Merge branch 'frontier' into production

这个提交包含在:
binary-husky
2023-11-11 14:09:39 +08:00
当前提交 9023aa6732
共有 14 个文件被更改,包括 286 次插入52 次删除

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@@ -139,7 +139,7 @@ git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss #
参考wikihttps://github.com/binary-husky/gpt_academic/wiki/%E9%80%82%E9%85%8DRWKV-Runner
# 【可选步骤IV】确保config.py配置文件的AVAIL_LLM_MODELS包含了期望的模型,目前支持的全部模型如下(jittorllms系列目前仅支持docker方案)
AVAIL_LLM_MODELS = ["gpt-3.5-turbo", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm", "newbing", "moss"] # + ["jittorllms_rwkv", "jittorllms_pangualpha", "jittorllms_llama"]
AVAIL_LLM_MODELS = ["gpt-3.5-turbo", "api2d-gpt-3.5-turbo", "gpt-4", "api2d-gpt-4", "chatglm", "moss"] # + ["jittorllms_rwkv", "jittorllms_pangualpha", "jittorllms_llama"]
```
</p>

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@@ -87,7 +87,8 @@ DEFAULT_FN_GROUPS = ['对话', '编程', '学术', '智能体']
# 模型选择是 (注意: LLM_MODEL是默认选中的模型, 它*必须*被包含在AVAIL_LLM_MODELS列表中 )
LLM_MODEL = "gpt-3.5-turbo" # 可选 ↓↓↓
AVAIL_LLM_MODELS = ["gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5",
AVAIL_LLM_MODELS = ["gpt-3.5-turbo-1106","gpt-4-1106-preview",
"gpt-3.5-turbo-16k", "gpt-3.5-turbo", "azure-gpt-3.5",
"api2d-gpt-3.5-turbo", 'api2d-gpt-3.5-turbo-16k',
"gpt-4", "gpt-4-32k", "azure-gpt-4", "api2d-gpt-4",
"chatglm3", "moss", "newbing", "claude-2"]

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@@ -349,18 +349,40 @@ def get_crazy_functions():
print('Load function plugin failed')
try:
from crazy_functions.图片生成 import 图片生成
from crazy_functions.图片生成 import 图片生成_DALLE2, 图片生成_DALLE3, 图片修改_DALLE2
function_plugins.update({
"图片生成先切换模型到openai或api2d": {
"图片生成_DALLE2先切换模型到openai或api2d": {
"Group": "对话",
"Color": "stop",
"AsButton": False,
"AdvancedArgs": True, # 调用时,唤起高级参数输入区默认False
"ArgsReminder": "在这里输入分辨率, 如256x256默认", # 高级参数输入区的显示提示
"Info": "图片生成 | 输入参数字符串,提供图像的内容",
"Function": HotReload(图片生成)
"ArgsReminder": "在这里输入分辨率, 如1024x1024默认,支持 256x256, 512x512, 1024x1024", # 高级参数输入区的显示提示
"Info": "使用DALLE2生成图片 | 输入参数字符串,提供图像的内容",
"Function": HotReload(图片生成_DALLE2)
},
})
function_plugins.update({
"图片生成_DALLE3先切换模型到openai或api2d": {
"Group": "对话",
"Color": "stop",
"AsButton": False,
"AdvancedArgs": True, # 调用时,唤起高级参数输入区默认False
"ArgsReminder": "在这里输入分辨率, 如1024x1024默认,支持 1024x1024, 1792x1024, 1024x1792", # 高级参数输入区的显示提示
"Info": "使用DALLE3生成图片 | 输入参数字符串,提供图像的内容",
"Function": HotReload(图片生成_DALLE3)
},
})
# function_plugins.update({
# "图片修改_DALLE2启动DALLE2图像修改向导程序": {
# "Group": "对话",
# "Color": "stop",
# "AsButton": False,
# "AdvancedArgs": True, # 调用时,唤起高级参数输入区默认False
# "ArgsReminder": "在这里输入分辨率, 如1024x1024默认,支持 1024x1024, 1792x1024, 1024x1792", # 高级参数输入区的显示提示
# # "Info": "使用DALLE2修改图片 | 输入参数字符串,提供图像的内容",
# "Function": HotReload(图片修改_DALLE2)
# },
# })
except:
print('Load function plugin failed')

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@@ -748,7 +748,7 @@ class nougat_interface():
yield from update_ui_lastest_msg("正在解析论文, 请稍候。进度正在加载NOUGAT... 提示首次运行需要花费较长时间下载NOUGAT参数",
chatbot=chatbot, history=history, delay=0)
self.nougat_with_timeout(f'nougat --out "{os.path.abspath(dst)}" "{os.path.abspath(fp)}"', os.getcwd(), timeout=3600)
