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4 Commits

Author SHA1 Message Date
2984aaa4be 修改崩溃bug 2025-07-10 09:30:45 +08:00
873dd45584 修改崩溃bug 2025-07-10 09:30:32 +08:00
d1326b7776 修复服务器bug 2025-07-09 19:58:44 +08:00
23b62b60a5 完善对话生成逻辑 2025-07-09 14:55:51 +08:00
17 changed files with 441 additions and 278 deletions

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@ -1,21 +1,47 @@
import logging
from typing import Tuple
import requests
from ollama import Client, ResponseError
import tiktoken
import random
from Utils.AIGCLog import AIGCLog
class AICore:
modelMaxTokens = 128000
# 初始化 DeepSeek 使用的 Tokenizer (cl100k_base)
encoder = tiktoken.get_encoding("cl100k_base")
logger = AIGCLog(name = "AIGC", log_file = "aigc.log")
def __init__(self, model):
#初始化ollama客户端
self.ollamaClient = Client(host='http://localhost:11434', headers={'x-some-header': 'some-value'})
self.modelName = model
response = self.ollamaClient.show(model)
modelMaxTokens = response.modelinfo['qwen2.context_length']
def getPromptToken(self, prompt)-> int:
tokens = self.encoder.encode(prompt)
return len(tokens)
def generateAI(self, promptStr: str) -> Tuple[bool, str]:
try:
response = self.ollamaClient.generate(
model = self.modelName,
stream = False,
prompt = promptStr,
options={
"temperature": random.uniform(1.0, 1.5),
"repeat_penalty": 1.2, # 抑制重复
"top_p": random.uniform(0.7, 0.95),
"num_ctx": 4096, # 上下文长度
}
)
return True, response.response
except ResponseError as e:
if e.status_code == 503:
print("🔄 服务不可用5秒后重试...")
return False,"ollama 服务不可用"
except Exception as e:
print(f"🔥 未预料错误: {str(e)}")
return False, "未预料错误"

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@ -103,17 +103,18 @@ class DatabaseHandle:
conn.commit()
return cursor.lastrowid
def get_chats_by_character_id(self, character_id: int) -> list:
def get_chats_by_character_id(self, character_id: str) -> list:
"""
根据角色ID查询聊天记录target_id为空时返回全部数据
:param target_id: 目标角色IDNone时返回全部记录
:return: 聊天记录字典列表
"""
sorted_ids = sorted(character_id.split(","), key=int) # 按数值升序
normalized_param = ",".join(sorted_ids)
with self._get_connection() as conn:
cursor = conn.cursor()
sql = "SELECT * FROM chat_records WHERE ',' || character_ids || ',' LIKE '%,' || ? || ',%'"
params = (str(character_id))
cursor.execute(sql, params)
# 转换结果为字典列表
sql = "SELECT * FROM chat_records WHERE character_ids = ?"
cursor.execute(sql, (normalized_param,))
columns = [col[0] for col in cursor.description]
return [dict(zip(columns, row)) for row in cursor.fetchall()]

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@ -2,7 +2,7 @@
chcp 65001 > nul
set OLLAMA_MODEL=deepseek-r1:7b
rem 启动Ollama服务
start "Ollama DeepSeek" cmd /k ollama run %OLLAMA_MODEL%
start "Ollama DeepSeek" cmd /k ollama serve
rem 检测11434端口是否就绪
echo 等待Ollama服务启动...

