6f03be9523
Previously, generation function were bundled with the request function causing the overall code structure and API to look ugly and unreadable. Split these up and cleanup a lot of the methods that were previously overlooked in the API itself. Signed-off-by: kingbri <bdashore3@proton.me>
476 lines
14 KiB
Python
476 lines
14 KiB
Python
import pathlib
|
|
import uvicorn
|
|
from fastapi import FastAPI, Depends, HTTPException, Request
|
|
from fastapi.concurrency import run_in_threadpool
|
|
from fastapi.middleware.cors import CORSMiddleware
|
|
from functools import partial
|
|
from loguru import logger
|
|
from sse_starlette import EventSourceResponse
|
|
|
|
from common import config, model, gen_logging, sampling
|
|
from common.auth import check_admin_key, check_api_key
|
|
from common.generators import (
|
|
call_with_semaphore,
|
|
generate_with_semaphore,
|
|
)
|
|
from common.logger import UVICORN_LOG_CONFIG
|
|
from common.templating import (
|
|
get_all_templates,
|
|
get_template_from_file,
|
|
)
|
|
from common.utils import (
|
|
handle_request_error,
|
|
unwrap,
|
|
)
|
|
from endpoints.OAI.types.completion import CompletionRequest
|
|
from endpoints.OAI.types.chat_completion import ChatCompletionRequest
|
|
from endpoints.OAI.types.lora import (
|
|
LoraCard,
|
|
LoraList,
|
|
LoraLoadRequest,
|
|
LoraLoadResponse,
|
|
)
|
|
from endpoints.OAI.types.model import (
|
|
ModelCard,
|
|
ModelLoadRequest,
|
|
ModelCardParameters,
|
|
)
|
|
from endpoints.OAI.types.sampler_overrides import SamplerOverrideSwitchRequest
|
|
from endpoints.OAI.types.template import TemplateList, TemplateSwitchRequest
|
|
from endpoints.OAI.types.token import (
|
|
TokenEncodeRequest,
|
|
TokenEncodeResponse,
|
|
TokenDecodeRequest,
|
|
TokenDecodeResponse,
|
|
)
|
|
from endpoints.OAI.utils.chat_completion import (
|
|
format_prompt_with_template,
|
|
generate_chat_completion,
|
|
stream_generate_chat_completion,
|
|
)
|
|
from endpoints.OAI.utils.completion import (
|
|
generate_completion,
|
|
stream_generate_completion,
|
|
)
|
|
from endpoints.OAI.utils.model import get_model_list, stream_model_load
|
|
from endpoints.OAI.utils.lora import get_lora_list
|
|
|
|
app = FastAPI(
|
|
title="TabbyAPI",
|
|
summary="An OAI compatible exllamav2 API that's both lightweight and fast",
|
|
description=(
|
|
"This docs page is not meant to send requests! Please use a service "
|
|
"like Postman or a frontend UI."
|
|
),
|
|
)
|
|
|
|
# ALlow CORS requests
|
|
app.add_middleware(
|
|
CORSMiddleware,
|
|
allow_origins=["*"],
|
|
allow_credentials=True,
|
|
allow_methods=["*"],
|
|
allow_headers=["*"],
|
|
)
|
|
|
|
|
|
async def check_model_container():
|
|
"""FastAPI depends that checks if a model isn't loaded or currently loading."""
|
|
|
|
if model.container is None or not (
|
|
model.container.model_is_loading or model.container.model_loaded
|
|
):
|
|
error_message = handle_request_error(
|
|
"No models are currently loaded.",
|
|
exc_info=False,
|
|
).error.message
|
|
|
|
raise HTTPException(400, error_message)
|
|
|
|
|
|
# Model list endpoint
|
|
@app.get("/v1/models", dependencies=[Depends(check_api_key)])
|
|
@app.get("/v1/model/list", dependencies=[Depends(check_api_key)])
|
|
async def list_models():
|
|
"""Lists all models in the model directory."""
|
|
model_config = config.model_config()
|
|
model_dir = unwrap(model_config.get("model_dir"), "models")
|
|
model_path = pathlib.Path(model_dir)
|
|
|
|
draft_model_dir = config.draft_model_config().get("draft_model_dir")
|
|
|
|
models = get_model_list(model_path.resolve(), draft_model_dir)
|
|
if unwrap(model_config.get("use_dummy_models"), False):
|
|
models.data.insert(0, ModelCard(id="gpt-3.5-turbo"))
|
|
|
|
return models
|
|
|
|
|
|
# Currently loaded model endpoint
|
|
@app.get(
|
|
"/v1/model",
|
|
dependencies=[Depends(check_api_key), Depends(check_model_container)],
|
|
)
|
|
async def get_current_model():
|
|
"""Returns the currently loaded model."""
|
|
model_params = model.container.get_model_parameters()
|
|
draft_model_params = model_params.pop("draft", {})
|
|
|
|
if draft_model_params:
|
|
model_params["draft"] = ModelCard(
|
|
id=unwrap(draft_model_params.get("name"), "unknown"),
|
|
parameters=ModelCardParameters.model_validate(draft_model_params),
|
|
)
|
|
else:
|
|
draft_model_params = None
|
|
|
|
model_card = ModelCard(
|
|
id=unwrap(model_params.pop("name", None), "unknown"),
|
|
parameters=ModelCardParameters.model_validate(model_params),
|
|
logging=gen_logging.PREFERENCES,
|
|
)
|
|
|
|
if draft_model_params:
|
|
draft_card = ModelCard(
|
|
id=unwrap(draft_model_params.pop("name", None), "unknown"),
|
|
parameters=ModelCardParameters.model_validate(draft_model_params),
|
|
)
|
|
|
|
model_card.parameters.draft = draft_card
|
|
|
|
return model_card
|
|
|
|
|
|
@app.get("/v1/model/draft/list", dependencies=[Depends(check_api_key)])
|
|
async def list_draft_models():
|
|
"""Lists all draft models in the model directory."""
|
|
draft_model_dir = unwrap(
|
|
config.draft_model_config().get("draft_model_dir"), "models"
|
|
)
|
|
draft_model_path = pathlib.Path(draft_model_dir)
|
|
|
|
models = get_model_list(draft_model_path.resolve())
|
|
|
|
return models
|
|
|
|
|
|
# Load model endpoint
|
|
@app.post("/v1/model/load", dependencies=[Depends(check_admin_key)])
|
|
async def load_model(request: Request, data: ModelLoadRequest):
|
|
"""Loads a model into the model container."""
|
|
|
|
# Verify request parameters
|
|
if not data.name:
|
|
raise HTTPException(400, "A model name was not provided.")
|
|
|
|
model_path = pathlib.Path(unwrap(config.model_config().get("model_dir"), "models"))
|
|
model_path = model_path / data.name
|
|
|
|
draft_model_path = None
|
|
if data.draft:
|
|
if not data.draft.draft_model_name:
|
|
raise HTTPException(
|
|
400, "draft_model_name was not found inside the draft object."
|
|
)
|
|
|
|
draft_model_path = unwrap(
|
|
config.draft_model_config().get("draft_model_dir"), "models"
|
|
)
|
|
|
|
if not model_path.exists():
|
|
raise HTTPException(400, "model_path does not exist. Check model_name?")
|
|
|
|
load_callback = partial(
|
|
stream_model_load, request, data, model_path, draft_model_path
|
|
)
|
|
|
|
# Wrap in a semaphore if the queue isn't being skipped
|
|
if data.skip_queue:
|
|
logger.warning(
|
|
"Model load request is skipping the completions queue. "
|
|
"Unexpected results may occur."
|
|
)
|
|
else:
|
|
load_callback = partial(generate_with_semaphore, load_callback)
|
|
|
|
return EventSourceResponse(load_callback())
|
|
|
|
|
|
# Unload model endpoint
|
|
@app.post(
|
|
"/v1/model/unload",
|
|
dependencies=[Depends(check_admin_key), Depends(check_model_container)],
|
|
)
|
|
async def unload_model():
|
|
"""Unloads the currently loaded model."""
|
|
await model.unload_model()
|
|
|
|
|
|
@app.get("/v1/templates", dependencies=[Depends(check_api_key)])
|
|
@app.get("/v1/template/list", dependencies=[Depends(check_api_key)])
|
|
async def get_templates():
|
|
templates = get_all_templates()
|
|
template_strings = list(map(lambda template: template.stem, templates))
|
|
return TemplateList(data=template_strings)
|
|
|
|
|
|
@app.post(
|
|
"/v1/template/switch",
|
|
dependencies=[Depends(check_admin_key), Depends(check_model_container)],
|
|
)
|
|
async def switch_template(data: TemplateSwitchRequest):
|
|
"""Switch the currently loaded template"""
|
|
if not data.name:
|
|
raise HTTPException(400, "New template name not found.")
|
|
|
|
try:
|
|
template = get_template_from_file(data.name)
|
|
model.container.prompt_template = template
|
|
except FileNotFoundError as e:
|
|
raise HTTPException(400, "Template does not exist. Check the name?") from e
|
|
|
|
|
|
@app.post(
|
|
"/v1/template/unload",
|
|
dependencies=[Depends(check_admin_key), Depends(check_model_container)],
|
|
)
|
|
async def unload_template():
|
|
"""Unloads the currently selected template"""
|
|
|
|
model.container.prompt_template = None
|
|
|
|
|
|
# Sampler override endpoints
|
|
@app.get("/v1/sampling/overrides", dependencies=[Depends(check_api_key)])
|
|
@app.get("/v1/sampling/override/list", dependencies=[Depends(check_api_key)])
|
|
async def list_sampler_overrides():
|
|
"""API wrapper to list all currently applied sampler overrides"""
|
|
|
|
return sampling.overrides
|
|
|
|
|
|
@app.post(
|
|
"/v1/sampling/override/switch",
|
|
dependencies=[Depends(check_admin_key)],
|
|
)
|
|
async def switch_sampler_override(data: SamplerOverrideSwitchRequest):
|
|
"""Switch the currently loaded override preset"""
|
|
|
|
if data.preset:
|
|
try:
|
|
sampling.overrides_from_file(data.preset)
|
|
except FileNotFoundError as e:
|
|
raise HTTPException(
|
|
400, "Sampler override preset does not exist. Check the name?"
|
|
) from e
|
|
elif data.overrides:
|
|
sampling.overrides_from_dict(data.overrides)
|
|
else:
|
|
raise HTTPException(
|
|
400, "A sampler override preset or dictionary wasn't provided."
|
|
)
|
|
|
|
|
|
@app.post(
|
|
"/v1/sampling/override/unload",
|
|
dependencies=[Depends(check_admin_key)],
|
|
)
|
|
async def unload_sampler_override():
|
|
"""Unloads the currently selected override preset"""
|
|
|
|
sampling.overrides_from_dict({})
|
|
|
|
|
|
# Lora list endpoint
|
|
@app.get("/v1/loras", dependencies=[Depends(check_api_key)])
|
|
@app.get("/v1/lora/list", dependencies=[Depends(check_api_key)])
|
|
async def get_all_loras():
|
|
"""Lists all LoRAs in the lora directory."""
|
|
lora_path = pathlib.Path(unwrap(config.lora_config().get("lora_dir"), "loras"))
|
|
loras = get_lora_list(lora_path.resolve())
|
|
|
|
return loras
|
|
|
|
|
|
# Currently loaded loras endpoint
|
|
@app.get(
|
|
"/v1/lora",
|
|
dependencies=[Depends(check_api_key), Depends(check_model_container)],
|
|
)
|
|
async def get_active_loras():
|
|
"""Returns the currently loaded loras."""
|
|
active_loras = LoraList(
|
|
data=list(
|
|
map(
|
|
lambda lora: LoraCard(
|
|
id=pathlib.Path(lora.lora_path).parent.name,
|
|
scaling=lora.lora_scaling * lora.lora_r / lora.lora_alpha,
|
|
),
|
|
model.container.active_loras,
|
|
)
|
|
)
|
|
)
|
|
|
|
return active_loras
|
|
|
|
|
|
# Load lora endpoint
|
|
@app.post(
|
|
"/v1/lora/load",
|
|
dependencies=[Depends(check_admin_key), Depends(check_model_container)],
|
|
)
|
|
async def load_lora(data: LoraLoadRequest):
|
|
"""Loads a LoRA into the model container."""
|
|
|
|
if not data.loras:
|
|
raise HTTPException(400, "List of loras to load is not found.")
|
|
|
|
lora_dir = pathlib.Path(unwrap(config.lora_config().get("lora_dir"), "loras"))
|
|
if not lora_dir.exists():
|
|
raise HTTPException(
|
|
400,
|
|
"A parent lora directory does not exist. Check your config.yml?",
|
|
)
|
|
|
|
load_callback = partial(
|
|
run_in_threadpool, model.load_loras, lora_dir, **data.model_dump()
|
|
)
|
|
|
|
# Wrap in a semaphore if the queue isn't being skipped
|
|
if data.skip_queue:
|
|
logger.warning(
|
|
"Lora load request is skipping the completions queue. "
|
|
"Unexpected results may occur."
|
|
)
|
|
else:
|
|
load_callback = partial(call_with_semaphore, load_callback)
|
|
|
|
load_result = await load_callback()
|
|
|
|
return LoraLoadResponse(
|
|
success=unwrap(load_result.get("success"), []),
|
|
failure=unwrap(load_result.get("failure"), []),
|
|
)
|
|
|
|
|
|
# Unload lora endpoint
|
|
@app.post(
|
|
"/v1/lora/unload",
|
|
dependencies=[Depends(check_admin_key), Depends(check_model_container)],
|
|
)
|
|
async def unload_loras():
|
|
"""Unloads the currently loaded loras."""
|
|
|
|
model.unload_loras()
|
|
|
|
|
|
# Encode tokens endpoint
|
|
@app.post(
|
|
"/v1/token/encode",
|
|
dependencies=[Depends(check_api_key), Depends(check_model_container)],
|
|
)
|
|
async def encode_tokens(data: TokenEncodeRequest):
|
|
"""Encodes a string into tokens."""
|
|
raw_tokens = model.container.encode_tokens(data.text, **data.get_params())
|
|
tokens = unwrap(raw_tokens, [])
|
|
response = TokenEncodeResponse(tokens=tokens, length=len(tokens))
|
|
|
|
return response
|
|
|
|
|
|
# Decode tokens endpoint
|
|
@app.post(
|
|
"/v1/token/decode",
|
|
dependencies=[Depends(check_api_key), Depends(check_model_container)],
|
|
)
|
|
async def decode_tokens(data: TokenDecodeRequest):
|
|
"""Decodes tokens into a string."""
|
|
message = model.container.decode_tokens(data.tokens, **data.get_params())
|
|
response = TokenDecodeResponse(text=unwrap(message, ""))
|
|
|
|
return response
|
|
|
|
|
|
# Completions endpoint
|
|
@app.post(
|
|
"/v1/completions",
|
|
dependencies=[Depends(check_api_key), Depends(check_model_container)],
|
|
)
|
|
async def completion_request(request: Request, data: CompletionRequest):
|
|
"""Generates a completion from a prompt."""
|
|
model_path = model.container.get_model_path()
|
|
|
|
if isinstance(data.prompt, list):
|
|
data.prompt = "\n".join(data.prompt)
|
|
|
|
disable_request_streaming = unwrap(
|
|
config.developer_config().get("disable_request_streaming"), False
|
|
)
|
|
|
|
if data.stream and not disable_request_streaming:
|
|
generator_callback = partial(
|
|
stream_generate_completion, request, data, model_path
|
|
)
|
|
|
|
return EventSourceResponse(generate_with_semaphore(generator_callback))
|
|
else:
|
|
response = await call_with_semaphore(
|
|
partial(generate_completion, data, model_path)
|
|
)
|
|
|
|
return response
|
|
|
|
|
|
# Chat completions endpoint
|
|
@app.post(
|
|
"/v1/chat/completions",
|
|
dependencies=[Depends(check_api_key), Depends(check_model_container)],
|
|
)
|
|
async def chat_completion_request(request: Request, data: ChatCompletionRequest):
|
|
"""Generates a chat completion from a prompt."""
|
|
|
|
if model.container.prompt_template is None:
|
|
raise HTTPException(
|
|
422,
|
|
"This endpoint is disabled because a prompt template is not set.",
|
|
)
|
|
|
|
model_path = model.container.get_model_path()
|
|
|
|
if isinstance(data.messages, str):
|
|
prompt = data.messages
|
|
else:
|
|
prompt = format_prompt_with_template(data)
|
|
|
|
disable_request_streaming = unwrap(
|
|
config.developer_config().get("disable_request_streaming"), False
|
|
)
|
|
|
|
if data.stream and not disable_request_streaming:
|
|
generator_callback = partial(
|
|
stream_generate_chat_completion, prompt, request, data, model_path
|
|
)
|
|
|
|
return EventSourceResponse(generate_with_semaphore(generator_callback))
|
|
else:
|
|
response = await call_with_semaphore(
|
|
partial(generate_chat_completion, prompt, request, data, model_path)
|
|
)
|
|
|
|
return response
|
|
|
|
|
|
def start_api(host: str, port: int):
|
|
"""Isolated function to start the API server"""
|
|
|
|
# TODO: Move OAI API to a separate folder
|
|
logger.info(f"Developer documentation: http://{host}:{port}/redoc")
|
|
logger.info(f"Completions: http://{host}:{port}/v1/completions")
|
|
logger.info(f"Chat completions: http://{host}:{port}/v1/chat/completions")
|
|
|
|
uvicorn.run(
|
|
app,
|
|
host=host,
|
|
port=port,
|
|
log_config=UVICORN_LOG_CONFIG,
|
|
)
|