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from fastapi import APIRouter, Request
from fastapi.responses import StreamingResponse
from llama_index.core.workflow import StopEvent
from llama_index.core.llms import ChatMessage
from workflow.sql_workflow import sql_workflow, SQLWorkflow
from workflow.roleplay_workflow import RolePlayWorkflow
from workflow.modules import load_chat_store, MySQLChatStore, ToyStatusStore
from workflow.events import TokenEvent, StatusEvent
import asyncio, os, json
from concurrent.futures import ThreadPoolExecutor
from contextlib import asynccontextmanager
from typing import Dict, Any
from workflow.modules import load_chat_store
from llama_index.llms.ollama import Ollama
from prompts.default_prompts import FINAL_RESPONSE_PROMPT
from workflow.vllm_model import MyVllm
from datetime import datetime


CHAT_STORE_PATH = os.getenv("CHAT_STORE_PATH")
MYSQL_HOST = os.getenv("MYSQL_HOST")
MYSQL_USER = os.getenv("MYSQL_USER")
MYSQL_PASSWORD = os.getenv("MYSQL_PASSWORD")
MYSQL_DATABASE = os.getenv("MYSQL_DATABASE")
MYSQL_PORT = int(os.getenv("MYSQL_PORT"))

sql_chat_router = APIRouter(
    prefix="/sql_chat",
    tags=["sql", "chat"]
)

chat_store_manager = APIRouter(
    prefix="/modify_chat_store",
    tags=["chat_store"]
)

roleplay_router = APIRouter(
    prefix="/roleplay",
    tags=["roleplay"]
)

"""
接收数据格式
{
  "query": "Top 5 porn videos with url.", # 用户提问
  "clientVersion": "ios_3.1.4", # 客户端版本, 不做处理
  "traceId": "1290325592508092416", # 请求唯一标识, 不做处理
  "messageId": 1290325592508092400, # message表示, 不做处理
  "llmSessionId": "xxxxxxxx", # sessionId用于调取用户对话上下文
  "llmUserId": "xxxxxx"
}
"""

# 全局资源管理

polling_variable = 0

class ResourceManager:
    def __init__(self, max_concurrent=8):  # 基于24G显存可以支持2个9G模型
        self.semaphore = asyncio.Semaphore(max_concurrent)
        self.thread_pool = ThreadPoolExecutor(max_workers=max_concurrent)
        self.chat_stores: Dict[str, Any] = {}  # 缓存chat store实例

    async def get_chat_store(self, store_name: str):
        if store_name not in self.chat_stores:
            self.chat_stores[store_name] = load_chat_store(store_name)
        return self.chat_stores[store_name]

# 全局资源管理器
resource_manager = ResourceManager()

@asynccontextmanager
async def acquire_model_resource():
    try:
        await resource_manager.semaphore.acquire()
        yield
    finally:
        resource_manager.semaphore.release()

@sql_chat_router.post("/")
async def chat(request: Request):
    requestJson = await request.json()
    query = str(requestJson.get("query"))
    sessionId = str(requestJson.get("llmSessionId"))
    try:
        isLLMContext = int(requestJson.get("isLlmContext"))
        adultMode = int(requestJson.get("adultMode"))
        # isCache = int(request.get("isCache"))
        print(f"adultMode: {adultMode} - isLLMContext: {isLLMContext}")
        if adultMode == 1:
            adultMode = True
        else:
            adultMode = False
    except Exception as e:
        isLLMContext = 0
        adultMode = False
    # 调取用户对话上下文 elasticsearch
    # chat_history = parse_chat_history(sessionId)
    # try:
    #     chat_store = load_chat_store("testing_chat_store")
    # except:
    #     # 获取当前日期
    #     current_date = datetime.now().strftime('%Y%m%d')
    #     chat_store = load_chat_store(current_date)
    chat_store = MySQLChatStore(host=MYSQL_HOST, port=MYSQL_PORT, user=MYSQL_USER, password=MYSQL_PASSWORD, database=MYSQL_DATABASE)
    print(f"query: {query} - sessionId: {sessionId}")
    
    llm = MyVllm(
        model="huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2",
        api_key="token-abc123",
        base_url="http://localhost:17777/v1",
    )
    
    response_synthesis_prompt = FINAL_RESPONSE_PROMPT
    # Ollama("solonglin/qwen2.5-q6_k-abliterated", temperature=0.8, request_timeout=120, context_window=5000, keep_alive=-1),
    wf = SQLWorkflow(
        response_llm=llm,
        response_synthesis_prompt=response_synthesis_prompt,
        chat_store=chat_store,
        sessionId=sessionId,
        context_flag=isLLMContext,
        adultMode=adultMode,
        verbose=True,
        timeout=60
    )
    r = wf.run(query=query)
    async def generator():
        async for event in r.stream_events():
            if await request.is_disconnected():
                break
            if isinstance(event, TokenEvent):
                token = event.token
                yield token
            if isinstance(event, StatusEvent):
                yield event.status
            if isinstance(event, str):
                yield event
            await asyncio.sleep(0)
        # result = await sql_workflow(query=query, chat_store=chat_store, sessionId=sessionId, llm=llm, context_flag=isLLMContext, adultMode=adultMode)
    return StreamingResponse(content=generator(), media_type="text/event-stream")

@roleplay_router.post("/")
async def roleplay(request: Request):
    requestJson = await request.json()
    query = str(requestJson.get("query"))
    sessionId = "rp_" + str(requestJson.get("llmSessionId"))
    # messageId = str(requestJson.get("messageId"))
    toy_info = requestJson.get("toyIds")
    if toy_info:
        toy_names = [item["name"] for item in toy_info]
    else:
        toy_names = None
    chat_store = MySQLChatStore(host=MYSQL_HOST, port=MYSQL_PORT, user=MYSQL_USER, password=MYSQL_PASSWORD, database=MYSQL_DATABASE)
    toy_status_store = ToyStatusStore(host=MYSQL_HOST, port=MYSQL_PORT, user=MYSQL_USER, password=MYSQL_PASSWORD, database=MYSQL_DATABASE)
    print(f"query: {query} - sessionId: {sessionId} - toyName: {toy_names}")
    
    # setup llm
    llm = MyVllm(
        model="huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2",
        api_key="token-abc123",
        base_url="http://localhost:17777/v1",
    )
    
    # init workflow
    wf = RolePlayWorkflow(
        response_llm=llm,
        chat_store=chat_store,
        toy_status_store=toy_status_store,
        sessionId=sessionId,
        gender="female",
        toy_names=toy_names,
        verbose=True,
        timeout=60,
    )
    r = wf.run(query=query)
    async def generator():
        async for event in r.stream_events():
            if await request.is_disconnected():
                break
            if isinstance(event, TokenEvent):
                token = event.token
                yield token
            if isinstance(event, StatusEvent):
                yield event.status
            if isinstance(event, str):
                yield event
            await asyncio.sleep(0)
    return StreamingResponse(content=generator(), media_type="text/event-stream")


@chat_store_manager.post("/")
async def modify_chat_store(request: Request):
    try:
        request = await request.json()
        sessionId = request.get("sessionId")
        upMessageBody = request.get("upMessageBody")
        downMessageBody = request.get("downMessageBody")
        
        chat_store = MySQLChatStore(MYSQL_HOST, MYSQL_PORT, MYSQL_USER, MYSQL_PASSWORD, MYSQL_DATABASE)
        chat_store.del_message(sessionId, upMessageBody)
        chat_store.del_message(sessionId, downMessageBody)
        return {"status": "SUCCESS"}
    except Exception as e:
        return {"status": "FAILED", "error": str(e)}

	from fastapi import APIRouter, Request
	from fastapi.responses import StreamingResponse
	from llama_index.core.workflow import StopEvent
	from llama_index.core.llms import ChatMessage
	from workflow.sql_workflow import sql_workflow, SQLWorkflow
	from workflow.roleplay_workflow import RolePlayWorkflow
	from workflow.modules import load_chat_store, MySQLChatStore, ToyStatusStore
	from workflow.events import TokenEvent, StatusEvent
	import asyncio, os, json
	from concurrent.futures import ThreadPoolExecutor
	from contextlib import asynccontextmanager
	from typing import Dict, Any
	from workflow.modules import load_chat_store
	from llama_index.llms.ollama import Ollama
	from prompts.default_prompts import FINAL_RESPONSE_PROMPT
	from workflow.vllm_model import MyVllm
	from datetime import datetime


	CHAT_STORE_PATH = os.getenv("CHAT_STORE_PATH")
	MYSQL_HOST = os.getenv("MYSQL_HOST")
	MYSQL_USER = os.getenv("MYSQL_USER")
	MYSQL_PASSWORD = os.getenv("MYSQL_PASSWORD")
	MYSQL_DATABASE = os.getenv("MYSQL_DATABASE")
	MYSQL_PORT = int(os.getenv("MYSQL_PORT"))

	sql_chat_router = APIRouter(
	prefix="/sql_chat",
	tags=["sql", "chat"]
	)

	chat_store_manager = APIRouter(
	prefix="/modify_chat_store",
	tags=["chat_store"]
	)

	roleplay_router = APIRouter(
	prefix="/roleplay",
	tags=["roleplay"]
	)

	"""
	接收数据格式
	{
	"query": "Top 5 porn videos with url.", # 用户提问
	"clientVersion": "ios_3.1.4", # 客户端版本, 不做处理
	"traceId": "1290325592508092416", # 请求唯一标识, 不做处理
	"messageId": 1290325592508092400, # message表示, 不做处理
	"llmSessionId": "xxxxxxxx", # sessionId用于调取用户对话上下文
	"llmUserId": "xxxxxx"
	}
	"""

	# 全局资源管理

	polling_variable = 0

	class ResourceManager:
	def __init__(self, max_concurrent=8): # 基于24G显存可以支持2个9G模型
	self.semaphore = asyncio.Semaphore(max_concurrent)
	self.thread_pool = ThreadPoolExecutor(max_workers=max_concurrent)
	self.chat_stores: Dict[str, Any] = {} # 缓存chat store实例

	async def get_chat_store(self, store_name: str):
	if store_name not in self.chat_stores:
	self.chat_stores[store_name] = load_chat_store(store_name)
	return self.chat_stores[store_name]

	# 全局资源管理器
	resource_manager = ResourceManager()

	@asynccontextmanager
	async def acquire_model_resource():
	try:
	await resource_manager.semaphore.acquire()
	yield
	finally:
	resource_manager.semaphore.release()

	@sql_chat_router.post("/")
	async def chat(request: Request):
	requestJson = await request.json()
	query = str(requestJson.get("query"))
	sessionId = str(requestJson.get("llmSessionId"))
	try:
	isLLMContext = int(requestJson.get("isLlmContext"))
	adultMode = int(requestJson.get("adultMode"))
	# isCache = int(request.get("isCache"))
	print(f"adultMode: {adultMode} - isLLMContext: {isLLMContext}")
	if adultMode == 1:
	adultMode = True
	else:
	adultMode = False
	except Exception as e:
	isLLMContext = 0
	adultMode = False
	# 调取用户对话上下文 elasticsearch
	# chat_history = parse_chat_history(sessionId)
	# try:
	# chat_store = load_chat_store("testing_chat_store")
	# except:
	# # 获取当前日期
	# current_date = datetime.now().strftime('%Y%m%d')
	# chat_store = load_chat_store(current_date)
	chat_store = MySQLChatStore(host=MYSQL_HOST, port=MYSQL_PORT, user=MYSQL_USER, password=MYSQL_PASSWORD, database=MYSQL_DATABASE)
	print(f"query: {query} - sessionId: {sessionId}")

	llm = MyVllm(
	model="huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2",
	api_key="token-abc123",
	base_url="http://localhost:17777/v1",
	)

	response_synthesis_prompt = FINAL_RESPONSE_PROMPT
	# Ollama("solonglin/qwen2.5-q6_k-abliterated", temperature=0.8, request_timeout=120, context_window=5000, keep_alive=-1),
	wf = SQLWorkflow(
	response_llm=llm,
	response_synthesis_prompt=response_synthesis_prompt,
	chat_store=chat_store,
	sessionId=sessionId,
	context_flag=isLLMContext,
	adultMode=adultMode,
	verbose=True,
	timeout=60
	)
	r = wf.run(query=query)
	async def generator():
	async for event in r.stream_events():
	if await request.is_disconnected():
	break
	if isinstance(event, TokenEvent):
	token = event.token
	yield token
	if isinstance(event, StatusEvent):
	yield event.status
	if isinstance(event, str):
	yield event
	await asyncio.sleep(0)
	# result = await sql_workflow(query=query, chat_store=chat_store, sessionId=sessionId, llm=llm, context_flag=isLLMContext, adultMode=adultMode)
	return StreamingResponse(content=generator(), media_type="text/event-stream")

	@roleplay_router.post("/")
	async def roleplay(request: Request):
	requestJson = await request.json()
	query = str(requestJson.get("query"))
	sessionId = "rp_" + str(requestJson.get("llmSessionId"))
	# messageId = str(requestJson.get("messageId"))
	toy_info = requestJson.get("toyIds")
	if toy_info:
	toy_names = [item["name"] for item in toy_info]
	else:
	toy_names = None
	chat_store = MySQLChatStore(host=MYSQL_HOST, port=MYSQL_PORT, user=MYSQL_USER, password=MYSQL_PASSWORD, database=MYSQL_DATABASE)
	toy_status_store = ToyStatusStore(host=MYSQL_HOST, port=MYSQL_PORT, user=MYSQL_USER, password=MYSQL_PASSWORD, database=MYSQL_DATABASE)
	print(f"query: {query} - sessionId: {sessionId} - toyName: {toy_names}")

	# setup llm
	llm = MyVllm(
	model="huihui-ai/Qwen2.5-7B-Instruct-abliterated-v2",
	api_key="token-abc123",
	base_url="http://localhost:17777/v1",
	)

	# init workflow
	wf = RolePlayWorkflow(
	response_llm=llm,
	chat_store=chat_store,
	toy_status_store=toy_status_store,
	sessionId=sessionId,
	gender="female",
	toy_names=toy_names,
	verbose=True,
	timeout=60,
	)
	r = wf.run(query=query)
	async def generator():
	async for event in r.stream_events():
	if await request.is_disconnected():
	break
	if isinstance(event, TokenEvent):
	token = event.token
	yield token
	if isinstance(event, StatusEvent):
	yield event.status
	if isinstance(event, str):
	yield event
	await asyncio.sleep(0)
	return StreamingResponse(content=generator(), media_type="text/event-stream")


	@chat_store_manager.post("/")
	async def modify_chat_store(request: Request):
	try:
	request = await request.json()
	sessionId = request.get("sessionId")
	upMessageBody = request.get("upMessageBody")
	downMessageBody = request.get("downMessageBody")

	chat_store = MySQLChatStore(MYSQL_HOST, MYSQL_PORT, MYSQL_USER, MYSQL_PASSWORD, MYSQL_DATABASE)
	chat_store.del_message(sessionId, upMessageBody)
	chat_store.del_message(sessionId, downMessageBody)
	return {"status": "SUCCESS"}
	except Exception as e:
	return {"status": "FAILED", "error": str(e)}