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fix: add rope settings during model load, fix CUDA (#821)

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Signed-off-by: Ettore Di Giacinto <mudler@localai.io>
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Ettore Di Giacinto 2023-07-27 21:56:05 +02:00 committed by GitHub
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7 changed files with 176 additions and 148 deletions
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3
Makefile
View File

@ -4,8 +4,7 @@ GOVET=$(GOCMD) vet
BINARY_NAME=local-ai BINARY_NAME=local-ai
# llama.cpp versions # llama.cpp versions
# Temporarly pinned to https://github.com/go-skynet/go-llama.cpp/pull/124 GOLLAMA_VERSION?=6ba16de8e965e5aa0f32d25ef9d6149bb6586565
GOLLAMA_VERSION?=562d2b5a71195627a63bb34f639e0fb0e2b2df3f
# gpt4all version # gpt4all version
GPT4ALL_REPO?=https://github.com/nomic-ai/gpt4all GPT4ALL_REPO?=https://github.com/nomic-ai/gpt4all

7
README.md
View File

@ -13,15 +13,13 @@
**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. **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.
For a list of the supported model families, please see [the model compatibility table](https://localai.io/model-compatibility/index.html#model-compatibility-table).
In a nutshell: In a nutshell:
- Local, OpenAI drop-in alternative REST API. You own your data. - Local, OpenAI drop-in alternative REST API. You own your data.
- NO GPU required. NO Internet access is required either - NO GPU required. NO Internet access is required either
- Optional, GPU Acceleration is available in `llama.cpp`-compatible LLMs. See also the [build section](https://localai.io/basics/build/index.html). - Optional, GPU Acceleration is available in `llama.cpp`-compatible LLMs. See also the [build section](https://localai.io/basics/build/index.html).
- Supports multiple models: - Supports multiple models:
- 📖 [Text generation with GPTs](https://localai.io/features/text-generation/) (`llama.cpp`, `gpt4all.cpp`, ... and more) - 📖 [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))
- 🗣 [Text to Audio](https://localai.io/features/text-to-audio/) - 🗣 [Text to Audio](https://localai.io/features/text-to-audio/)
- 🔈 [Audio to Text](https://localai.io/features/audio-to-text/) (Audio transcription with `whisper.cpp`) - 🔈 [Audio to Text](https://localai.io/features/audio-to-text/) (Audio transcription with `whisper.cpp`)
- 🎨 [Image generation with stable diffusion](https://localai.io/features/image-generation) - 🎨 [Image generation with stable diffusion](https://localai.io/features/image-generation)
@ -31,6 +29,8 @@ In a nutshell:
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! 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!
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)!
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/). 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/).
@ -53,6 +53,7 @@ See the [Getting started](https://localai.io/basics/getting_started/index.html)
- [ ] Upstream our golang bindings to llama.cpp (https://github.com/ggerganov/llama.cpp/issues/351) - [ ] Upstream our golang bindings to llama.cpp (https://github.com/ggerganov/llama.cpp/issues/351)
- [ ] Enable gallery management directly from the webui. - [ ] Enable gallery management directly from the webui.
- [x] 🔥 OpenAI functions: https://github.com/go-skynet/LocalAI/issues/588 - [x] 🔥 OpenAI functions: https://github.com/go-skynet/LocalAI/issues/588
- [ ] 🔥 GPTQ support: https://github.com/go-skynet/LocalAI/issues/796
## News ## News

28
api/backend/options.go
View File

@ -15,19 +15,21 @@ func gRPCModelOpts(c config.Config) *pb.ModelOptions {
b = c.Batch b = c.Batch
} }
return &pb.ModelOptions{ return &pb.ModelOptions{
ContextSize: int32(c.ContextSize), ContextSize: int32(c.ContextSize),
Seed: int32(c.Seed), Seed: int32(c.Seed),
NBatch: int32(b), NBatch: int32(b),
F16Memory: c.F16, F16Memory: c.F16,
MLock: c.MMlock, MLock: c.MMlock,
NUMA: c.NUMA, RopeFreqBase: c.RopeFreqBase,
Embeddings: c.Embeddings, RopeFreqScale: c.RopeFreqScale,
LowVRAM: c.LowVRAM, NUMA: c.NUMA,
NGPULayers: int32(c.NGPULayers), Embeddings: c.Embeddings,
MMap: c.MMap, LowVRAM: c.LowVRAM,
MainGPU: c.MainGPU, NGPULayers: int32(c.NGPULayers),
Threads: int32(c.Threads), MMap: c.MMap,
TensorSplit: c.TensorSplit, MainGPU: c.MainGPU,
Threads: int32(c.Threads),
TensorSplit: c.TensorSplit,
} }
} }

36
extra/grpc/huggingface/backend_pb2.py
View File

@ -13,7 +13,7 @@ _sym_db = _symbol_database.Default()
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') 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')
_globals = globals() _globals = globals()
_builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals) _builder.BuildMessageAndEnumDescriptors(DESCRIPTOR, _globals)
@ -29,21 +29,21 @@ if _descriptor._USE_C_DESCRIPTORS == False:
_globals['_REPLY']._serialized_start=820 _globals['_REPLY']._serialized_start=820
_globals['_REPLY']._serialized_end=844 _globals['_REPLY']._serialized_end=844
_globals['_MODELOPTIONS']._serialized_start=847 _globals['_MODELOPTIONS']._serialized_start=847
_globals['_MODELOPTIONS']._serialized_end=1147 _globals['_MODELOPTIONS']._serialized_end=1192
_globals['_RESULT']._serialized_start=1149 _globals['_RESULT']._serialized_start=1194
_globals['_RESULT']._serialized_end=1191 _globals['_RESULT']._serialized_end=1236
_globals['_EMBEDDINGRESULT']._serialized_start=1193 _globals['_EMBEDDINGRESULT']._serialized_start=1238
_globals['_EMBEDDINGRESULT']._serialized_end=1230 _globals['_EMBEDDINGRESULT']._serialized_end=1275
_globals['_TRANSCRIPTREQUEST']._serialized_start=1232 _globals['_TRANSCRIPTREQUEST']._serialized_start=1277
_globals['_TRANSCRIPTREQUEST']._serialized_end=1299 _globals['_TRANSCRIPTREQUEST']._serialized_end=1344
_globals['_TRANSCRIPTRESULT']._serialized_start=1301 _globals['_TRANSCRIPTRESULT']._serialized_start=1346
_globals['_TRANSCRIPTRESULT']._serialized_end=1379 _globals['_TRANSCRIPTRESULT']._serialized_end=1424
_globals['_TRANSCRIPTSEGMENT']._serialized_start=1381 _globals['_TRANSCRIPTSEGMENT']._serialized_start=1426
_globals['_TRANSCRIPTSEGMENT']._serialized_end=1470 _globals['_TRANSCRIPTSEGMENT']._serialized_end=1515
_globals['_GENERATEIMAGEREQUEST']._serialized_start=1473 _globals['_GENERATEIMAGEREQUEST']._serialized_start=1518
_globals['_GENERATEIMAGEREQUEST']._serialized_end=1631 _globals['_GENERATEIMAGEREQUEST']._serialized_end=1676
_globals['_TTSREQUEST']._serialized_start=1633 _globals['_TTSREQUEST']._serialized_start=1678
_globals['_TTSREQUEST']._serialized_end=1687 _globals['_TTSREQUEST']._serialized_end=1732
_globals['_BACKEND']._serialized_start=1690 _globals['_BACKEND']._serialized_start=1735
_globals['_BACKEND']._serialized_end=2181 _globals['_BACKEND']._serialized_end=2226
# @@protoc_insertion_point(module_scope) # @@protoc_insertion_point(module_scope)

27
pkg/grpc/llm/llama/llama.go
View File

@ -17,7 +17,10 @@ type LLM struct {
} }
func (llm *LLM) Load(opts *pb.ModelOptions) error { 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 { if opts.ContextSize != 0 {
llamaOpts = append(llamaOpts, llama.SetContext(int(opts.ContextSize))) 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 { func buildPredictOptions(opts *pb.PredictOptions) []llama.PredictOption {
predictOptions := []llama.PredictOption{ predictOptions := []llama.PredictOption{
llama.SetTemperature(float64(opts.Temperature)), llama.SetTemperature(opts.Temperature),
llama.SetTopP(float64(opts.TopP)), llama.SetTopP(opts.TopP),
llama.SetTopK(int(opts.TopK)), llama.SetTopK(int(opts.TopK)),
llama.SetTokens(int(opts.Tokens)), llama.SetTokens(int(opts.Tokens)),
llama.SetThreads(int(opts.Threads)), llama.SetThreads(int(opts.Threads)),
llama.WithGrammar(opts.Grammar), llama.WithGrammar(opts.Grammar),
llama.SetRopeFreqBase(float64(opts.RopeFreqBase)), llama.SetRopeFreqBase(opts.RopeFreqBase),
llama.SetRopeFreqScale(float64(opts.RopeFreqScale)), llama.SetRopeFreqScale(opts.RopeFreqScale),
llama.SetNegativePromptScale(float64(opts.NegativePromptScale)), llama.SetNegativePromptScale(opts.NegativePromptScale),
llama.SetNegativePrompt(opts.NegativePrompt), llama.SetNegativePrompt(opts.NegativePrompt),
} }
@ -86,11 +89,11 @@ func buildPredictOptions(opts *pb.PredictOptions) []llama.PredictOption {
} }
if opts.MirostatETA != 0 { if opts.MirostatETA != 0 {
predictOptions = append(predictOptions, llama.SetMirostatETA(float64(opts.MirostatETA))) predictOptions = append(predictOptions, llama.SetMirostatETA(opts.MirostatETA))
} }
if opts.MirostatTAU != 0 { if opts.MirostatTAU != 0 {
predictOptions = append(predictOptions, llama.SetMirostatTAU(float64(opts.MirostatTAU))) predictOptions = append(predictOptions, llama.SetMirostatTAU(opts.MirostatTAU))
} }
if opts.Debug { if opts.Debug {
@ -100,7 +103,7 @@ func buildPredictOptions(opts *pb.PredictOptions) []llama.PredictOption {
predictOptions = append(predictOptions, llama.SetStopWords(opts.StopPrompts...)) predictOptions = append(predictOptions, llama.SetStopWords(opts.StopPrompts...))
if opts.PresencePenalty != 0 { if opts.PresencePenalty != 0 {
predictOptions = append(predictOptions, llama.SetPenalty(float64(opts.PresencePenalty))) predictOptions = append(predictOptions, llama.SetPenalty(opts.PresencePenalty))
} }
if opts.NKeep != 0 { 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.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.SetMlock(opts.MLock))
predictOptions = append(predictOptions, llama.SetMemoryMap(opts.MMap)) predictOptions = append(predictOptions, llama.SetMemoryMap(opts.MMap))
predictOptions = append(predictOptions, llama.SetPredictionMainGPU(opts.MainGPU)) predictOptions = append(predictOptions, llama.SetPredictionMainGPU(opts.MainGPU))
predictOptions = append(predictOptions, llama.SetPredictionTensorSplit(opts.TensorSplit)) predictOptions = append(predictOptions, llama.SetPredictionTensorSplit(opts.TensorSplit))
predictOptions = append(predictOptions, llama.SetTailFreeSamplingZ(float64(opts.TailFreeSamplingZ))) predictOptions = append(predictOptions, llama.SetTailFreeSamplingZ(opts.TailFreeSamplingZ))
predictOptions = append(predictOptions, llama.SetTypicalP(float64(opts.TypicalP))) predictOptions = append(predictOptions, llama.SetTypicalP(opts.TypicalP))
return predictOptions return predictOptions
} }

