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Local LLM Execution Capabilities (#35)
# *Local LLM Execution Capabilities* ## ♻️ Current situation & Problem As of now, the Spezi ecosystem (via `SpeziML`) provides an OpenAI integration for easy LLM execution. However, using a remote, opaque service like OpenAI comes with a multitude of challenges, especially in the health domain. The challenges include privacy, trust, security but also financial considerations. ## ⚙️ Release Notes - Renaming the SPM package (and the entire repo) from `SpeziML` to `SpeziLLM` to better reflect the current functionality of the package. - Complete restructuring of the package to support local and remote LLM execution. Introduced four separate targets `SpeziLLM` (providing base LLM infrastructure), `SpeziLLMLocal` (providing local execution capabilities), `SpeziLLMLocalDownload` (providing download and local storage functionality), as well as `SpeziLLMOpenAI` (providing a OpenAI GPT integration). All of these targets are subject to change in the upcoming releases. ## 📚 Documentation Documentation has been provided via inline DocC comments and code examples. ## ✅ Testing Wrote appropriate UI Tests which utilize an LLM mock. ## 📝 Code of Conduct & Contributing Guidelines By submitting creating this pull request, you agree to follow our [Code of Conduct](https://github.com/StanfordSpezi/.github/blob/main/CODE_OF_CONDUCT.md) and [Contributing Guidelines](https://github.com/StanfordSpezi/.github/blob/main/CONTRIBUTING.md): - [x] I agree to follow the [Code of Conduct](https://github.com/StanfordSpezi/.github/blob/main/CODE_OF_CONDUCT.md) and [Contributing Guidelines](https://github.com/StanfordSpezi/.github/blob/main/CONTRIBUTING.md). --------- Co-authored-by: Paul Schmiedmayer <PSchmiedmayer@users.noreply.github.com>
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