evidentlyai/evidently
Nov 2024 – Feb 2026
15 Months active
Languages Used
PythonJavaScriptJSONJupyter NotebookTypeScriptSQLYAMLMarkdown
Technical Skills
Build SystemPython PackagingBackend DevelopmentBug FixingCode OrganizationData Processing
Mikhail Sveshnikov
PROFILE
Mikhail Sveshnikov
Mike contributed to the evidentlyai/evidently repository by building and refining core data evaluation, LLM integration, and analytics infrastructure over 15 months. He engineered modular APIs for prompt optimization, dataset management, and recommendation system evaluation, using Python, SQL, and React to support scalable workflows and robust UI features. His work included implementing cloud-enabled storage, PostgreSQL integration, and advanced metric calculation, while maintaining compatibility across evolving Python versions. Mike addressed reliability through targeted bug fixes and CI/CD upgrades, and improved developer experience with enhanced documentation and packaging. The depth of his contributions enabled flexible, provider-agnostic model evaluation and streamlined data governance.
Overall Statistics
Feature vs Bugs
79%Features
Repository Contributions
118Total
Bugs
15
Commits
118
Features
56
Lines of code
173,043
Activity Months15
Work History
February 2026
1 Commits • 1 Features
Feb 1, 2026February 2026: Delivered a critical compatibility upgrade for evidently, raising the minimum Python version to 3.10+ across configuration, CI workflows, and docs. This change positions the evidently project to leverage modern language features and libraries, improves maintainability, and reduces long-term risk. The work is fully traceable with commit 4090f012b9bf7e2491bd48c44298ac3709b5e864 (Drop python 3.9 support) as part of release alignment (#1811).
1 Commits • 1 Features
Feb 1, 2026February 2026: Delivered a critical compatibility upgrade for evidently, raising the minimum Python version to 3.10+ across configuration, CI workflows, and docs. This change positions the evidently project to leverage modern language features and libraries, improves maintainability, and reduces long-term risk. The work is fully traceable with commit 4090f012b9bf7e2491bd48c44298ac3709b5e864 (Drop python 3.9 support) as part of release alignment (#1811).
February 2026
December 2025
6 Commits • 3 Features
Dec 1, 2025December 2025 delivered a focused set of features, reliability improvements, and process upgrades that collectively increase the value of model evaluation and data tooling for Evidently. Key outcomes include a unified prompts ecosystem with versioned artifacts, a UI Prompts tab, and LLM judge endpoints; robust data handling fixes to preserve backward compatibility; comprehensive API documentation and dataset handling improvements; and modernization of packaging and CI workflows to improve build reliability and developer productivity.
December 2025
6 Commits • 3 Features
Dec 1, 2025December 2025 delivered a focused set of features, reliability improvements, and process upgrades that collectively increase the value of model evaluation and data tooling for Evidently. Key outcomes include a unified prompts ecosystem with versioned artifacts, a UI Prompts tab, and LLM judge endpoints; robust data handling fixes to preserve backward compatibility; comprehensive API documentation and dataset handling improvements; and modernization of packaging and CI workflows to improve build reliability and developer productivity.
November 2025
7 Commits • 4 Features
Nov 1, 2025Nov 2025 monthly summary for evidently: Delivered pivotal data storage, dataset management, observability, and demo capabilities, while stabilizing Windows CI. Business value includes scalable data storage with PostgreSQL, reusable datasets in local workspaces, richer analytics visuals, and improved monitoring across environments, enabling faster experimentation and reliable deployments.
7 Commits • 4 Features
Nov 1, 2025Nov 2025 monthly summary for evidently: Delivered pivotal data storage, dataset management, observability, and demo capabilities, while stabilizing Windows CI. Business value includes scalable data storage with PostgreSQL, reusable datasets in local workspaces, richer analytics visuals, and improved monitoring across environments, enabling faster experimentation and reliable deployments.
