1570 lines
59 KiB
Python
1570 lines
59 KiB
Python
|
||
"""
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||
该文件中主要包含2个函数，是所有LLM的通用接口，它们会继续向下调用更底层的LLM模型，处理多模型并行等细节
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||
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不具备多线程能力的函数：正常对话时使用，具备完备的交互功能，不可多线程
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1. predict(...)
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具备多线程调用能力的函数：在函数插件中被调用，灵活而简洁
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2. predict_no_ui_long_connection(...)
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||
"""
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import tiktoken, copy, re
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from loguru import logger
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from functools import lru_cache
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from concurrent.futures import ThreadPoolExecutor
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from toolbox import get_conf, trimmed_format_exc, apply_gpt_academic_string_mask, read_one_api_model_name
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from .bridge_chatgpt import predict_no_ui_long_connection as chatgpt_noui
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from .bridge_chatgpt import predict as chatgpt_ui
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from .bridge_chatgpt_vision import predict_no_ui_long_connection as chatgpt_vision_noui
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from .bridge_chatgpt_vision import predict as chatgpt_vision_ui
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from .bridge_chatglm import predict_no_ui_long_connection as chatglm_noui
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from .bridge_chatglm import predict as chatglm_ui
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from .bridge_chatglm3 import predict_no_ui_long_connection as chatglm3_noui
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from .bridge_chatglm3 import predict as chatglm3_ui
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from .bridge_chatglm4 import predict_no_ui_long_connection as chatglm4_noui
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from .bridge_chatglm4 import predict as chatglm4_ui
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from .bridge_qianfan import predict_no_ui_long_connection as qianfan_noui
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from .bridge_qianfan import predict as qianfan_ui
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from .bridge_google_gemini import predict as genai_ui
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from .bridge_google_gemini import predict_no_ui_long_connection as genai_noui
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from .bridge_zhipu import predict_no_ui_long_connection as zhipu_noui
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from .bridge_zhipu import predict as zhipu_ui
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from .bridge_taichu import predict_no_ui_long_connection as taichu_noui
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from .bridge_taichu import predict as taichu_ui
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from .bridge_cohere import predict as cohere_ui
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from .bridge_cohere import predict_no_ui_long_connection as cohere_noui
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from .oai_std_model_template import get_predict_function
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colors = ['#FF00FF', '#00FFFF', '#FF0000', '#990099', '#009999', '#990044']
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class LazyloadTiktoken(object):
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def __init__(self, model):
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self.model = model
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@staticmethod
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@lru_cache(maxsize=128)
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def get_encoder(model):
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logger.info('正在加载tokenizer，如果是第一次运行，可能需要一点时间下载参数')
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tmp = tiktoken.encoding_for_model(model)
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logger.info('加载tokenizer完毕')
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return tmp
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def encode(self, *args, **kwargs):
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encoder = self.get_encoder(self.model)
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return encoder.encode(*args, **kwargs)
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def decode(self, *args, **kwargs):
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encoder = self.get_encoder(self.model)
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return encoder.decode(*args, **kwargs)
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# Endpoint 重定向
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API_URL_REDIRECT, AZURE_ENDPOINT, AZURE_ENGINE = get_conf("API_URL_REDIRECT", "AZURE_ENDPOINT", "AZURE_ENGINE")
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openai_endpoint = "https://api.openai.com/v1/chat/completions"
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api2d_endpoint = "https://openai.api2d.net/v1/chat/completions"
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newbing_endpoint = "wss://sydney.bing.com/sydney/ChatHub"
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gemini_endpoint = "https://generativelanguage.googleapis.com/v1beta/models"
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claude_endpoint = "https://api.anthropic.com/v1/messages"
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||
cohere_endpoint = "https://api.cohere.ai/v1/chat"
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ollama_endpoint = "http://localhost:11434/api/chat"
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||
yimodel_endpoint = "https://api.lingyiwanwu.com/v1/chat/completions"
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deepseekapi_endpoint = "https://api.deepseek.com/v1/chat/completions"
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grok_model_endpoint = "https://api.x.ai/v1/chat/completions"
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volcengine_endpoint = "https://ark.cn-beijing.volces.com/api/v3/chat/completions"
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if not AZURE_ENDPOINT.endswith('/'): AZURE_ENDPOINT += '/'
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azure_endpoint = AZURE_ENDPOINT + f'openai/deployments/{AZURE_ENGINE}/chat/completions?api-version=2023-05-15'
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# 兼容旧版的配置
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try:
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API_URL = get_conf("API_URL")
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if API_URL != "https://api.openai.com/v1/chat/completions":
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openai_endpoint = API_URL
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logger.warning("警告！API_URL配置选项将被弃用，请更换为API_URL_REDIRECT配置")
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except:
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pass
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# 新版配置
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if openai_endpoint in API_URL_REDIRECT: openai_endpoint = API_URL_REDIRECT[openai_endpoint]
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if api2d_endpoint in API_URL_REDIRECT: api2d_endpoint = API_URL_REDIRECT[api2d_endpoint]
|
||
if newbing_endpoint in API_URL_REDIRECT: newbing_endpoint = API_URL_REDIRECT[newbing_endpoint]
|
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if gemini_endpoint in API_URL_REDIRECT: gemini_endpoint = API_URL_REDIRECT[gemini_endpoint]
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||
if claude_endpoint in API_URL_REDIRECT: claude_endpoint = API_URL_REDIRECT[claude_endpoint]
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||
if cohere_endpoint in API_URL_REDIRECT: cohere_endpoint = API_URL_REDIRECT[cohere_endpoint]
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||
if ollama_endpoint in API_URL_REDIRECT: ollama_endpoint = API_URL_REDIRECT[ollama_endpoint]
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||
if yimodel_endpoint in API_URL_REDIRECT: yimodel_endpoint = API_URL_REDIRECT[yimodel_endpoint]
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if deepseekapi_endpoint in API_URL_REDIRECT: deepseekapi_endpoint = API_URL_REDIRECT[deepseekapi_endpoint]
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if grok_model_endpoint in API_URL_REDIRECT: grok_model_endpoint = API_URL_REDIRECT[grok_model_endpoint]
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if volcengine_endpoint in API_URL_REDIRECT: volcengine_endpoint = API_URL_REDIRECT[volcengine_endpoint]
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# 获取tokenizer
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tokenizer_gpt35 = LazyloadTiktoken("gpt-3.5-turbo")
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tokenizer_gpt4 = LazyloadTiktoken("gpt-4")
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get_token_num_gpt35 = lambda txt: len(tokenizer_gpt35.encode(txt, disallowed_special=()))
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get_token_num_gpt4 = lambda txt: len(tokenizer_gpt4.encode(txt, disallowed_special=()))
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# 开始初始化模型
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AVAIL_LLM_MODELS, LLM_MODEL = get_conf("AVAIL_LLM_MODELS", "LLM_MODEL")
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AVAIL_LLM_MODELS = AVAIL_LLM_MODELS + [LLM_MODEL]
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# -=-=-=-=-=-=- 以下这部分是最早加入的最稳定的模型 -=-=-=-=-=-=-
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model_info = {
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# openai
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"gpt-3.5-turbo": {
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||
"fn_with_ui": chatgpt_ui,
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"fn_without_ui": chatgpt_noui,
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"endpoint": openai_endpoint,
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"max_token": 16385,
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"tokenizer": tokenizer_gpt35,
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"token_cnt": get_token_num_gpt35,
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},
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"taichu": {
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"fn_with_ui": taichu_ui,
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"fn_without_ui": taichu_noui,
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"endpoint": openai_endpoint,
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"max_token": 4096,
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"tokenizer": tokenizer_gpt35,
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"token_cnt": get_token_num_gpt35,
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||
},
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||
|
||
"gpt-3.5-turbo-16k": {
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||
"fn_with_ui": chatgpt_ui,
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||
"fn_without_ui": chatgpt_noui,
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||
"endpoint": openai_endpoint,
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||
"max_token": 16385,
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||
"tokenizer": tokenizer_gpt35,
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||
"token_cnt": get_token_num_gpt35,
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||
},
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||
|
||
"gpt-3.5-turbo-0613": {
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||
"fn_with_ui": chatgpt_ui,
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||
"fn_without_ui": chatgpt_noui,
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||
"endpoint": openai_endpoint,
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||
"max_token": 4096,
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||
"tokenizer": tokenizer_gpt35,
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||
"token_cnt": get_token_num_gpt35,
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||
},
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||
|
||
"gpt-3.5-turbo-16k-0613": {
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||
"fn_with_ui": chatgpt_ui,
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||
"fn_without_ui": chatgpt_noui,
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||
"endpoint": openai_endpoint,
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||
"max_token": 16385,
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||
"tokenizer": tokenizer_gpt35,
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"token_cnt": get_token_num_gpt35,
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},
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||
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"gpt-3.5-turbo-1106": { #16k
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"fn_with_ui": chatgpt_ui,
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||
"fn_without_ui": chatgpt_noui,
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||
"endpoint": openai_endpoint,
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||
"max_token": 16385,
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||
"tokenizer": tokenizer_gpt35,
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||
"token_cnt": get_token_num_gpt35,
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||
},
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||
|
||
"gpt-3.5-turbo-0125": { #16k
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||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
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||
"endpoint": openai_endpoint,
|
||
"max_token": 16385,
|
||
"tokenizer": tokenizer_gpt35,
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||
"token_cnt": get_token_num_gpt35,
|
||
},
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||
|
||
"gpt-4": {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": 8192,
|
||
"tokenizer": tokenizer_gpt4,
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||
"token_cnt": get_token_num_gpt4,
|
||
},
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||
|
||
"gpt-4-32k": {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": 32768,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
|
||
"gpt-4o": {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"endpoint": openai_endpoint,
|
||
"has_multimodal_capacity": True,
|
||
"max_token": 128000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
|
||
"gpt-4o-mini": {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"endpoint": openai_endpoint,
|
||
"has_multimodal_capacity": True,
|
||
"max_token": 128000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
|
||
"chatgpt-4o-latest": {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"endpoint": openai_endpoint,
|
||
"has_multimodal_capacity": True,
|
||
"max_token": 128000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
|
||
"gpt-4o-2024-05-13": {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"has_multimodal_capacity": True,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": 128000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
|
||
"gpt-4-turbo-preview": {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": 128000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
|
||
"gpt-4-1106-preview": {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": 128000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
|
||
"gpt-4-0125-preview": {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": 128000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
|
||
"o1-preview": {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": 128000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
"openai_disable_system_prompt": True,
|
||
"openai_disable_stream": True,
|
||
"openai_force_temperature_one": True,
|
||
},
|
||
|
||
"o1-mini": {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"endpoint": openai_endpoint,
|
||
"can_multi_thread": True,
|
||
"max_token": 128000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
"openai_disable_system_prompt": True,
|
||
"openai_disable_stream": True,
|
||
"openai_force_temperature_one": True,
|
||
},
|
||
|
||
"o1-2024-12-17": {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": 200000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
"openai_disable_system_prompt": True,
|
||
"openai_disable_stream": True,
|
||
"openai_force_temperature_one": True,
|
||
},
|
||
|
||
"o1": {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": 200000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
"openai_disable_system_prompt": True,
|
||
"openai_disable_stream": True,
|
||
"openai_force_temperature_one": True,
|
||
},
|
||
|
||
"gpt-4.1":{
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"has_multimodal_capacity": True,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": 828000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
|
||
"gpt-4.1-mini":{
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"has_multimodal_capacity": True,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": 828000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
|
||
"o3":{
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"has_multimodal_capacity": True,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": 828000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
"openai_disable_system_prompt": True,
|
||
"openai_disable_stream": True,
|
||
"openai_force_temperature_one": True,
|
||
},
|
||
|
||
"o4-mini":{
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"has_multimodal_capacity": True,
|
||
"can_multi_thread": True,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": 828000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
|
||
"gpt-4-turbo": {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"has_multimodal_capacity": True,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": 128000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
|
||
"gpt-4-turbo-2024-04-09": {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"has_multimodal_capacity": True,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": 128000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
|
||
"gpt-3.5-random": {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": 4096,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
|
||
"gpt-4-vision-preview": {
|
||
"fn_with_ui": chatgpt_vision_ui,
|
||
"fn_without_ui": chatgpt_vision_noui,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": 4096,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
|
||
|
||
# azure openai
|
||
"azure-gpt-3.5":{
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"endpoint": azure_endpoint,
|
||
"max_token": 4096,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
|
||
"azure-gpt-4":{
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"endpoint": azure_endpoint,
|
||
"max_token": 8192,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
|
||
# 智谱AI
|
||
"glm-4": {
|
||
"fn_with_ui": zhipu_ui,
|
||
"fn_without_ui": zhipu_noui,
|
||
"endpoint": None,
|
||
"max_token": 10124 * 8,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"glm-4-0520": {
|
||
"fn_with_ui": zhipu_ui,
|
||
"fn_without_ui": zhipu_noui,
|
||
"endpoint": None,
|
||
"max_token": 10124 * 8,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"glm-4-air": {
|
||
"fn_with_ui": zhipu_ui,
|
||
"fn_without_ui": zhipu_noui,
|
||
"endpoint": None,
|
||
"max_token": 10124 * 8,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"glm-4-airx": {
|
||
"fn_with_ui": zhipu_ui,
|
||
"fn_without_ui": zhipu_noui,
|
||
"endpoint": None,
|
||
"max_token": 10124 * 8,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"glm-4-flash": {
|
||
"fn_with_ui": zhipu_ui,
|
||
"fn_without_ui": zhipu_noui,
|
||
"endpoint": None,
|
||
"max_token": 10124 * 8,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"glm-4v": {
|
||
"fn_with_ui": zhipu_ui,
|
||
"fn_without_ui": zhipu_noui,
|
||
"endpoint": None,
|
||
"max_token": 1000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"glm-3-turbo": {
|
||
"fn_with_ui": zhipu_ui,
|
||
"fn_without_ui": zhipu_noui,
|
||
"endpoint": None,
|
||
"max_token": 10124 * 4,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"glm-4-plus":{
|
||
"fn_with_ui": zhipu_ui,
|
||
"fn_without_ui": zhipu_noui,
|
||
"endpoint": None,
|
||
"max_token": 10124 * 8,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
|
||
# api_2d (此后不需要在此处添加api2d的接口了，因为下面的代码会自动添加)
|
||
"api2d-gpt-4": {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"endpoint": api2d_endpoint,
|
||
"max_token": 8192,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
|
||
# ChatGLM本地模型
|
||
# 将 chatglm 直接对齐到 chatglm2
|
||
"chatglm": {
|
||
"fn_with_ui": chatglm_ui,
|
||
"fn_without_ui": chatglm_noui,
|
||
"endpoint": None,
|
||
"max_token": 1024,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"chatglm2": {
|
||
"fn_with_ui": chatglm_ui,
|
||
"fn_without_ui": chatglm_noui,
|
||
"endpoint": None,
|
||
"max_token": 1024,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"chatglm3": {
|
||
"fn_with_ui": chatglm3_ui,
|
||
"fn_without_ui": chatglm3_noui,
|
||
"endpoint": None,
|
||
"max_token": 8192,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"chatglm4": {
|
||
"fn_with_ui": chatglm4_ui,
|
||
"fn_without_ui": chatglm4_noui,
|
||
"endpoint": None,
|
||
"max_token": 8192,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"qianfan": {
