OAI: Add chat completions endpoint

Chat completions is the endpoint that will be used by OAI in the
future. Makes sense to support it even though the completions
endpoint will be used more often.

Also unify common parameters between the chat completion and completion
requests since they're very similar.

Signed-off-by: kingbri <bdashore3@proton.me>

OAI/types/completion.py

@@ -2,102 +2,26 @@ from uuid import uuid4
 from time import time
 from pydantic import BaseModel, Field
 from typing import List, Optional, Dict, Union
-from OAI.types.common import LogProbs, UsageStats
+from OAI.types.common import LogProbs, UsageStats, CommonCompletionRequest
 
 class CompletionRespChoice(BaseModel):
+    # Index is 0 since we aren't using multiple choices
+    index: int = 0
     finish_reason: str
-    index: int
     logprobs: Optional[LogProbs] = None
     text: str
 
-class CompletionRequest(BaseModel):
-    # Model information
-    model: str
-
+# Inherited from common request
+class CompletionRequest(CommonCompletionRequest):
     # Prompt can also contain token ids, but that's out of scope for this project.
     prompt: Union[str, List[str]]
 
-    # 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]]] = None
-
-    # Default to 150 as 16 makes no sense as a default
-    max_tokens: Optional[int] = 150
-
-    # Not supported sampling params
-    presence_penalty: Optional[float] = 0.0
-
-    # Aliased to repetition_penalty
-    frequency_penalty: Optional[float] = 0.0
-
-    # Sampling params
-    token_healing: Optional[bool] = False
-    temperature: Optional[float] = 1.0
-    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 prompt to a string
-        if isinstance(self.prompt, list):
-            self.prompt = "\n".join(self.prompt)
-
-        # 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 {
-            "prompt": self.prompt,
-            "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,
-            "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": True if self.mirostat_mode == 2 else False,
-            "mirostat_tau": self.mirostat_tau,
-            "mirostat_eta": self.mirostat_eta
-        }
-
 class CompletionResponse(BaseModel):
     id: str = Field(default_factory=lambda: f"cmpl-{uuid4().hex}")
     choices: List[CompletionRespChoice]
     created: int = Field(default_factory=lambda: int(time()))
     model: str
-    object: str = "text-completion"
+    object: str = "text_completion"
 
     # TODO: Add usage stats
     usage: Optional[UsageStats] = None