fb1d2f34c1
response_prefix is used to add a prefix before generating the next message. This is used in many cases such as continuining a prompt (see #96). Also if a template has BOS token specified, add_bos_token will append two BOS tokens. Add a check which strips a starting BOS token from the prompt if it exists. Signed-off-by: kingbri <bdashore3@proton.me>
107 lines
3.3 KiB
Python
107 lines
3.3 KiB
Python
"""Completion utilities for OAI server."""
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import pathlib
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from asyncio import CancelledError
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import threading
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from fastapi import HTTPException
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from typing import Optional
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from common import model
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from common.networking import (
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get_generator_error,
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handle_request_disconnect,
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handle_request_error,
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)
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from common.utils import unwrap
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from endpoints.OAI.types.completion import (
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CompletionRequest,
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CompletionResponse,
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CompletionRespChoice,
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CompletionLogProbs,
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)
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from endpoints.OAI.types.common import UsageStats
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def _create_response(generation: dict, model_name: Optional[str]):
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"""Create a completion response from the provided text."""
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logprob_response = None
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token_probs = unwrap(generation.get("token_probs"), {})
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if token_probs:
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logprobs = unwrap(generation.get("logprobs"), [])
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offset = unwrap(generation.get("offset"), [])
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logprob_response = CompletionLogProbs(
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text_offset=offset if isinstance(offset, list) else [offset],
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token_logprobs=token_probs.values(),
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tokens=token_probs.keys(),
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top_logprobs=logprobs if isinstance(logprobs, list) else [logprobs],
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)
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choice = CompletionRespChoice(
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finish_reason=generation.get("finish_reason"),
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text=unwrap(generation.get("text"), ""),
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logprobs=logprob_response,
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)
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prompt_tokens = unwrap(generation.get("prompt_tokens"), 0)
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completion_tokens = unwrap(generation.get("generated_tokens"), 0)
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response = CompletionResponse(
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choices=[choice],
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model=unwrap(model_name, ""),
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usage=UsageStats(
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prompt_tokens=prompt_tokens,
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completion_tokens=completion_tokens,
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total_tokens=prompt_tokens + completion_tokens,
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),
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)
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return response
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async def stream_generate_completion(data: CompletionRequest, model_path: pathlib.Path):
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"""Streaming generation for completions."""
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try:
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abort_event = threading.Event()
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new_generation = model.container.generate_gen(
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data.prompt, abort_event, **data.to_gen_params()
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)
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async for generation in new_generation:
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response = _create_response(generation, model_path.name)
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yield response.model_dump_json()
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# Break if the generation is finished
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if "finish_reason" in generation:
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yield "[DONE]"
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break
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except CancelledError:
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# Get out if the request gets disconnected
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abort_event.set()
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handle_request_disconnect("Completion generation cancelled by user.")
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except Exception:
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yield get_generator_error(
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"Completion aborted. Please check the server console."
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)
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async def generate_completion(data: CompletionRequest, model_path: pathlib.Path):
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"""Non-streaming generate for completions"""
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try:
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generation = await model.container.generate(data.prompt, **data.to_gen_params())
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response = _create_response(generation, model_path.name)
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return response
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except Exception as exc:
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error_message = handle_request_error(
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"Completion aborted. Maybe the model was unloaded? "
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"Please check the server console."
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).error.message
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# Server error if there's a generation exception
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raise HTTPException(503, error_message) from exc
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