16000
- io.wavfile.write(temp_file, NEW_SAMPLERATE, dsdata)
+ write_numpy_to_wave(temp_file, NEW_SAMPLERATE, dsdata)
# read pcm binary
with open(temp_file, "rb") as f: data = f.read()
- # print('audio len:', len(audio), '\t ds len:', len(dsdata), '\t need n send:', len(data)//640)
- slices = zip(*(iter(data),) * 640) # 640个字节为一组
- for i in slices: sr.send_audio(bytes(i))
+ is_speaking, info = is_speaker_speaking(vad, data, NEW_SAMPLERATE)
+
+ if is_speaking or echo_cnt > 0:
+ # 如果话筒激活 / 如果处于回声收尾阶段
+ echo_cnt -= 1
+ if not is_previous_frame_transmitted: # 上一帧没有人声，但是我们把上一帧同样加上
+ if previous_frame_data is not None: data = previous_frame_data + data
+ if is_speaking:
+ echo_cnt = echo_cnt_max
+ slices = zip(*(iter(data),) * 640) # 640个字节为一组
+ for i in slices: sr.send_audio(bytes(i))
+ keep_alive_last_send_time = time.time()
+ is_previous_frame_transmitted = True
+ else:
+ is_previous_frame_transmitted = False
+ echo_cnt = 0
+ # 保持链接激活，即使没有声音，也根据时间间隔，发送一些音频片段给服务器
+ if time.time() - keep_alive_last_send_time > timeout_limit_second/2:
+ slices = zip(*(iter(data),) * 640) # 640个字节为一组
+ for i in slices: sr.send_audio(bytes(i))
+ keep_alive_last_send_time = time.time()
+ is_previous_frame_transmitted = True
+ self.audio_shape = info
else:
time.sleep(0.1)
diff --git a/crazy_functions/live_audio/audio_io.py b/crazy_functions/live_audio/audio_io.py
index 3ff83a66e8d9f0bb15250f1c3c2b5ea36745ff55..00fd3f2d846ccf20eb300b796bb91842315e3482 100644
--- a/crazy_functions/live_audio/audio_io.py
+++ b/crazy_functions/live_audio/audio_io.py
@@ -35,7 +35,7 @@ class RealtimeAudioDistribution():
def read(self, uuid):
if uuid in self.data:
res = self.data.pop(uuid)
- print('\r read-', len(res), '-', max(res), end='', flush=True)
+ # print('\r read-', len(res), '-', max(res), end='', flush=True)
else:
res = None
return res
diff --git a/crazy_functions/multi_stage/multi_stage_utils.py b/crazy_functions/multi_stage/multi_stage_utils.py
new file mode 100644
index 0000000000000000000000000000000000000000..60f0778320463ade0e77438581d23cdf9ee176e2
--- /dev/null
+++ b/crazy_functions/multi_stage/multi_stage_utils.py
@@ -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']
\ No newline at end of file
diff --git a/crazy_functions/pdf_fns/parse_pdf.py b/crazy_functions/pdf_fns/parse_pdf.py
index a047efce291ea72a0c7aa6ce48158cd7095c4772..51f8811fc8f61500b4393466295574361658b7dd 100644
--- a/crazy_functions/pdf_fns/parse_pdf.py
+++ b/crazy_functions/pdf_fns/parse_pdf.py
@@ -14,7 +14,7 @@ import math
class GROBID_OFFLINE_EXCEPTION(Exception): pass
def get_avail_grobid_url():
- GROBID_URLS, = get_conf('GROBID_URLS')
+ GROBID_URLS = get_conf('GROBID_URLS')
if len(GROBID_URLS) == 0: return None
try:
_grobid_url = random.choice(GROBID_URLS) # 随机负载均衡
@@ -73,7 +73,7 @@ def produce_report_markdown(gpt_response_collection, meta, paper_meta_info, chat
return res_path
def translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_files, TOKEN_LIMIT_PER_FRAGMENT, DST_LANG):
- from crazy_functions.crazy_utils import construct_html
+ from crazy_functions.pdf_fns.report_gen_html import construct_html
from crazy_functions.crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
from crazy_functions.crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_and_high_efficiency
@@ -82,7 +82,7 @@ def translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_fi
# title
title = article_dict.get('title', '无法获取 title'); prompt += f'title:{title}\n\n'