221
pkg/grpc/proto/backend.pb.go
View File

@ -463,22 +463,24 @@ type ModelOptions struct {
sizeCache protoimpl.SizeCache sizeCache protoimpl.SizeCache
unknownFields protoimpl.UnknownFields unknownFields protoimpl.UnknownFields
Model string `protobuf:"bytes,1,opt,name=Model,proto3" json:"Model,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"` ContextSize int32 `protobuf:"varint,2,opt,name=ContextSize,proto3" json:"ContextSize,omitempty"`
Seed int32 `protobuf:"varint,3,opt,name=Seed,proto3" json:"Seed,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"` NBatch int32 `protobuf:"varint,4,opt,name=NBatch,proto3" json:"NBatch,omitempty"`
F16Memory bool `protobuf:"varint,5,opt,name=F16Memory,proto3" json:"F16Memory,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"` MLock bool `protobuf:"varint,6,opt,name=MLock,proto3" json:"MLock,omitempty"`
MMap bool `protobuf:"varint,7,opt,name=MMap,proto3" json:"MMap,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"` VocabOnly bool `protobuf:"varint,8,opt,name=VocabOnly,proto3" json:"VocabOnly,omitempty"`
LowVRAM bool `protobuf:"varint,9,opt,name=LowVRAM,proto3" json:"LowVRAM,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"` Embeddings bool `protobuf:"varint,10,opt,name=Embeddings,proto3" json:"Embeddings,omitempty"`
NUMA bool `protobuf:"varint,11,opt,name=NUMA,proto3" json:"NUMA,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"` NGPULayers int32 `protobuf:"varint,12,opt,name=NGPULayers,proto3" json:"NGPULayers,omitempty"`
MainGPU string `protobuf:"bytes,13,opt,name=MainGPU,proto3" json:"MainGPU,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"` TensorSplit string `protobuf:"bytes,14,opt,name=TensorSplit,proto3" json:"TensorSplit,omitempty"`
Threads int32 `protobuf:"varint,15,opt,name=Threads,proto3" json:"Threads,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"` 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() { func (x *ModelOptions) Reset() {
@ -625,6 +627,20 @@ func (x *ModelOptions) GetLibrarySearchPath() string {
return "" 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 { type Result struct {
state protoimpl.MessageState state protoimpl.MessageState
sizeCache protoimpl.SizeCache sizeCache protoimpl.SizeCache
@ -1175,7 +1191,7 @@ var file_pkg_grpc_proto_backend_proto_rawDesc = []byte{
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@ -1203,90 +1219,95 @@ var file_pkg_grpc_proto_backend_proto_rawDesc = []byte{
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} }
var ( var (

2
pkg/grpc/proto/backend.proto
View File

@ -85,6 +85,8 @@ message ModelOptions {
string TensorSplit = 14; string TensorSplit = 14;
int32 Threads = 15; int32 Threads = 15;
string LibrarySearchPath = 16; string LibrarySearchPath = 16;
float RopeFreqBase = 17;
float RopeFreqScale = 18;
} }
message Result { message Result {