OAI: Implement completion API endpoint

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>

OAI/models/common.py

@@ -0,0 +1,13 @@
+from pydantic import BaseModel, Field
+from typing import List, Dict
+
+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):
+    completion_tokens: int
+    prompt_tokens: int
+    total_tokens: int

OAI/models/completions.py

@@ -0,0 +1,99 @@
+from uuid import uuid4
+from time import time
+from pydantic import BaseModel, Field
+from typing import List, Optional, Dict, Union
+from OAI.models.common import LogProbs, UsageStats
+
+class CompletionRespChoice(BaseModel):
+    finish_reason: str
+    index: int
+    logprobs: Optional[LogProbs] = None
+    text: str
+
+class CompletionRequest(BaseModel):
+    # Model information
+    model: str
+
+    # 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[int] = 0
+
+    # Aliased to repetition_penalty
+    frequency_penalty: int = 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
+
+    # 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,
+            "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"
+
+    # TODO: Add usage stats
+    usage: Optional[UsageStats] = None

OAI/utils.py

@@ -0,0 +1,19 @@
+from OAI.models.completions import CompletionResponse, CompletionRespChoice
+from OAI.models.common import UsageStats
+from typing import Optional
+
+def create_completion_response(text: str, index: int, model_name: Optional[str]):
+    # TODO: Add method to get token amounts in model for UsageStats
+
+    choice = CompletionRespChoice(
+        finish_reason="Generated",
+        index = index,
+        text = text
+    )
+
+    response = CompletionResponse(
+        choices = [choice],
+        model = model_name or ""
+    )
+
+    return response