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update chat

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ACBBZ
2024-05-23 02:52:32 +00:00
parent 4f7f64a49a
commit 99ecc45a47
3 changed files with 66 additions and 48 deletions
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56
src/blackbox/blackbox_factory.py
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@ -1,14 +1,14 @@
# from .audio_chat import AudioChat from .audio_chat import AudioChat
# from .sentiment import Sentiment from .sentiment import Sentiment
# from .tts import TTS from .tts import TTS
# from .asr import ASR from .asr import ASR
# from .audio_to_text import AudioToText from .audio_to_text import AudioToText
from .blackbox import Blackbox from .blackbox import Blackbox
# from .text_to_audio import TextToAudio # from .text_to_audio import TextToAudio
# from .tesou import Tesou # from .tesou import Tesou
from .fastchat import Fastchat from .fastchat import Fastchat
# from .g2e import G2E from .g2e import G2E
# from .text_and_image import TextAndImage from .text_and_image import TextAndImage
from .chroma_query import ChromaQuery from .chroma_query import ChromaQuery
from .chroma_upsert import ChromaUpsert from .chroma_upsert import ChromaUpsert
from .chroma_chat import ChromaChat from .chroma_chat import ChromaChat
@ -20,29 +20,29 @@ class BlackboxFactory:
@inject @inject
def __init__(self, def __init__(self,
# audio_to_text: AudioToText, audio_to_text: AudioToText,
# text_to_audio: TextToAudio, text_to_audio: TextToAudio,
# asr: ASR, asr: ASR,
# tts: TTS, tts: TTS,
# sentiment_engine: Sentiment, sentiment_engine: Sentiment,
# tesou: Tesou, tesou: Tesou,
fastchat: Fastchat, fastchat: Fastchat,
# audio_chat: AudioChat, audio_chat: AudioChat,
# g2e: G2E, g2e: G2E,
# text_and_image:TextAndImage, text_and_image:TextAndImage,
chroma_query: ChromaQuery, chroma_query: ChromaQuery,
chroma_upsert: ChromaUpsert, chroma_upsert: ChromaUpsert,
chroma_chat: ChromaChat) -> None: chroma_chat: ChromaChat) -> None:
# self.models["audio_to_text"] = audio_to_text self.models["audio_to_text"] = audio_to_text
# self.models["text_to_audio"] = text_to_audio self.models["text_to_audio"] = text_to_audio
# self.models["asr"] = asr self.models["asr"] = asr
# self.models["tts"] = tts self.models["tts"] = tts
# self.models["sentiment_engine"] = sentiment_engine self.models["sentiment_engine"] = sentiment_engine
# self.models["tesou"] = tesou self.models["tesou"] = tesou
self.models["fastchat"] = fastchat self.models["fastchat"] = fastchat
# self.models["audio_chat"] = audio_chat self.models["audio_chat"] = audio_chat
# self.models["g2e"] = g2e self.models["g2e"] = g2e
# self.models["text_and_image"] = text_and_image self.models["text_and_image"] = text_and_image
self.models["chroma_query"] = chroma_query self.models["chroma_query"] = chroma_query
self.models["chroma_upsert"] = chroma_upsert self.models["chroma_upsert"] = chroma_upsert
self.models["chroma_chat"] = chroma_chat self.models["chroma_chat"] = chroma_chat
@ -50,8 +50,8 @@ class BlackboxFactory:
def __call__(self, *args, **kwargs): def __call__(self, *args, **kwargs):
return self.processing(*args, **kwargs) return self.processing(*args, **kwargs)
def call_blackbox(self, blackbox_name: str) -> Blackbox: def get_blackbox(self, blackbox_name: str) -> Blackbox:
model = self.models.get(blackbox_name) model = self.models.get(blackbox_name)
if model is None: if model is None:
raise ValueError("Invalid blockbox type") raise ValueError("Invalid Blackbox Type...")
return model return model

