mirror of
https://github.com/mudler/LocalAI.git
synced 2024-06-07 19:40:48 +00:00
fix: add rope settings during model load, fix CUDA (#821)
Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
This commit is contained in:
Ettore Di Giacinto
GitHub
parent
147cae9ed8
commit
096d98c3d9
3
Makefile
3
Makefile
@ -4,8 +4,7 @@ GOVET=$(GOCMD) vet
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BINARY_NAME=local-ai
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# llama.cpp versions
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# Temporarly pinned to https://github.com/go-skynet/go-llama.cpp/pull/124
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GOLLAMA_VERSION?=562d2b5a71195627a63bb34f639e0fb0e2b2df3f
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GOLLAMA_VERSION?=6ba16de8e965e5aa0f32d25ef9d6149bb6586565
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# gpt4all version
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GPT4ALL_REPO?=https://github.com/nomic-ai/gpt4all
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@ -13,15 +13,13 @@
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**LocalAI** is a drop-in replacement REST API that's compatible with OpenAI API specifications for local inferencing. It allows you to run LLMs (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families that are compatible with the ggml format. Does not require GPU.
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For a list of the supported model families, please see [the model compatibility table](https://localai.io/model-compatibility/index.html#model-compatibility-table).
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In a nutshell:
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- Local, OpenAI drop-in alternative REST API. You own your data.
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- NO GPU required. NO Internet access is required either
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- Optional, GPU Acceleration is available in `llama.cpp`-compatible LLMs. See also the [build section](https://localai.io/basics/build/index.html).
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- Supports multiple models:
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- 📖 [Text generation with GPTs](https://localai.io/features/text-generation/) (`llama.cpp`, `gpt4all.cpp`, ... and more)
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- 📖 [Text generation with GPTs](https://localai.io/features/text-generation/) (`llama.cpp`, `gpt4all.cpp`, ... [:book: and more](https://localai.io/model-compatibility/index.html#model-compatibility-table))
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- 🗣 [Text to Audio](https://localai.io/features/text-to-audio/)
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- 🔈 [Audio to Text](https://localai.io/features/audio-to-text/) (Audio transcription with `whisper.cpp`)
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- 🎨 [Image generation with stable diffusion](https://localai.io/features/image-generation)
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@ -31,6 +29,8 @@ In a nutshell:
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LocalAI was created by [Ettore Di Giacinto](https://github.com/mudler/) and is a community-driven project, focused on making the AI accessible to anyone. Any contribution, feedback and PR is welcome!
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Note that this started just as a [fun weekend project](https://localai.io/#backstory) in order to try to create the necessary pieces for a full AI assistant like `ChatGPT`: the community is growing fast and we are working hard to make it better and more stable. If you want to help, please consider contributing (see below)!
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See the [Getting started](https://localai.io/basics/getting_started/index.html) and [examples](https://github.com/go-skynet/LocalAI/tree/master/examples/) sections to learn how to use LocalAI. For a list of curated models check out the [model gallery](https://localai.io/models/).
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@ -53,6 +53,7 @@ See the [Getting started](https://localai.io/basics/getting_started/index.html)
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- [ ] Upstream our golang bindings to llama.cpp (https://github.com/ggerganov/llama.cpp/issues/351)
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- [ ] Enable gallery management directly from the webui.
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- [x] 🔥 OpenAI functions: https://github.com/go-skynet/LocalAI/issues/588
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- [ ] 🔥 GPTQ support: https://github.com/go-skynet/LocalAI/issues/796
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## News
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@ -15,19 +15,21 @@ func gRPCModelOpts(c config.Config) *pb.ModelOptions {
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b = c.Batch
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}
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return &pb.ModelOptions{
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ContextSize: int32(c.ContextSize),
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Seed: int32(c.Seed),
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NBatch: int32(b),
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F16Memory: c.F16,
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MLock: c.MMlock,
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NUMA: c.NUMA,
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Embeddings: c.Embeddings,
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LowVRAM: c.LowVRAM,
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NGPULayers: int32(c.NGPULayers),
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MMap: c.MMap,
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MainGPU: c.MainGPU,
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Threads: int32(c.Threads),
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TensorSplit: c.TensorSplit,
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ContextSize: int32(c.ContextSize),
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Seed: int32(c.Seed),
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NBatch: int32(b),
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F16Memory: c.F16,
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MLock: c.MMlock,
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RopeFreqBase: c.RopeFreqBase,
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RopeFreqScale: c.RopeFreqScale,
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NUMA: c.NUMA,
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Embeddings: c.Embeddings,
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LowVRAM: c.LowVRAM,
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NGPULayers: int32(c.NGPULayers),
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MMap: c.MMap,
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MainGPU: c.MainGPU,
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Threads: int32(c.Threads),
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TensorSplit: c.TensorSplit,
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}
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}
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@ -13,7 +13,7 @@ _sym_db = _symbol_database.Default()
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DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\rbackend.proto\x12\x07\x62\x61\x63kend\"\x0f\n\rHealthMessage\"\x86\x06\n\x0ePredictOptions\x12\x0e\n\x06Prompt\x18\x01 \x01(\t\x12\x0c\n\x04Seed\x18\x02 \x01(\x05\x12\x0f\n\x07Threads\x18\x03 \x01(\x05\x12\x0e\n\x06Tokens\x18\x04 \x01(\x05\x12\x0c\n\x04TopK\x18\x05 \x01(\x05\x12\x0e\n\x06Repeat\x18\x06 \x01(\x05\x12\r\n\x05\x42\x61tch\x18\x07 \x01(\x05\x12\r\n\x05NKeep\x18\x08 \x01(\x05\x12\x13\n\x0bTemperature\x18\t \x01(\x02\x12\x0f\n\x07Penalty\x18\n \x01(\x02\x12\r\n\x05\x46\x31\x36KV\x18\x0b \x01(\x08\x12\x11\n\tDebugMode\x18\x0c \x01(\x08\x12\x13\n\x0bStopPrompts\x18\r \x03(\t\x12\x11\n\tIgnoreEOS\x18\x0e \x01(\x08\x12\x19\n\x11TailFreeSamplingZ\x18\x0f \x01(\x02\x12\x10\n\x08TypicalP\x18\x10 \x01(\x02\x12\x18\n\x10\x46requencyPenalty\x18\x11 \x01(\x02\x12\x17\n\x0fPresencePenalty\x18\x12 \x01(\x02\x12\x10\n\x08Mirostat\x18\x13 \x01(\x05\x12\x13\n\x0bMirostatETA\x18\x14 \x01(\x02\x12\x13\n\x0bMirostatTAU\x18\x15 \x01(\x02\x12\x12\n\nPenalizeNL\x18\x16 \x01(\x08\x12\x11\n\tLogitBias\x18\x17 \x01(\t\x12\r\n\x05MLock\x18\x19 \x01(\x08\x12\x0c\n\x04MMap\x18\x1a \x01(\x08\x12\x16\n\x0ePromptCacheAll\x18\x1b \x01(\x08\x12\x15\n\rPromptCacheRO\x18\x1c \x01(\x08\x12\x0f\n\x07Grammar\x18\x1d \x01(\t\x12\x0f\n\x07MainGPU\x18\x1e \x01(\t\x12\x13\n\x0bTensorSplit\x18\x1f \x01(\t\x12\x0c\n\x04TopP\x18 \x01(\x02\x12\x17\n\x0fPromptCachePath\x18! \x01(\t\x12\r\n\x05\x44\x65\x62ug\x18\" \x01(\x08\x12\x17\n\x0f\x45mbeddingTokens\x18# \x03(\x05\x12\x12\n\nEmbeddings\x18$ \x01(\t\x12\x14\n\x0cRopeFreqBase\x18% \x01(\x02\x12\x15\n\rRopeFreqScale\x18& \x01(\x02\x12\x1b\n\x13NegativePromptScale\x18\' \x01(\x02\x12\x16\n\x0eNegativePrompt\x18( \x01(\t\"\x18\n\x05Reply\x12\x0f\n\x07message\x18\x01 \x01(\x0c\"\xac\x02\n\x0cModelOptions\x12\r\n\x05Model\x18\x01 \x01(\t\x12\x13\n\x0b\x43ontextSize\x18\x02 \x01(\x05\x12\x0c\n\x04Seed\x18\x03 \x01(\x05\x12\x0e\n\x06NBatch\x18\x04 \x01(\x05\x12\x11\n\tF16Memory\x18\x05 \x01(\x08\x12\r\n\x05MLock\x18\x06 \x01(\x08\x12\x0c\n\x04MMap\x18\x07 \x01(\x08\x12\x11\n\tVocabOnly\x18\x08 \x01(\x08\x12\x0f\n\x07LowVRAM\x18\t \x01(\x08\x12\x12\n\nEmbeddings\x18\n \x01(\x08\x12\x0c\n\x04NUMA\x18\x0b \x01(\x08\x12\x12\n\nNGPULayers\x18\x0c \x01(\x05\x12\x0f\n\x07MainGPU\x18\r \x01(\t\x12\x13\n\x0bTensorSplit\x18\x0e \x01(\t\x12\x0f\n\x07Threads\x18\x0f \x01(\x05\x12\x19\n\x11LibrarySearchPath\x18\x10 \x01(\t\"*\n\x06Result\x12\x0f\n\x07message\x18\x01 \x01(\t\x12\x0f\n\x07success\x18\x02 \x01(\x08\"%\n\x0f\x45mbeddingResult\x12\x12\n\nembeddings\x18\x01 \x03(\x02\"C\n\x11TranscriptRequest\x12\x0b\n\x03\x64st\x18\x02 \x01(\t\x12\x10\n\x08language\x18\x03 \x01(\t\x12\x0f\n\x07threads\x18\x04 \x01(\r\"N\n\x10TranscriptResult\x12,\n\x08segments\x18\x01 \x03(\x0b\x32\x1a.backend.TranscriptSegment\x12\x0c\n\x04text\x18\x02 \x01(\t\"Y\n\x11TranscriptSegment\x12\n\n\x02id\x18\x01 \x01(\x05\x12\r\n\x05start\x18\x02 \x01(\x03\x12\x0b\n\x03\x65nd\x18\x03 \x01(\x03\x12\x0c\n\x04text\x18\x04 \x01(\t\x12\x0e\n\x06tokens\x18\x05 \x03(\x05\"\x9e\x01\n\x14GenerateImageRequest\x12\x0e\n\x06height\x18\x01 \x01(\x05\x12\r\n\x05width\x18\x02 \x01(\x05\x12\x0c\n\x04mode\x18\x03 \x01(\x05\x12\x0c\n\x04step\x18\x04 \x01(\x05\x12\x0c\n\x04seed\x18\x05 \x01(\x05\x12\x17\n\x0fpositive_prompt\x18\x06 \x01(\t\x12\x17\n\x0fnegative_prompt\x18\x07 \x01(\t\x12\x0b\n\x03\x64st\x18\x08 \x01(\t\"6\n\nTTSRequest\x12\x0c\n\x04text\x18\x01 \x01(\t\x12\r\n\x05model\x18\x02 \x01(\t\x12\x0b\n\x03\x64st\x18\x03 \x01(\t2\xeb\x03\n\x07\x42\x61\x63kend\x12\x32\n\x06Health\x12\x16.backend.HealthMessage\x1a\x0e.backend.Reply\"\x00\x12\x34\n\x07Predict\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x12\x35\n\tLoadModel\x12\x15.backend.ModelOptions\x1a\x0f.backend.Result\"\x00\x12<\n\rPredictStream\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x30\x01\x12@\n\tEmbedding\x12\x17.backend.PredictOptions\x1a\x18.backend.EmbeddingResult\"\x00\x12\x41\n\rGenerateImage\x12\x1d.backend.GenerateImageRequest\x1a\x0f.backend.Result\"\x00\x12M\n\x12\x41udioTranscription\x12\x1a.backend.TranscriptRequest\x1a\x19.backend.TranscriptResult\"\x00\x12-\n\x03TTS\x12\x13.backend.TTSRequest\x1a\x0f.backend.Result\"\x00\x42Z\n\x19io.skynet.localai.backendB\x0eLocalAIBackendP\x01Z+github.com/go-skynet/LocalAI/pkg/grpc/protob\x06proto3')
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DESCRIPTOR = _descriptor_pool.Default().AddSerializedFile(b'\n\rbackend.proto\x12\x07\x62\x61\x63kend\"\x0f\n\rHealthMessage\"\x86\x06\n\x0ePredictOptions\x12\x0e\n\x06Prompt\x18\x01 \x01(\t\x12\x0c\n\x04Seed\x18\x02 \x01(\x05\x12\x0f\n\x07Threads\x18\x03 \x01(\x05\x12\x0e\n\x06Tokens\x18\x04 \x01(\x05\x12\x0c\n\x04TopK\x18\x05 \x01(\x05\x12\x0e\n\x06Repeat\x18\x06 \x01(\x05\x12\r\n\x05\x42\x61tch\x18\x07 \x01(\x05\x12\r\n\x05NKeep\x18\x08 \x01(\x05\x12\x13\n\x0bTemperature\x18\t \x01(\x02\x12\x0f\n\x07Penalty\x18\n \x01(\x02\x12\r\n\x05\x46\x31\x36KV\x18\x0b \x01(\x08\x12\x11\n\tDebugMode\x18\x0c \x01(\x08\x12\x13\n\x0bStopPrompts\x18\r \x03(\t\x12\x11\n\tIgnoreEOS\x18\x0e \x01(\x08\x12\x19\n\x11TailFreeSamplingZ\x18\x0f \x01(\x02\x12\x10\n\x08TypicalP\x18\x10 \x01(\x02\x12\x18\n\x10\x46requencyPenalty\x18\x11 \x01(\x02\x12\x17\n\x0fPresencePenalty\x18\x12 \x01(\x02\x12\x10\n\x08Mirostat\x18\x13 \x01(\x05\x12\x13\n\x0bMirostatETA\x18\x14 \x01(\x02\x12\x13\n\x0bMirostatTAU\x18\x15 \x01(\x02\x12\x12\n\nPenalizeNL\x18\x16 \x01(\x08\x12\x11\n\tLogitBias\x18\x17 \x01(\t\x12\r\n\x05MLock\x18\x19 \x01(\x08\x12\x0c\n\x04MMap\x18\x1a \x01(\x08\x12\x16\n\x0ePromptCacheAll\x18\x1b \x01(\x08\x12\x15\n\rPromptCacheRO\x18\x1c \x01(\x08\x12\x0f\n\x07Grammar\x18\x1d \x01(\t\x12\x0f\n\x07MainGPU\x18\x1e \x01(\t\x12\x13\n\x0bTensorSplit\x18\x1f \x01(\t\x12\x0c\n\x04TopP\x18 \x01(\x02\x12\x17\n\x0fPromptCachePath\x18! \x01(\t\x12\r\n\x05\x44\x65\x62ug\x18\" \x01(\x08\x12\x17\n\x0f\x45mbeddingTokens\x18# \x03(\x05\x12\x12\n\nEmbeddings\x18$ \x01(\t\x12\x14\n\x0cRopeFreqBase\x18% \x01(\x02\x12\x15\n\rRopeFreqScale\x18& \x01(\x02\x12\x1b\n\x13NegativePromptScale\x18\' \x01(\x02\x12\x16\n\x0eNegativePrompt\x18( \x01(\t\"\x18\n\x05Reply\x12\x0f\n\x07message\x18\x01 \x01(\x0c\"\xd9\x02\n\x0cModelOptions\x12\r\n\x05Model\x18\x01 \x01(\t\x12\x13\n\x0b\x43ontextSize\x18\x02 \x01(\x05\x12\x0c\n\x04Seed\x18\x03 \x01(\x05\x12\x0e\n\x06NBatch\x18\x04 \x01(\x05\x12\x11\n\tF16Memory\x18\x05 \x01(\x08\x12\r\n\x05MLock\x18\x06 \x01(\x08\x12\x0c\n\x04MMap\x18\x07 \x01(\x08\x12\x11\n\tVocabOnly\x18\x08 \x01(\x08\x12\x0f\n\x07LowVRAM\x18\t \x01(\x08\x12\x12\n\nEmbeddings\x18\n \x01(\x08\x12\x0c\n\x04NUMA\x18\x0b \x01(\x08\x12\x12\n\nNGPULayers\x18\x0c \x01(\x05\x12\x0f\n\x07MainGPU\x18\r \x01(\t\x12\x13\n\x0bTensorSplit\x18\x0e \x01(\t\x12\x0f\n\x07Threads\x18\x0f \x01(\x05\x12\x19\n\x11LibrarySearchPath\x18\x10 \x01(\t\x12\x14\n\x0cRopeFreqBase\x18\x11 \x01(\x02\x12\x15\n\rRopeFreqScale\x18\x12 \x01(\x02\"*\n\x06Result\x12\x0f\n\x07message\x18\x01 \x01(\t\x12\x0f\n\x07success\x18\x02 \x01(\x08\"%\n\x0f\x45mbeddingResult\x12\x12\n\nembeddings\x18\x01 \x03(\x02\"C\n\x11TranscriptRequest\x12\x0b\n\x03\x64st\x18\x02 \x01(\t\x12\x10\n\x08language\x18\x03 \x01(\t\x12\x0f\n\x07threads\x18\x04 \x01(\r\"N\n\x10TranscriptResult\x12,\n\x08segments\x18\x01 \x03(\x0b\x32\x1a.backend.TranscriptSegment\x12\x0c\n\x04text\x18\x02 \x01(\t\"Y\n\x11TranscriptSegment\x12\n\n\x02id\x18\x01 \x01(\x05\x12\r\n\x05start\x18\x02 \x01(\x03\x12\x0b\n\x03\x65nd\x18\x03 \x01(\x03\x12\x0c\n\x04text\x18\x04 \x01(\t\x12\x0e\n\x06tokens\x18\x05 \x03(\x05\"\x9e\x01\n\x14GenerateImageRequest\x12\x0e\n\x06height\x18\x01 \x01(\x05\x12\r\n\x05width\x18\x02 \x01(\x05\x12\x0c\n\x04mode\x18\x03 \x01(\x05\x12\x0c\n\x04step\x18\x04 \x01(\x05\x12\x0c\n\x04seed\x18\x05 \x01(\x05\x12\x17\n\x0fpositive_prompt\x18\x06 \x01(\t\x12\x17\n\x0fnegative_prompt\x18\x07 \x01(\t\x12\x0b\n\x03\x64st\x18\x08 \x01(\t\"6\n\nTTSRequest\x12\x0c\n\x04text\x18\x01 \x01(\t\x12\r\n\x05model\x18\x02 \x01(\t\x12\x0b\n\x03\x64st\x18\x03 \x01(\t2\xeb\x03\n\x07\x42\x61\x63kend\x12\x32\n\x06Health\x12\x16.backend.HealthMessage\x1a\x0e.backend.Reply\"\x00\x12\x34\n\x07Predict\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x12\x35\n\tLoadModel\x12\x15.backend.ModelOptions\x1a\x0f.backend.Result\"\x00\x12<\n\rPredictStream\x12\x17.backend.PredictOptions\x1a\x0e.backend.Reply\"\x00\x30\x01\x12@\n\tEmbedding\x12\x17.backend.PredictOptions\x1a\x18.backend.EmbeddingResult\"\x00\x12\x41\n\rGenerateImage\x12\x1d.backend.GenerateImageRequest\x1a\x0f.backend.Result\"\x00\x12M\n\x12\x41udioTranscription\x12\x1a.backend.TranscriptRequest\x1a\x19.backend.TranscriptResult\"\x00\x12-\n\x03TTS\x12\x13.backend.TTSRequest\x1a\x0f.backend.Result\"\x00\x42Z\n\x19io.skynet.localai.backendB\x0eLocalAIBackendP\x01Z+github.com/go-skynet/LocalAI/pkg/grpc/protob\x06proto3')
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_globals = globals()
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_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
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@ -29,21 +29,21 @@ if _descriptor._USE_C_DESCRIPTORS == False:
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_globals['_REPLY']._serialized_start=820
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_globals['_REPLY']._serialized_end=844
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_globals['_MODELOPTIONS']._serialized_start=847
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_globals['_MODELOPTIONS']._serialized_end=1147
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_globals['_RESULT']._serialized_start=1149
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_globals['_RESULT']._serialized_end=1191
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_globals['_EMBEDDINGRESULT']._serialized_start=1193
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_globals['_EMBEDDINGRESULT']._serialized_end=1230
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_globals['_TRANSCRIPTREQUEST']._serialized_start=1232
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_globals['_TRANSCRIPTREQUEST']._serialized_end=1299
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_globals['_TRANSCRIPTRESULT']._serialized_start=1301
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_globals['_TRANSCRIPTRESULT']._serialized_end=1379
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_globals['_TRANSCRIPTSEGMENT']._serialized_start=1381
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_globals['_TRANSCRIPTSEGMENT']._serialized_end=1470
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_globals['_GENERATEIMAGEREQUEST']._serialized_start=1473
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_globals['_GENERATEIMAGEREQUEST']._serialized_end=1631
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_globals['_TTSREQUEST']._serialized_start=1633
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_globals['_TTSREQUEST']._serialized_end=1687
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_globals['_BACKEND']._serialized_start=1690
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_globals['_BACKEND']._serialized_end=2181
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_globals['_MODELOPTIONS']._serialized_end=1192
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_globals['_RESULT']._serialized_start=1194
|
||||
_globals['_RESULT']._serialized_end=1236
|
||||
_globals['_EMBEDDINGRESULT']._serialized_start=1238
|
||||
_globals['_EMBEDDINGRESULT']._serialized_end=1275
|
||||
_globals['_TRANSCRIPTREQUEST']._serialized_start=1277
|
||||
_globals['_TRANSCRIPTREQUEST']._serialized_end=1344
|
||||
_globals['_TRANSCRIPTRESULT']._serialized_start=1346
|
||||
_globals['_TRANSCRIPTRESULT']._serialized_end=1424
|
||||
_globals['_TRANSCRIPTSEGMENT']._serialized_start=1426
|
||||
_globals['_TRANSCRIPTSEGMENT']._serialized_end=1515
|
||||
_globals['_GENERATEIMAGEREQUEST']._serialized_start=1518
|
||||
_globals['_GENERATEIMAGEREQUEST']._serialized_end=1676
|
||||
_globals['_TTSREQUEST']._serialized_start=1678
|
||||
_globals['_TTSREQUEST']._serialized_end=1732
|
||||
_globals['_BACKEND']._serialized_start=1735
|
||||
_globals['_BACKEND']._serialized_end=2226
|
||||
# @@protoc_insertion_point(module_scope)
|
||||
|
||||
@ -17,7 +17,10 @@ type LLM struct {
|
||||
}
|
||||
|
||||
func (llm *LLM) Load(opts *pb.ModelOptions) error {
|
||||
llamaOpts := []llama.ModelOption{}
|
||||
llamaOpts := []llama.ModelOption{
|
||||
llama.WithRopeFreqBase(opts.RopeFreqBase),
|
||||
llama.WithRopeFreqScale(opts.RopeFreqScale),
|
||||
}
|
||||
|
||||
if opts.ContextSize != 0 {
|
||||
llamaOpts = append(llamaOpts, llama.SetContext(int(opts.ContextSize)))
|
||||
@ -56,15 +59,15 @@ func (llm *LLM) Load(opts *pb.ModelOptions) error {
|
||||
|
||||
func buildPredictOptions(opts *pb.PredictOptions) []llama.PredictOption {
|
||||
predictOptions := []llama.PredictOption{
|
||||
llama.SetTemperature(float64(opts.Temperature)),
|
||||
llama.SetTopP(float64(opts.TopP)),
|
||||
llama.SetTemperature(opts.Temperature),
|
||||
llama.SetTopP(opts.TopP),
|
||||
llama.SetTopK(int(opts.TopK)),
|
||||
llama.SetTokens(int(opts.Tokens)),
|
||||
llama.SetThreads(int(opts.Threads)),
|
||||
llama.WithGrammar(opts.Grammar),
|
||||
llama.SetRopeFreqBase(float64(opts.RopeFreqBase)),
|
||||
llama.SetRopeFreqScale(float64(opts.RopeFreqScale)),
|
||||
llama.SetNegativePromptScale(float64(opts.NegativePromptScale)),
|
||||
llama.SetRopeFreqBase(opts.RopeFreqBase),
|
||||
llama.SetRopeFreqScale(opts.RopeFreqScale),
|
||||
llama.SetNegativePromptScale(opts.NegativePromptScale),
|
||||
llama.SetNegativePrompt(opts.NegativePrompt),
|
||||
}
|
||||
|
||||
@ -86,11 +89,11 @@ func buildPredictOptions(opts *pb.PredictOptions) []llama.PredictOption {
|
||||
}
|
||||
|
||||
if opts.MirostatETA != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetMirostatETA(float64(opts.MirostatETA)))
|
||||
predictOptions = append(predictOptions, llama.SetMirostatETA(opts.MirostatETA))
|
||||
}
|
||||
|
||||
if opts.MirostatTAU != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetMirostatTAU(float64(opts.MirostatTAU)))
|
||||
predictOptions = append(predictOptions, llama.SetMirostatTAU(opts.MirostatTAU))
|
||||
}
|
||||
|
||||
if opts.Debug {
|
||||
@ -100,7 +103,7 @@ func buildPredictOptions(opts *pb.PredictOptions) []llama.PredictOption {
|
||||
predictOptions = append(predictOptions, llama.SetStopWords(opts.StopPrompts...))
|
||||
|
||||
if opts.PresencePenalty != 0 {
|
||||
predictOptions = append(predictOptions, llama.SetPenalty(float64(opts.PresencePenalty)))
|
||||
predictOptions = append(predictOptions, llama.SetPenalty(opts.PresencePenalty))
|
||||
}
|
||||
|
||||
if opts.NKeep != 0 {
|
||||
@ -125,13 +128,13 @@ func buildPredictOptions(opts *pb.PredictOptions) []llama.PredictOption {
|
||||
|
||||
//predictOptions = append(predictOptions, llama.SetLogitBias(c.Seed))
|
||||
|
||||
predictOptions = append(predictOptions, llama.SetFrequencyPenalty(float64(opts.FrequencyPenalty)))
|
||||
predictOptions = append(predictOptions, llama.SetFrequencyPenalty(opts.FrequencyPenalty))
|
||||
predictOptions = append(predictOptions, llama.SetMlock(opts.MLock))
|
||||
predictOptions = append(predictOptions, llama.SetMemoryMap(opts.MMap))
|
||||
predictOptions = append(predictOptions, llama.SetPredictionMainGPU(opts.MainGPU))
|
||||
predictOptions = append(predictOptions, llama.SetPredictionTensorSplit(opts.TensorSplit))
|
||||
predictOptions = append(predictOptions, llama.SetTailFreeSamplingZ(float64(opts.TailFreeSamplingZ)))
|
||||
predictOptions = append(predictOptions, llama.SetTypicalP(float64(opts.TypicalP)))
|
||||
predictOptions = append(predictOptions, llama.SetTailFreeSamplingZ(opts.TailFreeSamplingZ))
|
||||
predictOptions = append(predictOptions, llama.SetTypicalP(opts.TypicalP))
|
||||
return predictOptions
|
||||
}
|
||||
|
||||
|
||||
@ -463,22 +463,24 @@ type ModelOptions struct {
|
||||
sizeCache protoimpl.SizeCache
|
||||
unknownFields protoimpl.UnknownFields
|
||||
|
||||
Model string `protobuf:"bytes,1,opt,name=Model,proto3" json:"Model,omitempty"`
|
||||
ContextSize int32 `protobuf:"varint,2,opt,name=ContextSize,proto3" json:"ContextSize,omitempty"`
|
||||
Seed int32 `protobuf:"varint,3,opt,name=Seed,proto3" json:"Seed,omitempty"`
|
||||
NBatch int32 `protobuf:"varint,4,opt,name=NBatch,proto3" json:"NBatch,omitempty"`
|
||||
F16Memory bool `protobuf:"varint,5,opt,name=F16Memory,proto3" json:"F16Memory,omitempty"`
|
||||
MLock bool `protobuf:"varint,6,opt,name=MLock,proto3" json:"MLock,omitempty"`
|
||||
MMap bool `protobuf:"varint,7,opt,name=MMap,proto3" json:"MMap,omitempty"`
|
||||
VocabOnly bool `protobuf:"varint,8,opt,name=VocabOnly,proto3" json:"VocabOnly,omitempty"`
|
||||
LowVRAM bool `protobuf:"varint,9,opt,name=LowVRAM,proto3" json:"LowVRAM,omitempty"`
|
||||
Embeddings bool `protobuf:"varint,10,opt,name=Embeddings,proto3" json:"Embeddings,omitempty"`
|
||||
NUMA bool `protobuf:"varint,11,opt,name=NUMA,proto3" json:"NUMA,omitempty"`
|
||||
NGPULayers int32 `protobuf:"varint,12,opt,name=NGPULayers,proto3" json:"NGPULayers,omitempty"`
|
||||
MainGPU string `protobuf:"bytes,13,opt,name=MainGPU,proto3" json:"MainGPU,omitempty"`
|
||||
TensorSplit string `protobuf:"bytes,14,opt,name=TensorSplit,proto3" json:"TensorSplit,omitempty"`
|
||||
Threads int32 `protobuf:"varint,15,opt,name=Threads,proto3" json:"Threads,omitempty"`
|
||||
LibrarySearchPath string `protobuf:"bytes,16,opt,name=LibrarySearchPath,proto3" json:"LibrarySearchPath,omitempty"`
|
||||
Model string `protobuf:"bytes,1,opt,name=Model,proto3" json:"Model,omitempty"`
|
||||
ContextSize int32 `protobuf:"varint,2,opt,name=ContextSize,proto3" json:"ContextSize,omitempty"`
|
||||
Seed int32 `protobuf:"varint,3,opt,name=Seed,proto3" json:"Seed,omitempty"`
|
||||
NBatch int32 `protobuf:"varint,4,opt,name=NBatch,proto3" json:"NBatch,omitempty"`
|
||||
F16Memory bool `protobuf:"varint,5,opt,name=F16Memory,proto3" json:"F16Memory,omitempty"`
|
||||
MLock bool `protobuf:"varint,6,opt,name=MLock,proto3" json:"MLock,omitempty"`
|
||||
MMap bool `protobuf:"varint,7,opt,name=MMap,proto3" json:"MMap,omitempty"`
|
||||
VocabOnly bool `protobuf:"varint,8,opt,name=VocabOnly,proto3" json:"VocabOnly,omitempty"`
|
||||
LowVRAM bool `protobuf:"varint,9,opt,name=LowVRAM,proto3" json:"LowVRAM,omitempty"`
|
||||
Embeddings bool `protobuf:"varint,10,opt,name=Embeddings,proto3" json:"Embeddings,omitempty"`
|
||||
NUMA bool `protobuf:"varint,11,opt,name=NUMA,proto3" json:"NUMA,omitempty"`
|
||||
NGPULayers int32 `protobuf:"varint,12,opt,name=NGPULayers,proto3" json:"NGPULayers,omitempty"`
|
||||
MainGPU string `protobuf:"bytes,13,opt,name=MainGPU,proto3" json:"MainGPU,omitempty"`
|
||||
TensorSplit string `protobuf:"bytes,14,opt,name=TensorSplit,proto3" json:"TensorSplit,omitempty"`
|
||||
Threads int32 `protobuf:"varint,15,opt,name=Threads,proto3" json:"Threads,omitempty"`
|
||||
LibrarySearchPath string `protobuf:"bytes,16,opt,name=LibrarySearchPath,proto3" json:"LibrarySearchPath,omitempty"`
|
||||
RopeFreqBase float32 `protobuf:"fixed32,17,opt,name=RopeFreqBase,proto3" json:"RopeFreqBase,omitempty"`
|
||||
RopeFreqScale float32 `protobuf:"fixed32,18,opt,name=RopeFreqScale,proto3" json:"RopeFreqScale,omitempty"`
|
||||
}
|
||||
|
||||
func (x *ModelOptions) Reset() {
|
||||
@ -625,6 +627,20 @@ func (x *ModelOptions) GetLibrarySearchPath() string {
|
||||
return ""
|
||||
}
|
||||
|
||||
func (x *ModelOptions) GetRopeFreqBase() float32 {
|
||||
if x != nil {
|
||||
return x.RopeFreqBase
|
||||
}
|
||||
return 0
|
||||
}
|
||||
|
||||
func (x *ModelOptions) GetRopeFreqScale() float32 {
|
||||
if x != nil {
|
||||
return x.RopeFreqScale
|
||||
}
|
||||
return 0
|
||||
}
|
||||
|
||||
type Result struct {
|
||||
state protoimpl.MessageState
|
||||
sizeCache protoimpl.SizeCache
|
||||
@ -1175,7 +1191,7 @@ var file_pkg_grpc_proto_backend_proto_rawDesc = []byte{
|
||||
0x0e, 0x4e, 0x65, 0x67, 0x61, 0x74, 0x69, 0x76, 0x65, 0x50, 0x72, 0x6f, 0x6d, 0x70, 0x74, 0x22,
|
||||
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|
||||
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|
||||
0x67, 0x65, 0x22, 0xca, 0x03, 0x0a, 0x0c, 0x4d, 0x6f, 0x64, 0x65, 0x6c, 0x4f, 0x70, 0x74, 0x69,
|
||||
0x67, 0x65, 0x22, 0x94, 0x04, 0x0a, 0x0c, 0x4d, 0x6f, 0x64, 0x65, 0x6c, 0x4f, 0x70, 0x74, 0x69,
|
||||
0x6f, 0x6e, 0x73, 0x12, 0x14, 0x0a, 0x05, 0x4d, 0x6f, 0x64, 0x65, 0x6c, 0x18, 0x01, 0x20, 0x01,
|
||||
0x28, 0x09, 0x52, 0x05, 0x4d, 0x6f, 0x64, 0x65, 0x6c, 0x12, 0x20, 0x0a, 0x0b, 0x43, 0x6f, 0x6e,
|
||||
0x74, 0x65, 0x78, 0x74, 0x53, 0x69, 0x7a, 0x65, 0x18, 0x02, 0x20, 0x01, 0x28, 0x05, 0x52, 0x0b,
|
||||
@ -1203,90 +1219,95 @@ var file_pkg_grpc_proto_backend_proto_rawDesc = []byte{
|
||||
0x64, 0x73, 0x18, 0x0f, 0x20, 0x01, 0x28, 0x05, 0x52, 0x07, 0x54, 0x68, 0x72, 0x65, 0x61, 0x64,
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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0x74, 0x6f, 0x33,
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||||
}
|
||||
|
||||
var (
|
||||
|
||||
@ -85,6 +85,8 @@ message ModelOptions {
|
||||
string TensorSplit = 14;
|
||||
int32 Threads = 15;
|
||||
string LibrarySearchPath = 16;
|
||||
float RopeFreqBase = 17;
|
||||
float RopeFreqScale = 18;
|
||||
}
|
||||
|
||||
message Result {
|
||||
|
||||
Loading…
Reference in New Issue
Block a user