self.nougat_with_timeout(f'nougat --out "{os.path.abspath(dst)}" "{os.path.abspath(fp)}" --recompute --no-skipping --markdown --batchsize 8', os.getcwd(), timeout=3600)
res = glob.glob(os.path.join(dst,'*.mmd'))
if len(res) == 0:
self.threadLock.release()

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@@ -0,0 +1,45 @@
from pydantic import BaseModel, Field
from typing import List
from toolbox import update_ui_lastest_msg, disable_auto_promotion
from request_llms.bridge_all import predict_no_ui_long_connection
from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
import time
import pickle
def have_any_recent_upload_files(chatbot):
_5min = 5 * 60
if not chatbot: return False # chatbot is None
most_recent_uploaded = chatbot._cookies.get("most_recent_uploaded", None)
if not most_recent_uploaded: return False # most_recent_uploaded is None
if time.time() - most_recent_uploaded["time"] < _5min: return True # most_recent_uploaded is new
else: return False # most_recent_uploaded is too old
class GptAcademicState():
def __init__(self):
self.reset()
def reset(self):
pass
def lock_plugin(self, chatbot):
chatbot._cookies['plugin_state'] = pickle.dumps(self)
def unlock_plugin(self, chatbot):
self.reset()
chatbot._cookies['plugin_state'] = pickle.dumps(self)
def set_state(self, chatbot, key, value):
setattr(self, key, value)
chatbot._cookies['plugin_state'] = pickle.dumps(self)
def get_state(chatbot, cls=None):
state = chatbot._cookies.get('plugin_state', None)
if state is not None: state = pickle.loads(state)
elif cls is not None: state = cls()
else: state = GptAcademicState()
state.chatbot = chatbot
return state
class GatherMaterials():
def __init__(self, materials) -> None:
materials = ['image', 'prompt']

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@@ -1,9 +1,8 @@
from toolbox import CatchException, update_ui, get_conf, select_api_key, get_log_folder
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
import datetime
from crazy_functions.multi_stage.multi_stage_utils import GptAcademicState
def gen_image(llm_kwargs, prompt, resolution="256x256"):
def gen_image(llm_kwargs, prompt, resolution="1024x1024", model="dall-e-2"):
import requests, json, time, os
from request_llms.bridge_all import model_info
@@ -23,6 +22,7 @@ def gen_image(llm_kwargs, prompt, resolution="256x256"):
'prompt': prompt,
'n': 1,
'size': resolution,
'model': model,
'response_format': 'url'
}
response = requests.post(url, headers=headers, json=data, proxies=proxies)
@@ -42,9 +42,48 @@ def gen_image(llm_kwargs, prompt, resolution="256x256"):
return image_url, file_path+file_name
def edit_image(llm_kwargs, prompt, image_path, resolution="1024x1024", model="dall-e-2"):
import requests, json, time, os
from request_llms.bridge_all import model_info
proxies = get_conf('proxies')
api_key = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model'])
chat_endpoint = model_info[llm_kwargs['llm_model']]['endpoint']
# 'https://api.openai.com/v1/chat/completions'
img_endpoint = chat_endpoint.replace('chat/completions','images/edits')
# # Generate the image
url = img_endpoint
headers = {
'Authorization': f"Bearer {api_key}",
'Content-Type': 'application/json'
}
data = {
'image': open(image_path, 'rb'),
'prompt': prompt,
'n': 1,
'size': resolution,
'model': model,
'response_format': 'url'
}
response = requests.post(url, headers=headers, json=data, proxies=proxies)
print(response.content)
try:
image_url = json.loads(response.content.decode('utf8'))['data'][0]['url']
except:
raise RuntimeError(response.content.decode())
# 文件保存到本地
r = requests.get(image_url, proxies=proxies)
file_path = f'{get_log_folder()}/image_gen/'
os.makedirs(file_path, exist_ok=True)
file_name = 'Image' + time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.png'
with open(file_path+file_name, 'wb+') as f: f.write(r.content)
return image_url, file_path+file_name
@CatchException
def 图片生成(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
def 图片生成_DALLE2(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
"""
txt 输入栏用户输入的文本,例如需要翻译的一段话,再例如一个包含了待处理文件的路径
llm_kwargs gpt模型参数,如温度和top_p等,一般原样传递下去就行
@@ -58,7 +97,7 @@ def 图片生成(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
chatbot.append(("这是什么功能?", "[Local Message] 生成图像, 请先把模型切换至gpt-*或者api2d-*。如果中文效果不理想, 请尝试英文Prompt。正在处理中 ....."))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间,我们先及时地做一次界面更新
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
resolution = plugin_kwargs.get("advanced_arg", '256x256')
resolution = plugin_kwargs.get("advanced_arg", '1024x1024')
image_url, image_path = gen_image(llm_kwargs, prompt, resolution)
chatbot.append([prompt,
f'图像中转网址: <br/>`{image_url}`<br/>'+
@@ -67,3 +106,92 @@ def 图片生成(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
f'本地文件预览: <br/><div align="center"><img src="file={image_path}"></div>'
])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
@CatchException
def 图片生成_DALLE3(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
history = [] # 清空历史,以免输入溢出
chatbot.append(("这是什么功能?", "[Local Message] 生成图像, 请先把模型切换至gpt-*或者api2d-*。如果中文效果不理想, 请尝试英文Prompt。正在处理中 ....."))
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 由于请求gpt需要一段时间,我们先及时地做一次界面更新
if ("advanced_arg" in plugin_kwargs) and (plugin_kwargs["advanced_arg"] == ""): plugin_kwargs.pop("advanced_arg")
resolution = plugin_kwargs.get("advanced_arg", '1024x1024')
image_url, image_path = gen_image(llm_kwargs, prompt, resolution)
chatbot.append([prompt,
f'图像中转网址: <br/>`{image_url}`<br/>'+
f'中转网址预览: <br/><div align="center"><img src="{image_url}"></div>'
f'本地文件地址: <br/>`{image_path}`<br/>'+
f'本地文件预览: <br/><div align="center"><img src="file={image_path}"></div>'
])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
class ImageEditState(GptAcademicState):
def get_image_file(self, x):
import os, glob
if len(x) == 0: return False, None
if not os.path.exists(x): return False, None
if x.endswith('.png'): return True, x
file_manifest = [f for f in glob.glob(f'{x}/**/*.png', recursive=True)]
confirm = (len(file_manifest) >= 1 and file_manifest[0].endswith('.png') and os.path.exists(file_manifest[0]))
file = None if not confirm else file_manifest[0]
return confirm, file
def get_resolution(self, x):
return (x in ['256x256', '512x512', '1024x1024']), x
def get_prompt(self, x):
confirm = (len(x)>=5) and (not self.get_resolution(x)[0]) and (not self.get_image_file(x)[0])
return confirm, x
def reset(self):
self.req = [
{'value':None, 'description': '请先上传图像(必须是.png格式, 然后再次点击本插件', 'verify_fn': self.get_image_file},
{'value':None, 'description': '请输入分辨率,可选256x256, 512x512 或 1024x1024', 'verify_fn': self.get_resolution},
{'value':None, 'description': '请输入修改需求,建议您使用英文提示词', 'verify_fn': self.get_prompt},
]
self.info = ""
def feed(self, prompt, chatbot):
for r in self.req:
if r['value'] is None:
confirm, res = r['verify_fn'](prompt)
if confirm:
r['value'] = res
self.set_state(chatbot, 'dummy_key', 'dummy_value')
break
return self
def next_req(self):
for r in self.req:
if r['value'] is None:
return r['description']
return "已经收集到所有信息"
def already_obtained_all_materials(self):
return all([x['value'] is not None for x in self.req])
@CatchException
def 图片修改_DALLE2(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
history = [] # 清空历史
state = ImageEditState.get_state(chatbot, ImageEditState)
state = state.feed(prompt, chatbot)
if not state.already_obtained_all_materials():
chatbot.append(["图片修改(先上传图片,再输入修改需求,最后输入分辨率)", state.next_req()])
yield from update_ui(chatbot=chatbot, history=history)
return
image_path = state.req[0]
resolution = state.req[1]
prompt = state.req[2]
chatbot.append(["图片修改, 执行中", f"图片:`{image_path}`<br/>分辨率:`{resolution}`<br/>修改需求:`{prompt}`"])
yield from update_ui(chatbot=chatbot, history=history)
image_url, image_path = edit_image(llm_kwargs, prompt, image_path, resolution)
chatbot.append([state.prompt,
f'图像中转网址: <br/>`{image_url}`<br/>'+
f'中转网址预览: <br/><div align="center"><img src="{image_url}"></div>'
f'本地文件地址: <br/>`{image_path}`<br/>'+
f'本地文件预览: <br/><div align="center"><img src="file={image_path}"></div>'
])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新

查看文件

@@ -19,6 +19,11 @@ from crazy_functions.agent_fns.persistent import GradioMultiuserManagerForPersis
from crazy_functions.agent_fns.auto_agent import AutoGenMath
import time
def remove_model_prefix(llm):
if llm.startswith('api2d-'): llm = llm.replace('api2d-', '')
if llm.startswith('azure-'): llm = llm.replace('azure-', '')
return llm
@CatchException
def 多智能体终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
@@ -32,10 +37,16 @@ def 多智能体终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
web_port 当前软件运行的端口号
"""
# 检查当前的模型是否符合要求
supported_llms = ['gpt-3.5-turbo-16k', 'gpt-4', 'gpt-4-32k',
'api2d-gpt-3.5-turbo-16k', 'api2d-gpt-4']
supported_llms = [
'gpt-3.5-16k',
'gpt-3.5-turbo-16k',
'gpt-3.5-turbo-1106',
'gpt-4',
'gpt-4-32k',
'gpt-4-1106-preview',
]
llm_kwargs['api_key'] = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model'])
if llm_kwargs['llm_model'] not in supported_llms:
if remove_model_prefix(llm_kwargs['llm_model']) not in supported_llms:
chatbot.append([f"处理任务: {txt}", f"当前插件只支持{str(supported_llms)}, 当前模型{llm_kwargs['llm_model']}."])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return

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@@ -57,22 +57,27 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
"批量翻译PDF文档。函数插件贡献者: Binary-Husky"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# 尝试导入依赖,如果缺少依赖,则给出安装建议
try:
import nougat
import tiktoken
except:
report_execption(chatbot, history,
a=f"解析项目: {txt}",
b=f"导入软件依赖失败。使用该模块需要额外依赖,安装方法```pip install --upgrade nougat-ocr tiktoken```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
# 清空历史,以免输入溢出
history = []
from .crazy_utils import get_files_from_everything
success, file_manifest, project_folder = get_files_from_everything(txt, type='.pdf')
if len(file_manifest) > 0:
# 尝试导入依赖,如果缺少依赖,则给出安装建议
try:
import nougat
import tiktoken
except:
report_execption(chatbot, history,
a=f"解析项目: {txt}",
b=f"导入软件依赖失败。使用该模块需要额外依赖,安装方法```pip install --upgrade nougat-ocr tiktoken```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
success_mmd, file_manifest_mmd, _ = get_files_from_everything(txt, type='.mmd')
success = success or success_mmd
file_manifest += file_manifest_mmd
chatbot.append(["文件列表:", ", ".join([e.split('/')[-1] for e in file_manifest])]);
yield from update_ui( chatbot=chatbot, history=history)
# 检测输入参数,如没有给定输入参数,直接退出
if not success:
if txt == "": txt = '空空如也的输入栏'
@@ -101,9 +106,13 @@ def 解析PDF_基于NOUGAT(file_manifest, project_folder, llm_kwargs, plugin_kwa
from crazy_functions.pdf_fns.report_gen_html import construct_html
nougat_handle = nougat_interface()
for index, fp in enumerate(file_manifest):
chatbot.append(["当前进度:", f"正在解析论文,请稍候。第一次运行时,需要花费较长时间下载NOUGAT参数"]); yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
fpp = yield from nougat_handle.NOUGAT_parse_pdf(fp, chatbot, history)
promote_file_to_downloadzone(fpp, rename_file=os.path.basename(fpp)+'.nougat.mmd', chatbot=chatbot)
if fp.endswith('pdf'):
chatbot.append(["当前进度:", f"正在解析论文,请稍候。第一次运行时,需要花费较长时间下载NOUGAT参数"]); yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
fpp = yield from nougat_handle.NOUGAT_parse_pdf(fp, chatbot, history)
promote_file_to_downloadzone(fpp, rename_file=os.path.basename(fpp)+'.nougat.mmd', chatbot=chatbot)
else:
chatbot.append(["当前论文无需解析:", fp]); yield from update_ui( chatbot=chatbot, history=history)
fpp = fp
with open(fpp, 'r', encoding='utf8') as f:
article_content = f.readlines()
article_dict = markdown_to_dict(article_content)

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@@ -265,7 +265,7 @@
"例如chatglm&gpt-3.5-turbo&api2d-gpt-4": "e.g. chatglm&gpt-3.5-turbo&api2d-gpt-4",
"先切换模型到openai或api2d": "Switch the model to openai or api2d first",
"在这里输入分辨率": "Enter the resolution here",
"如256x256": "e.g. 256x256",
"如1024x1024": "e.g. 1024x1024",
"默认": "Default",
"建议您复制一个config_private.py放自己的秘密": "We suggest you to copy a config_private.py file to keep your secrets, such as API and proxy URLs, from being accidentally uploaded to Github and seen by others.",
"如API和代理网址": "Such as API and proxy URLs",

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@@ -854,7 +854,7 @@
"查询版本和用户意见": "バージョンとユーザーの意見を検索する",
"提取摘要": "要約を抽出する",
"在gpt输出代码的中途": "GPTがコードを出力する途中で",
"如256x256": "256x256のように",
"如1024x1024": "1024x1024のように",
"概括其内容": "内容を要約する",
"剩下的情况都开头除去": "残りの場合はすべて先頭を除去する",
"至少一个线程任务意外失败": "少なくとも1つのスレッドタスクが予期しない失敗をした",

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@@ -1147,7 +1147,7 @@
"Y+回车=确认": "Y+回車=確認",
"正在同时咨询ChatGPT和ChatGLM……": "正在同時諮詢ChatGPT和ChatGLM……",