# authors
- authors = article_dict.get('authors', '无法获取 authors'); prompt += f'authors:{authors}\n\n'
+ authors = article_dict.get('authors', '无法获取 authors')[:100]; prompt += f'authors:{authors}\n\n'
# abstract
abstract = article_dict.get('abstract', '无法获取 abstract'); prompt += f'abstract:{abstract}\n\n'
# command
@@ -103,7 +103,7 @@ def translate_pdf(article_dict, llm_kwargs, chatbot, fp, generated_conclusion_fi
inputs_show_user_array = []
# get_token_num
- from request_llm.bridge_all import model_info
+ from request_llms.bridge_all import model_info
enc = model_info[llm_kwargs['llm_model']]['tokenizer']
def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
diff --git a/crazy_functions/pdf_fns/report_gen_html.py b/crazy_functions/pdf_fns/report_gen_html.py
new file mode 100644
index 0000000000000000000000000000000000000000..21829212ff13a2dfd1492f05ac9abc73907dce7b
--- /dev/null
+++ b/crazy_functions/pdf_fns/report_gen_html.py
@@ -0,0 +1,58 @@
+from toolbox import update_ui, get_conf, trimmed_format_exc, get_log_folder
+import os
+
+
+
+
+class construct_html():
+ def __init__(self) -> None:
+ self.html_string = ""
+
+ def add_row(self, a, b):
+ from toolbox import markdown_convertion
+ template = """
+ {
+ primary_col: {
+ header: String.raw`__PRIMARY_HEADER__`,
+ msg: String.raw`__PRIMARY_MSG__`,
+ },
+ secondary_rol: {
+ header: String.raw`__SECONDARY_HEADER__`,
+ msg: String.raw`__SECONDARY_MSG__`,
+ }
+ },
+ """
+ def std(str):
+ str = str.replace(r'`',r'`')
+ if str.endswith("\\"): str += ' '
+ if str.endswith("}"): str += ' '
+ if str.endswith("$"): str += ' '
+ return str
+
+ template_ = template
+ a_lines = a.split('\n')
+ b_lines = b.split('\n')
+
+ if len(a_lines) == 1 or len(a_lines[0]) > 50:
+ template_ = template_.replace("__PRIMARY_HEADER__", std(a[:20]))
+ template_ = template_.replace("__PRIMARY_MSG__", std(markdown_convertion(a)))
+ else:
+ template_ = template_.replace("__PRIMARY_HEADER__", std(a_lines[0]))
+ template_ = template_.replace("__PRIMARY_MSG__", std(markdown_convertion('\n'.join(a_lines[1:]))))
+
+ if len(b_lines) == 1 or len(b_lines[0]) > 50:
+ template_ = template_.replace("__SECONDARY_HEADER__", std(b[:20]))
+ template_ = template_.replace("__SECONDARY_MSG__", std(markdown_convertion(b)))
+ else:
+ template_ = template_.replace("__SECONDARY_HEADER__", std(b_lines[0]))
+ template_ = template_.replace("__SECONDARY_MSG__", std(markdown_convertion('\n'.join(b_lines[1:]))))
+ self.html_string += template_
+
+ def save_file(self, file_name):
+ from toolbox import get_log_folder
+ with open('crazy_functions/pdf_fns/report_template.html', 'r', encoding='utf8') as f:
+ html_template = f.read()
+ html_template = html_template.replace("__TF_ARR__", self.html_string)
+ with open(os.path.join(get_log_folder(), file_name), 'w', encoding='utf8') as f:
+ f.write(html_template.encode('utf-8', 'ignore').decode())
+ return os.path.join(get_log_folder(), file_name)
diff --git a/crazy_functions/pdf_fns/report_template.html b/crazy_functions/pdf_fns/report_template.html
new file mode 100644
index 0000000000000000000000000000000000000000..39a1e7ce482949978ff90c4738a9adb8803660e6
--- /dev/null
+++ b/crazy_functions/pdf_fns/report_template.html
@@ -0,0 +1,104 @@
+
+
+
+
+
+ __TITLE__
+
+
+
+
+
+
+
+
+
diff --git a/crazy_functions/vt_fns/vt_call_plugin.py b/crazy_functions/vt_fns/vt_call_plugin.py
index 455ac88bc0d7861441301c37490181181243a59a..f33644d9ad61c29c6809198a4b0d7466a9d98e48 100644
--- a/crazy_functions/vt_fns/vt_call_plugin.py
+++ b/crazy_functions/vt_fns/vt_call_plugin.py
@@ -1,7 +1,7 @@
from pydantic import BaseModel, Field
from typing import List
from toolbox import update_ui_lastest_msg, disable_auto_promotion
-from request_llm.bridge_all import predict_no_ui_long_connection
+from request_llms.bridge_all import predict_no_ui_long_connection
from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
import copy, json, pickle, os, sys, time
diff --git a/crazy_functions/vt_fns/vt_modify_config.py b/crazy_functions/vt_fns/vt_modify_config.py
index e7fd745c3dc2ee1cf260ac2ac97a053b2985d4c8..58a8531e8ef8fff970ecc002ae2a0c71ec313a1d 100644
--- a/crazy_functions/vt_fns/vt_modify_config.py
+++ b/crazy_functions/vt_fns/vt_modify_config.py
@@ -1,13 +1,13 @@
from pydantic import BaseModel, Field
from typing import List
from toolbox import update_ui_lastest_msg, get_conf
-from request_llm.bridge_all import predict_no_ui_long_connection
+from request_llms.bridge_all import predict_no_ui_long_connection
from crazy_functions.json_fns.pydantic_io import GptJsonIO
import copy, json, pickle, os, sys
def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
- ALLOW_RESET_CONFIG, = get_conf('ALLOW_RESET_CONFIG')
+ ALLOW_RESET_CONFIG = get_conf('ALLOW_RESET_CONFIG')
if not ALLOW_RESET_CONFIG:
yield from update_ui_lastest_msg(
lastmsg=f"当前配置不允许被修改！如需激活本功能，请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件。",
@@ -66,7 +66,7 @@ def modify_configuration_hot(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
)
def modify_configuration_reboot(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, user_intention):
- ALLOW_RESET_CONFIG, = get_conf('ALLOW_RESET_CONFIG')
+ ALLOW_RESET_CONFIG = get_conf('ALLOW_RESET_CONFIG')
if not ALLOW_RESET_CONFIG:
yield from update_ui_lastest_msg(
lastmsg=f"当前配置不允许被修改！如需激活本功能，请在config.py中设置ALLOW_RESET_CONFIG=True后重启软件。",
diff --git "a/crazy_functions/\344\270\213\350\275\275arxiv\350\256\272\346\226\207\347\277\273\350\257\221\346\221\230\350\246\201.py" "b/crazy_functions/\344\270\213\350\275\275arxiv\350\256\272\346\226\207\347\277\273\350\257\221\346\221\230\350\246\201.py"
index 8b4a5037a21d326ddcdcc7ee5dd6082d949c5a55..1e0fe63052b64503f219370bcb51b8aeba18f155 100644
--- "a/crazy_functions/\344\270\213\350\275\275arxiv\350\256\272\346\226\207\347\277\273\350\257\221\346\221\230\350\246\201.py"
+++ "b/crazy_functions/\344\270\213\350\275\275arxiv\350\256\272\346\226\207\347\277\273\350\257\221\346\221\230\350\246\201.py"
@@ -1,6 +1,6 @@
from toolbox import update_ui, get_log_folder
from toolbox import write_history_to_file, promote_file_to_downloadzone
-from toolbox import CatchException, report_execption, get_conf
+from toolbox import CatchException, report_exception, get_conf
import re, requests, unicodedata, os
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
def download_arxiv_(url_pdf):
@@ -43,7 +43,7 @@ def download_arxiv_(url_pdf):
file_path = download_dir+title_str
print('下载中')
- proxies, = get_conf('proxies')
+ proxies = get_conf('proxies')
r = requests.get(requests_pdf_url, proxies=proxies)
with open(file_path, 'wb+') as f:
f.write(r.content)
@@ -77,7 +77,7 @@ def get_name(_url_):
# print('在缓存中')
# return arxiv_recall[_url_]
- proxies, = get_conf('proxies')
+ proxies = get_conf('proxies')
res = requests.get(_url_, proxies=proxies)
bs = BeautifulSoup(res.text, 'html.parser')
@@ -144,7 +144,7 @@ def 下载arxiv论文并翻译摘要(txt, llm_kwargs, plugin_kwargs, chatbot, hi
try:
import bs4
except:
- report_execption(chatbot, history,
+ report_exception(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 beautifulsoup4```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
@@ -157,7 +157,7 @@ def 下载arxiv论文并翻译摘要(txt, llm_kwargs, plugin_kwargs, chatbot, hi
try:
pdf_path, info = download_arxiv_(txt)
except:
- report_execption(chatbot, history,
+ report_exception(chatbot, history,
a = f"解析项目: {txt}",
b = f"下载pdf文件未成功")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
diff --git "a/crazy_functions/\345\233\276\347\211\207\347\224\237\346\210\220.py" "b/crazy_functions/\345\233\276\347\211\207\347\224\237\346\210\220.py"
index 51a1baff54281c395e63a008581eabc04565ce2f..642a9e225a06e1fac8e79af41df8b02af4310fa8 100644
--- "a/crazy_functions/\345\233\276\347\211\207\347\224\237\346\210\220.py"
+++ "b/crazy_functions/\345\233\276\347\211\207\347\224\237\346\210\220.py"
@@ -1,13 +1,12 @@
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", quality=None):
import requests, json, time, os
- from request_llm.bridge_all import model_info
+ from request_llms.bridge_all import model_info
- proxies, = get_conf('proxies')
+ proxies = get_conf('proxies')
# Set up OpenAI API key and model
api_key = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model'])
chat_endpoint = model_info[llm_kwargs['llm_model']]['endpoint']
@@ -23,8 +22,10 @@ def gen_image(llm_kwargs, prompt, resolution="256x256"):
'prompt': prompt,
'n': 1,
'size': resolution,
+ 'model': model,
'response_format': 'url'
}
+ if quality is not None: data.update({'quality': quality})
response = requests.post(url, headers=headers, json=data, proxies=proxies)
print(response.content)
try:
@@ -42,23 +43,62 @@ 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
- plugin_kwargs 插件模型的参数，暂时没有用武之地
- chatbot 聊天显示框的句柄，用于显示给用户
- history 聊天历史，前情提要
+ 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
+ plugin_kwargs 插件模型的参数,暂时没有用武之地
+ chatbot 聊天显示框的句柄,用于显示给用户
+ history 聊天历史,前情提要
system_prompt 给gpt的静默提醒
web_port 当前软件运行的端口号
"""
- 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
+ history = [] # 清空历史,以免输入溢出
+ chatbot.append(("您正在调用“图像生成”插件。", "[Local Message] 生成图像, 请先把模型切换至gpt-*或者api2d-*。如果中文Prompt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:
`{image_url}`
'+
@@ -66,4 +106,99 @@ def 图片生成(prompt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
f'本地文件地址:
`{image_path}`
'+
f'本地文件预览:
'
])
- yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 # 界面更新
+ 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(("您正在调用“图像生成”插件。", "[Local Message] 生成图像, 请先把模型切换至gpt-*或者api2d-*。如果中文Prompt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').lower()
+ if resolution.endswith('-hd'):
+ resolution = resolution.replace('-hd', '')
+ quality = 'hd'
+ else:
+ quality = 'standard'
+ image_url, image_path = gen_image(llm_kwargs, prompt, resolution, model="dall-e-3", quality=quality)
+ chatbot.append([prompt,
+ f'图像中转网址:
`{image_url}`
'+
+ f'中转网址预览:
'
+ f'本地文件地址:
`{image_path}`
'+
+ f'本地文件预览:
'
+ ])
+ yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 界面更新
+
+class ImageEditState(GptAcademicState):
+ # 尚未完成
+ 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):
+ # 尚未完成
+ 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}`
分辨率:`{resolution}`
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:
`{image_url}`
'+
+ f'中转网址预览:
'
+ f'本地文件地址:
