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release v1.1.1

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will.yang
2024-10-18 18:14:14 +08:00
parent 71773f050a
commit 61edffefc1
15 changed files with 229 additions and 104 deletions
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8
rkllm-runtime/examples/rkllm_server_demo/README.md
View File

@@ -8,8 +8,8 @@ Before running the demo, you need to prepare the following files:
### Build
You can run the demo with the only command:
```bash
# Usage: ./build_rkllm_server_flask.sh --workshop [RKLLM-Server Working Path] --model_path [Absolute Path of Converted RKLLM Model on Board] --platform [Target Platform: rk3588/rk3576] --npu_num [NPU Core Count] [--lora_model_path [Lora Model Path]] [--prompt_cache_path [Prompt Cache File Path]]
./build_rkllm_server_flask.sh --workshop /user/data --model_path /user/data/model.rkllm --platform rk3588 --npu_num 3
# Usage: ./build_rkllm_server_flask.sh --workshop [RKLLM-Server Working Path] --model_path [Absolute Path of Converted RKLLM Model on Board] --platform [Target Platform: rk3588/rk3576] [--lora_model_path [Lora Model Path]] [--prompt_cache_path [Prompt Cache File Path]]
./build_rkllm_server_flask.sh --workshop /user/data --model_path /user/data/model.rkllm --platform rk3588
```
### Access with API
After building the RKLLM-Server-Flask, You can use ‘chat_api_flask.py’ to access the RKLLM-Server-Flask and get the answser of RKLLM models.
@@ -20,8 +20,8 @@ Attention: you should check the IP address of the board with 'ifconfig' command
### Build
You can run the demo with the only command:
```bash
# Usage: ./build_rkllm_server_gradio.sh --workshop [RKLLM-Server Working Path] --model_path [Absolute Path of Converted RKLLM Model on Board] --platform [Target Platform: rk3588/rk3576] --npu_num [NPU Core Count] [--lora_model_path [Lora Model Path]] [--prompt_cache_path [Prompt Cache File Path]]
./build_rkllm_server_gradio.sh --workshop /user/data --model_path /user/data/model.rkllm --platform rk3588 --npu_num 3
# Usage: ./build_rkllm_server_gradio.sh --workshop [RKLLM-Server Working Path] --model_path [Absolute Path of Converted RKLLM Model on Board] --platform [Target Platform: rk3588/rk3576] [--lora_model_path [Lora Model Path]] [--prompt_cache_path [Prompt Cache File Path]]
./build_rkllm_server_gradio.sh --workshop /user/data --model_path /user/data/model.rkllm --platform rk3588
```
### Access the Server
After running the demo, You can access the RKLLM-Server-Gradio with two ways:

12
rkllm-runtime/examples/rkllm_server_demo/build_rkllm_server_flask.sh
View File

@@ -3,8 +3,8 @@
#*****************************************************************************************#
