tabbyAPI-ollama/OAI/types/common.py
2023-11-27 20:05:05 -08:00

87 lines
3.1 KiB
Python

from pydantic import BaseModel, Field
from typing import List, Dict, Optional, Union
class LogProbs(BaseModel):
text_offset: List[int] = Field(default_factory=list)
token_logprobs: List[float] = Field(default_factory=list)
tokens: List[str] = Field(default_factory=list)
top_logprobs: List[Dict[str, float]] = Field(default_factory=list)
class UsageStats(BaseModel):
prompt_tokens: int
completion_tokens: int
total_tokens: int
class CommonCompletionRequest(BaseModel):
# Model information
# This parameter is not used, the loaded model is used instead
model: Optional[str] = None
# Extra OAI request stuff
best_of: Optional[int] = None
echo: Optional[bool] = False
logit_bias: Optional[Dict[str, float]] = None
logprobs: Optional[int] = None
n: Optional[int] = 1
suffix: Optional[str] = None
user: Optional[str] = None
# Generation info
seed: Optional[int] = -1
stream: Optional[bool] = False
stop: Optional[Union[str, List[str]]] = []
# Default to 150 as 16 makes no sense as a default
max_tokens: Optional[int] = 150
# Aliased to repetition_penalty
frequency_penalty: Optional[float] = 0.0
# Sampling params
token_healing: Optional[bool] = False
temperature: Optional[float] = 1.0
temperature_last: Optional[bool] = False
top_k: Optional[int] = 0
top_p: Optional[float] = 1.0
typical: Optional[float] = 0.0
min_p: Optional[float] = 0.0
tfs: Optional[float] = 1.0
repetition_penalty: Optional[float] = 1.0
repetition_penalty_range: Optional[int] = 0
repetition_decay: Optional[int] = 0
mirostat_mode: Optional[int] = 0
mirostat_tau: Optional[float] = 1.5
mirostat_eta: Optional[float] = 0.1
add_bos_token: Optional[bool] = True
ban_eos_token: Optional[bool] = False
# Converts to internal generation parameters
def to_gen_params(self):
# Convert stop to an array of strings
if isinstance(self.stop, str):
self.stop = [self.stop]
# Set repetition_penalty to frequency_penalty if repetition_penalty isn't already defined
if (self.repetition_penalty is None or self.repetition_penalty == 1.0) and self.frequency_penalty:
self.repetition_penalty = self.frequency_penalty
return {
"stop": self.stop,
"max_tokens": self.max_tokens,
"add_bos_token": self.add_bos_token,
"ban_eos_token": self.ban_eos_token,
"token_healing": self.token_healing,
"temperature": self.temperature,
"temperature_last": self.temperature_last,
"top_k": self.top_k,
"top_p": self.top_p,
"typical": self.typical,
"min_p": self.min_p,
"tfs": self.tfs,
"repetition_penalty": self.repetition_penalty,
"repetition_penalty_range": self.repetition_penalty_range,
"repetition_decay": self.repetition_decay,
"mirostat": self.mirostat_mode == 2,
"mirostat_tau": self.mirostat_tau,
"mirostat_eta": self.mirostat_eta,
}