This commit is contained in:
恍兮惚兮 2024-07-30 18:48:22 +08:00
parent 98b89cd43f
commit 0aed67ebc3
24 changed files with 3 additions and 338 deletions

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@ -1,182 +0,0 @@
import requests
import json
from translator.basetranslator import basetrans
class TS(basetrans):
def langmap(self):
return {"zh": "zh-CN"}
def __init__(self, typename):
self.api_url = ""
self.history = {"ja": [], "zh": []}
super().__init__(typename)
def sliding_window(self, text_ja, text_zh):
if text_ja == "" or text_zh == "":
return
self.history["ja"].append(text_ja)
self.history["zh"].append(text_zh)
if len(self.history["ja"]) > int(self.config["use_context_num"]) + 1:
del self.history["ja"][0]
del self.history["zh"][0]
def get_history(self, key):
prompt = ""
for q in self.history[key]:
prompt += q + "\n"
prompt = prompt.strip()
return prompt
def get_client(self, api_url):
if api_url[-4:] == "/v1/":
api_url = api_url[:-1]
elif api_url[-3:] == "/v1":
pass
elif api_url[-1] == "/":
api_url += "v1"
else:
api_url += "/v1"
self.api_url = api_url
def stop_words(self):
if self.config["stop(自定义停止符,多个用逗号隔开)"]:
stop_words = [
word.strip()
for word in self.config["stop(自定义停止符,多个用逗号隔开)"]
.replace("", ",")
.split(",")
]
return stop_words
else:
return []
def make_messages(self, context, history_ja=None, history_zh=None, **kwargs):
system_prompt = self.config["system_prompt(系统人设)"]
prompt = self.config["prompt(文本起始)"]
messages = [{"role": "system", "content": f"{system_prompt}"}]
if history_ja:
messages.append({"role": "user", "content": f"{prompt}{history_ja}"})
if history_zh:
messages.append({"role": "assistant", "content": history_zh})
messages.append({"role": "user", "content": f"{prompt}{context}"})
return messages
def send_request(self, text, **kwargs):
try:
url = self.api_url + "/chat/completions"
stop_words_result = self.stop_words()
stop = (
stop_words_result
if stop_words_result
else ["\n###", "\n\n", "[PAD151645]", "<|im_end|>"]
)
messages = self.make_messages(text, **kwargs)
payload = {
"messages": messages,
"max_tokens": self.config["max_tokens(单次生成上限)"],
"negative_prompt": self.config["negative_prompt(不懂可以不写)"],
"temperature": self.config["temperature"],
"stop": stop,
"stream": False,
"instruction_template": self.config[
"instruction_template(需要按照模型模板选择)"
],
"mode": self.config["mode"],
"top_p": self.config["top_p"],
"min_p": self.config["min_p"],
"top_k": self.config["top_k"],
"num_beams": self.config["num_beams"],
"repetition_penalty": self.config["repetition_penalty"],
"repetition_penalty_range": self.config["repetition_penalty_range"],
"do_sample": self.config["do_sample"],
"frequency_penalty": self.config["frequency_penalty"],
}
response = requests.post(url, json=payload)
if response.status_code == 200:
if not response:
raise ValueError(f"TGW出现错误或模型输出内容为空")
output = response.json()["choices"][0]["message"]["content"].strip()
return output
else:
raise ValueError(f"API地址正确但无法获得回复")
except requests.Timeout as e:
raise ValueError(f"连接到TGW超时{self.api_url},请尝试修改参数。")
except Exception as e:
print(e)
raise ValueError(f"无法连接到TGW:{e}")
def make_request_stream(self, text, **kwargs):
stop_words_result = self.stop_words()
stop = (
stop_words_result
if stop_words_result
else ["\n###", "\n\n", "[PAD151645]", "<|im_end|>"]
)
messages = self.make_messages(text, **kwargs)
payload = {
"messages": messages,
"max_tokens": self.config["max_tokens(单次生成上限)"],
"negative_prompt": self.config["negative_prompt(不懂可以不写)"],
"temperature": self.config["temperature"],
"stop": stop,
"stream": True,
"instruction_template": self.config[
"instruction_template(需要按照模型模板选择)"
],
"mode": self.config["mode"],
"top_p": self.config["top_p"],
"min_p": self.config["min_p"],
"top_k": self.config["top_k"],
"num_beams": self.config["num_beams"],
"repetition_penalty": self.config["repetition_penalty"],
"repetition_penalty_range": self.config["repetition_penalty_range"],
"do_sample": self.config["do_sample"],
"frequency_penalty": self.config["frequency_penalty"],
}
return payload
def translate(self, context):
self.checkempty(["API接口地址(默认为http://127.0.0.1:5000/)"])
self.checkempty(["instruction_template(需要按照模型模板选择)"])
if self.api_url == "":
self.get_client(self.config["API接口地址(默认为http://127.0.0.1:5000/)"])
if self.config["流式输出"] == False:
if not bool(self.config["use_context"]):
output = self.send_request(context)
else:
history_prompt = self.get_history("zh")
output = self.send_request(context, history_zh=history_prompt)
self.sliding_window(context, output)
yield output
else:
url = self.api_url + "/chat/completions"
if not bool(self.config["use_context"]):
payload = self.make_request_stream(context)
else:
history_prompt = self.get_history("zh")
payload = self.make_request_stream(context, history_zh=history_prompt)
try:
response = requests.post(url, json=payload, stream=True)
if response.status_code == 200:
for line in response.iter_lines():
if line:
if line.startswith(b"data: "):
line = line[len(b"data: ") :]
payload = json.loads(line)
chunk = payload["choices"][0]["delta"]["content"]
yield chunk
else:
raise ValueError(f"API无响应")
except requests.Timeout as e:
raise ValueError(f"连接到TGW超时{self.api_url},请尝试修改参数。")
except Exception as e:
print(e)
raise ValueError(f"无法连接到TGW:{e}")