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@ -26,11 +26,15 @@ parser.add_argument('--model', type=str, default='deepseek-r1:1.5b',
args = parser.parse_args()
logger.log(logging.INFO, f"使用的模型是 {args.model}")
maxAIRegerateCount = 5
maxAIRegerateCount = 5 #最大重新生成次数
regenerateCount = 1 #当前重新生成次数
totalAIGenerateCount = 1 #客户端生成AI响应总数
currentGenerateCount = 0 #当前生成次数
lastPrompt = ""
character_id1 = 0
character_id2 = 0
aicore = AICore(args.model)
database = DatabaseHandle()
async def heartbeat(websocket: WebSocket):
pass
@ -48,6 +52,18 @@ async def senddata(websocket: WebSocket, protocol: dict):
json_string = json.dumps(protocol, ensure_ascii=False)
await websocket.send_text(json_string)
async def sendprotocol(websocket: WebSocket, cmd: str, status: int, message: str, data: str):
# 将AI响应发送回UE5
protocol = {}
protocol["cmd"] = cmd
protocol["status"] = status
protocol["message"] = message
protocol["data"] = data
if websocket.client_state == WebSocketState.CONNECTED:
json_string = json.dumps(protocol, ensure_ascii=False)
await websocket.send_text(json_string)
# WebSocket路由处理
@app.websocket("/ws/{client_id}")
async def websocket_endpoint(websocket: WebSocket, client_id: str):
@ -62,20 +78,7 @@ async def websocket_endpoint(websocket: WebSocket, client_id: str):
data = await websocket.receive_text()
logger.log(logging.INFO, f"收到UE5消息 [{client_id}]: {data}")
await process_protocol_json(data, websocket)
# success, prompt = process_prompt(data)
# global lastPrompt
# lastPrompt = prompt
# # 调用AI生成响应
# if(success):
# asyncio.create_task(generateAIChat(prompt, websocket))
# await senddata(websocket, 0, [])
# else:
# await senddata(websocket, -1, [])
except WebSocketDisconnect:
#manager.disconnect(client_id)
logger.log(logging.WARNING, f"UE5客户端主动断开 [{client_id}]")
@ -87,7 +90,7 @@ async def handle_characterlist(client: WebSocket):
### 获得数据库中的角色信息###
characters = database.get_character_byname("")
protocol = {}
protocol["cmd"] = "CharacterList"
protocol["cmd"] = "RequestCharacterInfos"
protocol["status"] = 1
protocol["message"] = "success"
characterforUE = {}
@ -95,6 +98,84 @@ async def handle_characterlist(client: WebSocket):
protocol["data"] = json.dumps(characterforUE)
await senddata(client, protocol)
async def handle_characternames(client: WebSocket):
### 获得数据库中的角色信息###
characters = database.get_character_byname("")
protocol = {}
protocol["cmd"] = "RequestCharacterNames"
protocol["status"] = 1
protocol["message"] = "success"
characterforUE = {}
characterforUE["characterInfos"] = characters
protocol["data"] = json.dumps(characterforUE)
await senddata(client, protocol)
async def generate_aichat(promptStr: str, client: WebSocket| None = None):
dynamic_token = str(int(time.time() % 1000))
promptStr = f"""
[动态标识码:{dynamic_token}]
""" + promptStr
logger.log(logging.INFO, "prompt:" + promptStr)
starttime = time.time()
success, response, = aicore.generateAI(promptStr)
if(success):
logger.log(logging.INFO, "接口调用耗时 :" + str(time.time() - starttime))
logger.log(logging.INFO, "AI生成" + response)
#处理ai输出内容
think_remove_text = re.sub(r'<think>.*?</think>', '', response, flags=re.DOTALL)
pattern = r".*<format>(.*?)</format>" # .* 吞掉前面所有字符,定位最后一组
match = re.search(pattern, think_remove_text, re.DOTALL)
if not match:
#生成内容格式错误
if await reGenerateAIChat(lastPrompt, client):
pass
else:
#超过重新生成次数
logger.log(logging.ERROR, "请更换prompt,或者升级模型大小")
await sendprotocol(client, "AiChatGenerate", 0, "请更换prompt,或者升级模型大小", "")
else:
#生成内容格式正确
core_dialog = match.group(1).strip()
dialog_lines = [line.strip() for line in core_dialog.split('\n') if line.strip()]
if len(dialog_lines) != 4:
#生成内容格式错误
if await reGenerateAIChat(lastPrompt, client):
pass
else:
logger.log(logging.ERROR, "请更换prompt或者升级模型大小")
await sendprotocol(client, "AiChatGenerate", 0, "请更换prompt或者升级模型大小", "")
else:
logger.log(logging.INFO, "AI的输出正确\n" + core_dialog)
global regenerateCount
regenerateCount = 0
#保存数据到数据库
database.add_chat({"character_ids":f"{character_id1},{character_id2}","chat":f"{" ".join(dialog_lines)}"})
await sendprotocol(client, "AiChatGenerate", 1, "AI生成成功", "|".join(dialog_lines))
else:
await sendprotocol(client, "AiChatGenerate", -1, "调用ollama服务失败", "")
async def handle_aichat_generate(client: WebSocket, aichat_data:str):
### 处理ai prompt###
success, prompt = process_prompt(aichat_data)
global lastPrompt
lastPrompt = prompt
# 调用AI生成响应
if(success):
#asyncio.create_task(generateAIChat(prompt, client))
global currentGenerateCount
while currentGenerateCount < totalAIGenerateCount:
currentGenerateCount += 1
await generate_aichat(prompt, client)
currentGenerateCount = 0
#全部生成完成
await sendprotocol(client, "AiChatGenerate", 2, "AI生成成功", "")
else:
#prompt生成失败
await sendprotocol(client, "AiChatGenerate", -1, "prompt convert failed", "")
async def handle_addcharacter(client: WebSocket, chracterJson: str):
### 添加角色到数据库 ###
character_info = json.loads(chracterJson)
@ -109,10 +190,14 @@ async def process_protocol_json(json_str: str, client: WebSocket):
protocol = json.loads(json_str)
cmd = protocol.get("cmd")
data = protocol.get("data")
if cmd == "CharacterList":
if cmd == "RequestCharacterInfos":
await handle_characterlist(client)
elif cmd == "RequestCharacterNames":
await handle_characternames(client)
elif cmd == "AddCharacter":
await handle_addcharacter(client, data)
elif cmd == "AiChatGenerate":
await handle_aichat_generate(client, data)
except json.JSONDecodeError as e:
print(f"JSON解析错误: {e}")
@ -121,42 +206,65 @@ async def process_protocol_json(json_str: str, client: WebSocket):
def process_prompt(promptFromUE: str) -> Tuple[bool, str]:
try:
data = json.loads(promptFromUE)
global maxAIRegerateCount
# 提取数据
dialog_scene = data["dialogContent"]["dialogScene"]
persons = data["persons"]
dialog_scene = data["dialogScene"]
global totalAIGenerateCount
totalAIGenerateCount = data["generateCount"]
persons = data["characterName"]
assert len(persons) == 2
for person in persons:
print(f" 姓名: {person['name']}, 职业: {person['job']}")
characterInfo1 = database.get_character_byname(persons[0])
characterInfo2 = database.get_character_byname(persons[1])
global character_id1, character_id2
character_id1 = characterInfo1[0]["id"]
character_id2 = characterInfo2[0]["id"]
chat_history = database.get_chats_by_character_id(str(character_id1) + "," + str(character_id2))
#整理对话记录
result = result = '\n'.join([item['chat'] for item in chat_history])
prompt = f"""
你是一个游戏NPC对话生成器请严格按以下要求生成两个路人NPC{persons[0]["name"]}{persons[1]["name"]}的日常对话
1. 生成2轮完整对话每轮包含双方各一次发言共4句
2. 对话场景{dialog_scene}
3. 角色设定
{persons[0]["name"]}{persons[0]["job"]}
{persons[1]["name"]}{persons[1]["job"]}
4. 对话要求
* 每轮对话需自然衔接体现生活细节
* 避免任务指引或玩家交互内容
* 结尾保持对话未完成感
5. 输出格式
<format>
{persons[0]["name"]}[第一轮发言]
{persons[1]["name"]}[第一轮回应]
{persons[0]["name"]}[第二轮发言]
{persons[1]["name"]}[第二轮回应]
</format>
6.重要若未按此格式输出请重新生成直至完全符合
#你是一个游戏NPC对话生成器。请严格按以下要求生成两个角色的日常对话
#对话的背景
{dialog_scene}
1. 生成2轮完整对话每轮包含双方各一次发言共4句
2.角色设定
{characterInfo1[0]["name"]}: {{
"姓名": {characterInfo1[0]["name"]},
"年龄": {characterInfo1[0]["age"]},
"性格": {characterInfo1[0]["personality"]},
"职业": {characterInfo1[0]["profession"]},
"背景": {characterInfo1[0]["characterBackground"]},
"语言风格": {characterInfo1[0]["chat_style"]}
}},
{characterInfo2[0]["name"]}: {{
"姓名": {characterInfo2[0]["name"]},
"年龄": {characterInfo2[0]["age"]},
"性格": {characterInfo2[0]["personality"]},
"职业": {characterInfo2[0]["profession"]},
"背景": {characterInfo2[0]["characterBackground"]},
"语言风格": {characterInfo2[0]["chat_style"]}
}}
3.参考的历史对话内容
{result}
4.输出格式
<format>
张三[第一轮发言]
李明[第一轮回应]
张三[第二轮发言]
李明[第二轮回应]
</format>
5.重要若未按此格式输出请重新生成直至完全符合
"""
return True, prompt
except json.JSONDecodeError as e:
print(f"JSON解析错误: {e}")
return False, ""
except KeyError as e:
print(f"缺少必要字段: {e}")
except Exception as e:
print(f"发生错误:{type(e).__name__} - {e}")
return False, ""
@ -173,91 +281,15 @@ def run_webserver():
log_level="info"
)
async def generateAIChat(promptStr: str, websocket: WebSocket| None = None):
#动态标识吗 防止重复输入导致的结果重复
dynamic_token = str(int(time.time() % 1000))
promptStr = f"""
[动态标识码:{dynamic_token}]
""" + promptStr
logger.log(logging.INFO, "prompt:" + promptStr)
starttime = time.time()
receivemessage=[
{"role": "system", "content": promptStr}
]
try:
# response = ollamaClient.chat(
# model = args.model,
# stream = False,
# messages = receivemessage,
# options={
# "temperature": random.uniform(1.0, 1.5),
# "repeat_penalty": 1.2, # 抑制重复
# "top_p": random.uniform(0.7, 0.95),
# "num_ctx": 4096, # 上下文长度
# "seed": int(time.time() * 1000) % 1000000
# }
# )
response = ollamaClient.generate(
model = args.model,
stream = False,
prompt = promptStr,
options={
"temperature": random.uniform(1.0, 1.5),
"repeat_penalty": 1.2, # 抑制重复
"top_p": random.uniform(0.7, 0.95),
"num_ctx": 4096, # 上下文长度
}
)
except ResponseError as e:
if e.status_code == 503:
print("🔄 服务不可用5秒后重试...")
return await senddata(websocket, -1, messages=["ollama 服务不可用"])
except Exception as e:
print(f"🔥 未预料错误: {str(e)}")
return await senddata(websocket, -1, messages=["未预料错误"])
logger.log(logging.INFO, "接口调用耗时 :" + str(time.time() - starttime))
#aiResponse = response['message']['content']
aiResponse = response['response']
logger.log(logging.INFO, "AI生成" + aiResponse)
#处理ai输出内容
think_remove_text = re.sub(r'<think>.*?</think>', '', aiResponse, flags=re.DOTALL)
pattern = r".*<format>(.*?)</format>" # .* 吞掉前面所有字符,定位最后一组
match = re.search(pattern, think_remove_text, re.DOTALL)
if not match:
if await reGenerateAIChat(lastPrompt, websocket):
pass
else:
logger.log(logging.ERROR, "请更换prompt或者升级模型大小")
await senddata(websocket, -1, messages=["请更换prompt或者升级模型大小"])
else:
core_dialog = match.group(1).strip()
dialog_lines = [line for line in core_dialog.split('\n') if line.strip()]
if len(dialog_lines) != 4:
if await reGenerateAIChat(lastPrompt, websocket):
pass
else:
logger.log(logging.ERROR, "请更换prompt或者升级模型大小")
await senddata(websocket, -1, messages=["请更换prompt或者升级模型大小"])
else:
logger.log(logging.INFO, "AI的输出正确\n" + core_dialog)
global regenerateCount
regenerateCount = 0
await senddata(websocket, 1, dialog_lines)
regenerateCount = 1
async def reGenerateAIChat(prompt: str, websocket: WebSocket):
global regenerateCount
if regenerateCount < maxAIRegerateCount:
regenerateCount += 1
logger.log(logging.ERROR, f"AI输出格式不正确重新进行生成 {regenerateCount}/{maxAIRegerateCount}")
await senddata(websocket, 2, messages=["ai生成格式不正确 重新进行生成"])
await sendprotocol(websocket, "AiChatGenerate", 0, "ai生成格式不正确 重新进行生成", "")
await asyncio.sleep(0)
prompt = prompt + "补充上一次的输出格式错误严格执行prompt中第5条的输出格式要求"
await generateAIChat(prompt, websocket)
prompt = prompt + "补充上一次的输出格式错误严格执行prompt中的输出格式要求"
await generate_aichat(prompt, websocket)
return True
else:
regenerateCount = 0
@ -272,19 +304,18 @@ if __name__ == "__main__":
#Test database
database = DatabaseHandle()
id = database.add_character({"name":"李明","age":30,"personality":"活泼健谈","profession":"产品经理"
,"characterBackground":"公司资深产品经理","chat_style":"热情"})
# id = database.add_character({"name":"李明","age":30,"personality":"活泼健谈","profession":"产品经理"
# ,"characterBackground":"公司资深产品经理","chat_style":"热情"})
characters = database.get_character_byname("")
#characters = database.get_character_byname("")
#chat_id = database.add_chat({"character_ids":"1,2","chat":"张三:[第一轮发言] 李明:[第一轮回应] 张三:[第二轮发言] 李明:[第二轮回应"})
chat = database.get_chats_by_character_id(3)
if id == 0:
logger.log(logging.ERROR, f"角色 张三已经添加到数据库")
#chat = database.get_chats_by_character_id(3)
#
# Test AI
aicore.getPromptToken("测试功能")
#aicore.getPromptToken("测试功能")
# asyncio.run(
# generateAIChat(promptStr = f"""
# #你是一个游戏NPC对话生成器。请严格按以下要求生成两个角色的日常对话

Binary file not shown.

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@ -1,5 +1,6 @@
#include "Definations.h"
FString FNetCommand::CharacterList = TEXT("CharacterList");
FString FNetCommand::RequestCharacterInfos = TEXT("RequestCharacterInfos");
FString FNetCommand::RequestCharacterNames = TEXT("RequestCharacterNames");
FString FNetCommand::AddCharacter = TEXT("AddCharacter");
FString FNetCommand::AiChatGenerate = TEXT("AiChatGenerate");

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@ -188,8 +188,19 @@ void FAIGCModule::InitWebSocketManager()
auto& Settings = *GetDefault<UAIGCSetting>();
WebSocketManager = NewObject<UWebSocketManager>();
WebSocketManager->InitWebSocket(Settings.ServerIP);
WebSocketManager->OnConnectDelegate.AddLambda([this](bool bSuccess)
{
if (!bSuccess)
{
WebSocketManager->ConditionalBeginDestroy();
WebSocketManager = nullptr;
}
});
//WebSocketManager->OnConnectDelegate.AddRaw(this, &FAIGCModule::OnWebSocketConnect);
}
#undef LOCTEXT_NAMESPACE
IMPLEMENT_MODULE(FAIGCModule, AIGC)

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@ -15,15 +15,6 @@ void SAIGCWindow::Construct(const FArguments& InArgs)
{
ChildSlot[
SNew(SVerticalBox)
+ SVerticalBox::Slot()
.AutoHeight()
.Padding(10)
[
SAssignNew(ServerIP, SConfigItem_Text)
.Title(LOCTEXT("Server", "服务器ip"))
.HintText(LOCTEXT("HintServer", "请输入服务器ip"))
.DefaultText(LOCTEXT("InputServer", "127.0.0.1"))
]
+ SVerticalBox::Slot()
.AutoHeight()
.Padding(10)
@ -36,35 +27,48 @@ void SAIGCWindow::Construct(const FArguments& InArgs)
.AutoHeight()
.Padding(10)
[
SAssignNew(NPCName1, SConfigItem_Text)
SAssignNew(NPCName1, SConfigItem_ComboBox<TSharedPtr<FCharacterInfo>>)
.Title(LOCTEXT("Name1", "名称1"))
.HintText(LOCTEXT("HintName", "请输入名称"))
.OptionsSource(&CharacterInfos)
.Content()
[
SNew(STextBlock)
.Text_Lambda([this]() -> FText {
return FText::FromString(SelectedCharacter1.name);
})
]
.OnGenerateWidget_Lambda([this](TSharedPtr<FCharacterInfo> CharacterInfo) {
return SNew(STextBlock).Text(FText::FromString(CharacterInfo->name));
})
.OnSelectionChanged_Lambda([this](TSharedPtr<FCharacterInfo> CharacterInfo, ESelectInfo::Type)
{
SelectedCharacter1 = *CharacterInfo;
})
]
+ SVerticalBox::Slot()
.AutoHeight()
.Padding(10)
[
SAssignNew(NPCJob1, SConfigItem_Text)
.Title(LOCTEXT("Job1", "职业1"))
.HintText(LOCTEXT("HintJon", "请输入职业"))
]
+ SVerticalBox::Slot()
.AutoHeight()
.Padding(10)
[
SAssignNew(NPCName2, SConfigItem_Text)
.Title(LOCTEXT("Name2", "名称2"))
.HintText(LOCTEXT("HintName", "请输入名称"))
]
+ SVerticalBox::Slot()
.AutoHeight()
.Padding(10)
[
SAssignNew(NPCJob2, SConfigItem_Text)
.Title(LOCTEXT("Job2", "职业2"))
.HintText(LOCTEXT("HintJon", "请输入职业"))
]
.AutoHeight()
.Padding(10)
[
SAssignNew(NPCName2, SConfigItem_ComboBox<TSharedPtr<FCharacterInfo>>)
.Title(LOCTEXT("Name2", "名称2"))
.OptionsSource(&CharacterInfos)
.Content()
[
SNew(STextBlock)
.Text_Lambda([this]() -> FText {
return FText::FromString(SelectedCharacter2.name);
})
]
.OnGenerateWidget_Lambda([this](TSharedPtr<FCharacterInfo> CharacterInfo) {
return SNew(STextBlock).Text(FText::FromString(CharacterInfo->name));
})
.OnSelectionChanged_Lambda([this](TSharedPtr<FCharacterInfo> CharacterInfo, ESelectInfo::Type)
{
SelectedCharacter2 = *CharacterInfo;
})
]
+ SVerticalBox::Slot()
.AutoHeight()
.Padding(10)
@ -111,14 +115,19 @@ EActiveTimerReturnType SAIGCWindow::OnPostPaint(double X, float Arg)
if (ModulePtr)
{
UWebSocketManager* WebSocketManager = ModulePtr->GetWebSocketManager();
if (!WebSocketManager)
if (!IsValid(WebSocketManager))
{
ModulePtr->InitWebSocketManager();
WebSocketManager = ModulePtr->GetWebSocketManager();
}
WebSocketManager->OnConnectDelegate.AddLambda([this](bool bSuccess)
else
{
WebSocketManager->SendData(FNetCommand::RequestCharacterNames, TEXT(""));
}
WebSocketManager->OnConnectDelegate.AddLambda([this, WebSocketManager](bool bSuccess)
{
GenerateButton->SetEnabled(bSuccess);
WebSocketManager->SendData(FNetCommand::RequestCharacterNames, TEXT(""));
});
WebSocketManager->OnDataReceiveDelaget.AddRaw(this, &SAIGCWindow::HandleReceiveData);
@ -131,11 +140,27 @@ void SAIGCWindow::OnAIGenerateClicked()
{
GenerateButton->SetEnabled(false);
RequireGenerateCount = GenerateCount->GetNumber();
UE_LOG(LogTemp, Warning, TEXT("生成次数 %d prompt:%s"), RequireGenerateCount, *GeneratePromptJson());
FAIGCModule* ModulePtr = FModuleManager::GetModulePtr<FAIGCModule>("AIGC");
//生成ai 配置信息
FRequestAIChat RequestAIChat;
RequestAIChat.DialogScene =DialogScene->GetInputText();
RequestAIChat.GenerateCount = GenerateCount->GetNumber();
RequestAIChat.CharacterName.Add(SelectedCharacter1.name);
RequestAIChat.CharacterName.Add(SelectedCharacter2.name);
FString dataJson;
FJsonObjectConverter::UStructToJsonObjectString(
FRequestAIChat::StaticStruct(),
&RequestAIChat,
dataJson,
0,
0
);
//发送ai对话生成请求
if (ModulePtr)
{
ModulePtr->GetWebSocketManager()->SendData(FNetCommand::AiChatGenerate, GeneratePromptJson());
ModulePtr->GetWebSocketManager()->SendData(FNetCommand::AiChatGenerate, dataJson);
}
}
@ -143,60 +168,55 @@ void SAIGCWindow::OnAIGenerateClicked()
void SAIGCWindow::HandleReceiveData(FNetProtocol protocol)
{
// UE_LOG(LogTemp, Warning, TEXT("AI当前进度 %d/%d"), GeneratedCount, RequireGenerateCount);
// //添加数据到dataTable中
// if (AiMessages.Num() > 0)
// {
// FAIGCModule* ModulePtr = FModuleManager::GetModulePtr<FAIGCModule>("AIGC");
// if (ModulePtr) {
// FString DataPath = FString::Printf(TEXT("/Game/Test/%s.%s"), *DataName->GetInputText(), *DataName->GetInputText());
// FString Final = "";
// for (auto message: AiMessages)
// {
// Final += message + TEXT("|");
// }
// ModulePtr->CreateOrAddData(DataPath, Final);
// }
// }
//
// //是否生成足够数量
// if (GeneratedCount < RequireGenerateCount)
// {
// GeneratedCount++;
// FAIGCModule* ModulePtr = FModuleManager::GetModulePtr<FAIGCModule>("AIGC");
// if (ModulePtr)
// {
// ModulePtr->GetWebSocketManager()->SendData(FNetCommand::AiChatGenerate, GeneratePromptJson());
// }
//
// }
// else
// {
// GeneratedCount = 0;
// GenerateButton->SetEnabled(true);
// UE_LOG(LogTemp, Warning, TEXT("生成结束!"));
// }
if (protocol.cmd == FNetCommand::RequestCharacterNames)
{
//解析json角色信息
FJsonObjectConverter::JsonObjectStringToUStruct<FCharacterArray>(
protocol.data,
&Characters,
0, // 检查标志位
0 // 转换标志位
);
CharacterInfos.Empty();
for (auto Character: Characters.characterInfos)
{
CharacterInfos.Add(MakeShareable(new FCharacterInfo(Character)));
}
NPCName1->RefreshOptions();
NPCName2->RefreshOptions();
}
else if (protocol.cmd == FNetCommand::AiChatGenerate)
{
if (protocol.status == -1)
{
//需要重新生成
GenerateButton->SetEnabled(true);
UE_LOG(LogTemp, Error, TEXT("Chat Generate Failed reson = %s"), *protocol.message);
}
else if (protocol.status == 0)
{
UE_LOG(LogTemp, Warning, TEXT("Chat Generate warning reson = %s"), *protocol.message);
}
else if (protocol.status == 1)
{
UE_LOG(LogTemp, Warning, TEXT("Chat Generate success chat = %s"), *protocol.data);
FAIGCModule* ModulePtr = FModuleManager::GetModulePtr<FAIGCModule>("AIGC");
if (ModulePtr) {
FString DataPath = FString::Printf(TEXT("/Game/Test/%s.%s"), *DataName->GetInputText(), *DataName->GetInputText());
ModulePtr->CreateOrAddData(DataPath, protocol.data);
}
}
else if (protocol.status == 2)
{
//全部生成完成
UE_LOG(LogTemp, Warning, TEXT("Chat Generate has all generated"));
GenerateButton->SetEnabled(true);
}
}
}
FString SAIGCWindow::GeneratePromptJson()
{
FPrompt PromptData;
PromptData.DialogContent = FDialogContent(DialogScene->GetInputText());
PromptData.Persons.Add(FPersonInfo(NPCName1->GetInputText(), NPCJob1->GetInputText()));
PromptData.Persons.Add(FPersonInfo(NPCName2->GetInputText(), NPCJob2->GetInputText()));
// 结构体转JSON字符串
FString OutputString;
FJsonObjectConverter::UStructToJsonObjectString(
FPrompt::StaticStruct(),
&PromptData,
OutputString,
0,
0
);
return OutputString;
}
#undef LOCTEXT_NAMESPACE

View File

@ -12,7 +12,6 @@
void SCharacterWindow::Construct(const FArguments& InArgs)
{
ChildSlot[
SNew(SVerticalBox)
+SVerticalBox::Slot()
@ -129,12 +128,12 @@ EActiveTimerReturnType SCharacterWindow::OnPostPaint(double X, float Arg)
}
else
{
WebSocketManager->SendData(FNetCommand::CharacterList, TEXT(""));
WebSocketManager->SendData(FNetCommand::RequestCharacterInfos, TEXT(""));
}
WebSocketManager->OnDataReceiveDelaget.AddRaw(this, &SCharacterWindow::HandleReceiveData);
WebSocketManager->OnConnectDelegate.AddLambda([this, WebSocketManager](bool bSuccess)
{
WebSocketManager->SendData(FNetCommand::CharacterList, TEXT(""));
WebSocketManager->SendData(FNetCommand::RequestCharacterInfos, TEXT(""));
});
}
return EActiveTimerReturnType::Stop;
@ -142,7 +141,7 @@ EActiveTimerReturnType SCharacterWindow::OnPostPaint(double X, float Arg)
void SCharacterWindow::HandleReceiveData(FNetProtocol protocol)
{
if (protocol.cmd == FNetCommand::CharacterList)
if (protocol.cmd == FNetCommand::RequestCharacterInfos)
{
//解析json角色信息

View File

@ -0,0 +1,5 @@
// Fill out your copyright notice in the Description page of Project Settings.
#include "Widget/ConfigItem_ComboBox.h"

View File

@ -50,6 +50,7 @@ public:
void CreateOrAddData(const FString& DataTablePath, const FString& RowValue);
class UWebSocketManager* GetWebSocketManager();
void InitWebSocketManager();
//void OnWebSocketConnect(bool bSuccess);
private:
TSharedPtr<class FUICommandList> PluginCommands;

View File

@ -3,49 +3,42 @@
#include "CoreMinimal.h"
#include "Definations.generated.h"
// USTRUCT()
// struct FDialogContent
// {
// GENERATED_BODY()
// FDialogContent() {};
//
// FDialogContent(const FString& InDialogScene) : DialogScene(InDialogScene) {}
// UPROPERTY()
// FString DialogScene;
// };
// USTRUCT()
// struct FPersonInfo
// {
// GENERATED_BODY()
// FPersonInfo() {}
// FPersonInfo(const FString& InName, const FString& InJob):
// Name(InName), Job(InJob){}
// UPROPERTY()
// FString Name;
// UPROPERTY()
// FString Job;
//
// };
USTRUCT()
struct FDialogContent
struct FRequestAIChat
{
GENERATED_BODY()
FDialogContent() {};
FDialogContent(const FString& InDialogScene) : DialogScene(InDialogScene) {}
UPROPERTY()
FString DialogScene;
UPROPERTY()
int32 GenerateCount;
UPROPERTY()
TArray<FString> CharacterName;
};
USTRUCT()
struct FPersonInfo
{
GENERATED_BODY()
FPersonInfo() {}
FPersonInfo(const FString& InName, const FString& InJob):
Name(InName), Job(InJob){}
UPROPERTY()
FString Name;
UPROPERTY()
FString Job;
};
USTRUCT()
struct FPrompt
{
GENERATED_BODY()
UPROPERTY()
FDialogContent DialogContent;
UPROPERTY()
TArray<FPersonInfo> Persons;
};
USTRUCT()
struct FAIServerData
{
GENERATED_BODY()
UPROPERTY()
int32 statusCode;
UPROPERTY()
TArray<FString> messages;
};
USTRUCT()
struct FCharacterInfo
@ -92,7 +85,8 @@ USTRUCT()
struct FNetCommand
{
GENERATED_BODY()
static FString CharacterList;
static FString RequestCharacterInfos;
static FString RequestCharacterNames;
static FString AddCharacter;
static FString AiChatGenerate;
};

View File

@ -3,6 +3,7 @@
#pragma once
#include "CoreMinimal.h"
#include "ConfigItem_ComboBox.h"
#include "ConfigItem_NumberSpin.h"
#include "ConfigItem_Text.h"
#include "Definations.h"
@ -26,19 +27,22 @@ public:
void HandleReceiveData(FNetProtocol protocol);
private:
FString GeneratePromptJson();
int32 RequireGenerateCount;
int32 GeneratedCount = 1;
FCharacterArray Characters;
TArray<TSharedPtr<FCharacterInfo>> CharacterInfos;
FCharacterInfo SelectedCharacter1;
FCharacterInfo SelectedCharacter2;
protected:
TSharedPtr<SConfigItem_Text> ServerIP; //服务器IP
TSharedPtr<SConfigItem_Text> DataName; //datatable 名称
TSharedPtr<SConfigItem_Text> NPCName1; //npc1的名称
TSharedPtr<SConfigItem_Text> NPCJob1; //npc1的职业
TSharedPtr<SConfigItem_Text> NPCName2; //npc2的名称
TSharedPtr<SConfigItem_Text> NPCJob2; //npc2的职业
TSharedPtr<SConfigItem_ComboBox<TSharedPtr<FCharacterInfo>>> NPCName1; //npc1的名称
TSharedPtr<SConfigItem_ComboBox<TSharedPtr<FCharacterInfo>>> NPCName2; //npc2的名称
TSharedPtr<SConfigItem_Text> DialogScene; //对话场景
TSharedPtr<SConfigItem_NumberSpin<int32>> GenerateCount; //生成数目
TSharedPtr<SButton> GenerateButton; //生成按钮
};

View File

@ -0,0 +1,69 @@
// Fill out your copyright notice in the Description page of Project Settings.
#pragma once
#include "CoreMinimal.h"
/**
*
*/
template <typename OptionType>
class AIGC_API SConfigItem_ComboBox: public SCompoundWidget
{
public:
typedef typename TSlateDelegates<OptionType>::FOnGenerateWidget FOnGenerateWidget;
typedef typename TSlateDelegates<OptionType>::FOnSelectionChanged FOnSelectionChanged;
SLATE_BEGIN_ARGS( SConfigItem_ComboBox )
:_Title()
,_Content()
{}
SLATE_ARGUMENT(FText, Title) // 标题参数
SLATE_ITEMS_SOURCE_ARGUMENT( OptionType, OptionsSource ) //数据源
SLATE_EVENT(FOnGenerateWidget, OnGenerateWidget )
SLATE_EVENT( FOnSelectionChanged, OnSelectionChanged )
SLATE_NAMED_SLOT(FArguments, Content)//显示
SLATE_END_ARGS()
void Construct(const FArguments& InArgs)
{
//OptionSource = InArgs.GetOptionsSource();
ChildSlot
[
SNew(SHorizontalBox)
+ SHorizontalBox::Slot()
.AutoWidth()
.Padding(10, 0)
[
SNew(STextBlock)
.Text(InArgs._Title)
]
+ SHorizontalBox::Slot()
.FillWidth(1.0f)
.Padding(10, 0)
[
SAssignNew(ComboBox, SComboBox<OptionType>)
.OptionsSource(InArgs.GetOptionsSource())
.Content()
[
InArgs._Content.Widget
]
.OnGenerateWidget(InArgs._OnGenerateWidget)
.OnSelectionChanged(InArgs._OnSelectionChanged)
]
];
}
void RefreshOptions()
{
ComboBox->RefreshOptions();
}
private:
TSharedPtr<SComboBox<OptionType>> ComboBox;
//TArray<OptionType>* OptionSource; //数据源指针
// FOnGenerateWidget OnGenerateWidgetDelegate;
// FOnSelectionChanged OnSelectionChangedDelegate;
};

View File

@ -25,6 +25,7 @@ public:
void Construct(const FArguments& InArgs)
{
InputValue = InArgs._MinNumber;
ChildSlot
[
SNew(SHorizontalBox)