mirror of
https://github.com/theroyallab/tabbyAPI.git
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eee8b642bd
Add support for /v1/completions with the option to use streaming if needed. Also rewrite API endpoints to use async when possible since that improves request performance. Model container parameter names also needed rewrites as well and set fallback cases to their disabled values. 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.models.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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