# This script is an automated setup script for the RKLLM-Server-Flask service.
# Users can run this script to automate the deployment of the RKLLM-Server-Flask service on a Linux board.
# Usage: ./build_rkllm_server_flask.sh --workshop [RKLLM-Server Working Path] --model_path [Absolute Path of Converted RKLLM Model on Board] --platform [Target Platform: rk3588/rk3576] --npu_num [NPU Core Count] [--lora_model_path [Lora Model Path]] [--prompt_cache_path [Prompt Cache File Path]]
# example: ./build_rkllm_server_flask.sh --workshop /user/data --model_path /user/data/model.rkllm --platform rk3588 --npu_num 3
# Usage: ./build_rkllm_server_flask.sh --workshop [RKLLM-Server Working Path] --model_path [Absolute Path of Converted RKLLM Model on Board] --platform [Target Platform: rk3588/rk3576] [--lora_model_path [Lora Model Path]] [--prompt_cache_path [Prompt Cache File Path]]
# example: ./build_rkllm_server_flask.sh --workshop /user/data --model_path /user/data/model.rkllm --platform rk3588
#*****************************************************************************************#
LORA_PATH=""
@@ -12,7 +12,7 @@ PROMPT_FILE_PATH=""
# Function to display help
function show_help {
echo "Usage: ./build_rkllm_server_flask.sh --workshop [RKLLM-Server Working Path] --model_path [Absolute Path of Converted RKLLM Model on Board] --platform [Target Platform: rk3588/rk3576] --npu_num [NPU Core Count] [--lora_path [Lora Model Path]] [--prompt_cache_path [Prompt Cache File Path]]"
echo "Usage: ./build_rkllm_server_flask.sh --workshop [RKLLM-Server Working Path] --model_path [Absolute Path of Converted RKLLM Model on Board] --platform [Target Platform: rk3588/rk3576] [--lora_path [Lora Model Path]] [--prompt_cache_path [Prompt Cache File Path]]"
}
# Parse command-line options
@@ -30,10 +30,6 @@ while [[ $# -gt 0 ]]; do
TARGET_PLATFORM="$2"
shift 2
;;
--npu_num)
NPU_CORE_COUNT="$2"
shift 2
;;
--lora_model_path)
LORA_PATH="$2"
shift 2
@@ -93,7 +89,7 @@ cp ../../runtime/Linux/librkllm_api/aarch64/librkllmrt.so ./rkllm_server/lib/
adb push ./rkllm_server $WORKING_PATH
#################### Enter the board terminal and start the server service. ####################
CMD="python3 flask_server.py --rkllm_model_path $MODEL_PATH --target_platform $TARGET_PLATFORM --num_npu_core $NPU_CORE_COUNT"
CMD="python3 flask_server.py --rkllm_model_path $MODEL_PATH --target_platform $TARGET_PLATFORM"
if [[ -n "$LORA_PATH" ]]; then
CMD="$CMD --lora_model_path $LORA_PATH"
fi

12
rkllm-runtime/examples/rkllm_server_demo/build_rkllm_server_gradio.sh
View File

@@ -3,8 +3,8 @@
#*****************************************************************************************#
# This script is an automated setup script for the RKLLM-Server-Gradio service.
# Users can run this script to automate the deployment of the RKLLM-Server-Gradio service on a Linux board.
# Usage: ./build_rkllm_server_gradio.sh --workshop [RKLLM-Server Working Path] --model_path [Absolute Path of Converted RKLLM Model on Board] --platform [Target Platform: rk3588/rk3576] --npu_num [NPU Core Count] [--lora_model_path [Lora Model Path]] [--prompt_cache_path [Prompt Cache File Path]]
# example: ./build_rkllm_server_gradio.sh --workshop /user/data --model_path /user/data/model.rkllm --platform rk3588 --npu_num 3
# Usage: ./build_rkllm_server_gradio.sh --workshop [RKLLM-Server Working Path] --model_path [Absolute Path of Converted RKLLM Model on Board] --platform [Target Platform: rk3588/rk3576] [--lora_model_path [Lora Model Path]] [--prompt_cache_path [Prompt Cache File Path]]
# example: ./build_rkllm_server_gradio.sh --workshop /user/data --model_path /user/data/model.rkllm --platform rk3588
#*****************************************************************************************#
LORA_PATH=""
@@ -12,7 +12,7 @@ PROMPT_FILE_PATH=""
# Function to display help
function show_help {
echo "Usage: ./build_rkllm_server_gradio.sh --workshop [RKLLM-Server Working Path] --model_path [Absolute Path of Converted RKLLM Model on Board] --platform [Target Platform: rk3588/rk3576] --npu_num [NPU Core Count] [--lora_path [Lora Model Path]] [--prompt_cache_path [Prompt Cache File Path]]"
echo "Usage: ./build_rkllm_server_gradio.sh --workshop [RKLLM-Server Working Path] --model_path [Absolute Path of Converted RKLLM Model on Board] --platform [Target Platform: rk3588/rk3576] [--lora_path [Lora Model Path]] [--prompt_cache_path [Prompt Cache File Path]]"
}
# Parse command-line options
@@ -30,10 +30,6 @@ while [[ $# -gt 0 ]]; do
TARGET_PLATFORM="$2"
shift 2
;;
--npu_num)
NPU_CORE_COUNT="$2"
shift 2
;;
--lora_model_path)
LORA_PATH="$2"
shift 2
@@ -92,7 +88,7 @@ cp ../../runtime/Linux/librkllm_api/aarch64/librkllmrt.so ./rkllm_server/lib/
adb push ./rkllm_server $WORKING_PATH
#################### Enter the board terminal and start the server service. ####################
CMD="python3 gradio_server.py --rkllm_model_path $MODEL_PATH --target_platform $TARGET_PLATFORM --num_npu_core $NPU_CORE_COUNT"
CMD="python3 gradio_server.py --rkllm_model_path $MODEL_PATH --target_platform $TARGET_PLATFORM"
if [[ -n "$LORA_PATH" ]]; then
CMD="$CMD --lora_model_path $LORA_PATH"

66
rkllm-runtime/examples/rkllm_server_demo/rkllm_server/flask_server.py
View File

@@ -23,9 +23,10 @@ userdata = ctypes.c_void_p(None)
LLMCallState = ctypes.c_int
LLMCallState.RKLLM_RUN_NORMAL = 0
LLMCallState.RKLLM_RUN_FINISH = 1
LLMCallState.RKLLM_RUN_ERROR = 2
LLMCallState.RKLLM_RUN_GET_LAST_HIDDEN_LAYER = 3
LLMCallState.RKLLM_RUN_WAITING = 1
LLMCallState.RKLLM_RUN_FINISH = 2
LLMCallState.RKLLM_RUN_ERROR = 3
LLMCallState.RKLLM_RUN_GET_LAST_HIDDEN_LAYER = 4
RKLLMInputMode = ctypes.c_int
RKLLMInputMode.RKLLM_INPUT_PROMPT = 0
@@ -37,15 +38,17 @@ RKLLMInferMode = ctypes.c_int
RKLLMInferMode.RKLLM_INFER_GENERATE = 0
RKLLMInferMode.RKLLM_INFER_GET_LAST_HIDDEN_LAYER = 1
class RKLLMExtendParam(ctypes.Structure):
_fields_ = [
("base_domain_id", ctypes.c_int32),
("reserved", ctypes.c_uint8 * 112)
]
class RKLLMParam(ctypes.Structure):
_fields_ = [
("model_path", ctypes.c_char_p),
("license_path", ctypes.c_char_p),
("num_npu_core", ctypes.c_int32),
("max_context_len", ctypes.c_int32),
("n_prefill_batch", ctypes.c_int32),
("max_new_tokens", ctypes.c_int32),
("skip_special_token", ctypes.c_bool),
("top_k", ctypes.c_int32),
("top_p", ctypes.c_float),
("temperature", ctypes.c_float),
@@ -55,12 +58,12 @@ class RKLLMParam(ctypes.Structure):
("mirostat", ctypes.c_int32),
("mirostat_tau", ctypes.c_float),
("mirostat_eta", ctypes.c_float),
("logprobs", ctypes.c_bool),
("top_logprobs", ctypes.c_int32),
("skip_special_token", ctypes.c_bool),
("is_async", ctypes.c_bool),
("img_start", ctypes.c_char_p),
("img_end", ctypes.c_char_p),
("img_content", ctypes.c_char_p),
("extend_param", RKLLMExtendParam),
]
class RKLLMLoraAdapter(ctypes.Structure):
@@ -70,17 +73,6 @@ class RKLLMLoraAdapter(ctypes.Structure):
("scale", ctypes.c_float)
]
class RKLLMLoraParam(ctypes.Structure):