|
||
"fn_with_ui": qianfan_ui,
|
||
"fn_without_ui": qianfan_noui,
|
||
"endpoint": None,
|
||
"max_token": 2000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
# Gemini
|
||
# Note: now gemini-pro is an alias of gemini-1.0-pro.
|
||
# Warning: gemini-pro-vision has been deprecated.
|
||
# Support for gemini-pro-vision has been removed.
|
||
"gemini-pro": {
|
||
"fn_with_ui": genai_ui,
|
||
"fn_without_ui": genai_noui,
|
||
"endpoint": gemini_endpoint,
|
||
"has_multimodal_capacity": False,
|
||
"max_token": 1024 * 32,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"gemini-1.0-pro": {
|
||
"fn_with_ui": genai_ui,
|
||
"fn_without_ui": genai_noui,
|
||
"endpoint": gemini_endpoint,
|
||
"has_multimodal_capacity": False,
|
||
"max_token": 1024 * 32,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"gemini-1.5-pro": {
|
||
"fn_with_ui": genai_ui,
|
||
"fn_without_ui": genai_noui,
|
||
"endpoint": gemini_endpoint,
|
||
"has_multimodal_capacity": True,
|
||
"max_token": 1024 * 204800,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"gemini-1.5-flash": {
|
||
"fn_with_ui": genai_ui,
|
||
"fn_without_ui": genai_noui,
|
||
"endpoint": gemini_endpoint,
|
||
"has_multimodal_capacity": True,
|
||
"max_token": 1024 * 204800,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"gemini-2.0-flash": {
|
||
"fn_with_ui": genai_ui,
|
||
"fn_without_ui": genai_noui,
|
||
"endpoint": gemini_endpoint,
|
||
"has_multimodal_capacity": True,
|
||
"max_token": 1024 * 204800,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
|
||
# cohere
|
||
"cohere-command-r-plus": {
|
||
"fn_with_ui": cohere_ui,
|
||
"fn_without_ui": cohere_noui,
|
||
"can_multi_thread": True,
|
||
"endpoint": cohere_endpoint,
|
||
"max_token": 1024 * 4,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
|
||
}
|
||
# -=-=-=-=-=-=- 月之暗面 -=-=-=-=-=-=-
|
||
from request_llms.bridge_moonshot import predict as moonshot_ui
|
||
from request_llms.bridge_moonshot import predict_no_ui_long_connection as moonshot_no_ui
|
||
model_info.update({
|
||
"moonshot-v1-8k": {
|
||
"fn_with_ui": moonshot_ui,
|
||
"fn_without_ui": moonshot_no_ui,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 1024 * 8,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"moonshot-v1-32k": {
|
||
"fn_with_ui": moonshot_ui,
|
||
"fn_without_ui": moonshot_no_ui,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 1024 * 32,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"moonshot-v1-128k": {
|
||
"fn_with_ui": moonshot_ui,
|
||
"fn_without_ui": moonshot_no_ui,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 1024 * 128,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
}
|
||
})
|
||
# -=-=-=-=-=-=- api2d 对齐支持 -=-=-=-=-=-=-
|
||
for model in AVAIL_LLM_MODELS:
|
||
if model.startswith('api2d-') and (model.replace('api2d-','') in model_info.keys()):
|
||
mi = copy.deepcopy(model_info[model.replace('api2d-','')])
|
||
mi.update({"endpoint": api2d_endpoint})
|
||
model_info.update({model: mi})
|
||
|
||
# -=-=-=-=-=-=- azure 对齐支持 -=-=-=-=-=-=-
|
||
for model in AVAIL_LLM_MODELS:
|
||
if model.startswith('azure-') and (model.replace('azure-','') in model_info.keys()):
|
||
mi = copy.deepcopy(model_info[model.replace('azure-','')])
|
||
mi.update({"endpoint": azure_endpoint})
|
||
model_info.update({model: mi})
|
||
|
||
# -=-=-=-=-=-=- 以下部分是新加入的模型，可能附带额外依赖 -=-=-=-=-=-=-
|
||
# claude家族
|
||
claude_models = ["claude-instant-1.2","claude-2.0","claude-2.1","claude-3-haiku-20240307","claude-3-sonnet-20240229","claude-3-opus-20240229","claude-3-5-sonnet-20240620"]
|
||
if any(item in claude_models for item in AVAIL_LLM_MODELS):
|
||
from .bridge_claude import predict_no_ui_long_connection as claude_noui
|
||
from .bridge_claude import predict as claude_ui
|
||
model_info.update({
|
||
"claude-instant-1.2": {
|
||
"fn_with_ui": claude_ui,
|
||
"fn_without_ui": claude_noui,
|
||
"endpoint": claude_endpoint,
|
||
"max_token": 100000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
})
|
||
model_info.update({
|
||
"claude-2.0": {
|
||
"fn_with_ui": claude_ui,
|
||
"fn_without_ui": claude_noui,
|
||
"endpoint": claude_endpoint,
|
||
"max_token": 100000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
})
|
||
model_info.update({
|
||
"claude-2.1": {
|
||
"fn_with_ui": claude_ui,
|
||
"fn_without_ui": claude_noui,
|
||
"endpoint": claude_endpoint,
|
||
"max_token": 200000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
})
|
||
model_info.update({
|
||
"claude-3-haiku-20240307": {
|
||
"fn_with_ui": claude_ui,
|
||
"fn_without_ui": claude_noui,
|
||
"endpoint": claude_endpoint,
|
||
"max_token": 200000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
})
|
||
model_info.update({
|
||
"claude-3-sonnet-20240229": {
|
||
"fn_with_ui": claude_ui,
|
||
"fn_without_ui": claude_noui,
|
||
"endpoint": claude_endpoint,
|
||
"max_token": 200000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
})
|
||
model_info.update({
|
||
"claude-3-opus-20240229": {
|
||
"fn_with_ui": claude_ui,
|
||
"fn_without_ui": claude_noui,
|
||
"endpoint": claude_endpoint,
|
||
"max_token": 200000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
})
|
||
model_info.update({
|
||
"claude-3-5-sonnet-20240620": {
|
||
"fn_with_ui": claude_ui,
|
||
"fn_without_ui": claude_noui,
|
||
"endpoint": claude_endpoint,
|
||
"max_token": 200000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
})
|
||
if "jittorllms_rwkv" in AVAIL_LLM_MODELS:
|
||
from .bridge_jittorllms_rwkv import predict_no_ui_long_connection as rwkv_noui
