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Update README.md
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Create outreach_agent.py
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Create research_agent.py
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Create analytics_agent.py
Verified signatureanalytics_agent.py implementing live metrics on demand, end-of-day reports (scheduled), batch export (7/30/90 days), API/UI hooks, error logging/reporting, and config-driven specs. See functions: get_live_metrics, run_end_of_day_report, batch_export, expose_endpoint, get_errors. Needs analytics_utils.py. Update README for usage/testing.7c98bdb -
Create docs/configs/ANALYTICS_SPEC.md
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Create docs/configs/analytics_config.json
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Update README with comprehensive Human Validation Agent documentation
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Create Human Validation Agent module with batch review, schema validation, and queue integration
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Update README.md
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Add simulation for queue handoff to enrichment agent with browser and human fallback
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Add enrichment agent config with prioritized sources, rate limits, and retry policies
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Create recovery_enrichment_agent.py
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Add comprehensive browser agent MCP/container verification documentation
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Document browser agent MCP/container verification steps
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Update activity_log.csv
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Update test_schema_tools.py
Verified signatureAdd data recovery columns, batch error handling, human validation, and lead scrub/approve logic.765341b -
Add test script for schema registry and query/search agent tools
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Add query/search agent with advanced mapping, validation, error reporting, and JSON support
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Add schema registry with mapping, validation, and audit capabilities
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Add atomic activity ingestion validation script
Verified signatureValidates core ingestion with four test scenarios: - Valid insert (should succeed) - Invalid status value (should fail) - Missing required field (should fail) - Confirm atomic insert (should always succeed if schema-valid) Each test outputs PASS/FAIL and error details for review.bf1af21 -
Add comprehensive schema versioning and rollback documentation
Verified signatureComplete schema version control system documentation including: - Schema v1.0 definition with all required fields - Detailed version history tracking - Git-based rollback procedures (soft, hard, file-specific) - Commit tracking system (request_id, commit_hash) - Build-specific rollback for dev/staging/production - Pre/post validation procedures - Error recovery protocols - Schema change tracking format - Testing checklist - Quick reference commands This documentation ensures reliable version control, data integrity, and seamless rollback capability for all future schema modifications across different build environments.cc10b69 -
Implement atomic activity ingestion with schema validation and commit tracking
Verified signatureFEATURES: - Atomic row additions using temp file + rename pattern - Schema validation (v1.0) with required fields and valid value checks - Request ID generation for tracking - ISO 8601 timestamp generation - Full error handling with custom exceptions - File locking for concurrent access safety - Operation logging for audit trail - Commit hash generation for versioning - Comprehensive test suite with 5 test cases VERSION CONTROL: - Schema version: 1.0 - Supports rollback via git history - All operations logged with request_id and timestamp - Commit hashes enable change tracking USAGE: - Run directly: python activity_ingestion.py (runs tests) - Import: from activity_ingestion import atomic_append_activity This implementation ensures data integrity and provides full audit trail for production use.3a67095 -
Validate schema and confirm agent write access
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Add canonical activity_log.csv schema for agent tracking
Verified signatureEstablishes canonical CSV schema for activity tracking with standardized columns: - timestamp: ISO 8601 format (UTC) - agent_id: identifier for the agent performing the activity - activity_type: type of activity (init, read, write, update, delete, query, etc.) - entity_id: identifier for the entity being acted upon - status: status of the activity (created, updated, success, failed, pending, etc.) - notes: human-readable description of the activity - context: additional context or metadata about the activity This schema provides a clean foundation for agent integration and data flow tracking.a6db97b -
Create tools.csv
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Update app.py
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Create smolagents/.env.sample
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Update requirements.txt
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Create smolagents/tools.py
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Update app.py
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Update README.md
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gradio
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import gradio as gr def greet(name): return "Hello " + name + "!!" demo = gr.Interface(fn=greet, inputs="text", outputs="text") demo.launch()
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initial commit
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