_fields_ = [
("lora_adapter_name", ctypes.c_char_p)
]
class RKLLMPromptCacheParam(ctypes.Structure):
_fields_ = [
("save_prompt_cache", ctypes.c_int),
("prompt_cache_path", ctypes.c_char_p)
]
class RKLLMEmbedInput(ctypes.Structure):
_fields_ = [
("embed", ctypes.POINTER(ctypes.c_float)),
@@ -113,6 +105,18 @@ class RKLLMInput(ctypes.Structure):
("input_mode", ctypes.c_int),
("input_data", RKLLMInputUnion)
]
class RKLLMLoraParam(ctypes.Structure):
_fields_ = [
("lora_adapter_name", ctypes.c_char_p)
]
class RKLLMPromptCacheParam(ctypes.Structure):
_fields_ = [
("save_prompt_cache", ctypes.c_int),
("prompt_cache_path", ctypes.c_char_p)
]
class RKLLMInferParam(ctypes.Structure):
_fields_ = [
("mode", RKLLMInferMode),
@@ -199,14 +203,11 @@ callback = callback_type(callback_impl)
# Define the RKLLM class, which includes initialization, inference, and release operations for the RKLLM model in the dynamic library
class RKLLM(object):
def __init__(self, model_path, num_npu_core, lora_model_path = None, prompt_cache_path = None):
def __init__(self, model_path, lora_model_path = None, prompt_cache_path = None):
rkllm_param = RKLLMParam()
rkllm_param.model_path = bytes(model_path, 'utf-8')
rkllm_param.license_path = None
rkllm_param.num_npu_core = num_npu_core
rkllm_param.max_context_len = 512
rkllm_param.n_prefill_batch = 512
rkllm_param.max_new_tokens = -1
rkllm_param.skip_special_token = True
@@ -221,20 +222,20 @@ class RKLLM(object):
rkllm_param.mirostat_tau = 5.0
rkllm_param.mirostat_eta = 0.1
rkllm_param.logprobs = False
rkllm_param.top_logprobs = 5
rkllm_param.is_async = False
rkllm_param.img_start = "".encode('utf-8')
rkllm_param.img_end = "".encode('utf-8')
rkllm_param.img_content = "".encode('utf-8')
rkllm_param.extend_param.base_domain_id = 0
self.handle = RKLLM_Handle_t()
self.rkllm_init = rkllm_lib.rkllm_init
self.rkllm_init.argtypes = [ctypes.POINTER(RKLLM_Handle_t), RKLLMParam, callback_type]
self.rkllm_init.argtypes = [ctypes.POINTER(RKLLM_Handle_t), ctypes.POINTER(RKLLMParam), callback_type]
self.rkllm_init.restype = ctypes.c_int
self.rkllm_init(ctypes.byref(self.handle), rkllm_param, callback)
self.rkllm_init(ctypes.byref(self.handle), ctypes.byref(rkllm_param), callback)
self.rkllm_run = rkllm_lib.rkllm_run
self.rkllm_run.argtypes = [RKLLM_Handle_t, ctypes.POINTER(RKLLMInput), ctypes.POINTER(RKLLMInferParam), ctypes.c_void_p]
@@ -294,7 +295,6 @@ if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--rkllm_model_path', type=str, required=True, help='Absolute path of the converted RKLLM model on the Linux board;')
parser.add_argument('--target_platform', type=str, required=True, help='Target platform: e.g., rk3588/rk3576;')
parser.add_argument('--num_npu_core', type=int, required=True, help='Target num_npu_core;')
parser.add_argument('--lora_model_path', type=str, help='Absolute path of the lora_model on the Linux board;')
parser.add_argument('--prompt_cache_path', type=str, help='Absolute path of the prompt_cache file on the Linux board;')
args = parser.parse_args()
@@ -309,11 +309,6 @@ if __name__ == "__main__":
sys.stdout.flush()
exit()
if not (args.num_npu_core in [1, 2, 3]):
print("Error: rk3576 supports 1/2 cores, rk3588 supports 1/2/3 cores, please specify the correct number of cores.")
sys.stdout.flush()
exit()
if args.lora_model_path:
if not os.path.exists(args.lora_model_path):
print("Error: Please provide the correct lora_model path, and advise it is the absolute path on the board.")
@@ -337,8 +332,7 @@ if __name__ == "__main__":
print("=========init....===========")
sys.stdout.flush()
model_path = args.rkllm_model_path
num_npu_core = args.num_npu_core
rkllm_model = RKLLM(model_path, num_npu_core, args.lora_model_path, args.prompt_cache_path)
rkllm_model = RKLLM(model_path, args.lora_model_path, args.prompt_cache_path)
print("RKLLM Model has been initialized successfully！")
print("==============================")
sys.stdout.flush()

66
rkllm-runtime/examples/rkllm_server_demo/rkllm_server/gradio_server.py
View File

@@ -24,9 +24,10 @@ userdata = ctypes.c_void_p(None)
LLMCallState = ctypes.c_int
LLMCallState.RKLLM_RUN_NORMAL = 0
LLMCallState.RKLLM_RUN_FINISH = 1
LLMCallState.RKLLM_RUN_ERROR = 2
LLMCallState.RKLLM_RUN_GET_LAST_HIDDEN_LAYER = 3
LLMCallState.RKLLM_RUN_WAITING = 1
LLMCallState.RKLLM_RUN_FINISH = 2
LLMCallState.RKLLM_RUN_ERROR = 3
LLMCallState.RKLLM_RUN_GET_LAST_HIDDEN_LAYER = 4
RKLLMInputMode = ctypes.c_int
RKLLMInputMode.RKLLM_INPUT_PROMPT = 0
@@ -38,15 +39,17 @@ RKLLMInferMode = ctypes.c_int
RKLLMInferMode.RKLLM_INFER_GENERATE = 0
RKLLMInferMode.RKLLM_INFER_GET_LAST_HIDDEN_LAYER = 1
class RKLLMExtendParam(ctypes.Structure):
_fields_ = [
("base_domain_id", ctypes.c_int32),
("reserved", ctypes.c_uint8 * 112)
]
class RKLLMParam(ctypes.Structure):
_fields_ = [
("model_path", ctypes.c_char_p),
("license_path", ctypes.c_char_p),
("num_npu_core", ctypes.c_int32),
("max_context_len", ctypes.c_int32),
("n_prefill_batch", ctypes.c_int32),
("max_new_tokens", ctypes.c_int32),
("skip_special_token", ctypes.c_bool),
("top_k", ctypes.c_int32),
("top_p", ctypes.c_float),
("temperature", ctypes.c_float),
@@ -56,12 +59,12 @@ class RKLLMParam(ctypes.Structure):
("mirostat", ctypes.c_int32),
("mirostat_tau", ctypes.c_float),
("mirostat_eta", ctypes.c_float),
("logprobs", ctypes.c_bool),
("top_logprobs", ctypes.c_int32),
("skip_special_token", ctypes.c_bool),
("is_async", ctypes.c_bool),
("img_start", ctypes.c_char_p),
("img_end", ctypes.c_char_p),
("img_content", ctypes.c_char_p),
("extend_param", RKLLMExtendParam),
]
class RKLLMLoraAdapter(ctypes.Structure):
@@ -71,17 +74,6 @@ class RKLLMLoraAdapter(ctypes.Structure):
("scale", ctypes.c_float)
]
class RKLLMLoraParam(ctypes.Structure):
_fields_ = [
("lora_adapter_name", ctypes.c_char_p)
]
class RKLLMPromptCacheParam(ctypes.Structure):
_fields_ = [
("save_prompt_cache", ctypes.c_int),
("prompt_cache_path", ctypes.c_char_p)
]
class RKLLMEmbedInput(ctypes.Structure):
_fields_ = [
("embed", ctypes.POINTER(ctypes.c_float)),
@@ -114,6 +106,18 @@ class RKLLMInput(ctypes.Structure):
("input_mode", ctypes.c_int),
("input_data", RKLLMInputUnion)
]
class RKLLMLoraParam(ctypes.Structure):
_fields_ = [
("lora_adapter_name", ctypes.c_char_p)
]
class RKLLMPromptCacheParam(ctypes.Structure):
_fields_ = [
("save_prompt_cache", ctypes.c_int),
("prompt_cache_path", ctypes.c_char_p)
]
class RKLLMInferParam(ctypes.Structure):
_fields_ = [
("mode", RKLLMInferMode),
@@ -193,14 +197,11 @@ callback = callback_type(callback_impl)
# Define the RKLLM class, which includes initialization, inference, and release operations for the RKLLM model in the dynamic library
class RKLLM(object):
def __init__(self, model_path, num_npu_core, lora_model_path = None, prompt_cache_path = None):
def __init__(self, model_path, lora_model_path = None, prompt_cache_path = None):
rkllm_param = RKLLMParam()
rkllm_param.model_path = bytes(model_path, 'utf-8')
rkllm_param.license_path = None
rkllm_param.num_npu_core = num_npu_core
rkllm_param.max_context_len = 512
rkllm_param.n_prefill_batch = 512
rkllm_param.max_new_tokens = -1
rkllm_param.skip_special_token = True
@@ -215,20 +216,20 @@ class RKLLM(object):
rkllm_param.mirostat_tau = 5.0
rkllm_param.mirostat_eta = 0.1
rkllm_param.logprobs = False
rkllm_param.top_logprobs = 5
rkllm_param.is_async = False
rkllm_param.img_start = "".encode('utf-8')
rkllm_param.img_end = "".encode('utf-8')
rkllm_param.img_content = "".encode('utf-8')
rkllm_param.extend_param.base_domain_id = 0
self.handle = RKLLM_Handle_t()
self.rkllm_init = rkllm_lib.rkllm_init
self.rkllm_init.argtypes = [ctypes.POINTER(RKLLM_Handle_t), RKLLMParam, callback_type]
self.rkllm_init.argtypes = [ctypes.POINTER(RKLLM_Handle_t), ctypes.POINTER(RKLLMParam), callback_type]
self.rkllm_init.restype = ctypes.c_int
self.rkllm_init(ctypes.byref(self.handle), rkllm_param, callback)
self.rkllm_init(ctypes.byref(self.handle), ctypes.byref(rkllm_param), callback)
self.rkllm_run = rkllm_lib.rkllm_run
self.rkllm_run.argtypes = [RKLLM_Handle_t, ctypes.POINTER(RKLLMInput), ctypes.POINTER(RKLLMInferParam), ctypes.c_void_p]
@@ -288,7 +289,6 @@ if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument('--rkllm_model_path', type=str, required=True, help='Absolute path of the converted RKLLM model on the Linux board;')
parser.add_argument('--target_platform', type=str, required=True, help='Target platform: e.g., rk3588/rk3576;')
parser.add_argument('--num_npu_core', type=int, required=True, help='Target num_npu_core;')
parser.add_argument('--lora_model_path', type=str, help='Absolute path of the lora_model on the Linux board;')
parser.add_argument('--prompt_cache_path', type=str, help='Absolute path of the prompt_cache file on the Linux board;')
args = parser.parse_args()
@@ -303,11 +303,6 @@ if __name__ == "__main__":
sys.stdout.flush()
exit()
if not (args.num_npu_core in [1, 2, 3]):
print("Error: rk3576 supports 1/2 cores, rk3588 supports 1/2/3 cores, please specify the correct number of cores.")
sys.stdout.flush()
exit()
if args.lora_model_path:
if not os.path.exists(args.lora_model_path):
print("Error: Please provide the correct lora_model path, and advise it is the absolute path on the board.")
@@ -331,8 +326,7 @@ if __name__ == "__main__":
print("=========init....===========")
sys.stdout.flush()
model_path = args.rkllm_model_path
num_npu_core = args.num_npu_core
rkllm_model = RKLLM(model_path, num_npu_core, args.lora_model_path, args.prompt_cache_path)
rkllm_model = RKLLM(model_path, args.lora_model_path, args.prompt_cache_path)
print("RKLLM Model has been initialized successfully！")
print("==============================")
sys.stdout.flush()