06ff47e2b4
The new async dynamic job allows for native async support without the need of threading. Also add logprobs and metrics back to responses. Signed-off-by: kingbri <bdashore3@proton.me>
103 lines
3.2 KiB
Python
103 lines
3.2 KiB
Python
"""Completion utilities for OAI server."""
|
|
|
|
import pathlib
|
|
from asyncio import CancelledError
|
|
from fastapi import HTTPException
|
|
from typing import Optional
|
|
|
|
from common import model
|
|
from common.networking import (
|
|
get_generator_error,
|
|
handle_request_disconnect,
|
|
handle_request_error,
|
|
)
|
|
from common.utils import unwrap
|
|
from endpoints.OAI.types.completion import (
|
|
CompletionRequest,
|
|
CompletionResponse,
|
|
CompletionRespChoice,
|
|
CompletionLogProbs,
|
|
)
|
|
from endpoints.OAI.types.common import UsageStats
|
|
|
|
|
|
def _create_response(generation: dict, model_name: Optional[str]):
|
|
"""Create a completion response from the provided text."""
|
|
|
|
logprob_response = None
|
|
|
|
token_probs = unwrap(generation.get("token_probs"), {})
|
|
if token_probs:
|
|
logprobs = unwrap(generation.get("logprobs"), [])
|
|
offset = unwrap(generation.get("offset"), [])
|
|
|
|
logprob_response = CompletionLogProbs(
|
|
text_offset=offset if isinstance(offset, list) else [offset],
|
|
token_logprobs=token_probs.values(),
|
|
tokens=token_probs.keys(),
|
|
top_logprobs=logprobs if isinstance(logprobs, list) else [logprobs],
|
|
)
|
|
|
|
choice = CompletionRespChoice(
|
|
finish_reason=generation.get("finish_reason"),
|
|
text=unwrap(generation.get("text"), ""),
|
|
logprobs=logprob_response,
|
|
)
|
|
|
|
prompt_tokens = unwrap(generation.get("prompt_tokens"), 0)
|
|
completion_tokens = unwrap(generation.get("generated_tokens"), 0)
|
|
|
|
response = CompletionResponse(
|
|
choices=[choice],
|
|
model=unwrap(model_name, ""),
|
|
usage=UsageStats(
|
|
prompt_tokens=prompt_tokens,
|
|
completion_tokens=completion_tokens,
|
|
total_tokens=prompt_tokens + completion_tokens,
|
|
),
|
|
)
|
|
|
|
return response
|
|
|
|
|
|
async def stream_generate_completion(data: CompletionRequest, model_path: pathlib.Path):
|
|
"""Streaming generation for completions."""
|
|
|
|
try:
|
|
new_generation = model.container.generate_gen(
|
|
data.prompt, **data.to_gen_params()
|
|
)
|
|
async for generation in new_generation:
|
|
response = _create_response(generation, model_path.name)
|
|
yield response.model_dump_json()
|
|
|
|
# Break if the generation is finished
|
|
if "finish_reason" in generation:
|
|
yield "[DONE]"
|
|
break
|
|
except CancelledError:
|
|
# Get out if the request gets disconnected
|
|
|
|
handle_request_disconnect("Completion generation cancelled by user.")
|
|
except Exception:
|
|
yield get_generator_error(
|
|
"Completion aborted. Please check the server console."
|
|
)
|
|
|
|
|
|
async def generate_completion(data: CompletionRequest, model_path: pathlib.Path):
|
|
"""Non-streaming generate for completions"""
|
|
|
|
try:
|
|
generation = await model.container.generate(data.prompt, **data.to_gen_params())
|
|
response = _create_response(generation, model_path.name)
|
|
|
|
return response
|
|
except Exception as exc:
|
|
error_message = handle_request_error(
|
|
"Completion aborted. Maybe the model was unloaded? "
|
|
"Please check the server console."
|
|
).error.message
|
|
|
|
# Server error if there's a generation exception
|
|
raise HTTPException(503, error_message) from exc
|