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Browse files- CHANGELOG.md +14 -0
- app.py +16 -18
CHANGELOG.md
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## Changes Made
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### [PROBLEM: LLM Quota Exhaustion - Retry Logic]
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**Modified Files:**
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## Changes Made
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### [PROBLEM: Ground Truth Architecture - Single Source Simplification]
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**Modified Files:**
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- **app.py** (~10 lines modified)
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- Removed `ground_truth` parameter from `export_results_to_json()` function signature
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- Removed double work: no longer access `ground_truth.metadata` in export function
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- Changed `_annotator_metadata` to `annotator_metadata` (removed underscore prefix)
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- Updated all 6 function calls to remove `ground_truth` parameter (lines 448, 489, 504, 513, 522, 531)
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- Updated comment: "both UI and JSON show identical data" (line 426)
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- Updated docstring: "Single source: Both UI and JSON use identical results_log data" (line 58)
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- Simplified JSON export to use `result.get("annotator_metadata")` instead of accessing metadata again (lines 119-121)
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- Result: One object (results_log) → Two formats (UI table + JSON), both identical, no filtering
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### [PROBLEM: LLM Quota Exhaustion - Retry Logic]
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**Modified Files:**
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app.py
CHANGED
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@@ -49,20 +49,19 @@ def export_results_to_json(
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submission_status: str,
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execution_time: float = None,
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submission_response: dict = None,
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ground_truth = None,
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) -> str:
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"""Export evaluation results to JSON file for easy processing.
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- Local: Saves to ~/Downloads/gaia_results_TIMESTAMP.json
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- HF Spaces: Saves to ./exports/gaia_results_TIMESTAMP.json
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- Format: Clean JSON with full error messages, no truncation
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Args:
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results_log: List of question results
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submission_status: Status message from submission
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execution_time: Total execution time in seconds
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submission_response: Response from GAIA API with correctness info
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ground_truth: GAIAGroundTruth object for metadata access
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"""
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from datetime import datetime
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if result.get("Ground Truth Answer"):
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result_dict["ground_truth_answer"] = result.get("Ground Truth Answer")
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# Add annotator metadata if available (
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if
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metadata_item = ground_truth.metadata.get(task_id, {})
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annotator_metadata = metadata_item.get("Annotator Metadata", {})
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if annotator_metadata:
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result_dict["annotator_metadata"] = annotator_metadata
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results_array.append(result_dict)
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# Compare with ground truth if available
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is_correct = ground_truth.compare_answer(result["task_id"], result["answer"])
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# Get ground truth answer
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gt_answer = ground_truth.get_answer(result["task_id"])
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# Add to results log
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result_entry = {
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if is_correct is not None:
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result_entry["Correct?"] = "✅ Yes" if is_correct else "❌ No"
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result_entry["Ground Truth Answer"] = gt_answer
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#
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results_log.append(result_entry)
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results_df = pd.DataFrame(results_log)
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execution_time = time.time() - start_time
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export_path = export_results_to_json(
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results_log, status_message, execution_time, None
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)
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return status_message, results_df, export_path
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results_df = pd.DataFrame(results_log)
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# Export to JSON with execution time and submission response
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export_path = export_results_to_json(
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results_log, final_status, execution_time, result_data
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)
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return final_status, results_df, export_path
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except requests.exceptions.HTTPError as e:
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execution_time = time.time() - start_time
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results_df = pd.DataFrame(results_log)
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export_path = export_results_to_json(
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results_log, status_message, execution_time, None
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)
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return status_message, results_df, export_path
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except requests.exceptions.Timeout:
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execution_time = time.time() - start_time
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results_df = pd.DataFrame(results_log)
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export_path = export_results_to_json(
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results_log, status_message, execution_time, None
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)
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return status_message, results_df, export_path
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except requests.exceptions.RequestException as e:
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execution_time = time.time() - start_time
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results_df = pd.DataFrame(results_log)
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export_path = export_results_to_json(
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results_log, status_message, execution_time, None
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)
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return status_message, results_df, export_path
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except Exception as e:
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execution_time = time.time() - start_time
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results_df = pd.DataFrame(results_log)
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export_path = export_results_to_json(
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results_log, status_message, execution_time, None
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)
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return status_message, results_df, export_path
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submission_status: str,
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execution_time: float = None,
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submission_response: dict = None,
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) -> str:
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"""Export evaluation results to JSON file for easy processing.
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- Local: Saves to ~/Downloads/gaia_results_TIMESTAMP.json
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- HF Spaces: Saves to ./exports/gaia_results_TIMESTAMP.json
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- Format: Clean JSON with full error messages, no truncation
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- Single source: Both UI and JSON use identical results_log data
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Args:
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results_log: List of question results (single source of truth)
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submission_status: Status message from submission
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execution_time: Total execution time in seconds
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submission_response: Response from GAIA API with correctness info
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"""
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from datetime import datetime
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if result.get("Ground Truth Answer"):
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result_dict["ground_truth_answer"] = result.get("Ground Truth Answer")
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# Add annotator metadata if available (already stored in results_log)
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if result.get("annotator_metadata"):
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result_dict["annotator_metadata"] = result.get("annotator_metadata")
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results_array.append(result_dict)
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# Compare with ground truth if available
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is_correct = ground_truth.compare_answer(result["task_id"], result["answer"])
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# Get ground truth answer and metadata (fetch once)
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gt_answer = ground_truth.get_answer(result["task_id"])
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metadata_item = ground_truth.metadata.get(result["task_id"], {})
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annotator_metadata = metadata_item.get("Annotator Metadata", {})
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# Add to results log
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result_entry = {
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if is_correct is not None:
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result_entry["Correct?"] = "✅ Yes" if is_correct else "❌ No"
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result_entry["Ground Truth Answer"] = gt_answer
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# Store metadata (both UI and JSON show identical data)
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result_entry["annotator_metadata"] = annotator_metadata
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results_log.append(result_entry)
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results_df = pd.DataFrame(results_log)
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execution_time = time.time() - start_time
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export_path = export_results_to_json(
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results_log, status_message, execution_time, None
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)
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return status_message, results_df, export_path
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results_df = pd.DataFrame(results_log)
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# Export to JSON with execution time and submission response
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export_path = export_results_to_json(
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results_log, final_status, execution_time, result_data
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)
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return final_status, results_df, export_path
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except requests.exceptions.HTTPError as e:
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execution_time = time.time() - start_time
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results_df = pd.DataFrame(results_log)
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export_path = export_results_to_json(
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results_log, status_message, execution_time, None
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)
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return status_message, results_df, export_path
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except requests.exceptions.Timeout:
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execution_time = time.time() - start_time
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results_df = pd.DataFrame(results_log)
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export_path = export_results_to_json(
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results_log, status_message, execution_time, None
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)
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return status_message, results_df, export_path
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except requests.exceptions.RequestException as e:
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execution_time = time.time() - start_time
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results_df = pd.DataFrame(results_log)
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export_path = export_results_to_json(
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results_log, status_message, execution_time, None
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)
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return status_message, results_df, export_path
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except Exception as e:
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execution_time = time.time() - start_time
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results_df = pd.DataFrame(results_log)
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export_path = export_results_to_json(
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results_log, status_message, execution_time, None
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)
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return status_message, results_df, export_path
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