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OSS Report: ollama/ollama

Ollama Project Faces Critical Performance Challenges Amid Active Development

Ollama, a framework for running large language models locally, is experiencing notable issues with performance and hardware compatibility, particularly concerning AMD GPUs, while maintaining active development.

Recent Activity

Recent issues highlight significant challenges with performance and resource management. Notable issues include high CPU usage (#6901) and EOF errors (#6903), indicating potential inefficiencies and connectivity problems. Feature requests like tracking running requests (#6904) suggest a need for enhanced monitoring tools.

Development Team and Recent Activity

  1. Daniel Hiltgen (dhiltgen)

    • Fixed Windows CPU runner dependencies.
    • Enhanced CI for Windows ARM builds.
    • Added Windows ARM64 support.

  2. Patrick Devine (pdevine)

    • Improved model stopping documentation.
    • Fixed Gemma2-2B conversion issues.

  3. Ryan Marten (RyanMarten)

    • Added Python examples for community engagement.

  4. Michael Yang (mxyng)

    • Refactored show output, added model support.
    • Contributed to CI improvements.

  5. Jeffrey Morgan (jmorganca)

    • Implemented tool parsing support.
    • Worked on vision model support.

  6. Jesse Gross (jessegross)

    • Enhanced error handling in the runner.
    • Improved cache management.

Of Note

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Recent GitHub Issues Activity

Timespan Opened Closed Comments Labeled Milestones
7 Days 78 34 192 3 1
14 Days 160 87 467 4 1
30 Days 303 180 1064 7 1
All Time 4375 3358 - - -

Like all software activity quantification, these numbers are imperfect but sometimes useful. Comments, Labels, and Milestones refer to those issues opened in the timespan in question.

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Quantified Commit Activity Over 30 Days

Developer Avatar Branches PRs Commits Files Changes
Pascal Patry 1 2/1/0 1 2 24598
Jeffrey Morgan 4 10/9/1 13 262 23187
Daniel Hiltgen 3 36/30/5 32 59 2586
Patrick Devine 4 11/11/0 21 33 2193
Michael Yang 2 10/11/0 15 50 1964
Jesse Gross 4 12/11/0 19 10 1949
Josh 5 0/0/0 17 19 889
Ryan Marten 1 1/1/0 1 6 346
frob 1 4/2/1 2 2 60
R0CKSTAR 1 1/0/0 1 1 20
Vimal Kumar 1 1/1/0 1 1 13
Tomoya Fujita 1 0/1/0 1 1 9
Yaroslav 1 1/1/0 1 2 8
rayfiyo 1 1/1/0 1 1 6
FellowTraveler 1 0/0/0 1 1 6
Adrian Cole 1 1/1/0 1 3 6
dcasota 1 0/0/0 1 1 4
Rune Berg 1 0/1/0 1 1 4
王卿 1 0/0/0 1 1 4
Viz 1 1/1/0 1 1 3
Augustinas Malinauskas 1 0/0/0 1 1 3
Amith Koujalgi 1 1/1/0 1 1 3
Michael 1 0/0/0 1 1 2
Tobias Heinze 1 2/1/0 1 1 2
Erkin Alp Güney 1 0/1/0 1 1 2
Carter 1 0/1/0 1 1 2
Bryan Honof 1 0/0/0 1 1 2
SnoopyTlion 1 1/1/0 1 1 2
Sean Khatiri 1 1/1/0 1 1 2
Jonathan Hecl 1 1/1/0 1 1 2
RAPID ARCHITECT 1 3/2/1 2 1 2
Mitar 1 0/1/0 1 1 1
Petr Mironychev 1 1/1/0 1 1 1
Zeyo 1 0/0/0 1 1 1
imoize 1 1/1/0 1 1 1
Sam 1 1/1/0 1 1 1
Edward Cui 1 1/1/0 1 1 1
OpenVMP 1 1/1/0 1 1 1
Pepo 1 1/1/0 1 1 1
presbrey 1 2/1/0 1 1 1
Arda Günsüren 1 0/1/0 1 1 1
jk011ru 1 1/1/0 1 1 1
Michael Yang 1 1/1/0 1 1 1
亢奋猫 1 1/1/0 1 1 1
Silas Marvin 1 0/0/0 1 1 1
nickthecook 1 2/1/1 1 1 1
Teïlo M 1 0/0/0 1 1 1
Mateusz Migas 1 0/0/0 1 1 1
Vitaly Zdanevich 1 0/0/0 1 1 1
Yury Sokov (Yurzs) 0 1/0/0 0 0 0
None (alwqx) 0 1/0/1 0 0 0
None (nopoz) 0 1/0/0 0 0 0
None (tc-mb) 0 1/0/1 0 0 0
None (JHubi1) 0 1/0/0 0 0 0
Alessandro de Oliveira Faria (A.K.A.CABELO) (cabelo) 0 1/0/1 0 0 0
None (ecyht2) 0 1/0/0 0 0 0
None (JingWoo) 0 2/0/0 0 0 0
Amila Kumaranayaka (amila-ku) 0 1/0/0 0 0 0
Anuraag (Rag) Agrawal (anuraaga) 0 1/0/0 0 0 0
Meng Zhuo (mengzhuo) 0 1/0/0 0 0 0
Manjunath Kumatagi (mkumatag) 0 1/0/0 0 0 0
Yash Parmar (Yash-1511) 0 1/0/0 0 0 0
None (liufriendd) 0 1/0/1 0 0 0
Pablo (pnmartinez) 0 1/0/1 0 0 0
Anita Graser (anitagraser) 0 1/0/1 0 0 0
Gabe Goodhart (gabe-l-hart) 0 1/0/0 0 0 0
Hernan Martinez (hmartinez82) 0 0/0/1 0 0 0
Raymond Camden (cfjedimaster) 0 1/0/0 0 0 0
Ricky Bobby (rpreslar4765) 0 2/0/2 0 0 0
None (wallacelance) 0 1/0/0 0 0 0
Yu Bingjiao (yubingjiaocn) 0 1/0/0 0 0 0
Marcin Szczygliński (szczyglis-dev) 0 1/0/0 0 0 0
Vaibhav Acharya (VaibhavAcharya) 0 0/0/1 0 0 0

PRs: created by that dev and opened/merged/closed-unmerged during the period

Detailed Reports

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Recent Activity Analysis

The GitHub repository for the Ollama project shows significant recent activity, with 1017 open issues. Notably, issues related to model performance, bugs, and feature requests dominate the discussions. There are several critical bugs reported that could impact user experience, such as performance regressions and memory issues when running large models.

A recurring theme is the struggle with GPU utilization and memory management across various hardware configurations, particularly with AMD GPUs. Many users report crashes and slow performance, indicating potential underlying issues with the Ollama framework's compatibility with specific hardware setups.

Issue Details

Most Recently Created Issues

  1. Issue #6904: Option to know number of running requests in Ollama

    • Priority: Feature Request
    • Status: Open
    • Created: 0 days ago

  2. Issue #6903: nexusraven:13b-v2-q2_K EOF

    • Priority: Bug
    • Status: Open
    • Created: 0 days ago

  3. Issue #6902: No Ollama model can recognize the referenced information.

    • Priority: Bug
    • Status: Open
    • Created: 0 days ago

  4. Issue #6901: High CPU and slow token generation.

    • Priority: Bug
    • Status: Open
    • Created: 1 day ago

  5. Issue #6896: Model request for Ovis1.6-Gemma2-9B small vision model.

    • Priority: Model Request
    • Status: Open
    • Created: 1 day ago

Most Recently Updated Issues

  1. Issue #6889: Qwen/Qwen2.5-Math (Edited 1 day ago)

    • Priority: Model Request
    • Status: Open

  2. Issue #6888: An unknown error was encountered while running the model (Edited 1 day ago)

    • Priority: Bug
    • Status: Open

  3. Issue #6887: temperature for reader-lm should be 0 (Edited 1 day ago)

    • Priority: Model Request
    • Status: Open

  4. Issue #6886: Fetch model by hash (Edited 2 days ago)

    • Priority: Feature Request
    • Status: Open

  5. Issue #6885: Please support FreeBSD (Edited 1 day ago)

    • Priority: Feature Request
    • Status: Open

Analysis of Notable Issues

  • The issue regarding high CPU usage (#6901) indicates a potential inefficiency in how models utilize system resources, especially in CPU-only environments.
  • The EOF error in issue #6903 suggests connectivity or configuration problems that could hinder user experience.
  • The problem with models not recognizing referenced information (#6902) raises concerns about the robustness of the model's understanding capabilities.
  • The request for a feature to track running requests (#6904) reflects a need for better monitoring tools within the Ollama framework.

Common Themes

  • Many issues revolve around performance and resource management, particularly concerning GPU utilization and memory allocation.
  • Users frequently report difficulties with specific models, indicating inconsistencies in model behavior across different hardware configurations.
  • Feature requests often focus on enhancing usability and monitoring capabilities within the Ollama environment.

This analysis highlights critical areas for improvement within the Ollama project, particularly regarding performance optimization and user experience enhancements.

Report On: Fetch pull requests



Overview

The analysis of the provided pull requests (PRs) for the Ollama project reveals a dynamic and rapidly evolving software ecosystem. With a significant number of open and closed PRs, the project demonstrates active development and community engagement. The PRs cover a wide range of topics, including performance improvements, new features, bug fixes, documentation updates, and CI/CD enhancements.

Summary of Pull Requests

Open Pull Requests

  • #6905: Addresses CPU inference performance issues on Windows by adjusting process priority.
  • #6899: Introduces support for vision models in the runner, enhancing functionality and performance.
  • #6855: Cleans up unused environment variables in scripts.
  • #6854: Adds an environment variable to disable memory mapping globally.
  • #6850: Improves terminal input handling by allowing Ctrl-J for new lines.
  • #6845: Fixes race conditions in parallel make processes.
  • #6844: Prevents panics during sequence processing errors.
  • #6842: Refines Windows developer documentation for clarity and accuracy.
  • #6837: Adds support for the IBM POWER architecture.
  • #6784: Enhances OpenAI API integration with usage streaming options.
  • #6775: Notifies systemd when the Ollama server is ready.
  • #6760: Adds support for IBM granite/granitemoe architectures.

Closed Pull Requests

  • #6900, #6898, #6897, #6895: Various CI/CD improvements and adjustments for Windows ARM builds.
  • #6884: Fixes missing dependency paths on Windows CPU runners.
  • #6849, #6848, #6846, #6841: Add support for new tools, architectures, and improve existing functionalities.

Analysis of Pull Requests

The analysis of the PRs indicates several key themes:

  1. Performance Enhancements: Multiple PRs focus on improving performance across different platforms and configurations. For instance, PR #6905 addresses CPU inference performance on Windows by adjusting process priority, while PR #6899 introduces support for vision models, potentially enhancing model capabilities.

  2. Cross-Platform Support: The project shows a strong emphasis on cross-platform compatibility. PRs like #6837 add support for different architectures (e.g., IBM POWER), while others (#6854) introduce configuration options that affect behavior across platforms.

  3. Community Contributions: The presence of numerous community-driven integrations and enhancements (e.g., PR #6459 adding AutoGPT integration) highlights an active community contributing to the project's ecosystem.

  4. Continuous Improvement and Maintenance: The frequent updates to documentation (#6842), CI/CD pipelines (#6900), and bug fixes (#6784) reflect ongoing efforts to maintain and improve the software's reliability and usability.

  5. Feature Expansion: Several PRs introduce new features or expand existing ones (e.g., #6899 adding vision model support), indicating an active development effort aimed at enhancing the software's capabilities.

In conclusion, the Ollama project is characterized by active development, a focus on performance and cross-platform support, strong community engagement, and continuous improvement efforts. These factors contribute to its robustness as a framework for leveraging large language models locally.

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Repo Commits Analysis

Development Team and Recent Activity

Team Members and Their Recent Activities

  1. Daniel Hiltgen (dhiltgen)

    • Recent Commits: 32 commits across 59 files.
    • Key Contributions:
    • Fixed missing dependency paths for Windows CPU runners.
    • Made adjustments to CI for Windows ARM builds, including artifact distribution and step ordering.
    • Added Windows ARM64 support to official builds.
    • Improved documentation related to model stopping and troubleshooting.
    • Collaboration: Worked closely with other team members on CI improvements and documentation updates.

  2. Patrick Devine (pdevine)

    • Recent Commits: 21 commits across 33 files.
    • Key Contributions:
    • Documented stopping a model and improved import documentation.
    • Fixed issues related to the Gemma2-2B conversion.
    • Collaboration: Engaged in discussions on documentation with other developers.

  3. Ryan Marten (RyanMarten)

    • Recent Commits: 1 commit adding Python examples for bespoke-minicheck.
    • Key Contributions: Expanded example usage for community engagement.

  4. Michael Yang (mxyng)

    • Recent Commits: 15 commits across 50 files.
    • Key Contributions:
    • Refactored show output and added support for various models.
    • Contributed to CI improvements and integration of new features.
    • Collaboration: Actively merged pull requests from other developers.

  5. Jeffrey Morgan (jmorganca)

    • Recent Commits: 13 commits across 262 files.
    • Key Contributions:
    • Implemented tool parsing support and updated documentation for model usage.
    • Worked on vision model support in the runner.
    • Collaboration: Collaborated with Jesse Gross on runner improvements.

  6. Jesse Gross (jessegross)

    • Recent Commits: 19 commits across 10 files.
    • Key Contributions:
    • Enhanced error handling in the runner, preventing panics during sequence processing.
    • Improved cache management to optimize performance.
    • Collaboration: Worked with multiple team members on runner optimizations.

Patterns, Themes, and Conclusions

  • Focus on CI/CD Improvements: A significant portion of recent activity revolves around enhancing continuous integration processes, particularly for Windows builds. This indicates a strong commitment to ensuring robust deployment pipelines.

  • Documentation Enhancements: Several team members have contributed to improving documentation, which is crucial for user engagement and onboarding new contributors.

  • Active Collaboration: The development team exhibits a collaborative spirit, frequently merging pull requests from each other and addressing issues collectively.

  • Feature Expansion and Bug Fixes: The team is actively working on expanding features related to model support while simultaneously addressing bugs, particularly around model conversions and error handling.

  • Diverse Contributions Across Areas: Contributions span various areas including core functionality, CI improvements, documentation, and examples, showcasing a well-rounded approach to development.

Overall, the development team is actively engaged in enhancing the Ollama framework through collaborative efforts focused on improving functionality, user experience, and deployment processes.