November 2025
October 2025
6 Commits • 3 Features
Oct 1, 2025October 2025 (2025-10) summary for evidentlyai/evidently: Delivered a unified Text Analysis framework with the new TextMatches descriptor, introduced Advanced RecSys evaluation via RecsysPreset and accompanying metrics, and enabled Dynamic Metrics Parameter Resolution with DataFrame-based metrics; updated descriptor notebooks, added recsys metrics notebooks, and stabilized tests and linting. These changes collectively improve consistency, benchmarking capabilities, and targeted testing efficiency, accelerating experimentation and maintainability.
October 2025
6 Commits • 3 Features
Oct 1, 2025October 2025 (2025-10) summary for evidentlyai/evidently: Delivered a unified Text Analysis framework with the new TextMatches descriptor, introduced Advanced RecSys evaluation via RecsysPreset and accompanying metrics, and enabled Dynamic Metrics Parameter Resolution with DataFrame-based metrics; updated descriptor notebooks, added recsys metrics notebooks, and stabilized tests and linting. These changes collectively improve consistency, benchmarking capabilities, and targeted testing efficiency, accelerating experimentation and maintainability.
September 2025
5 Commits • 3 Features
Sep 1, 2025September 2025: Delivered flexible configuration, advanced evaluation, and modular analytics in evidentl y. Focused on enabling richer customization, extensible prompts, and scalable analytics. Key work includes configurable PromptOptimizerConfig via config_kwargs, LLM evaluation v2 with template-based prompts and a Prompt Registry example notebook, and a refactor of correlation analytics into distinct metric/preset components with updated date/time utilities. No standalone bug fixes are documented in this dataset; improvements are primarily feature-driven with accompanying tests and lint fixes to stabilize the pipeline. These changes collectively reduce integration friction, enable richer model evaluation, and provide actionable analytics for product teams.
5 Commits • 3 Features
Sep 1, 2025September 2025: Delivered flexible configuration, advanced evaluation, and modular analytics in evidentl y. Focused on enabling richer customization, extensible prompts, and scalable analytics. Key work includes configurable PromptOptimizerConfig via config_kwargs, LLM evaluation v2 with template-based prompts and a Prompt Registry example notebook, and a refactor of correlation analytics into distinct metric/preset components with updated date/time utilities. No standalone bug fixes are documented in this dataset; improvements are primarily feature-driven with accompanying tests and lint fixes to stabilize the pipeline. These changes collectively reduce integration friction, enable richer model evaluation, and provide actionable analytics for product teams.
September 2025
August 2025
7 Commits • 3 Features
Aug 1, 2025Month: 2025-08 Summary: - Key features delivered: 1) Snapshot management reliability: fixed delete path, tightened authentication permission checks, and stabilized observer behavior for incomplete or partially written snapshot files. Commits: 98fd432ca889a0a3391e969f7f81593e851df51b; abaaab8017a0782720c390fd4302e2a7aaec354a 2) Prompt optimization framework enhancements: API refactor, introduced NoopOptimizationScorer and NoopPromptExecutor, and expanded strategies with improved examples and scoring/handling. Commits: f8ff22f4a08a01028839680e0cb352daddeb47d2; 238619fea3ad6eaa5d5f3c552fc94172e439412c 3) Test reporting enhancements: RowTestSummary metric, updated TextEvals preset, and enriched rendering with SpecialColumnInfo, TestSummaryInfo, and TestSummaryInfoPreset. Commits: 3e8a1207384ae48e903261ba9f9b3dffe34113e6; 95f689ea21fb175ae70bb6470d425b86908fe260 4) Datagen tutorial enhancements: updated tutorial to demonstrate multiple LLM providers and RAG capabilities, including OpenAI and Anthropic examples with file-based knowledge bases and git diffs. Commit: 98964a947d4561cbb3dcaae2e529f6fa160ca040 - Major bugs fixed: - Snapshot deletion issues and authentication permission checks resolved; observer stability improved for incomplete snapshots. (Linked commits above) - Overall impact and accomplishments: - Increased reliability and observability across critical data evaluation pipelines; faster iteration on prompts via API refinements; richer test-result rendering for QA and compliance; broader Datagen coverage enabling multi-provider workflows and real-world RAG scenarios, supporting broader adoption and trust. - Technologies/skills demonstrated: - API refactoring and design of NoopOptimizationScorer and NoopPromptExecutor; expanded prompt strategies with robust scoring/handling; enhanced test reporting architecture; multi-provider data generation and RAG integration; strong Git-based traceability through explicit commit references.
August 2025
7 Commits • 3 Features
Aug 1, 2025Month: 2025-08 Summary: - Key features delivered: 1) Snapshot management reliability: fixed delete path, tightened authentication permission checks, and stabilized observer behavior for incomplete or partially written snapshot files. Commits: 98fd432ca889a0a3391e969f7f81593e851df51b; abaaab8017a0782720c390fd4302e2a7aaec354a 2) Prompt optimization framework enhancements: API refactor, introduced NoopOptimizationScorer and NoopPromptExecutor, and expanded strategies with improved examples and scoring/handling. Commits: f8ff22f4a08a01028839680e0cb352daddeb47d2; 238619fea3ad6eaa5d5f3c552fc94172e439412c 3) Test reporting enhancements: RowTestSummary metric, updated TextEvals preset, and enriched rendering with SpecialColumnInfo, TestSummaryInfo, and TestSummaryInfoPreset. Commits: 3e8a1207384ae48e903261ba9f9b3dffe34113e6; 95f689ea21fb175ae70bb6470d425b86908fe260 4) Datagen tutorial enhancements: updated tutorial to demonstrate multiple LLM providers and RAG capabilities, including OpenAI and Anthropic examples with file-based knowledge bases and git diffs. Commit: 98964a947d4561cbb3dcaae2e529f6fa160ca040 - Major bugs fixed: - Snapshot deletion issues and authentication permission checks resolved; observer stability improved for incomplete snapshots. (Linked commits above) - Overall impact and accomplishments: - Increased reliability and observability across critical data evaluation pipelines; faster iteration on prompts via API refinements; richer test-result rendering for QA and compliance; broader Datagen coverage enabling multi-provider workflows and real-world RAG scenarios, supporting broader adoption and trust. - Technologies/skills demonstrated: - API refactoring and design of NoopOptimizationScorer and NoopPromptExecutor; expanded prompt strategies with robust scoring/handling; enhanced test reporting architecture; multi-provider data generation and RAG integration; strong Git-based traceability through explicit commit references.
July 2025
10 Commits • 4 Features
Jul 1, 2025July 2025 monthly summary for evidentlyai/evidently: Deliveries across prompt optimization, configuration management, LLM integration and data generation, UI enhancements, and stability fixes. These efforts strengthen model evaluation, configurable workflows, data pipelines, and user experience. Notable work includes a prompt optimization workflow with cookbook examples for booking classification, code review quality, and tweet generation; a new configuration store with versioning and metadata handling; reorganized LLM utilities and templates, Litellm provider upgrades, Nebius support, and synthetic data generation; UI widgets for column tests; and critical fixes for type-mismatch handling and few-shot serialization.
10 Commits • 4 Features
Jul 1, 2025July 2025 monthly summary for evidentlyai/evidently: Deliveries across prompt optimization, configuration management, LLM integration and data generation, UI enhancements, and stability fixes. These efforts strengthen model evaluation, configurable workflows, data pipelines, and user experience. Notable work includes a prompt optimization workflow with cookbook examples for booking classification, code review quality, and tweet generation; a new configuration store with versioning and metadata handling; reorganized LLM utilities and templates, Litellm provider upgrades, Nebius support, and synthetic data generation; UI widgets for column tests; and critical fixes for type-mismatch handling and few-shot serialization.
July 2025
June 2025
12 Commits • 5 Features
Jun 1, 2025June 2025 focused on expanding provider-agnostic LLM workflows, enriching data governance, and tightening the automation surface. Key outcomes include modular LLM wrappers (Vertex AI and Gemini) with new GeminiOptions and improved API-key parsing, a multi-provider descriptor tutorial, and metadata/cloud serialization for Dataset management. CLI enhancements now enable running reports/descriptors and loading configurations, accelerating reproducibility. Descriptor tests and schema validation improvements strengthen reliability and automation. These changes deliver business value by enabling flexible provider configurations, richer data management, and streamlined operational workflows.
June 2025
12 Commits • 5 Features
Jun 1, 2025June 2025 focused on expanding provider-agnostic LLM workflows, enriching data governance, and tightening the automation surface. Key outcomes include modular LLM wrappers (Vertex AI and Gemini) with new GeminiOptions and improved API-key parsing, a multi-provider descriptor tutorial, and metadata/cloud serialization for Dataset management. CLI enhancements now enable running reports/descriptors and loading configurations, accelerating reproducibility. Descriptor tests and schema validation improvements strengthen reliability and automation. These changes deliver business value by enabling flexible provider configurations, richer data management, and streamlined operational workflows.
May 2025
10 Commits • 4 Features
May 1, 2025Concise monthly summary for evidently repository (May 2025): Delivered cross-run analysis, robust metric handling, UI improvements, and expanded LLM/provider capabilities, strengthening data-driven decision-making and developer productivity.
10 Commits • 4 Features
May 1, 2025Concise monthly summary for evidently repository (May 2025): Delivered cross-run analysis, robust metric handling, UI improvements, and expanded LLM/provider capabilities, strengthening data-driven decision-making and developer productivity.
May 2025
April 2025
17 Commits • 5 Features
Apr 1, 2025April 2025 focused on delivering flexible feature tooling, robust dashboards, and an improved developer experience. Key achievements include a serializable descriptor system with better cross-version compatibility, a local workspace UI for Evidently, and enhanced missing-value metrics. We also hardened graph/panel rendering with downsampling and smart widget handling, and upgraded CI/CD/test infrastructure to Python 3.13. A data-summarization bug fix improved context handling and consistency across current/reference datasets. These efforts deliver tangible business value: richer feature generation, more reliable dashboards, offline-friendly workflows, faster tests, and a cleaner upgrade path for future releases.
April 2025
17 Commits • 5 Features
Apr 1, 2025April 2025 focused on delivering flexible feature tooling, robust dashboards, and an improved developer experience. Key achievements include a serializable descriptor system with better cross-version compatibility, a local workspace UI for Evidently, and enhanced missing-value metrics. We also hardened graph/panel rendering with downsampling and smart widget handling, and upgraded CI/CD/test infrastructure to Python 3.13. A data-summarization bug fix improved context handling and consistency across current/reference datasets. These efforts deliver tangible business value: richer feature generation, more reliable dashboards, offline-friendly workflows, faster tests, and a cleaner upgrade path for future releases.
March 2025
5 Commits • 5 Features
Mar 1, 2025March 2025 monthly summary for the evidently repository. Delivered a set of core features and infrastructure improvements focused on data validation, cloud-enabled workflows, versioning, and evaluation enhancements. Achievements span data modeling, cloud data management, workspace architecture, test configurability, and multiclass evaluation, driving cloud readiness, compatibility, and deeper analytical capabilities.
5 Commits • 5 Features
Mar 1, 2025March 2025 monthly summary for the evidently repository. Delivered a set of core features and infrastructure improvements focused on data validation, cloud-enabled workflows, versioning, and evaluation enhancements. Achievements span data modeling, cloud data management, workspace architecture, test configurability, and multiclass evaluation, driving cloud readiness, compatibility, and deeper analytical capabilities.
March 2025
February 2025
11 Commits • 7 Features
Feb 1, 2025February 2025 monthly summary for evidently repository highlights delivery across LLM integration, UI improvements, metric extensibility, and system robustness. Key outcomes include asynchronous LLM wrappers with rate-limiting and default Litellm integration, provider-management refactor for greater model selection flexibility, improved Evidently UI test hover context and clearer error handling, support for uploading unknown metrics (MeanStdValue) with proper fingerprint handling, and architectural enhancements for metrics and reporting (nested metric containers, advanced categorical metrics, column generator, and flexible descriptor/options). A notable bug fix corrected range aggregation from count() to sum(), improving accuracy for in-range and out-of-range metrics. Overall, these efforts increase reliability, data quality, platform flexibility, and business value for customers relying on robust model evaluation and reporting.
February 2025
11 Commits • 7 Features
Feb 1, 2025February 2025 monthly summary for evidently repository highlights delivery across LLM integration, UI improvements, metric extensibility, and system robustness. Key outcomes include asynchronous LLM wrappers with rate-limiting and default Litellm integration, provider-management refactor for greater model selection flexibility, improved Evidently UI test hover context and clearer error handling, support for uploading unknown metrics (MeanStdValue) with proper fingerprint handling, and architectural enhancements for metrics and reporting (nested metric containers, advanced categorical metrics, column generator, and flexible descriptor/options). A notable bug fix corrected range aggregation from count() to sum(), improving accuracy for in-range and out-of-range metrics. Overall, these efforts increase reliability, data quality, platform flexibility, and business value for customers relying on robust model evaluation and reporting.
January 2025
15 Commits • 5 Features
Jan 1, 2025January 2025: Delivered core improvements across testing, recommender metrics, visualization, feature naming, and Workspace API, driving reliability, better model evaluation, and streamlined data workflows. A notable bug fix addressed LLM Judge prompt templates and mock LLM JSON structure to improve prompt reliability.
15 Commits • 5 Features
Jan 1, 2025January 2025: Delivered core improvements across testing, recommender metrics, visualization, feature naming, and Workspace API, driving reliability, better model evaluation, and streamlined data workflows. A notable bug fix addressed LLM Judge prompt templates and mock LLM JSON structure to improve prompt reliability.
January 2025
December 2024
5 Commits • 4 Features
Dec 1, 2024December 2024 was marked by targeted improvements across data reliability, UX, architecture, and test instrumentation, delivering tangible business value and preparing the codebase for scalable growth.
December 2024
5 Commits • 4 Features
Dec 1, 2024December 2024 was marked by targeted improvements across data reliability, UX, architecture, and test instrumentation, delivering tangible business value and preparing the codebase for scalable growth.
November 2024
1 Commits
Nov 1, 2024November 2024 (evidently/evidently repo): Focused on stability, cross-environment compatibility, and maintenance. No new user-facing features shipped this month. Major bug fix: Python 3.13 compatibility import fix for pipes, ensuring builds and imports don’t fail on newer Python versions. The import was moved to be conditional based on OS and availability of list2cmdline from subprocess to avoid import errors across environments, strengthening CI reliability and cross-platform deployment. Technologies demonstrated include Python import mechanics, conditional imports, OS detection, and subprocess interoperability, reflecting strong maintenance and quality assurance value for the product.
1 Commits
Nov 1, 2024November 2024 (evidently/evidently repo): Focused on stability, cross-environment compatibility, and maintenance. No new user-facing features shipped this month. Major bug fix: Python 3.13 compatibility import fix for pipes, ensuring builds and imports don’t fail on newer Python versions. The import was moved to be conditional based on OS and availability of list2cmdline from subprocess to avoid import errors across environments, strengthening CI reliability and cross-platform deployment. Technologies demonstrated include Python import mechanics, conditional imports, OS detection, and subprocess interoperability, reflecting strong maintenance and quality assurance value for the product.
November 2024
Activity
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Quality Metrics
Correctness86.6%
Maintainability84.8%
Architecture85.0%
Performance76.4%
AI Usage29.8%
Skills & Technologies
Programming Languages
JSONJavaScriptJupyter NotebookMarkdownPythonSQLShellTypeScriptYAML
Technical Skills
API DesignAPI DevelopmentAPI IntegrationAPI developmentAPI integrationAlembicAsynchronous ProgrammingBackend DevelopmentBug FixBug FixingBuild SystemCI/CDCLI DevelopmentCloud IntegrationCloud Services
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline