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https://github.com/theroyallab/tabbyAPI.git
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b625bface9
Models can be loaded and unloaded via the API. Also add authentication to use the API and for administrator tasks. Both types of authorization use different keys. Also fix the unload function to properly free all used vram. Signed-off-by: kingbri <bdashore3@proton.me>
100 lines
3.3 KiB
Python
100 lines
3.3 KiB
Python
from uuid import uuid4
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from time import time
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from pydantic import BaseModel, Field
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from typing import List, Optional, Dict, Union
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from OAI.types.common import LogProbs, UsageStats
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class CompletionRespChoice(BaseModel):
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finish_reason: str
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index: int
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logprobs: Optional[LogProbs] = None
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text: str
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class CompletionRequest(BaseModel):
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# Model information
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model: str
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# Prompt can also contain token ids, but that's out of scope for this project.
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prompt: Union[str, List[str]]
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# Extra OAI request stuff
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best_of: Optional[int] = None
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echo: Optional[bool] = False
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logit_bias: Optional[Dict[str, float]] = None
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logprobs: Optional[int] = None
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n: Optional[int] = 1
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suffix: Optional[str] = None
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user: Optional[str] = None
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# Generation info
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seed: Optional[int] = -1
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stream: Optional[bool] = False
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stop: Optional[Union[str, List[str]]] = None
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# Default to 150 as 16 makes no sense as a default
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max_tokens: Optional[int] = 150
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# Not supported sampling params
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presence_penalty: Optional[int] = 0
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# Aliased to repetition_penalty
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frequency_penalty: int = 0
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# Sampling params
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token_healing: Optional[bool] = False
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temperature: Optional[float] = 1.0
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top_k: Optional[int] = 0
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top_p: Optional[float] = 1.0
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typical: Optional[float] = 0.0
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min_p: Optional[float] = 0.0
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tfs: Optional[float] = 1.0
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repetition_penalty: Optional[float] = 1.0
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repetition_penalty_range: Optional[int] = 0
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repetition_decay: Optional[int] = 0
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mirostat_mode: Optional[int] = 0
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mirostat_tau: Optional[float] = 1.5
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mirostat_eta: Optional[float] = 0.1
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# Converts to internal generation parameters
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def to_gen_params(self):
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# Convert prompt to a string
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if isinstance(self.prompt, list):
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self.prompt = "\n".join(self.prompt)
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# Convert stop to an array of strings
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if isinstance(self.stop, str):
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self.stop = [self.stop]
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# Set repetition_penalty to frequency_penalty if repetition_penalty isn't already defined
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if (self.repetition_penalty is None or self.repetition_penalty == 1.0) and self.frequency_penalty:
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self.repetition_penalty = self.frequency_penalty
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return {
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"prompt": self.prompt,
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"stop": self.stop,
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"max_tokens": self.max_tokens,
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"token_healing": self.token_healing,
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"temperature": self.temperature,
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"top_k": self.top_k,
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"top_p": self.top_p,
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"typical": self.typical,
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"min_p": self.min_p,
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"tfs": self.tfs,
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"repetition_penalty": self.repetition_penalty,
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"repetition_penalty_range": self.repetition_penalty_range,
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"repetition_decay": self.repetition_decay,
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"mirostat": True if self.mirostat_mode == 2 else False,
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"mirostat_tau": self.mirostat_tau,
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"mirostat_eta": self.mirostat_eta
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}
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class CompletionResponse(BaseModel):
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id: str = Field(default_factory=lambda: f"cmpl-{uuid4().hex}")
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choices: List[CompletionRespChoice]
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created: int = Field(default_factory=lambda: int(time()))
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model: str
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object: str = "text-completion"
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# TODO: Add usage stats
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usage: Optional[UsageStats] = None
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