25
src/blackbox/chat.py
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@ -21,7 +21,7 @@ class Chat(Blackbox):
return isinstance(data, list) return isinstance(data, list)
# model_name有 Qwen1.5-14B-Chat , internlm2-chat-20b # model_name有 Qwen1.5-14B-Chat , internlm2-chat-20b
def processing(self, model_name, prompt, template, context: list, temperature, top_p, n, max_tokens) -> str: def processing(self, model_name, prompt, template, context: list, temperature, top_p, n, max_tokens,stop,frequency_penalty,presence_penalty) -> str:
if context == None: if context == None:
context = [] context = []
@ -49,7 +49,9 @@ class Chat(Blackbox):
"top_p": top_p, "top_p": top_p,
"n": n, "n": n,
"max_tokens": max_tokens, "max_tokens": max_tokens,
"stream": False, "frequency_penalty": frequency_penalty,
"presence_penalty": presence_penalty,
"stop": stop
} }
header = { header = {
@ -75,7 +77,9 @@ class Chat(Blackbox):
user_top_p = data.get("top_p") user_top_p = data.get("top_p")
user_n = data.get("n") user_n = data.get("n")
user_max_tokens = data.get("max_tokens") user_max_tokens = data.get("max_tokens")
user_stop = data.get("stop")
user_frequency_penalty = data.get("frequency_penalty")
user_presence_penalty = data.get("presence_penalty")
if user_question is None: if user_question is None:
return JSONResponse(content={"error": "question is required"}, status_code=status.HTTP_400_BAD_REQUEST) return JSONResponse(content={"error": "question is required"}, status_code=status.HTTP_400_BAD_REQUEST)
@ -87,10 +91,10 @@ class Chat(Blackbox):
user_template = "" user_template = ""
if user_temperature is None or user_temperature == "": if user_temperature is None or user_temperature == "":
user_temperature = 0.7 user_temperature = 0.8
if user_top_p is None or user_top_p == "": if user_top_p is None or user_top_p == "":
user_top_p = 1 user_top_p = 0.8
if user_n is None or user_n == "": if user_n is None or user_n == "":
user_n = 1 user_n = 1
@ -98,6 +102,15 @@ class Chat(Blackbox):
if user_max_tokens is None or user_max_tokens == "": if user_max_tokens is None or user_max_tokens == "":
user_max_tokens = 1024 user_max_tokens = 1024
if user_stop is None or user_stop == "":
user_stop = 100
if user_frequency_penalty is None or user_frequency_penalty == "":
user_frequency_penalty = 0.5
if user_presence_penalty is None or user_presence_penalty == "":
user_presence_penalty = 0.8
return JSONResponse(content={"response": self.processing(user_model_name, user_question, user_template, user_context, return JSONResponse(content={"response": self.processing(user_model_name, user_question, user_template, user_context,
user_temperature, user_top_p, user_n, user_max_tokens)}, status_code=status.HTTP_200_OK) user_temperature, user_top_p, user_n, user_max_tokens,user_stop,user_frequency_penalty,user_presence_penalty)}, status_code=status.HTTP_200_OK)

33
src/blackbox/g2e.py
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@ -19,11 +19,11 @@ class G2E(Blackbox):
return isinstance(data, list) return isinstance(data, list)
# model_name有 Qwen1.5-14B-Chat , internlm2-chat-20b # model_name有 Qwen1.5-14B-Chat , internlm2-chat-20b
def processing(self, model_name, prompt, template, context: list) -> str: def processing(self, model_name, prompt, template, context: list) -> str:
if context == None: if context == None:
context = [] context = []
url = 'http://120.196.116.194:48890/v1' #url = 'http://120.196.116.194:48890/v1'
#url = 'http://120.196.116.194:48892/v1' url = 'http://120.196.116.194:48892/v1'
background_prompt = '''KOMBUKIKI是一款茶饮料，目标受众 年龄：20-35岁 性别：女性 地点：一线城市、二线城市 职业：精英中产、都市白领 收入水平：中高收入，有一定消费能力 兴趣和爱好：注重健康，有运动习惯 background_prompt = '''KOMBUKIKI是一款茶饮料，目标受众 年龄：20-35岁 性别：女性 地点：一线城市、二线城市 职业：精英中产、都市白领 收入水平：中高收入，有一定消费能力 兴趣和爱好：注重健康，有运动习惯
@ -42,41 +42,46 @@ class G2E(Blackbox):
KOMBUKIKI康普茶价格 内地常规版：25 RMB 澳门常规版：28-29 MOP''' KOMBUKIKI康普茶价格 内地常规版：25 RMB 澳门常规版：28-29 MOP'''
prompt1 = ''''你是琪琪，活泼的康普茶看板娘，同时你对澳门十分熟悉，是一个澳门旅游专家，请回答任何关于澳门旅游的问题，回答尽量简练明了。 prompt1 = '''你是琪琪，活泼的康普茶看板娘，同时你对澳门十分熟悉，是一个澳门旅游专家，请回答任何关于澳门旅游的问题，回答尽量简练明了。'''
'''
inject_prompt = '(用活泼的语气说话回答，回答严格限制50字以内)'
#inject_prompt = '(用活泼的语气说话回答，回答严格限制50字以内)'
inject_prompt = '(回答简练，不要输出重复内容，只讲中文)'
prompt_template = [
{"role": "system", "content": background_prompt + prompt1},
]
#prompt_template = [ #prompt_template = [
# {"role": "system", "content": ''}, # {"role": "system", "content": background_prompt + prompt1},
#] #]
prompt_template = [
{"role": "system", "content": ''}
]
messages = prompt_template + context + [ messages = prompt_template + context + [
{ {
"role": "user", "role": "user",
"content": prompt + inject_prompt "content": prompt
} }
] ]
print("**** History with current prompt input ： ****")
print(messages)
client = OpenAI( client = OpenAI(
api_key='YOUR_API_KEY', api_key='YOUR_API_KEY',
base_url=url base_url=url
) )
model_name = client.models.list().data[0].id model_name = client.models.list().data[0].id
#model_name = client.models.list().data[1].id
print(model_name) print(model_name)
response = client.chat.completions.create( response = client.chat.completions.create(
model=model_name, model=model_name,
messages=messages, messages=messages,
temperature=0.8, temperature=0.8,
top_p=0.8, top_p=0.8,
# max_tokens = 50 frequency_penalty=0.5,
presence_penalty=0.8,
stop=100
) )
fastchat_content = response.choices[0].message.content fastchat_content = response.choices[0].message.content
print("*** Model response: " + fastchat_content + " ***")
return fastchat_content return fastchat_content
async def fast_api_handler(self, request: Request) -> Response: async def fast_api_handler(self, request: Request) -> Response: