Ollama is a popular and active project, facilitating local use of large language models. It supports various OS and Docker, with detailed documentation and community integrations. However, the high number of open issues suggests potential challenges or areas for improvement.
39 open PRs indicate active community contributions, documentation updates, API enhancements, and code refactoring. Notable PRs include:
Recently opened issues (#1006 to #946) cover diverse topics from feature requests to software errors. Older open issues (#764 to #156) also cover a broad range of topics, indicating the project is actively used and tested in various scenarios.
The recently opened issues for this software project range from #1006 to #946. The issues are diverse, covering a wide range of topics. Some of the issues are requests for new features or enhancements, such as mobile app support (#1006), improved context window size management (#1005), and support for Modelfile management API (#1003). There are also several issues related to errors or problems with the software, such as models not loading after an upgrade (#998), issues with running Ollama on AWS (#997) and on a TPU (#990), and a segmentation fault with prompts longer than 5 / 6 tokens on an Intel Mac (#987). Other issues include requests for additional functionality such as adding message history to the /generate API (#981) and an option to "Save / Cache model in RAM" for faster switching (#976). There are also issues related to the use of Ollama in different environments, such as running it on a nix flake (#973) and viewing the Ollama server log (#967).
The older open issues range from #764 to #156. These issues are also diverse, covering a wide range of topics. Some of the issues are requests for new features or enhancements, such as support for more params when running Ollama (#902), setting correct rope frequency on llama2-chinese (#901), and support for multi-modal models (#746). There are also several issues related to errors or problems with the software, such as permissions error on ollama create on Linux (#892), low memory systems with a lot of VRAM hitting a memory issue (#939), and a digest mismatch on download (#941). Other issues include requests for additional functionality such as support for remote ollama create (#891), support for ppc64le architecture (#932), and support for image generating models (#786).
The recently closed issues are not provided in the list. However, based on the open issues, it can be inferred that the software project has a broad range of issues related to feature requests, software errors, and usage in different environments. The issues also indicate that the project is actively being used and tested in a variety of scenarios, suggesting a high level of user engagement and interest.
There are 39 open pull requests (PRs) for the software project, with the most recent ones being #1001, #1000, #999, #996, #994, #993, #992, #991, #988, #985, #980, #959, #955, #953, #952, #951, #944, #943, #898, #830, #814, #774, #723, #709, and #440.
Community Contributions: There are several PRs that add community integrations, such as PRs #1001, #999, and #996. This suggests that the project has an active community contributing to its development.
Documentation Updates: Several PRs aim to improve the project's documentation, like PRs #994, #992, #955, #944, and #723. This indicates that the project is actively being maintained and updated.
API Enhancements: PRs like #991, #988, and #952 propose enhancements to the project's API, suggesting that the project is evolving to meet new requirements or use cases.
Error Handling and Code Refactoring: PRs such as #993 and #814 focus on improving error handling and refactoring code, indicating an ongoing effort to improve the project's code quality and robustness.
PR #898 (create remote models): This PR has several review comments, indicating a disagreement or discussion about the implementation. The PR includes changes to multiple files and has a significant number of line changes, suggesting a substantial change to the project.
PR #830 (Add basic JSON Schema support to the API): This PR is based on another PR and adds a new feature to the API. It has been open for 18 days and has been edited recently, indicating that it might be a complex feature that requires more time to review and merge.
PR #814 (ROCm support): This PR has been open for 19 days and has been edited recently, indicating that it might be a complex feature that requires more time to review and merge. It also has several review comments, suggesting a discussion or disagreement about the implementation.
PR #774 (add version api and show server version in cli): This PR has been open for 23 days and has been edited recently. It also has several review comments, indicating a discussion or disagreement about the implementation.
No recently closed pull requests were provided in the data.
The Ollama project is a software designed to facilitate the local use of large language models like Llama 2. Created by jmorganca, the software is written in Go and licensed under the MIT License. The project provides a simple way to download, install, and run various language models on different operating systems, including macOS, Linux, and Windows (coming soon). It also supports Docker and provides detailed instructions for customizing and importing models.
The Ollama repository is quite active and popular, with a size of 5727 kB, 1269 commits, and 52 branches. It has garnered significant attention with 13446 stars and 691 forks. The repository has 159 open issues, indicating active development and community engagement. The software's technical architecture is primarily based on Go, and it utilizes a command-line interface for most of its operations. It also provides a REST API for running and managing models.
The repository stands out for its extensive documentation, including detailed instructions for installing and running the software on different platforms, customizing models, and using the REST API. It also provides a comprehensive list of community integrations, demonstrating its wide usage and adaptability. However, the high number of open issues may indicate potential challenges in using the software or areas for improvement. The project's popularity and active development suggest that it is a significant contribution to the field of language modeling.
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