RWKV-Runner/backend-python/routes/completion.py
2024-04-30 21:52:47 +08:00

566 lines
20 KiB
Python

import asyncio
import json
from threading import Lock
from typing import List, Union
from enum import Enum
import base64
from fastapi import APIRouter, Request, status, HTTPException
from sse_starlette.sse import EventSourceResponse
from pydantic import BaseModel, Field
import tiktoken
from utils.rwkv import *
from utils.log import quick_log
import global_var
router = APIRouter()
class Role(Enum):
User = "user"
Assistant = "assistant"
System = "system"
class Message(BaseModel):
role: Role
content: str = Field(min_length=0)
raw: bool = Field(False, description="Whether to treat content as raw text")
default_stop = [
"\n\nUser",
"\n\nQuestion",
"\n\nQ",
"\n\nHuman",
"\n\nBob",
"\n\nAssistant",
"\n\nAnswer",
"\n\nA",
"\n\nBot",
"\n\nAlice",
]
class ChatCompletionBody(ModelConfigBody):
messages: Union[List[Message], None]
model: Union[str, None] = "rwkv"
stream: bool = False
stop: Union[str, List[str], None] = default_stop
user_name: Union[str, None] = Field(
None, description="Internal user name", min_length=1
)
assistant_name: Union[str, None] = Field(
None, description="Internal assistant name", min_length=1
)
system_name: Union[str, None] = Field(
None, description="Internal system name", min_length=1
)
presystem: bool = Field(
True, description="Whether to insert default system prompt at the beginning"
)
model_config = {
"json_schema_extra": {
"example": {
"messages": [
{"role": Role.User.value, "content": "hello", "raw": False}
],
"model": "rwkv",
"stream": False,
"stop": None,
"user_name": None,
"assistant_name": None,
"system_name": None,
"presystem": True,
"max_tokens": 1000,
"temperature": 1,
"top_p": 0.3,
"presence_penalty": 0,
"frequency_penalty": 1,
}
}
}
class CompletionBody(ModelConfigBody):
prompt: Union[str, List[str], None]
model: Union[str, None] = "rwkv"
stream: bool = False
stop: Union[str, List[str], None] = None
model_config = {
"json_schema_extra": {
"example": {
"prompt": "The following is an epic science fiction masterpiece that is immortalized, "
+ "with delicate descriptions and grand depictions of interstellar civilization wars.\nChapter 1.\n",
"model": "rwkv",
"stream": False,
"stop": None,
"max_tokens": 100,
"temperature": 1,
"top_p": 0.3,
"presence_penalty": 0,
"frequency_penalty": 1,
}
}
}
completion_lock = Lock()
requests_num = 0
async def eval_rwkv(
model: AbstractRWKV,
request: Request,
body: ModelConfigBody,
prompt: str,
stream: bool,
stop: Union[str, List[str], None],
chat_mode: bool,
):
global requests_num
requests_num = requests_num + 1
quick_log(request, None, "Start Waiting. RequestsNum: " + str(requests_num))
while completion_lock.locked():
if await request.is_disconnected():
requests_num = requests_num - 1
print(f"{request.client} Stop Waiting (Lock)")
quick_log(
request,
None,
"Stop Waiting (Lock). RequestsNum: " + str(requests_num),
)
return
await asyncio.sleep(0.1)
else:
with completion_lock:
if await request.is_disconnected():
requests_num = requests_num - 1
print(f"{request.client} Stop Waiting (Lock)")
quick_log(
request,
None,
"Stop Waiting (Lock). RequestsNum: " + str(requests_num),
)
return
set_rwkv_config(model, global_var.get(global_var.Model_Config))
set_rwkv_config(model, body)
print(get_rwkv_config(model))
response, prompt_tokens, completion_tokens = "", 0, 0
for response, delta, prompt_tokens, completion_tokens in model.generate(
prompt,
stop=stop,
):
if await request.is_disconnected():
break
if stream:
yield json.dumps(
{
"object": (
"chat.completion.chunk"
if chat_mode
else "text_completion"
),
# "response": response,
"model": model.name,
"choices": [
(
{
"delta": {"content": delta},
"index": 0,
"finish_reason": None,
}
if chat_mode
else {
"text": delta,
"index": 0,
"finish_reason": None,
}
)
],
}
)
# torch_gc()
requests_num = requests_num - 1
if await request.is_disconnected():
print(f"{request.client} Stop Waiting")
quick_log(
request,
body,
response + "\nStop Waiting. RequestsNum: " + str(requests_num),
)
return
quick_log(
request,
body,
response + "\nFinished. RequestsNum: " + str(requests_num),
)
if stream:
yield json.dumps(
{
"object": (
"chat.completion.chunk" if chat_mode else "text_completion"
),
# "response": response,
"model": model.name,
"choices": [
(
{
"delta": {},
"index": 0,
"finish_reason": "stop",
}
if chat_mode
else {
"text": "",
"index": 0,
"finish_reason": "stop",
}
)
],
}
)
yield "[DONE]"
else:
yield {
"object": "chat.completion" if chat_mode else "text_completion",
# "response": response,
"model": model.name,
"usage": {
"prompt_tokens": prompt_tokens,
"completion_tokens": completion_tokens,
"total_tokens": prompt_tokens + completion_tokens,
},
"choices": [
(
{
"message": {
"role": Role.Assistant.value,
"content": response,
},
"index": 0,
"finish_reason": "stop",
}
if chat_mode
else {
"text": response,
"index": 0,
"finish_reason": "stop",
}
)
],
}
def chat_template_old(
model: TextRWKV, body: ChatCompletionBody, interface: str, user: str, bot: str
):
is_raven = model.rwkv_type == RWKVType.Raven
completion_text: str = ""
basic_system: Union[str, None] = None
if body.presystem:
if body.messages[0].role == Role.System:
basic_system = body.messages[0].content
if basic_system is None:
completion_text = (
f"""
The following is a coherent verbose detailed conversation between a girl named {bot} and her friend {user}. \
{bot} is very intelligent, creative and friendly. \
{bot} is unlikely to disagree with {user}, and {bot} doesn't like to ask {user} questions. \
{bot} likes to tell {user} a lot about herself and her opinions. \
{bot} usually gives {user} kind, helpful and informative advices.\n
"""
if is_raven
else (
f"{user}{interface} hi\n\n{bot}{interface} Hi. "
+ "I am your assistant and I will provide expert full response in full details. Please feel free to ask any question and I will always answer it.\n\n"
)
)
else:
if not body.messages[0].raw:
basic_system = (
basic_system.replace("\r\n", "\n")
.replace("\r", "\n")
.replace("\n\n", "\n")
.replace("\n", " ")
.strip()
)
completion_text = (
(
f"The following is a coherent verbose detailed conversation between a girl named {bot} and her friend {user}. "
if is_raven
else f"{user}{interface} hi\n\n{bot}{interface} Hi. "
)
+ basic_system.replace("You are", f"{bot} is" if is_raven else "I am")
.replace("you are", f"{bot} is" if is_raven else "I am")
.replace("You're", f"{bot} is" if is_raven else "I'm")
.replace("you're", f"{bot} is" if is_raven else "I'm")
.replace("You", f"{bot}" if is_raven else "I")
.replace("you", f"{bot}" if is_raven else "I")
.replace("Your", f"{bot}'s" if is_raven else "My")
.replace("your", f"{bot}'s" if is_raven else "my")
.replace("", f"{bot}" if is_raven else "")
+ "\n\n"
)
for message in body.messages[(0 if basic_system is None else 1) :]:
append_message: str = ""
if message.role == Role.User:
append_message = f"{user}{interface} " + message.content
elif message.role == Role.Assistant:
append_message = f"{bot}{interface} " + message.content
elif message.role == Role.System:
append_message = message.content
if not message.raw:
append_message = (
append_message.replace("\r\n", "\n")
.replace("\r", "\n")
.replace("\n\n", "\n")
.strip()
)
completion_text += append_message + "\n\n"
completion_text += f"{bot}{interface}"
return completion_text
def chat_template(
model: TextRWKV, body: ChatCompletionBody, interface: str, user: str, bot: str
):
completion_text: str = ""
if body.presystem:
completion_text = (
f"{user}{interface} hi\n\n{bot}{interface} Hi. "
+ "I am your assistant and I will provide expert full response in full details. Please feel free to ask any question and I will always answer it.\n\n"
)
system = "System" if body.system_name is None else body.system_name
for message in body.messages:
append_message: str = ""
if message.role == Role.User:
append_message = f"{user}{interface} " + message.content
elif message.role == Role.Assistant:
append_message = f"{bot}{interface} " + message.content
elif message.role == Role.System:
append_message = f"{system}{interface} " + message.content
completion_text += append_message + "\n\n"
completion_text += f"{bot}{interface}"
return completion_text
@router.post("/v1/chat/completions", tags=["Completions"])
@router.post("/chat/completions", tags=["Completions"])
async def chat_completions(body: ChatCompletionBody, request: Request):
model: TextRWKV = global_var.get(global_var.Model)
if model is None:
raise HTTPException(status.HTTP_400_BAD_REQUEST, "model not loaded")
if body.messages is None or body.messages == []:
raise HTTPException(status.HTTP_400_BAD_REQUEST, "messages not found")
interface = model.interface
user = model.user if body.user_name is None else body.user_name
bot = model.bot if body.assistant_name is None else body.assistant_name
if model.version < 5:
completion_text = chat_template_old(model, body, interface, user, bot)
else:
completion_text = chat_template(model, body, interface, user, bot)
user_code = model.pipeline.decode([model.pipeline.encode(user)[0]])
bot_code = model.pipeline.decode([model.pipeline.encode(bot)[0]])
if type(body.stop) == str:
body.stop = [body.stop, f"\n\n{user_code}", f"\n\n{bot_code}"]
elif type(body.stop) == list:
body.stop.append(f"\n\n{user_code}")
body.stop.append(f"\n\n{bot_code}")
elif body.stop is None:
body.stop = default_stop + [f"\n\n{user_code}", f"\n\n{bot_code}"]
# if not body.presystem:
# body.stop.append("\n\n")
if body.stream:
return EventSourceResponse(
eval_rwkv(
model, request, body, completion_text, body.stream, body.stop, True
)
)
else:
try:
return await eval_rwkv(
model, request, body, completion_text, body.stream, body.stop, True
).__anext__()
except StopAsyncIteration:
return None
@router.post("/v1/completions", tags=["Completions"])
@router.post("/completions", tags=["Completions"])
async def completions(body: CompletionBody, request: Request):
model: AbstractRWKV = global_var.get(global_var.Model)
if model is None:
raise HTTPException(status.HTTP_400_BAD_REQUEST, "model not loaded")
if body.prompt is None or body.prompt == "" or body.prompt == []:
raise HTTPException(status.HTTP_400_BAD_REQUEST, "prompt not found")
if type(body.prompt) == list:
body.prompt = body.prompt[0] # TODO: support multiple prompts
if body.stream:
return EventSourceResponse(
eval_rwkv(model, request, body, body.prompt, body.stream, body.stop, False)
)
else:
try:
return await eval_rwkv(
model, request, body, body.prompt, body.stream, body.stop, False
).__anext__()
except StopAsyncIteration:
return None
class EmbeddingsBody(BaseModel):
input: Union[str, List[str], List[List[int]], None]
model: Union[str, None] = "rwkv"
encoding_format: str = None
fast_mode: bool = False
model_config = {
"json_schema_extra": {
"example": {
"input": "a big apple",
"model": "rwkv",
"encoding_format": None,
"fast_mode": False,
}
}
}
def embedding_base64(embedding: List[float]) -> str:
import numpy as np
return base64.b64encode(np.array(embedding).astype(np.float32)).decode("utf-8")
@router.post("/v1/embeddings", tags=["Embeddings"])
@router.post("/embeddings", tags=["Embeddings"])
@router.post("/v1/engines/text-embedding-ada-002/embeddings", tags=["Embeddings"])
@router.post("/engines/text-embedding-ada-002/embeddings", tags=["Embeddings"])
async def embeddings(body: EmbeddingsBody, request: Request):
model: AbstractRWKV = global_var.get(global_var.Model)
if model is None:
raise HTTPException(status.HTTP_400_BAD_REQUEST, "model not loaded")
if body.input is None or body.input == "" or body.input == [] or body.input == [[]]:
raise HTTPException(status.HTTP_400_BAD_REQUEST, "input not found")
global requests_num
requests_num = requests_num + 1
quick_log(request, None, "Start Waiting. RequestsNum: " + str(requests_num))
while completion_lock.locked():
if await request.is_disconnected():
requests_num = requests_num - 1
print(f"{request.client} Stop Waiting (Lock)")
quick_log(
request,
None,
"Stop Waiting (Lock). RequestsNum: " + str(requests_num),
)
return
await asyncio.sleep(0.1)
else:
with completion_lock:
if await request.is_disconnected():
requests_num = requests_num - 1
print(f"{request.client} Stop Waiting (Lock)")
quick_log(
request,
None,
"Stop Waiting (Lock). RequestsNum: " + str(requests_num),
)
return
base64_format = False
if body.encoding_format == "base64":
base64_format = True
embeddings = []
prompt_tokens = 0
if type(body.input) == list:
if type(body.input[0]) == list:
encoding = tiktoken.model.encoding_for_model(
"text-embedding-ada-002"
)
for i in range(len(body.input)):
if await request.is_disconnected():
break
input = encoding.decode(body.input[i])
embedding, token_len = model.get_embedding(
input, body.fast_mode
)
prompt_tokens = prompt_tokens + token_len
if base64_format:
embedding = embedding_base64(embedding)
embeddings.append(embedding)
else:
for i in range(len(body.input)):
if await request.is_disconnected():
break
embedding, token_len = model.get_embedding(
body.input[i], body.fast_mode
)
prompt_tokens = prompt_tokens + token_len
if base64_format:
embedding = embedding_base64(embedding)
embeddings.append(embedding)
else:
embedding, prompt_tokens = model.get_embedding(
body.input, body.fast_mode
)
if base64_format:
embedding = embedding_base64(embedding)
embeddings.append(embedding)
requests_num = requests_num - 1
if await request.is_disconnected():
print(f"{request.client} Stop Waiting")
quick_log(
request,
None,
"Stop Waiting. RequestsNum: " + str(requests_num),
)
return
quick_log(
request,
None,
"Finished. RequestsNum: " + str(requests_num),
)
ret_data = [
{
"object": "embedding",
"index": i,
"embedding": embedding,
}
for i, embedding in enumerate(embeddings)
]
return {
"object": "list",
"data": ret_data,
"model": model.name,
"usage": {
"prompt_tokens": prompt_tokens,
"total_tokens": prompt_tokens,
},
}