|
||
from .bridge_jittorllms_rwkv import predict as rwkv_ui
|
||
model_info.update({
|
||
"jittorllms_rwkv": {
|
||
"fn_with_ui": rwkv_ui,
|
||
"fn_without_ui": rwkv_noui,
|
||
"endpoint": None,
|
||
"max_token": 1024,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
})
|
||
if "jittorllms_llama" in AVAIL_LLM_MODELS:
|
||
from .bridge_jittorllms_llama import predict_no_ui_long_connection as llama_noui
|
||
from .bridge_jittorllms_llama import predict as llama_ui
|
||
model_info.update({
|
||
"jittorllms_llama": {
|
||
"fn_with_ui": llama_ui,
|
||
"fn_without_ui": llama_noui,
|
||
"endpoint": None,
|
||
"max_token": 1024,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
})
|
||
if "jittorllms_pangualpha" in AVAIL_LLM_MODELS:
|
||
from .bridge_jittorllms_pangualpha import predict_no_ui_long_connection as pangualpha_noui
|
||
from .bridge_jittorllms_pangualpha import predict as pangualpha_ui
|
||
model_info.update({
|
||
"jittorllms_pangualpha": {
|
||
"fn_with_ui": pangualpha_ui,
|
||
"fn_without_ui": pangualpha_noui,
|
||
"endpoint": None,
|
||
"max_token": 1024,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
})
|
||
if "moss" in AVAIL_LLM_MODELS:
|
||
from .bridge_moss import predict_no_ui_long_connection as moss_noui
|
||
from .bridge_moss import predict as moss_ui
|
||
model_info.update({
|
||
"moss": {
|
||
"fn_with_ui": moss_ui,
|
||
"fn_without_ui": moss_noui,
|
||
"endpoint": None,
|
||
"max_token": 1024,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
})
|
||
if "stack-claude" in AVAIL_LLM_MODELS:
|
||
from .bridge_stackclaude import predict_no_ui_long_connection as claude_noui
|
||
from .bridge_stackclaude import predict as claude_ui
|
||
model_info.update({
|
||
"stack-claude": {
|
||
"fn_with_ui": claude_ui,
|
||
"fn_without_ui": claude_noui,
|
||
"endpoint": None,
|
||
"max_token": 8192,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
}
|
||
})
|
||
if "newbing" in AVAIL_LLM_MODELS: # same with newbing-free
|
||
try:
|
||
from .bridge_newbingfree import predict_no_ui_long_connection as newbingfree_noui
|
||
from .bridge_newbingfree import predict as newbingfree_ui
|
||
model_info.update({
|
||
"newbing": {
|
||
"fn_with_ui": newbingfree_ui,
|
||
"fn_without_ui": newbingfree_noui,
|
||
"endpoint": newbing_endpoint,
|
||
"max_token": 4096,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
}
|
||
})
|
||
except:
|
||
logger.error(trimmed_format_exc())
|
||
if "chatglmft" in AVAIL_LLM_MODELS: # same with newbing-free
|
||
try:
|
||
from .bridge_chatglmft import predict_no_ui_long_connection as chatglmft_noui
|
||
from .bridge_chatglmft import predict as chatglmft_ui
|
||
model_info.update({
|
||
"chatglmft": {
|
||
"fn_with_ui": chatglmft_ui,
|
||
"fn_without_ui": chatglmft_noui,
|
||
"endpoint": None,
|
||
"max_token": 4096,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
}
|
||
})
|
||
except:
|
||
logger.error(trimmed_format_exc())
|
||
# -=-=-=-=-=-=- 上海AI-LAB书生大模型 -=-=-=-=-=-=-
|
||
if "internlm" in AVAIL_LLM_MODELS:
|
||
try:
|
||
from .bridge_internlm import predict_no_ui_long_connection as internlm_noui
|
||
from .bridge_internlm import predict as internlm_ui
|
||
model_info.update({
|
||
"internlm": {
|
||
"fn_with_ui": internlm_ui,
|
||
"fn_without_ui": internlm_noui,
|
||
"endpoint": None,
|
||
"max_token": 4096,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
}
|
||
})
|
||
except:
|
||
logger.error(trimmed_format_exc())
|
||
if "chatglm_onnx" in AVAIL_LLM_MODELS:
|
||
try:
|
||
from .bridge_chatglmonnx import predict_no_ui_long_connection as chatglm_onnx_noui
|
||
from .bridge_chatglmonnx import predict as chatglm_onnx_ui
|
||
model_info.update({
|
||
"chatglm_onnx": {
|
||
"fn_with_ui": chatglm_onnx_ui,
|
||
"fn_without_ui": chatglm_onnx_noui,
|
||
"endpoint": None,
|
||
"max_token": 4096,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
}
|
||
})
|
||
except:
|
||
logger.error(trimmed_format_exc())
|
||
# -=-=-=-=-=-=- 通义-本地模型 -=-=-=-=-=-=-
|
||
if "qwen-local" in AVAIL_LLM_MODELS:
|
||
try:
|
||
from .bridge_qwen_local import predict_no_ui_long_connection as qwen_local_noui
|
||
from .bridge_qwen_local import predict as qwen_local_ui
|
||
model_info.update({
|
||
"qwen-local": {
|
||
"fn_with_ui": qwen_local_ui,
|
||
"fn_without_ui": qwen_local_noui,
|
||
"can_multi_thread": False,
|
||
"endpoint": None,
|
||
"max_token": 4096,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
}
|
||
})
|
||
except:
|
||
logger.error(trimmed_format_exc())
|
||
|
||
# -=-=-=-=-=-=- 阿里云百炼（通义）-在线模型 -=-=-=-=-=-=-
|
||
qwen_models = ["qwen-max-latest", "qwen-max-2025-01-25","qwen-max","qwen-turbo","qwen-plus",
|
||
"dashscope-deepseek-r1","dashscope-deepseek-v3",
|
||
"dashscope-qwen3-14b", "dashscope-qwen3-235b-a22b", "dashscope-qwen3-qwen3-32b",
|
||
]
|
||
if any(item in qwen_models for item in AVAIL_LLM_MODELS):
|
||
try:
|
||
from .bridge_qwen import predict_no_ui_long_connection as qwen_noui
|
||
from .bridge_qwen import predict as qwen_ui
|
||
model_info.update({
|
||
"qwen-turbo": {
|
||
"fn_with_ui": qwen_ui,
|
||
"fn_without_ui": qwen_noui,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 100000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"qwen-plus": {
|
||
"fn_with_ui": qwen_ui,
|
||
"fn_without_ui": qwen_noui,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 129024,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"qwen-max": {
|
||
"fn_with_ui": qwen_ui,
|
||
"fn_without_ui": qwen_noui,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 30720,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"qwen-max-latest": {
|
||
"fn_with_ui": qwen_ui,
|
||
"fn_without_ui": qwen_noui,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 30720,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"qwen-max-2025-01-25": {
|
||
"fn_with_ui": qwen_ui,
|
||
"fn_without_ui": qwen_noui,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 30720,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"dashscope-deepseek-r1": {
|
||
"fn_with_ui": qwen_ui,
|
||
"fn_without_ui": qwen_noui,
|
||
"enable_reasoning": True,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 57344,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"dashscope-deepseek-v3": {
|
||
"fn_with_ui": qwen_ui,
|
||
"fn_without_ui": qwen_noui,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 57344,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"dashscope-qwen3-14b": {
|
||
"fn_with_ui": qwen_ui,
|
||
"fn_without_ui": qwen_noui,
|
||
"enable_reasoning": True,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 129024,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"dashscope-qwen3-235b-a22b": {
|
||
"fn_with_ui": qwen_ui,
|
||
"fn_without_ui": qwen_noui,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 129024,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"dashscope-qwen3-32b": {
|
||
"fn_with_ui": qwen_ui,
|
||
"fn_without_ui": qwen_noui,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 129024,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
}
|
||
})
|
||
except:
|
||
logger.error(trimmed_format_exc())
|
||
|
||
# -=-=-=-=-=-=- 零一万物模型 -=-=-=-=-=-=-
|
||
yi_models = ["yi-34b-chat-0205","yi-34b-chat-200k","yi-large","yi-medium","yi-spark","yi-large-turbo","yi-large-preview"]
|
||
if any(item in yi_models for item in AVAIL_LLM_MODELS):
|
||
try:
|
||
yimodel_4k_noui, yimodel_4k_ui = get_predict_function(
|
||
api_key_conf_name="YIMODEL_API_KEY", max_output_token=600, disable_proxy=False
|
||
)
|
||
yimodel_16k_noui, yimodel_16k_ui = get_predict_function(
|
||
api_key_conf_name="YIMODEL_API_KEY", max_output_token=4000, disable_proxy=False
|
||
)
|
||
yimodel_200k_noui, yimodel_200k_ui = get_predict_function(
|
||
api_key_conf_name="YIMODEL_API_KEY", max_output_token=4096, disable_proxy=False
|
||
)
|
||
model_info.update({
|
||
"yi-34b-chat-0205": {
|
||
"fn_with_ui": yimodel_4k_ui,
|
||
"fn_without_ui": yimodel_4k_noui,
|
||
"can_multi_thread": False, # 目前来说，默认情况下并发量极低，因此禁用
|
||
"endpoint": yimodel_endpoint,
|
||
"max_token": 4000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"yi-34b-chat-200k": {
|
||
"fn_with_ui": yimodel_200k_ui,
|
||
"fn_without_ui": yimodel_200k_noui,
|
||
"can_multi_thread": False, # 目前来说，默认情况下并发量极低，因此禁用
|
||
"endpoint": yimodel_endpoint,
|
||
"max_token": 200000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"yi-large": {
|
||
"fn_with_ui": yimodel_16k_ui,
|
||
"fn_without_ui": yimodel_16k_noui,
|
||
"can_multi_thread": False, # 目前来说，默认情况下并发量极低，因此禁用
|
||
"endpoint": yimodel_endpoint,
|
||
"max_token": 16000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"yi-medium": {
|
||
"fn_with_ui": yimodel_16k_ui,
|
||
"fn_without_ui": yimodel_16k_noui,
|
||
"can_multi_thread": True, # 这个并发量稍微大一点
|
||
"endpoint": yimodel_endpoint,
|
||
"max_token": 16000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"yi-spark": {
|
||
"fn_with_ui": yimodel_16k_ui,
|
||
"fn_without_ui": yimodel_16k_noui,
|
||
"can_multi_thread": True, # 这个并发量稍微大一点
|
||
"endpoint": yimodel_endpoint,
|
||
"max_token": 16000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"yi-large-turbo": {
|
||
"fn_with_ui": yimodel_16k_ui,
|
||
"fn_without_ui": yimodel_16k_noui,
|
||
"can_multi_thread": False, # 目前来说，默认情况下并发量极低，因此禁用
|
||
"endpoint": yimodel_endpoint,
|
||
"max_token": 16000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"yi-large-preview": {
|
||
"fn_with_ui": yimodel_16k_ui,
|
||
"fn_without_ui": yimodel_16k_noui,
|
||
"can_multi_thread": False, # 目前来说，默认情况下并发量极低，因此禁用
|
||
"endpoint": yimodel_endpoint,
|
||
"max_token": 16000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
})
|
||
except:
|
||
logger.error(trimmed_format_exc())
|
||
|
||
|
||
# -=-=-=-=-=-=- Grok model from x.ai -=-=-=-=-=-=-
|
||
grok_models = ["grok-beta"]
|
||
if any(item in grok_models for item in AVAIL_LLM_MODELS):
|
||
try:
|
||
grok_beta_128k_noui, grok_beta_128k_ui = get_predict_function(
|
||
api_key_conf_name="GROK_API_KEY", max_output_token=8192, disable_proxy=False
|
||
)
|
||
|
||
model_info.update({
|
||
"grok-beta": {
|
||
"fn_with_ui": grok_beta_128k_ui,
|
||
"fn_without_ui": grok_beta_128k_noui,
|
||
"can_multi_thread": True,
|
||
"endpoint": grok_model_endpoint,
|
||
"max_token": 128000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
|
||
})
|
||
except:
|
||
logger.error(trimmed_format_exc())
|
||
|
||
# -=-=-=-=-=-=- 讯飞星火认知大模型 -=-=-=-=-=-=-
|
||
if "spark" in AVAIL_LLM_MODELS:
|
||
try:
|
||
from .bridge_spark import predict_no_ui_long_connection as spark_noui
|
||
from .bridge_spark import predict as spark_ui
|
||
model_info.update({
|
||
"spark": {
|
||
"fn_with_ui": spark_ui,
|
||
"fn_without_ui": spark_noui,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 4096,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
}
|
||
})
|
||
except:
|
||
logger.error(trimmed_format_exc())
|
||
if "sparkv2" in AVAIL_LLM_MODELS: # 讯飞星火认知大模型
|
||
try:
|
||
from .bridge_spark import predict_no_ui_long_connection as spark_noui
|
||
from .bridge_spark import predict as spark_ui
