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Merge pull request #37 from codefuse-ai/modelcache_dev_mm
add todo list in readme.md
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README.md

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@@ -251,11 +251,23 @@ In ModelCache, we adopted the main idea of GPTCache, includes core modules: ada
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- Asynchronous log write-back capability for data analysis and statistics.
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- Added model field and data statistics field for feature expansion.
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Future Features Under Development:
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## Todo List
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### Adapter
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- [ ] Register adapter for Milvus:Based on the "model" parameter in the scope, initialize the corresponding Collection and perform the load operation.
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### Embedding model&inference
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- [ ] Inference Optimization: Optimizing the speed of embedding inference, compatible with inference engines such as FasterTransformer, TurboTransformers, and ByteTransformer.
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- [ ] Compatibility with Hugging Face models and ModelScope models, offering more methods for model loading.
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### Scalar Storage
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- [ ] Support MongoDB
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- [ ] Support ElasticSearch
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### Vector Storage
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- [ ] Adapts Faiss storage in multimodal scenarios.
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### Rank能力
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- [ ] Add ranking model to refine the order of data after embedding recall.
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### Service
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- [ ] Supports FastAPI.
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- [ ] Add visual interface to offer a more direct user experience.
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- [ ] Data isolation based on hyperparameters.
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- [ ] System prompt partitioning storage capability to enhance accuracy and efficiency of similarity matching.
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- [ ] More versatile embedding models and similarity evaluation algorithms.
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## Acknowledgements
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This project has referenced the following open-source projects. We would like to express our gratitude to the projects and their developers for their contributions and research.<br />[GPTCache](https://github.com/zilliztech/GPTCache)
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README_CN.md

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## Todo List
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### Adapter
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- [ ] register adapter for Milvus:根据scope中的model参数,初始化对应Collection 并且执行load操作。
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Embedding model&inference
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- [ ] inference优化:优化embedding推理速度,适配fastertransformer, TurboTransformers, ByteTransformer等推理引擎
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### Embedding model&inference
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- [ ] inference优化:优化embedding推理速度,适配fastertransformer, TurboTransformers, ByteTransformer等推理引擎
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- [ ] 兼容huggingface模型和modelscope模型,提供更多模型加载方式。
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### Scalar Storage
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- [ ] Support MongoDB
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- [ ] Support ElasticSearch
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- [ ] Support MongoDB
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- [ ] Support ElasticSearch
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### Vector Storage
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- [ ] 在多模态场景中适配faiss存储
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### Rank能力
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- [ ] 增加Rank模型,对embedding召回后的数据,进行精排
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- [ ] 在多模态场景中适配faiss存储
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### Ranking
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- [ ] 增加Rank模型,对embedding召回后的数据,进行精排
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### Service
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- [ ] 支持fastapi
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- [ ] 增加前端界面,用于测试
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- [ ] 支持fastapi
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- [ ] 增加前端界面,用于测试
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## 致谢
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本项目参考了以下开源项目,在此对相关项目和研究开发人员表示感谢。<br />[GPTCache](https://github.com/zilliztech/GPTCache)

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