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193 | class OpenVINOLLM(HuggingFaceLLM):
r"""OpenVINOLLM LLM.
Examples:
`pip install llama-index-llms-openvino`
```python
from llama_index.llms.openvino import OpenVINOLLM
def messages_to_prompt(messages):
prompt = ""
for message in messages:
if message.role == 'system':
prompt += f"<|system|>\n{message.content}</s>\n"
elif message.role == 'user':
prompt += f"<|user|>\n{message.content}</s>\n"
elif message.role == 'assistant':
prompt += f"<|assistant|>\n{message.content}</s>\n"
# ensure we start with a system prompt, insert blank if needed
if not prompt.startswith("<|system|>\n"):
prompt = "<|system|>\n</s>\n" + prompt
# add final assistant prompt
prompt = prompt + "<|assistant|>\n"
return prompt
def completion_to_prompt(completion):
return f"<|system|>\n</s>\n<|user|>\n{completion}</s>\n<|assistant|>\n"
import torch
from llama_index.core.prompts import PromptTemplate
from llama_index.llms.openvino import OpenVINOLLM
ov_config = {
"PERFORMANCE_HINT": "LATENCY",
"NUM_STREAMS": "1",
"CACHE_DIR": "",
}
llm = OpenVINOLLM(
model_name="HuggingFaceH4/zephyr-7b-beta",
tokenizer_name="HuggingFaceH4/zephyr-7b-beta",
context_window=3900,
max_new_tokens=256,
model_kwargs={"ov_config": ov_config},
generate_kwargs={"temperature": 0.7, "top_k": 50, "top_p": 0.95},
messages_to_prompt=messages_to_prompt,
completion_to_prompt=completion_to_prompt,
device_map="auto",
)
response = llm.complete("What is the meaning of life?")
print(str(response))
```
"""
model_name: str = Field(
default=DEFAULT_HUGGINGFACE_MODEL,
description=(
"The model name to use from HuggingFace. "
"Unused if `model` is passed in directly."
),
)
tokenizer_name: str = Field(
default=DEFAULT_HUGGINGFACE_MODEL,
description=(
"The name of the tokenizer to use from HuggingFace. "
"Unused if `tokenizer` is passed in directly."
),
)
def __init__(
self,
context_window: int = DEFAULT_CONTEXT_WINDOW,
max_new_tokens: int = DEFAULT_NUM_OUTPUTS,
query_wrapper_prompt: Union[str, PromptTemplate] = "{query_str}",
tokenizer_name: str = DEFAULT_HUGGINGFACE_MODEL,
model_name: str = DEFAULT_HUGGINGFACE_MODEL,
model: Optional[Any] = None,
tokenizer: Optional[Any] = None,
device_map: Optional[str] = "auto",
stopping_ids: Optional[List[int]] = None,
tokenizer_kwargs: Optional[dict] = None,
tokenizer_outputs_to_remove: Optional[list] = None,
model_kwargs: Optional[dict] = None,
generate_kwargs: Optional[dict] = None,
is_chat_model: Optional[bool] = False,
callback_manager: Optional[CallbackManager] = None,
system_prompt: str = "",
messages_to_prompt: Optional[Callable[[Sequence[ChatMessage]], str]] = None,
completion_to_prompt: Optional[Callable[[str], str]] = None,
pydantic_program_mode: PydanticProgramMode = PydanticProgramMode.DEFAULT,
output_parser: Optional[BaseOutputParser] = None,
) -> None:
"""Initialize params."""
model_kwargs = model_kwargs or {}
def require_model_export(
model_id: str, revision: Any = None, subfolder: Any = None
) -> bool:
model_dir = Path(model_id)
if subfolder is not None:
model_dir = model_dir / subfolder
if model_dir.is_dir():
return (
not (model_dir / "openvino_model.xml").exists()
or not (model_dir / "openvino_model.bin").exists()
)
hf_api = HfApi()
try:
model_info = hf_api.model_info(model_id, revision=revision or "main")
normalized_subfolder = (
None if subfolder is None else Path(subfolder).as_posix()
)
model_files = [
file.rfilename
for file in model_info.siblings
if normalized_subfolder is None
or file.rfilename.startswith(normalized_subfolder)
]
ov_model_path = (
"openvino_model.xml"
if subfolder is None
else f"{normalized_subfolder}/openvino_model.xml"
)
return (
ov_model_path not in model_files
or ov_model_path.replace(".xml", ".bin") not in model_files
)
except Exception:
return True
if require_model_export(model_name):
# use remote model
ov_model = model or OVModelForCausalLM.from_pretrained(
model_name, export=True, device=device_map, **model_kwargs
)
else:
# use local model
ov_model = model or OVModelForCausalLM.from_pretrained(
model_name, device=device_map, **model_kwargs
)
super().__init__(
context_window=context_window,
max_new_tokens=max_new_tokens,
query_wrapper_prompt=query_wrapper_prompt,
tokenizer_name=tokenizer_name,
model_name=model_name,
model=ov_model,
tokenizer=tokenizer,
device_map=device_map,
stopping_ids=stopping_ids or [],
tokenizer_kwargs=tokenizer_kwargs or {},
tokenizer_outputs_to_remove=tokenizer_outputs_to_remove or [],
model_kwargs=model_kwargs or {},
generate_kwargs=generate_kwargs or {},
is_chat_model=is_chat_model,
callback_manager=callback_manager,
system_prompt=system_prompt,
messages_to_prompt=messages_to_prompt,
completion_to_prompt=completion_to_prompt,
pydantic_program_mode=pydantic_program_mode,
output_parser=output_parser,
)
@classmethod
def class_name(cls) -> str:
return "OpenVINO_LLM"
|