|
||
model_info.update({
|
||
"sparkv2": {
|
||
"fn_with_ui": spark_ui,
|
||
"fn_without_ui": spark_noui,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 4096,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
}
|
||
})
|
||
except:
|
||
logger.error(trimmed_format_exc())
|
||
if any(x in AVAIL_LLM_MODELS for x in ("sparkv3", "sparkv3.5", "sparkv4")): # 讯飞星火认知大模型
|
||
try:
|
||
from .bridge_spark import predict_no_ui_long_connection as spark_noui
|
||
from .bridge_spark import predict as spark_ui
|
||
model_info.update({
|
||
"sparkv3": {
|
||
"fn_with_ui": spark_ui,
|
||
"fn_without_ui": spark_noui,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 4096,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"sparkv3.5": {
|
||
"fn_with_ui": spark_ui,
|
||
"fn_without_ui": spark_noui,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 4096,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"sparkv4":{
|
||
"fn_with_ui": spark_ui,
|
||
"fn_without_ui": spark_noui,
|
||
"can_multi_thread": True,
|
||
"endpoint": None,
|
||
"max_token": 4096,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
}
|
||
})
|
||
except:
|
||
logger.error(trimmed_format_exc())
|
||
if "llama2" in AVAIL_LLM_MODELS: # llama2
|
||
try:
|
||
from .bridge_llama2 import predict_no_ui_long_connection as llama2_noui
|
||
from .bridge_llama2 import predict as llama2_ui
|
||
model_info.update({
|
||
"llama2": {
|
||
"fn_with_ui": llama2_ui,
|
||
"fn_without_ui": llama2_noui,
|
||
"endpoint": None,
|
||
"max_token": 4096,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
}
|
||
})
|
||
except:
|
||
logger.error(trimmed_format_exc())
|
||
# -=-=-=-=-=-=- 智谱 -=-=-=-=-=-=-
|
||
if "zhipuai" in AVAIL_LLM_MODELS: # zhipuai 是glm-4的别名，向后兼容配置
|
||
try:
|
||
model_info.update({
|
||
"zhipuai": {
|
||
"fn_with_ui": zhipu_ui,
|
||
"fn_without_ui": zhipu_noui,
|
||
"endpoint": None,
|
||
"max_token": 10124 * 8,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
})
|
||
except:
|
||
logger.error(trimmed_format_exc())
|
||
# -=-=-=-=-=-=- 幻方-深度求索本地大模型 -=-=-=-=-=-=-
|
||
if "deepseekcoder" in AVAIL_LLM_MODELS: # deepseekcoder
|
||
try:
|
||
from .bridge_deepseekcoder import predict_no_ui_long_connection as deepseekcoder_noui
|
||
from .bridge_deepseekcoder import predict as deepseekcoder_ui
|
||
model_info.update({
|
||
"deepseekcoder": {
|
||
"fn_with_ui": deepseekcoder_ui,
|
||
"fn_without_ui": deepseekcoder_noui,
|
||
"endpoint": None,
|
||
"max_token": 2048,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
}
|
||
})
|
||
except:
|
||
logger.error(trimmed_format_exc())
|
||
|
||
# -=-=-=-=-=-=- 幻方-深度求索大模型在线API -=-=-=-=-=-=-
|
||
claude_models = ["deepseek-chat", "deepseek-coder", "deepseek-reasoner"]
|
||
if any(item in claude_models for item in AVAIL_LLM_MODELS):
|
||
try:
|
||
deepseekapi_noui, deepseekapi_ui = get_predict_function(
|
||
api_key_conf_name="DEEPSEEK_API_KEY", max_output_token=4096, disable_proxy=False
|
||
)
|
||
model_info.update({
|
||
"deepseek-chat":{
|
||
"fn_with_ui": deepseekapi_ui,
|
||
"fn_without_ui": deepseekapi_noui,
|
||
"endpoint": deepseekapi_endpoint,
|
||
"can_multi_thread": True,
|
||
"max_token": 64000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"deepseek-coder":{
|
||
"fn_with_ui": deepseekapi_ui,
|
||
"fn_without_ui": deepseekapi_noui,
|
||
"endpoint": deepseekapi_endpoint,
|
||
"can_multi_thread": True,
|
||
"max_token": 16000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"deepseek-reasoner":{
|
||
"fn_with_ui": deepseekapi_ui,
|
||
"fn_without_ui": deepseekapi_noui,
|
||
"endpoint": deepseekapi_endpoint,
|
||
"can_multi_thread": True,
|
||
"max_token": 64000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
"enable_reasoning": True
|
||
},
|
||
})
|
||
except:
|
||
logger.error(trimmed_format_exc())
|
||
|
||
# -=-=-=-=-=-=- 火山引擎 对齐支持 -=-=-=-=-=-=-
|
||
for model in [m for m in AVAIL_LLM_MODELS if m.startswith("volcengine-")]:
|
||
# 为了更灵活地接入volcengine多模型管理界面，设计了此接口，例子：AVAIL_LLM_MODELS = ["volcengine-deepseek-r1-250120(max_token=6666)"]
|
||
# 其中
|
||
# "volcengine-" 是前缀（必要）
|
||
# "deepseek-r1-250120" 是模型名（必要）
|
||
# "(max_token=6666)" 是配置（非必要）
|
||
model_info_extend = model_info
|
||
model_info_extend.update({
|
||
"deepseek-r1-250120": {
|
||
"max_token": 16384,
|
||
"enable_reasoning": True,
|
||
"can_multi_thread": True,
|
||
"endpoint": volcengine_endpoint,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
"deepseek-v3-241226": {
|
||
"max_token": 16384,
|
||
"enable_reasoning": False,
|
||
"can_multi_thread": True,
|
||
"endpoint": volcengine_endpoint,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
})
|
||
try:
|
||
origin_model_name, max_token_tmp = read_one_api_model_name(model)
|
||
# 如果是已知模型，则尝试获取其信息
|
||
original_model_info = model_info_extend.get(origin_model_name.replace("volcengine-", "", 1), None)
|
||
except:
|
||
logger.error(f"volcengine模型 {model} 的 max_token 配置不是整数，请检查配置文件。")
|
||
continue
|
||
|
||
volcengine_noui, volcengine_ui = get_predict_function(api_key_conf_name="ARK_API_KEY", max_output_token=8192, disable_proxy=True, model_remove_prefix = ["volcengine-"])
|
||
|
||
this_model_info = {
|
||
"fn_with_ui": volcengine_ui,
|
||
"fn_without_ui": volcengine_noui,
|
||
"endpoint": volcengine_endpoint,
|
||
"can_multi_thread": True,
|
||
"max_token": 64000,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
}
|
||
|
||
# 同步已知模型的其他信息
|
||
attribute = "has_multimodal_capacity"
|
||
if original_model_info is not None and original_model_info.get(attribute, None) is not None: this_model_info.update({attribute: original_model_info.get(attribute, None)})
|
||
attribute = "enable_reasoning"
|
||
if original_model_info is not None and original_model_info.get(attribute, None) is not None: this_model_info.update({attribute: original_model_info.get(attribute, None)})
|
||
model_info.update({model: this_model_info})
|
||
|
||
# -=-=-=-=-=-=- one-api 对齐支持 -=-=-=-=-=-=-
|
||
for model in [m for m in AVAIL_LLM_MODELS if m.startswith("one-api-")]:
|
||
# 为了更灵活地接入one-api多模型管理界面，设计了此接口，例子：AVAIL_LLM_MODELS = ["one-api-mixtral-8x7b(max_token=6666)"]
|
||
# 其中
|
||
# "one-api-" 是前缀（必要）
|
||
# "mixtral-8x7b" 是模型名（必要）
|
||
# "(max_token=6666)" 是配置（非必要）
|
||
try:
|
||
origin_model_name, max_token_tmp = read_one_api_model_name(model)
|
||
# 如果是已知模型，则尝试获取其信息
|
||
original_model_info = model_info.get(origin_model_name.replace("one-api-", "", 1), None)
|
||
except:
|
||
logger.error(f"one-api模型 {model} 的 max_token 配置不是整数，请检查配置文件。")
|
||
continue
|
||
this_model_info = {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"can_multi_thread": True,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": max_token_tmp,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
}
|
||
|
||
# 同步已知模型的其他信息
|
||
attribute = "has_multimodal_capacity"
|
||
if original_model_info is not None and original_model_info.get(attribute, None) is not None: this_model_info.update({attribute: original_model_info.get(attribute, None)})
|
||
# attribute = "attribute2"
|
||
# if original_model_info is not None and original_model_info.get(attribute, None) is not None: this_model_info.update({attribute: original_model_info.get(attribute, None)})
|
||
# attribute = "attribute3"
|
||
# if original_model_info is not None and original_model_info.get(attribute, None) is not None: this_model_info.update({attribute: original_model_info.get(attribute, None)})
|
||
model_info.update({model: this_model_info})
|
||
|
||
# -=-=-=-=-=-=- vllm 对齐支持 -=-=-=-=-=-=-
|
||
for model in [m for m in AVAIL_LLM_MODELS if m.startswith("vllm-")]:
|
||
# 为了更灵活地接入vllm多模型管理界面，设计了此接口，例子：AVAIL_LLM_MODELS = ["vllm-/home/hmp/llm/cache/Qwen1___5-32B-Chat(max_token=6666)"]
|
||
# 其中
|
||
# "vllm-" 是前缀（必要）
|
||
# "mixtral-8x7b" 是模型名（必要）
|
||
# "(max_token=6666)" 是配置（非必要）
|
||
try:
|
||
_, max_token_tmp = read_one_api_model_name(model)
|
||
except:
|
||
logger.error(f"vllm模型 {model} 的 max_token 配置不是整数，请检查配置文件。")
|
||
continue
|
||
model_info.update({
|
||
model: {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"can_multi_thread": True,
|
||
"endpoint": openai_endpoint,
|
||
"max_token": max_token_tmp,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
})
|
||
# -=-=-=-=-=-=- ollama 对齐支持 -=-=-=-=-=-=-
|
||
for model in [m for m in AVAIL_LLM_MODELS if m.startswith("ollama-")]:
|
||
from .bridge_ollama import predict_no_ui_long_connection as ollama_noui
|
||
from .bridge_ollama import predict as ollama_ui
|
||
break
|
||
for model in [m for m in AVAIL_LLM_MODELS if m.startswith("ollama-")]:
|
||
# 为了更灵活地接入ollama多模型管理界面，设计了此接口，例子：AVAIL_LLM_MODELS = ["ollama-phi3(max_token=6666)"]
|
||
# 其中
|
||
# "ollama-" 是前缀（必要）
|
||
# "phi3" 是模型名（必要）
|
||
# "(max_token=6666)" 是配置（非必要）
|
||
try:
|
||
_, max_token_tmp = read_one_api_model_name(model)
|
||
except:
|
||
logger.error(f"ollama模型 {model} 的 max_token 配置不是整数，请检查配置文件。")
|
||
continue
|
||
model_info.update({
|
||
model: {
|
||
"fn_with_ui": ollama_ui,
|
||
"fn_without_ui": ollama_noui,
|
||
"endpoint": ollama_endpoint,
|
||
"max_token": max_token_tmp,
|
||
"tokenizer": tokenizer_gpt35,
|
||
"token_cnt": get_token_num_gpt35,
|
||
},
|
||
})
|
||
|
||
# -=-=-=-=-=-=- azure模型对齐支持 -=-=-=-=-=-=-
|
||
AZURE_CFG_ARRAY = get_conf("AZURE_CFG_ARRAY") # <-- 用于定义和切换多个azure模型 -->
|
||
if len(AZURE_CFG_ARRAY) > 0:
|
||
for azure_model_name, azure_cfg_dict in AZURE_CFG_ARRAY.items():
|
||
# 可能会覆盖之前的配置，但这是意料之中的
|
||
if not azure_model_name.startswith('azure'):
|
||
raise ValueError("AZURE_CFG_ARRAY中配置的模型必须以azure开头")
|
||
endpoint_ = azure_cfg_dict["AZURE_ENDPOINT"] + \
|
||
f'openai/deployments/{azure_cfg_dict["AZURE_ENGINE"]}/chat/completions?api-version=2023-05-15'
|
||
model_info.update({
|
||
azure_model_name: {
|
||
"fn_with_ui": chatgpt_ui,
|
||
"fn_without_ui": chatgpt_noui,
|
||
"endpoint": endpoint_,
|
||
"azure_api_key": azure_cfg_dict["AZURE_API_KEY"],
|
||
"max_token": azure_cfg_dict["AZURE_MODEL_MAX_TOKEN"],
|
||
"tokenizer": tokenizer_gpt35, # tokenizer只用于粗估token数量
|
||
"token_cnt": get_token_num_gpt35,
|
||
}
|
||
})
|
||
if azure_model_name not in AVAIL_LLM_MODELS:
|
||
AVAIL_LLM_MODELS += [azure_model_name]
|
||
|
||
# -=-=-=-=-=-=- Openrouter模型对齐支持 -=-=-=-=-=-=-
|
||
# 为了更灵活地接入Openrouter路由，设计了此接口
|
||
for model in [m for m in AVAIL_LLM_MODELS if m.startswith("openrouter-")]:
|
||
from request_llms.bridge_openrouter import predict_no_ui_long_connection as openrouter_noui
|
||
from request_llms.bridge_openrouter import predict as openrouter_ui
|
||
model_info.update({
|
||
model: {
|
||
"fn_with_ui": openrouter_ui,
|
||
"fn_without_ui": openrouter_noui,
|
||
# 以下参数参考gpt-4o-mini的配置, 请根据实际情况修改
|
||
"endpoint": openai_endpoint,
|
||
"has_multimodal_capacity": True,
|
||
"max_token": 128000,
|
||
"tokenizer": tokenizer_gpt4,
|
||
"token_cnt": get_token_num_gpt4,
|
||
},
|
||
})
|
||
|
||
|
||
# -=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=-=-=
|
||
# -=-=-=-=-=-=-=-=-=- ☝️ 以上是模型路由 -=-=-=-=-=-=-=-=-=
|
||
# -=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=-=-=
|
||
|
||
# -=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=-=-=
|
||
# -=-=-=-=-=-=-= 👇 以下是多模型路由切换函数 -=-=-=-=-=-=-=
|
||
# -=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=--=-=-=-=-=-=-=-=
|
||
|
||
|
||
def LLM_CATCH_EXCEPTION(f):
|
||
"""
|
||
装饰器函数，将错误显示出来
|
||
"""
|
||
def decorated(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list, console_silence:bool):
|
||
try:
|
||
return f(inputs, llm_kwargs, history, sys_prompt, observe_window, console_silence)
|
||
except Exception as e:
|
||
tb_str = '\n```\n' + trimmed_format_exc() + '\n```\n'
|
||
observe_window[0] = tb_str
|
||
return tb_str
|
||
return decorated
|
||
|
||
|
||
def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list, sys_prompt:str, observe_window:list=[], console_silence:bool=False):
|
||
"""
|
||
发送至LLM，等待回复，一次性完成，不显示中间过程。但内部（尽可能地）用stream的方法避免中途网线被掐。
|
||
inputs：
|
||
是本次问询的输入
|
||
sys_prompt:
|
||
系统静默prompt
|
||
llm_kwargs：
|
||
LLM的内部调优参数
|
||
history：
|
||
是之前的对话列表
|
||
observe_window = None：
|
||
用于负责跨越线程传递已经输出的部分，大部分时候仅仅为了fancy的视觉效果，留空即可。observe_window[0]：观测窗。observe_window[1]：看门狗
|
||
"""
|
||
import threading, time, copy
|
||
|
||
inputs = apply_gpt_academic_string_mask(inputs, mode="show_llm")
|
||
model = llm_kwargs['llm_model']
|
||
n_model = 1
|
||
if '&' not in model:
|
||
# 如果只询问“一个”大语言模型（多数情况）：
|
||
method = model_info[model]["fn_without_ui"]
|
||
return method(inputs, llm_kwargs, history, sys_prompt, observe_window, console_silence)
|
||
else:
|
||
# 如果同时询问“多个”大语言模型，这个稍微啰嗦一点，但思路相同，您不必读这个else分支
|
||
executor = ThreadPoolExecutor(max_workers=4)
|
||
models = model.split('&')
|
||
n_model = len(models)
|
||
|
||
window_len = len(observe_window)
|
||
assert window_len==3
|
||
window_mutex = [["", time.time(), ""] for _ in range(n_model)] + [True]
|
||
|
||
futures = []
|
||
for i in range(n_model):
|
||
model = models[i]
|
||
method = model_info[model]["fn_without_ui"]
|
||
llm_kwargs_feedin = copy.deepcopy(llm_kwargs)
|
||
llm_kwargs_feedin['llm_model'] = model
|
||
future = executor.submit(LLM_CATCH_EXCEPTION(method), inputs, llm_kwargs_feedin, history, sys_prompt, window_mutex[i], console_silence)
|
||
futures.append(future)
|
||
|
||
def mutex_manager(window_mutex, observe_window):
|
||
while True:
|
||
time.sleep(0.25)
|
||
if not window_mutex[-1]: break
|
||
# 看门狗（watchdog）
|
||
for i in range(n_model):
|
||
window_mutex[i][1] = observe_window[1]
|
||
# 观察窗（window）
|
||
chat_string = []
|
||
for i in range(n_model):
|
||
color = colors[i%len(colors)]
|
||
chat_string.append( f"【{str(models[i])} 说】: <font color=\"{color}\"> {window_mutex[i][0]} </font>" )
|
||
res = '<br/><br/>\n\n---\n\n'.join(chat_string)
|
||
# # # # # # # # # # #
|
||
observe_window[0] = res
|
||
|
||
t_model = threading.Thread(target=mutex_manager, args=(window_mutex, observe_window), daemon=True)
|
||
t_model.start()
|
||
|
||
return_string_collect = []
|
||
while True:
|
||
worker_done = [h.done() for h in futures]
|
||
if all(worker_done):
|
||
executor.shutdown()
|
||
break
|
||
time.sleep(1)
|
||
|
||
for i, future in enumerate(futures): # wait and get
|
||
color = colors[i%len(colors)]
|
||
return_string_collect.append( f"【{str(models[i])} 说】: <font color=\"{color}\"> {future.result()} </font>" )
|
||
|
||
window_mutex[-1] = False # stop mutex thread
|
||
res = '<br/><br/>\n\n---\n\n'.join(return_string_collect)
|
||
return res
|
||
|
||
# 根据基础功能区 ModelOverride 参数调整模型类型，用于 `predict` 中
|
||
import importlib
|
||
import core_functional
|
||
def execute_model_override(llm_kwargs, additional_fn, method):
|
||
functional = core_functional.get_core_functions()
|
||
if (additional_fn in functional) and 'ModelOverride' in functional[additional_fn]:
|
||
# 热更新Prompt & ModelOverride
|
||
importlib.reload(core_functional)
|
||
functional = core_functional.get_core_functions()
|
||
model_override = functional[additional_fn]['ModelOverride']
|
||
if model_override not in model_info:
|
||
raise ValueError(f"模型覆盖参数 '{model_override}' 指向一个暂不支持的模型，请检查配置文件。")
|
||
method = model_info[model_override]["fn_with_ui"]
|
||
llm_kwargs['llm_model'] = model_override
|
||
return llm_kwargs, additional_fn, method
|
||
# 默认返回原参数
|
||
return llm_kwargs, additional_fn, method
|
||
|
||
def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot,
|
||
history:list=[], system_prompt:str='', stream:bool=True, additional_fn:str=None):
|
||
"""
|
||
发送至LLM，流式获取输出。
|
||
用于基础的对话功能。
|
||
|
||
完整参数列表：
|
||
predict(
|
||
inputs:str, # 是本次问询的输入
|
||
llm_kwargs:dict, # 是LLM的内部调优参数
|
||
plugin_kwargs:dict, # 是插件的内部参数
|
||
chatbot:ChatBotWithCookies, # 原样传递，负责向用户前端展示对话，兼顾前端状态的功能
|
||
history:list=[], # 是之前的对话列表
|
||
system_prompt:str='', # 系统静默prompt
|
||
stream:bool=True, # 是否流式输出（已弃用）
|
||
additional_fn:str=None # 基础功能区按钮的附加功能
|
||
):
|
||
"""
|
||
|
||
inputs = apply_gpt_academic_string_mask(inputs, mode="show_llm")
|
||
|
||
if llm_kwargs['llm_model'] not in model_info:
|
||
from toolbox import update_ui
|
||
chatbot.append([inputs, f"很抱歉，模型 '{llm_kwargs['llm_model']}' 暂不支持<br/>(1) 检查config中的AVAIL_LLM_MODELS选项<br/>(2) 检查request_llms/bridge_all.py中的模型路由"])
|
||
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
|
||
|
||
method = model_info[llm_kwargs['llm_model']]["fn_with_ui"] # 如果这里报错，检查config中的AVAIL_LLM_MODELS选项
|
||
|
||
if additional_fn: # 根据基础功能区 ModelOverride 参数调整模型类型
|
||
llm_kwargs, additional_fn, method = execute_model_override(llm_kwargs, additional_fn, method)
|
||
|
||
# 更新一下llm_kwargs的参数，否则会出现参数不匹配的问题
|
||
yield from method(inputs, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, stream, additional_fn)
|