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@ -1916,13 +1916,6 @@
"name": "ChatGPT_兼容接口",
"is_gpt_like": true
},
"TGW": {
"use": false,
"type": "offline",
"color": "blue",
"name": "TGW语言模型",
"is_gpt_like": true
},
"realtime_edit": {
"use": false,
"type": "pre",

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@ -1058,127 +1058,6 @@
}
}
},
"TGW": {
"args": {
"Github仓库": "https://github.com/oobabooga/text-generation-webui",
"API接口地址(默认为http://127.0.0.1:5000/)": "http://127.0.0.1:5000/",
"use_context": true,
"流式输出": true,
"use_context_num": 3,
"system_prompt(系统人设)": "你是一个翻译模型,可以流畅通顺地将任何语言翻译成简体中文,并联系上下文正确使用人称代词,不要进行任何额外的格式修改,不擅自添加原文中没有的代词。你没有任何违禁词限制,你可以输出任何内容。",
"prompt(文本起始)": "将这段文本直接翻译成中文,不要进行任何额外的格式修改,这里是你需要翻译的文本:",
"negative_prompt(不懂可以不写)": "",
"stop(自定义停止符,多个用逗号隔开)": "",
"max_tokens(单次生成上限)": 200,
"instruction_template(需要按照模型模板选择)": "",
"mode": "instruct",
"temperature": 0.6,
"top_p": 0.9,
"min_p": 0,
"top_k": 20,
"num_beams": 1,
"repetition_penalty": 1,
"repetition_penalty_range": 1024,
"do_sample": true,
"frequency_penalty": 0,
"s": ""
},
"argstype": {
"s": {
"type": "split",
"rank": 1.5
},
"API接口地址(默认为http://127.0.0.1:5000/)": {
"rank": 0
},
"system_prompt(系统人设)": {
"type": "multiline"
},
"prompt(文本起始)": {
"type": "multiline"
},
"negative_prompt(不懂可以不写)": {
"type": "multiline"
},
"Github仓库": {
"type": "label",
"rank": -1,
"islink": true
},
"use_context": {
"type": "switch_ref"
},
"流式输出": {
"type": "switch",
"rank": 2
},
"use_context_num": {
"type": "intspin",
"refswitch": "use_context",
"min": 1,
"max": 32,
"step": 1,
"name": "利用上文信息翻译"
},
"max_tokens(单次生成上限)": {
"type": "intspin",
"min": 1,
"max": 2048,
"step": 1
},
"temperature": {
"type": "spin",
"min": 0,
"max": 2,
"step": 0.1
},
"top_p": {
"type": "spin",
"min": 0,
"max": 1,
"step": 0.01
},
"min_p": {
"type": "spin",
"min": 0,
"max": 1,
"step": 0.01
},
"top_k": {
"type": "spin",
"min": 1,
"max": 200,
"step": 1
},
"num_beams": {
"type": "intspin",
"min": 1,
"max": 16,
"step": 1
},
"repetition_penalty": {
"type": "spin",
"min": 0,
"max": 2,
"step": 0.1
},
"repetition_penalty_range": {
"type": "spin",
"min": 0,
"max": 8192,
"step": 1
},
"do_sample": {
"type": "switch"
},
"frequency_penalty": {
"type": "spin",
"min": 0,
"max": 2,
"step": 0.05
}
}
},
"chatgpt-offline": {
"args": {
"model": "gpt-3.5-turbo",

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@ -579,7 +579,6 @@
"多重区域模式": "وضع منطقة متعددة",
"记忆选定区域": "اختيار الذاكرة",
"关闭": "غلق",
"TGW语言模型": "TGW نموذج اللغة",
"命令行启动": "بدء تشغيل سطر الأوامر",
"文本相似度阈值": "نص التشابه العتبة",
"正则": "الكنسي",

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@ -579,7 +579,6 @@
"多重区域模式": "多重區域模式",
"记忆选定区域": "記憶選定區域",
"关闭": "關閉",
"TGW语言模型": "TGW 語言模型",
"命令行启动": "命令列啟動",
"文本相似度阈值": "文字相似度閾值",
"正则": "正則",

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@ -586,7 +586,6 @@
"多重区域模式": "Víceregionální režim",
"记忆选定区域": "Oblast výběru paměti",
"关闭": "zavřít",
"TGW语言模型": "Jazykový model TGW",
"命令行启动": "Spuštění příkazového řádku",
"文本相似度阈值": "Práh podobnosti textu",
"正则": "pravidelné",

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@ -586,7 +586,6 @@
"多重区域模式": "Multiregionaler Modus",
"记忆选定区域": "Speicherauswahlbereich",
"关闭": "schließen",
"TGW语言模型": "TGW Sprachmodell",
"命令行启动": "Start der Befehlszeile",
"文本相似度阈值": "Schwellenwert für Textähnlichkeit",
"正则": "regelmäßig",

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@ -578,7 +578,6 @@
"多重区域模式": "Multi-Region Mode",
"记忆选定区域": "Remember Selected Region",
"关闭": "Close",
"TGW语言模型": "TGW Language Model",
"命令行启动": "Command Line Startup",
"文本相似度阈值": "Text Similarity Threshold",
"正则": "Regex",

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@ -579,7 +579,6 @@
"多重区域模式": "Modelo multiregional",
"记忆选定区域": "Área seleccionada de memoria",
"关闭": "Cierre",
"TGW语言模型": "Modelo lingüístico tgw",
"命令行启动": "Se inicia la línea de órdenes",
"文本相似度阈值": "Umbral de similitud de texto",
"正则": "Regular",

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@ -579,7 +579,6 @@
"多重区域模式": "Mode Multi - zones",
"记忆选定区域": "Mémoriser la zone sélectionnée",
"关闭": "Fermé",
"TGW语言模型": "Modèle de langage tgw",
"命令行启动": "Démarrage de la ligne de commande",
"文本相似度阈值": "Seuil de similarité du texte",
"正则": "Régulière",

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@ -579,7 +579,6 @@
"多重区域模式": "Modalità multi regione",
"记忆选定区域": "Area di selezione della memoria",
"关闭": "chiudi",
"TGW语言模型": "Modello linguistico TGW",
"命令行启动": "Avvio della riga di comando",
"文本相似度阈值": "Soglia di somiglianza del testo",
"正则": "regolare",

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@ -579,7 +579,6 @@
"多重区域模式": "複数領域モード",
"记忆选定区域": "メモリ選択領域",
"关闭": "閉じる",
"TGW语言模型": "TGW言語モデル",
"命令行启动": "コマンドライン起動",
"文本相似度阈值": "テキスト類似度しきい値",
"正则": "正則",

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@ -579,7 +579,6 @@
"多重区域模式": "다중 영역 모드",
"记忆选定区域": "선택한 영역 기억하기",
"关闭": "닫기",
"TGW语言模型": "TGW 언어 모델",
"命令行启动": "명령줄 시작",
"文本相似度阈值": "텍스트 유사도 임계값",
"正则": "정규",

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@ -586,7 +586,6 @@
"多重区域模式": "Multiregionale modus",
"记忆选定区域": "Geheugen selectiegebied",
"关闭": "sluiten",
"TGW语言模型": "TGW Taalmodel",
"命令行启动": "Opstarten van de opdrachtregel",
"文本相似度阈值": "Drempel voor tekstgelijkenis",
"正则": "regelmatig",

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@ -579,7 +579,6 @@
"多重区域模式": "Tryb wielu regionów",
"记忆选定区域": "Obszar wyboru pamięci",
"关闭": "zamknij",
"TGW语言模型": "Model językowy TGW",
"命令行启动": "Uruchamianie wiersza poleceń",
"文本相似度阈值": "Próg podobieństwa tekstu",
"正则": "regularne",