"根据 heuristic 规则": "根據heuristic規則",
"如256x256": "如256x256",
"如1024x1024": "如1024x1024",
"函数插件区": "函數插件區",
"*** API_KEY 导入成功": "*** API_KEY 導入成功",
"请对下面的程序文件做一个概述文件名是": "請對下面的程序文件做一個概述文件名是",

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@@ -94,7 +94,7 @@ model_info = {
"fn_with_ui": chatgpt_ui,
"fn_without_ui": chatgpt_noui,
"endpoint": openai_endpoint,
"max_token": 1024*16,
"max_token": 16385,
"tokenizer": tokenizer_gpt35,
"token_cnt": get_token_num_gpt35,
},
@@ -112,7 +112,16 @@ model_info = {
"fn_with_ui": chatgpt_ui,
"fn_without_ui": chatgpt_noui,
"endpoint": openai_endpoint,
"max_token": 1024 * 16,
"max_token": 16385,
"tokenizer": tokenizer_gpt35,
"token_cnt": get_token_num_gpt35,
},
"gpt-3.5-turbo-1106": {#16k
"fn_with_ui": chatgpt_ui,
"fn_without_ui": chatgpt_noui,
"endpoint": openai_endpoint,
"max_token": 16385,
"tokenizer": tokenizer_gpt35,
"token_cnt": get_token_num_gpt35,
},
@@ -135,6 +144,15 @@ model_info = {
"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-3.5-random": {
"fn_with_ui": chatgpt_ui,
"fn_without_ui": chatgpt_noui,
@@ -159,11 +177,11 @@ model_info = {
"fn_without_ui": chatgpt_noui,
"endpoint": azure_endpoint,
"max_token": 8192,
"tokenizer": tokenizer_gpt35,
"token_cnt": get_token_num_gpt35,
"tokenizer": tokenizer_gpt4,
"token_cnt": get_token_num_gpt4,
},
# api_2d
# 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-3.5-turbo": {
"fn_with_ui": chatgpt_ui,
"fn_without_ui": chatgpt_noui,
@@ -182,15 +200,6 @@ model_info = {
"token_cnt": get_token_num_gpt4,
},
"api2d-gpt-3.5-turbo-16k": {
"fn_with_ui": chatgpt_ui,
"fn_without_ui": chatgpt_noui,
"endpoint": api2d_endpoint,
"max_token": 1024*16,
"tokenizer": tokenizer_gpt35,
"token_cnt": get_token_num_gpt35,
},
# 将 chatglm 直接对齐到 chatglm2
"chatglm": {
"fn_with_ui": chatglm_ui,
@@ -226,6 +235,13 @@ model_info = {
},
}
# -=-=-=-=-=-=- api2d 对齐支持 -=-=-=-=-=-=-
for model in AVAIL_LLM_MODELS:
if model.startswith('api2d-') and (model.replace('api2d-','') in model_info.keys()):
mi = model_info[model.replace('api2d-','')]
mi.update({"endpoint": api2d_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 -=-=-=-=-=-=-
if "claude-1-100k" in AVAIL_LLM_MODELS or "claude-2" in AVAIL_LLM_MODELS:
from .bridge_claude import predict_no_ui_long_connection as claude_noui

查看文件

@@ -359,6 +359,7 @@ def generate_payload(inputs, llm_kwargs, history, system_prompt, stream):
model = random.choice([
"gpt-3.5-turbo",
"gpt-3.5-turbo-16k",
"gpt-3.5-turbo-1106",
"gpt-3.5-turbo-0613",
"gpt-3.5-turbo-16k-0613",
"gpt-3.5-turbo-0301",

查看文件

@@ -625,13 +625,14 @@ def on_file_uploaded(request: gradio.Request, files, chatbot, txt, txt2, checkbo
def on_report_generated(cookies, files, chatbot):
from toolbox import find_recent_files
PATH_LOGGING = get_conf('PATH_LOGGING')
# from toolbox import find_recent_files
# PATH_LOGGING = get_conf('PATH_LOGGING')
if 'files_to_promote' in cookies:
report_files = cookies['files_to_promote']
cookies.pop('files_to_promote')
else:
report_files = find_recent_files(PATH_LOGGING)
report_files = []
# report_files = find_recent_files(PATH_LOGGING)
if len(report_files) == 0:
return cookies, None, chatbot
# files.extend(report_files)