tenstorrent/tt-inference-server
Apr 2026 – Jul 2026
4 Months active
Languages Used
PythonMarkdownBashJSONbashpython
Technical Skills
API developmentPythonasynchronous programmingbackend developmentdata handlingdata processing
Dunja Djukic
PROFILE
Dunja Djukic
Worked on the tenstorrent/tt-inference-server repository, delivering 27 features and resolving 8 bugs over four months. Focused on migrating core inference and benchmarking workflows to a new v2 architecture, the work included refactoring LLM modules, expanding test coverage with parameterized and end-to-end tests, and centralizing reporting with automated Markdown generation. Leveraged Python, Bash, and CI/CD practices to improve reliability, maintainability, and performance validation across audio, image, and language models. Enhanced backend infrastructure by introducing agentic skills frameworks, workflow runners, and robust metadata handling, resulting in faster validation cycles, reduced upgrade risk, and more actionable, unified reporting for stakeholders.
Overall Statistics
Feature vs Bugs
77%Features
Repository Contributions
47Total
Bugs
8
Commits
47
Features
27
Lines of code
67,717
Activity Months4
Your Network
427 peopleWork History
July 2026
1 Commits • 1 Features
Jul 1, 2026July 2026 monthly summary for tenstorrent/tt-inference-server focusing on feature delivery, bug fixes, and business impact. Delivered Enhanced LLM Release Reports and Validation for vLLM with a unified evaluation table, improved metadata, and targeted validation enhancements. The work included parameter-conformance spec tests for vLLM, refined blockers display, and fixes to accuracy checks. All changes consolidated in a single commit with quality formatting (Ruff).
1 Commits • 1 Features
Jul 1, 2026July 2026 monthly summary for tenstorrent/tt-inference-server focusing on feature delivery, bug fixes, and business impact. Delivered Enhanced LLM Release Reports and Validation for vLLM with a unified evaluation table, improved metadata, and targeted validation enhancements. The work included parameter-conformance spec tests for vLLM, refined blockers display, and fixes to accuracy checks. All changes consolidated in a single commit with quality formatting (Ruff).
July 2026
June 2026
21 Commits • 14 Features
Jun 1, 2026June 2026 — tt-inference-server (tenstorrent/tt-inference-server) achieved a major milestone by migrating core components to v2, expanding test coverage, and stabilizing upgrade paths. Key features delivered include routing Whisper models to v2 (plus adding Whisper to routed models and venv decoupling in v2_bridge.py), SDXL benchmark prompts update, and bridging prefix-cache benchmarks and agentic workflows to v2. Other notable work includes propagating the server URL into the v2 code path, migrating image models to v2, and enabling v2-focused tests (including unit tests and end-to-end tests). A new agentic skills framework was created, and the v2 tests ran in place of the previous tt-shield-based tests. Several stability fixes were implemented to improve reliability in production migrations and reporting (missing report uploads, SDXL concurrency, v1 Whisper removal, report run_command normalization, Motif test reliability). The combined effect improves time-to-market for v2 features, reduces upgrade risk, and increases confidence in benchmarking results.
June 2026
21 Commits • 14 Features
Jun 1, 2026June 2026 — tt-inference-server (tenstorrent/tt-inference-server) achieved a major milestone by migrating core components to v2, expanding test coverage, and stabilizing upgrade paths. Key features delivered include routing Whisper models to v2 (plus adding Whisper to routed models and venv decoupling in v2_bridge.py), SDXL benchmark prompts update, and bridging prefix-cache benchmarks and agentic workflows to v2. Other notable work includes propagating the server URL into the v2 code path, migrating image models to v2, and enabling v2-focused tests (including unit tests and end-to-end tests). A new agentic skills framework was created, and the v2 tests ran in place of the previous tt-shield-based tests. Several stability fixes were implemented to improve reliability in production migrations and reporting (missing report uploads, SDXL concurrency, v1 Whisper removal, report run_command normalization, Motif test reliability). The combined effect improves time-to-market for v2 features, reduces upgrade risk, and increases confidence in benchmarking results.
May 2026
21 Commits • 10 Features
May 1, 2026May 2026 monthly summary for tenstorrent/tt-inference-server: Delivered a major refactor of the V2 LLM module with a dedicated adapter layer for LLM benchmark tools, enabling unified benchmarking and faster performance validation. Introduced V2 stress tests and benchmark target checks to enforce performance targets. Migrated test infrastructure to V2 with categorization, suite-config, blockify tests, and renderer improvements, improving test coverage and maintainability. Ported critical upstream changes to tt-inference-server-v2 and extended reporting with missing metadata and multi-size benchmarks. Added SDXL routing to V2 workflows, initialization scaffolding, onboarding docs, and ongoing improvements to LoRA tests and evaluation metrics. Resolved a bug in reports output_dir and delivered core workflow improvements including workflow runner and command factory.
21 Commits • 10 Features
May 1, 2026May 2026 monthly summary for tenstorrent/tt-inference-server: Delivered a major refactor of the V2 LLM module with a dedicated adapter layer for LLM benchmark tools, enabling unified benchmarking and faster performance validation. Introduced V2 stress tests and benchmark target checks to enforce performance targets. Migrated test infrastructure to V2 with categorization, suite-config, blockify tests, and renderer improvements, improving test coverage and maintainability. Ported critical upstream changes to tt-inference-server-v2 and extended reporting with missing metadata and multi-size benchmarks. Added SDXL routing to V2 workflows, initialization scaffolding, onboarding docs, and ongoing improvements to LoRA tests and evaluation metrics. Resolved a bug in reports output_dir and delivered core workflow improvements including workflow runner and command factory.
May 2026
April 2026
4 Commits • 2 Features
Apr 1, 2026April 2026 monthly summary for tenstorrent/tt-inference-server. Focused on reliability, test infrastructure, and scalable reporting to support faster, high-quality deployments. Key features delivered include standardizing evaluation naming to improve cross-model consistency, enhancements to the testing framework with parameterized tests and better test organization, and a comprehensive overhaul of the reporting module to centralize markdown generation and improve evaluation accuracy. These efforts reduce flaky evaluations, accelerate validation cycles, and provide maintainable, auto-generated performance reporting for stakeholders.
April 2026
4 Commits • 2 Features
Apr 1, 2026April 2026 monthly summary for tenstorrent/tt-inference-server. Focused on reliability, test infrastructure, and scalable reporting to support faster, high-quality deployments. Key features delivered include standardizing evaluation naming to improve cross-model consistency, enhancements to the testing framework with parameterized tests and better test organization, and a comprehensive overhaul of the reporting module to centralize markdown generation and improve evaluation accuracy. These efforts reduce flaky evaluations, accelerate validation cycles, and provide maintainable, auto-generated performance reporting for stakeholders.
Activity
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Quality Metrics
Correctness87.2%
Maintainability84.2%
Architecture86.8%
Performance83.0%
AI Usage40.0%
Skills & Technologies
Programming Languages
BashJSONMarkdownPythonbashpython
Technical Skills
API developmentAPI testingCI/CDData AnalysisDevOpsMachine LearningPythonPython scriptingTestingVirtual Environment ConfigurationWorkflow Managementasync programmingasynchronous programmingaudio processingback end development
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