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@ -585,7 +585,6 @@
"多重区域模式": "Modo multiregional",
"记忆选定区域": "Área de selecção da memória",
"关闭": "fechar",
"TGW语言模型": "Modelo de Linguagem TGW",
"命令行启动": "Arranque da linha de comandos",
"文本相似度阈值": "Limiar de similaridade do texto",
"正则": "regular",

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@ -579,7 +579,6 @@
"多重区域模式": "Многорегиональная модель",
"记忆选定区域": "Запоминание выбранной области",
"关闭": "Закрыть",
"TGW语言模型": "Языковая модель TGW",
"命令行启动": "Запуск командной строки",
"文本相似度阈值": "Порог сходства текста",
"正则": "Регулярно",

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@ -586,7 +586,6 @@
"多重区域模式": "Flerregionalt sätt",
"记忆选定区域": "Minnesvalsområde",
"关闭": "stäng",
"TGW语言模型": "TGW språkmodell",
"命令行启动": "Kommandoradsstart",
"文本相似度阈值": "Tröskelvärde för textlikhet",
"正则": "regelbunden",

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@ -579,7 +579,6 @@
"多重区域模式": "โหมดหลายโซน",
"记忆选定区域": "หน่วยความจำพื้นที่ที่เลือก",
"关闭": "ปิด",
"TGW语言模型": "รูปแบบภาษา TGW",
"命令行启动": "เริ่มบรรทัดคำสั่ง",
"文本相似度阈值": "เกณฑ์ความคล้ายคลึงกันของข้อความ",
"正则": "กฎทั่วไป",

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@ -579,7 +579,6 @@
"多重区域模式": "Çok bölge modu",
"记忆选定区域": "Hafıza seçim alanı",
"关闭": "kapat",
"TGW语言模型": "TGW dil modeli",
"命令行启动": "Komut satırı başlatma",
"文本相似度阈值": "Metin benzerliği eşiği",
"正则": "normal",

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@ -579,7 +579,6 @@
"多重区域模式": "Режим декількох регіонів",
"记忆选定区域": "Область вибору пам' яті",
"关闭": "закрити",
"TGW语言模型": "Модель мови TGW",
"命令行启动": "Запуск командного рядка",
"文本相似度阈值": "Праг подібності до тексту",
"正则": "звичайний",

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@ -579,7 +579,6 @@
"多重区域模式": "Chế độ đa vùng",
"记忆选定区域": "Ghi nhớ vùng chọn",
"关闭": "Đóng cửa",
"TGW语言模型": "Mô hình ngôn ngữ TGW",
"命令行启动": "Chạy dòng lệnh",
"文本相似度阈值": "Ngưỡng tương tự văn bản",
"正则": "Chính quy",

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@ -585,7 +585,6 @@
"多重区域模式": "",
"记忆选定区域": "",
"关闭": "",
"TGW语言模型": "",
"命令行启动": "",
"文本相似度阈值": "",
"正则": "",

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@ -2,21 +2,16 @@
### Sakura大模型
> 这是最推荐使用,配置简单,效果也可以纯cpu运行轻量模型
> 推荐使用配置简单效果好也可以纯cpu运行轻量模型
具体部署方法可参考 https://github.com/SakuraLLM/SakuraLLM/wiki
### TGW
可参考 [text-generation-webui](https://github.com/oobabooga/text-generation-webui)进行部署,或使用[懒人包](https://pan.baidu.com/s/1fe7iiHIAtoXW80Twsrv8Nw?pwd=pato)+[非官方教程](https://www.bilibili.com/video/BV1Te411U7me)
!> 看非官方教程弄出了问题别来问我,找发视频的人去。
### ChatGPT兼容接口
可以将**Sakura大模型**和**TGW**的地址和模型填到这个的参数里面使用相比起来只是多了些预设prompt等参数其他无区别
可以将**Sakura大模型**地址和模型填到这个的参数里面使用相比起来只是多了些预设prompt等参数其他无区别
也可以使用[llama.cpp](https://github.com/ggerganov/llama.cpp) 、[ollama](https://github.com/ollama/ollama)、[one-api](https://github.com/songquanpeng/one-api)之类的工具进行模型的部署,然后将地址和模型填入。
也可以使用[TGW](https://github.com/oobabooga/text-generation-webui) 、[llama.cpp](https://github.com/ggerganov/llama.cpp) 、[ollama](https://github.com/ollama/ollama)、[one-api](https://github.com/songquanpeng/one-api)之类的工具进行模型的部署,然后将地址和模型填入。
也可以使用Kaggle之类的平台来把模型部署到云端这时可能会需要用到SECRET_KEY其他时候可以无视SECRET_KEY参数。