly improves the developer experience when debugging validation failures.
packages/sample-app/sample_app/experiment/made_by_traceloop/agents_exp.py (5)
1-12: Clear and informative module docstring.The docstring provides a good overview of the five agent evaluators being demonstrated.
29-29: Good security practice: API key accessed via environment variable.Using
os.getenv("OPENAI_API_KEY")follows the coding guidelines for not hardcoding secrets.
52-109: Excellent documentation of field synonym mapping.The detailed docstring explaining synonym mappings is very helpful for users learning the SDK. The task function demonstrates practical usage of synonyms.
153-155: Hardcoded dataset slug requires user action.The comment on line 154 explains the user needs to create a matching dataset, which is appropriate for a sample app. Consider adding this to the README or top-level docstring as well.
137-143: Clean evaluator configuration demonstrating all 5 agent evaluators.The evaluator setup clearly shows usage of the new factory methods.
packages/traceloop-sdk/traceloop/sdk/evaluator/field_mapping.py (3)
52-63: LGTM!The function correctly returns all synonyms for a given field, with appropriate fallback behavior when the field has no defined synonyms.
129-149: LGTM!The synonym-based field suggestion logic is correct and efficient. The use of set intersection to identify synonym overlap is appropriate.
152-167: LGTM!The help formatting logic correctly handles both single fields and fields with synonyms. Good use of
sorted()on line 166 to ensure consistent output.
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1. packages/traceloop-sdk/tests/evaluator/test_field_mapping.py:28
- Draft comment:
Updated test for 'question' now checks for the 'query' synonym and expects 4 items. This aligns with the updated synonym mapping. - Reason this comment was not posted:
Comment did not seem useful. Confidence is useful =0%<= threshold50%This comment is purely informative, explaining what was changed in the test. It doesn't provide any suggestions or raise any issues that need to be addressed. According to the rules, purely informative comments should be removed.
2. packages/traceloop-sdk/traceloop/sdk/evaluator/evaluators_made_by_traceloop.py:299
- Draft comment:
New 'context_relevance' evaluator added with required fields ['query', 'context']. Looks consistent; ensure documentation reflects the new evaluator. - Reason this comment was not posted:
Comment did not seem useful. Confidence is useful =0%<= threshold50%The comment is asking to ensure that documentation reflects a new feature. This is a request for confirmation and does not provide a specific code suggestion or ask for a test to be written. It violates the rule against asking the PR author to ensure something is done.
3. packages/traceloop-sdk/traceloop/sdk/evaluator/evaluators_made_by_traceloop.py:477
- Draft comment:
Removed 'prompt_perplexity' evaluator. Confirm that this renaming (to 'perplexity') is intentional and that any external references or documentation have been updated accordingly. - Reason this comment was not posted:
Comment was not on a location in the diff, so it can't be submitted as a review comment.
4. packages/traceloop-sdk/traceloop/sdk/evaluator/field_mapping.py:21
- Draft comment:
The input/question synonym group now includes 'query'—this change is consistent with evaluator updates. Ensure all related docs/tests are in sync. - Reason this comment was not posted:
Comment did not seem useful. Confidence is useful =0%<= threshold50%The comment is asking the PR author to ensure that all related documentation and tests are in sync with the change. This falls under the rule of not asking the author to ensure things are tested or documented, which is not allowed.
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Actionable comments posted: 1
♻️ Duplicate comments (2)
packages/traceloop-sdk/traceloop/sdk/evaluator/field_mapping.py (2)
11-28: Clarify/remove “canonical form” wording for unordered synonym groups.SYNONYM_GROUPS are sets, so there is no stable “first field” or canonical element. The comment on Line 12 is misleading and may confuse future maintainers. Either drop the canonical-form claim or switch to an ordered type (e.g., tuple/list) if you truly need a canonical element.
97-119: Make synonym selection deterministic when multiple synonyms are present.The loop over
synonyms(a set) means that when the task output contains multiple synonyms for a required field (e.g., both"answer"and"response"for"completion"), which one is chosen is effectively random across runs/Python versions. This can yield inconsistent normalized outputs.Make the selection ordered, for example:
- Sort before iterating:
for synonym in sorted(synonyms): ..., or- Define SYNONYM_GROUPS as ordered (e.g., tuples with canonical-first) and iterate that sequence.
Your test for preferring an exact match already covers one important case; this change will make the remaining cases deterministic as well.
🧹 Nitpick comments (3)
packages/traceloop-sdk/traceloop/sdk/evaluator/evaluators_made_by_traceloop.py (2)
241-243: Minor docstring indentation inconsistency.Line 242 has 11 leading spaces while the modified line 243 has 10 leading spaces. Consider aligning them for consistency.
Required task output fields: - - numerator_text: The numerator text for ratio calculation - - denominator_text: The denominator text for ratio calculation + - numerator_text: The numerator text for ratio calculation + - denominator_text: The denominator text for ratio calculation
500-503: Remove extra blank line (PEP 8 E303).There are two consecutive blank lines between methods. PEP 8 recommends a maximum of two blank lines between top-level definitions, but only one blank line between method definitions inside a class.
return EvaluatorDetails( slug="answer-completeness", version=None, config=config, required_input_fields=["question", "completion", "context"], ) - @staticmethod def answer_correctness(packages/traceloop-sdk/traceloop/sdk/evaluator/field_mapping.py (1)
31-64: Avoid exposing and sharing mutable synonym sets across callers.
_build_synonym_mapstores each group set directly, andget_synonymsreturns that same set instance. Any caller that mutates the returned set will silently change_SYNONYM_MAP(and effectively SYNONYM_GROUPS) for the entire process.To make this safer, consider one of:
- Clone groups when building the map:
synonym_map[field] = set(group).- Or keep the current map but have
get_synonymsreturn a copy orfrozenset(synonyms).This keeps internal configuration immutable from the outside while preserving current behavior.
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packages/traceloop-sdk/tests/evaluator/test_field_mapping.py (3)
packages/traceloop-sdk/traceloop/sdk/evaluator/field_mapping.py (4)
get_synonyms(52-63)normalize_task_output(66-126)get_field_suggestions(129-149)format_field_help(152-167)packages/traceloop-sdk/traceloop/sdk/evaluator/evaluator.py (1)
validate_and_normalize_task_output(149-218)packages/traceloop-sdk/traceloop/sdk/evaluator/config.py (1)
EvaluatorDetails(5-23)
packages/traceloop-sdk/traceloop/sdk/evaluator/evaluators_made_by_traceloop.py (1)
packages/traceloop-sdk/traceloop/sdk/evaluator/config.py (1)
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🔇 Additional comments (3)
packages/traceloop-sdk/traceloop/sdk/evaluator/evaluators_made_by_traceloop.py (3)
302-322: LGTM!The
context_relevanceevaluator follows the established pattern with appropriate required fields (query,context) and clear documentation.
526-633: LGTM!The agent-focused evaluators (
uncertainty_detector,agent_tool_error_detector,agent_flow_quality,agent_efficiency,agent_goal_completeness) are well-structured with appropriate required input fields for their respective use cases. The trajectory-based evaluators consistently requiretrajectory_promptsandtrajectory_completions, which aligns with the PR's agent evaluation objectives.
635-722: LGTM!The remaining evaluators (
instruction_adherence,conversation_quality,intent_change,tone_detection) are well-implemented with clear documentation. The docstrings helpfully specify the expected data format for conversation-based evaluators (e.g., "flattened dict with llm.prompts.X.content/role").
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1. packages/sample-app/sample_app/agents/travel_agent_example.py:178
- Draft comment:
Consider using an asynchronous HTTP client (e.g., aiohttp) instead of blocking 'requests.get' calls in async functions to avoid blocking the event loop. - Reason this comment was not posted:
Decided after close inspection that this draft comment was likely wrong and/or not actionable: usefulness confidence = 30% vs. threshold = 50% This is a code quality/performance suggestion about using async HTTP clients in async functions. While technically correct that blocking calls in async functions can block the event loop, I need to consider: 1) This is a sample/demo app (in "sample-app" directory), 2) The author explicitly usedrequeststhroughout despite writing async code, suggesting a deliberate choice, 3) The comment is somewhat generic and doesn't point to a specific bug or broken functionality, 4) According to the rules, I should only keep comments with STRONG EVIDENCE of correctness and that require clear code changes. This feels more like a "nice to have" optimization rather than a critical issue. The code will work as-is, just not optimally from an async perspective. This could be a legitimate performance concern if the application is meant to handle concurrent requests efficiently. The blocking calls could indeed cause issues in a production async application. The comment is actionable (switch to aiohttp) and technically correct. Maybe I'm being too lenient by dismissing it as just a sample app issue. While the technical advice is sound, the rules state I should not keep comments unless there's STRONG EVIDENCE of incorrectness. This is more of a best practice/optimization suggestion rather than a bug. The code functions correctly as written. The author clearly made a deliberate choice to use synchronous requests (they imported requests, used it consistently throughout, and added asyncio.sleep calls showing async awareness). For a sample/demo app, this is acceptable. The comment doesn't point to broken functionality that would be caught as a bug. This is a valid best practice suggestion but not a critical issue. The code works correctly as written, and this appears to be a deliberate design choice in a sample application. The comment is more of a "nice to have" optimization rather than pointing to broken functionality. According to the rules requiring STRONG EVIDENCE of incorrectness, this should be deleted.
2. packages/sample-app/sample_app/agents/travel_agent_example.py:536
- Draft comment:
Verify if the OpenAI client call is non-blocking. If the client is synchronous, consider using an async client or running it in an executor. - Reason this comment was not posted:
Decided after close inspection that this draft comment was likely wrong and/or not actionable: usefulness confidence = 10% vs. threshold = 50% The comment raises a valid concern about using a synchronous OpenAI client in an async function. However, there are several issues: 1) The comment is placed on the client instantiation line (536) rather than the actual API call line (561), 2) The comment uses weak language like "Verify if..." which violates the rule against asking the author to confirm things, 3) Looking at the actual usage at line 561,client.beta.chat.completions.parse()is indeed a synchronous call that could block the event loop. While the underlying concern is valid (synchronous API calls in async functions are problematic), the comment's phrasing ("Verify if...") makes it non-actionable and speculative rather than definitive. The underlying technical concern is legitimate - using synchronous OpenAI client methods in an async function can block the event loop. However, the comment violates the rule against asking authors to "verify" or "ensure" things. It should either definitively state the problem and suggest a fix, or not be made at all. While the technical concern is valid, the comment explicitly violates the rules by starting with "Verify if..." which is a pattern we're told to reject. The rules state: "Do NOT ask the PR author to confirm their intention, to explain, to double-check things, to ensure the behavior is intended... If the comments starts with 'Verify that...' or 'Ensure that...', it is likely not useful." This comment should be deleted based on its phrasing alone. Delete this comment. It violates the rule against asking authors to "verify" things. Even though there's a legitimate technical concern about using synchronous OpenAI calls in async functions, the comment's phrasing makes it non-actionable and speculative rather than definitive.
3. packages/traceloop-sdk/tests/evaluator/test_field_mapping.py:327
- Draft comment:
Docstring and function references updated to 'validate_and_normalize_task_output' look correct. Ensure all module references are consistent. - Reason this comment was not posted:
Confidence changes required:0%<= threshold50%None
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♻️ Duplicate comments (1)
packages/traceloop-sdk/tests/evaluator/test_field_mapping.py (1)
327-412: Integration tests give good end-to-end coverage; minor naming nitThe integration tests do a nice job of verifying that
validate_and_normalize_task_outputactually wires in normalization and synonym-aware error messages, including the new trajectory fields for agent evaluators.One minor naming nit: the class name
TestIntegrationWithValidateTaskOutput(Line 327) still references the old function name, even though the tests now correctly exercisevalidate_and_normalize_task_output. Renaming the class (e.g. toTestIntegrationWithValidateAndNormalizeTaskOutputor similar) would avoid confusion for future readers.
🧹 Nitpick comments (6)
packages/sample-app/sample_app/agents/travel_agent_example.py (5)
2-2: Remove unused import.The
jsonmodule is imported but never used in this file.import asyncio -import json import random
313-320: Remove debug traceback output before production use.The
traceback.print_exc()call is useful for debugging but should be removed or replaced with structured logging for production code. This applies here and at line 585-586 as well.except Exception as e: print(f"Error getting weather forecast (Exception): {type(e).__name__}: {str(e)}") - import traceback - traceback.print_exc() return WeatherResponse( status="error", message=f"Failed to get weather forecast: {type(e).__name__}: {str(e)}" )
583-590: Remove debug traceback output.Same as the earlier occurrence—remove or replace with structured logging.
except Exception as e: print(f"Error creating itinerary: {type(e).__name__}: {str(e)}") - import traceback - traceback.print_exc() return ItineraryResponse( status="error", message=f"Failed to create itinerary: {str(e)}" )
706-706: Remove unused variabletravel_ctx.The
travel_ctxis instantiated but never passed to the runner or agent.- travel_ctx = TravelContext(conversation_history=[]) travel_agent = TravelPlannerAgent()
871-873: Useasyncio.sleepin async context.Using blocking
time.sleepin an async function blocks the event loop. While this is at the end of a query iteration and doesn't block concurrent operations in this demo, usingasyncio.sleepis more idiomatic.if i < args.count: print(f"\nWaiting {args.delay} seconds before next query...") - time.sleep(args.delay) + await asyncio.sleep(args.delay)packages/traceloop-sdk/tests/evaluator/test_field_mapping.py (1)
10-76: Robust synonym tests; length checks may be brittle over timeThe coverage of synonym groups and symmetry looks solid. The strict
len(synonyms) == Nassertions (Lines 20, 29, 37, 44, 51) will force test updates any time a new synonym is added, even when such additions are backwards compatible. If you expect synonym groups to evolve, consider asserting only membership (e.g. required subset) and dropping the length checks to make the tests less brittle.
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packages/traceloop-sdk/tests/evaluator/test_field_mapping.py (3)
packages/traceloop-sdk/traceloop/sdk/evaluator/field_mapping.py (4)
get_synonyms(52-63)normalize_task_output(66-126)get_field_suggestions(129-149)format_field_help(152-167)packages/traceloop-sdk/traceloop/sdk/evaluator/evaluator.py (1)
validate_and_normalize_task_output(149-218)packages/traceloop-sdk/traceloop/sdk/evaluator/config.py (1)
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packages/sample-app/sample_app/agents/travel_agent_example.py (3)
packages/traceloop-sdk/traceloop/sdk/__init__.py (2)
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packages/sample-app/sample_app/agents/travel_agent_example.py
[error] 2-2: 'json' imported but unused
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[error] 186-186: continuation line under-indented for visual indent
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[error] 706-706: local variable 'travel_ctx' is assigned to but never used
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packages/sample-app/sample_app/agents/travel_agent_example.py
[failure] 238-238: Clear-text logging of sensitive information
This expression logs sensitive data (private) as clear text.
This expression logs sensitive data (private) as clear text.
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packages/sample-app/sample_app/agents/travel_agent_example.py
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706-706: Local variable travel_ctx is assigned to but never used
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🔇 Additional comments (5)
packages/sample-app/sample_app/agents/travel_agent_example.py (2)
141-148: LGTM!The mutable default for
conversation_historyis correctly handled using__post_init__to avoid the common Python pitfall of shared mutable defaults.
593-649: LGTM!The agent class is well-structured with comprehensive instructions that guide the LLM through different query specificity levels. The tool configuration is correct.
packages/traceloop-sdk/tests/evaluator/test_field_mapping.py (3)
78-241: normalize_task_output test matrix is comprehensiveThese tests exercise the key behaviors of
normalize_task_output: synonym mapping in both single- and multi-field scenarios, preservation of extra fields, handling of empty inputs/requirements, preference for exact matches, and coexistence with non-synonym fields. This gives good confidence that the normalization logic matches the documented behavior.
243-297: get_field_suggestions tests align well with synonym logicThe suggestion tests cover positive matches, negative cases, multiple-suggestion scenarios, and empty availability. They mirror the
get_field_suggestionssemantics closely and should catch regressions in how synonym overlap is computed without over-specifying formatting.
300-325: format_field_help tests validate both branched behaviorsYou verify both the single-synonym case and the multi-synonym formatting, plus a small multi-field sanity check. This is an appropriate level of assertion (checking for key substrings rather than exact formatting), keeping tests resilient to minor wording tweaks while still guarding behavior.
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Reviewed 2f8dd94 in 1 minute and 2 seconds. Click for details.
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3draft comments. View those below. - Modify your settings and rules to customize what types of comments Ellipsis leaves. And don't forget to react with 👍 or 👎 to teach Ellipsis.
1. packages/sample-app/sample_app/agents/travel_agent_example.py:703
- Draft comment:
Good removal: the unused 'travel_ctx' variable was removed since it's not utilized. Ensure that context is managed internally. - Reason this comment was not posted:
Comment was not on a location in the diff, so it can't be submitted as a review comment.
2. packages/sample-app/sample_app/agents/travel_agent_example.py:728
- Draft comment:
Improved readability by converting query templates into multi-line parenthesized strings. This formatting change is clear and improves maintainability. - Reason this comment was not posted:
Comment did not seem useful. Confidence is useful =0%<= threshold50%This comment is purely informative and does not provide any actionable feedback or suggestions for improvement. It simply praises the change without offering any specific guidance or questions.
3. packages/traceloop-sdk/traceloop/sdk/evaluator/evaluators_made_by_traceloop.py:243
- Draft comment:
Added the missing '- denominator_text' description in the word_count_ratio evaluator docstring. The documentation now fully reflects the required input fields. - Reason this comment was not posted:
Comment was not on a location in the diff, so it can't be submitted as a review comment.
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Actionable comments posted: 1
♻️ Duplicate comments (4)
packages/sample-app/sample_app/agents/travel_agent_example.py (4)
404-413: URL‑encodedestination_namein Wikipedia request (duplicate of existing suggestion).Concatenating
destination_namedirectly into the path will break for spaces and special characters and can cause 404s or misrouted requests. Encode it before building the URL.+ from urllib.parse import quote @@ - url = "https://en.wikipedia.org/api/rest_v1/page/summary/" + destination_name + encoded_name = quote(destination_name, safe="") + url = "https://en.wikipedia.org/api/rest_v1/page/summary/" + encoded_nameMake sure the import is at the top of the file.
848-854: Argparse help text doesn’t match the actual default (duplicate of existing suggestion).
--counthasdefault=1but the help string still says “default: 3”. Recommend updating the help to avoid confusing users:parser.add_argument( "--count", type=int, default=1, - help="Number of queries to run (default: 3)" + help="Number of queries to run (default: 1)" )
237-238: Printed location + coordinates may be sensitive (duplicate of existing warning).
print(f"Getting weather forecast for {location_name} ({latitude}, {longitude})")logs a potentially identifying place together with precise coordinates. For production usage, consider either removing this log, redacting coordinates, or downgrading it behind a debug flag, especially if logs are retained centrally.
889-891: Useawait asyncio.sleepinstead oftime.sleepinasync def main(duplicate of existing suggestion).
time.sleep(args.delay)blocks the entire event loop between queries. Replace it withawait asyncio.sleep(args.delay)to keep the async runtime responsive:- if i < args.count: - print(f"\nWaiting {args.delay} seconds before next query...") - time.sleep(args.delay) + if i < args.count: + print(f"\nWaiting {args.delay} seconds before next query...") + await asyncio.sleep(args.delay)
🧹 Nitpick comments (5)
packages/sample-app/sample_app/agents/travel_agent_example.py (5)
150-155: Unusedcwcontext parameter in tool functions (ARG001).Ruff flags
cwas unused here and in the other@function_toolfunctions. If you don't plan to use the context inside these tools, consider renaming to_cw(or adding# noqa: ARG001on the function) to keep the signature compatible with the framework while silencing the lint warning.
168-179: Blocking HTTP calls insideasynctools.All the
@function_toolcoroutines (search_destinations,get_weather_forecast,get_location_coordinates,get_destination_info) callrequests.getdirectly, which blocks the event loop and can stall other async work. For better responsiveness, either switch to an async HTTP client (e.g.,httpx.AsyncClient) or wrap blocking calls withawait asyncio.to_thread(requests.get, ...).
211-216: Error handling: avoid echoing raw exceptions and address RUF010.Two points here (and similarly in other error handlers):
f"... {str(e)}"triggers Ruff RUF010; preferf"... {e!s}"or simplyf"... {e}".- Returning/logging the full exception string to the user can leak implementation details; consider logging the detailed error internally and returning a generic, user‑friendly message instead.
Same pattern appears in the weather, coordinates, destination info, distance, and itinerary helpers.
497-502: Broadexcept Exceptionin distance calculation.Catching
Exceptionhides programming errors and makes debugging harder. If you mainly expect numeric issues or bad inputs, narrow this to specific exception types (e.g.,ValueError,TypeError) and let unexpected errors surface, or re‑raise after logging.
584-591: Broadexcept Exceptionincreate_itinerary.Same concern as in
calculate_travel_distance: a blanketexcept Exceptionwill swallow unexpected bugs (including misconfiguration of the OpenAI client). Prefer catching the specific OpenAI/library exceptions you expect plus input/validation errors, and allow truly unexpected failures to propagate or be re‑raised after logging.
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packages/sample-app/sample_app/agents/travel_agent_example.py (2)
packages/traceloop-sdk/traceloop/sdk/__init__.py (2)
Traceloop(36-267)init(48-198)packages/traceloop-sdk/traceloop/sdk/decorators/__init__.py (1)
tool(61-71)
packages/traceloop-sdk/traceloop/sdk/evaluator/evaluators_made_by_traceloop.py (1)
packages/traceloop-sdk/traceloop/sdk/evaluator/config.py (1)
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🔇 Additional comments (4)
packages/traceloop-sdk/traceloop/sdk/evaluator/evaluators_made_by_traceloop.py (4)
243-243: Good documentation fix.The missing
denominator_textfield documentation now aligns with therequired_input_fieldsspecification on line 254.
479-544: LGTM! Answer evaluators are well-structured.The three new answer-focused evaluators follow consistent patterns with existing code. Each has clear documentation and appropriate required fields for its evaluation purpose.
546-632: LGTM! Agent evaluators are well-designed.The agent evaluators follow a coherent design where three trajectory-based evaluators (
agent_flow_quality,agent_efficiency,agent_goal_completeness) appropriately share the same input fields while evaluating different aspects of agent behavior. Theagent_tool_error_detectorcorrectly uses distinct fields for tool monitoring.
634-721: LGTM! Conversation and tone evaluators are consistent.The evaluators follow logical groupings with appropriate field sharing between
conversation_qualityandintent_change. Documentation clearly distinguishes between conversation-level analysis (usingprompts/completions) and agent trajectory analysis.
Fixes TLP-1313
feat(instrumentation): ...orfix(instrumentation): ....Important
Add agent evaluators and synonym mapping for flexible task output validation, with comprehensive tests.
agents_exp.py.field_mapping.pyto allow flexible task output.test_field_mapping.pyandtest_evaluator.py.test_experiment.pyto test validation with multiple evaluators and synonym mapping.validate_task_outputtovalidate_and_normalize_task_outputinevaluator.pyto include normalization.This description was created by
for 2f8dd94. You can customize this summary. It will automatically update as commits are pushed.
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