`{image_path}`
'+
+ f'本地文件预览:
'
+ ])
+ yield from update_ui(chatbot=chatbot, history=history) # 刷新界面 界面更新
+
diff --git "a/crazy_functions/\345\244\232\346\231\272\350\203\275\344\275\223.py" "b/crazy_functions/\345\244\232\346\231\272\350\203\275\344\275\223.py"
new file mode 100644
index 0000000000000000000000000000000000000000..d2adee00866b12a771ce0704cd8917d7969a3f0b
--- /dev/null
+++ "b/crazy_functions/\345\244\232\346\231\272\350\203\275\344\275\223.py"
@@ -0,0 +1,108 @@
+# 本源代码中, ⭐ = 关键步骤
+"""
+测试：
+ - show me the solution of $x^2=cos(x)$, solve this problem with figure, and plot and save image to t.jpg
+
+"""
+
+
+from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, ProxyNetworkActivate
+from toolbox import get_conf, select_api_key, update_ui_lastest_msg, Singleton
+from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_plugin_arg
+from crazy_functions.crazy_utils import input_clipping, try_install_deps
+from crazy_functions.agent_fns.persistent import GradioMultiuserManagerForPersistentClasses
+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):
+ """
+ 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
+ plugin_kwargs 插件模型的参数
+ chatbot 聊天显示框的句柄，用于显示给用户
+ history 聊天历史，前情提要
+ system_prompt 给gpt的静默提醒
+ 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-3.5-turbo-1106',
+ "gpt-4",
+ "gpt-4-32k",
+ 'gpt-4-1106-preview',
+ "azure-gpt-3.5-turbo-16k",
+ "azure-gpt-3.5-16k",
+ "azure-gpt-4",
+ "azure-gpt-4-32k",
+ ]
+ from request_llms.bridge_all import model_info
+ if model_info[llm_kwargs['llm_model']]["max_token"] < 8000: # 至少是8k上下文的模型
+ 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']}的最大上下文长度太短, 不能支撑AutoGen运行。"])
+ yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+ return
+ if model_info[llm_kwargs['llm_model']]["endpoint"] is not None: # 如果不是本地模型，加载API_KEY
+ llm_kwargs['api_key'] = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model'])
+
+ # 检查当前的模型是否符合要求
+ API_URL_REDIRECT = get_conf('API_URL_REDIRECT')
+ if len(API_URL_REDIRECT) > 0:
+ chatbot.append([f"处理任务: {txt}", f"暂不支持中转."])
+ yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+ return
+
+ # 尝试导入依赖，如果缺少依赖，则给出安装建议
+ try:
+ import autogen
+ if get_conf("AUTOGEN_USE_DOCKER"):
+ import docker
+ except:
+ chatbot.append([ f"处理任务: {txt}",
+ 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 pyautogen docker```。"])
+ yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+ return
+
+ # 尝试导入依赖，如果缺少依赖，则给出安装建议
+ try:
+ import autogen
+ import glob, os, time, subprocess
+ if get_conf("AUTOGEN_USE_DOCKER"):
+ subprocess.Popen(["docker", "--version"])
+ except:
+ chatbot.append([f"处理任务: {txt}", f"缺少docker运行环境！"])
+ yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+ return
+
+ # 解锁插件
+ chatbot.get_cookies()['lock_plugin'] = None
+ persistent_class_multi_user_manager = GradioMultiuserManagerForPersistentClasses()
+ user_uuid = chatbot.get_cookies().get('uuid')
+ persistent_key = f"{user_uuid}->多智能体终端"
+ if persistent_class_multi_user_manager.already_alive(persistent_key):
+ # 当已经存在一个正在运行的多智能体终端时，直接将用户输入传递给它，而不是再次启动一个新的多智能体终端
+ print('[debug] feed new user input')
+ executor = persistent_class_multi_user_manager.get(persistent_key)
+ exit_reason = yield from executor.main_process_ui_control(txt, create_or_resume="resume")
+ else:
+ # 运行多智能体终端 (首次)
+ print('[debug] create new executor instance')
+ history = []
+ chatbot.append(["正在启动: 多智能体终端", "插件动态生成, 执行开始, 作者 Microsoft & Binary-Husky."])
+ yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+ executor = AutoGenMath(llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port)
+ persistent_class_multi_user_manager.set(persistent_key, executor)
+ exit_reason = yield from executor.main_process_ui_control(txt, create_or_resume="create")
+
+ if exit_reason == "wait_feedback":
+ # 当用户点击了“等待反馈”按钮时，将executor存储到cookie中，等待用户的再次调用
+ executor.chatbot.get_cookies()['lock_plugin'] = 'crazy_functions.多智能体->多智能体终端'
+ else:
+ executor.chatbot.get_cookies()['lock_plugin'] = None
+ yield from update_ui(chatbot=executor.chatbot, history=executor.history) # 更新状态
diff --git "a/crazy_functions/\345\257\271\350\257\235\345\216\206\345\217\262\345\255\230\346\241\243.py" "b/crazy_functions/\345\257\271\350\257\235\345\216\206\345\217\262\345\255\230\346\241\243.py"
index f89faeda27786afad2c246148601d3148dd44ea5..3f603f9b828d066ab003457d001380f66fa974a9 100644
--- "a/crazy_functions/\345\257\271\350\257\235\345\216\206\345\217\262\345\255\230\346\241\243.py"
+++ "b/crazy_functions/\345\257\271\350\257\235\345\216\206\345\217\262\345\255\230\346\241\243.py"
@@ -1,7 +1,8 @@
-from toolbox import CatchException, update_ui, promote_file_to_downloadzone, get_log_folder
-from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
+from toolbox import CatchException, update_ui, promote_file_to_downloadzone, get_log_folder, get_user
import re
+f_prefix = 'GPT-Academic对话存档'
+
def write_chat_to_file(chatbot, history=None, file_name=None):
"""
将对话记录history以Markdown格式写入文件中。如果没有指定文件名，则使用当前时间生成文件名。
@@ -9,8 +10,8 @@ def write_chat_to_file(chatbot, history=None, file_name=None):
import os
import time
if file_name is None:
- file_name = 'chatGPT对话历史' + time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.html'
- fp = os.path.join(get_log_folder(), file_name)
+ file_name = f_prefix + time.strftime("%Y-%m-%d-%H-%M-%S", time.localtime()) + '.html'
+ fp = os.path.join(get_log_folder(get_user(chatbot), plugin_name='chat_history'), file_name)
with open(fp, 'w', encoding='utf8') as f:
from themes.theme import advanced_css
f.write(f'对话历史')
@@ -80,7 +81,7 @@ def 对话历史存档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
"""
chatbot.append(("保存当前对话",
- f"[Local Message] {write_chat_to_file(chatbot, history)}，您可以调用“载入对话历史存档”还原当下的对话。\n警告！被保存的对话历史可以被使用该系统的任何人查阅。"))
+ f"[Local Message] {write_chat_to_file(chatbot, history)}，您可以调用下拉菜单中的“载入对话历史存档”还原当下的对话。"))
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
def hide_cwd(str):
@@ -106,7 +107,12 @@ def 载入对话历史存档(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
if not success:
if txt == "": txt = '空空如也的输入栏'
import glob
- local_history = "
".join(["`"+hide_cwd(f)+f" ({gen_file_preview(f)})"+"`" for f in glob.glob(f'{get_log_folder()}/**/chatGPT对话历史*.html', recursive=True)])
+ local_history = "
".join([
+ "`"+hide_cwd(f)+f" ({gen_file_preview(f)})"+"`"
+ for f in glob.glob(
+ f'{get_log_folder(get_user(chatbot), plugin_name="chat_history")}/**/{f_prefix}*.html',
+ recursive=True
+ )])
chatbot.append([f"正在查找对话历史文件（html格式）: {txt}", f"找不到任何html文件: {txt}。但本地存储了以下历史文件，您可以将任意一个文件路径粘贴到输入区，然后重试：
{local_history}"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
@@ -132,8 +138,12 @@ def 删除所有本地对话历史记录(txt, llm_kwargs, plugin_kwargs, chatbot
"""
import glob, os
- local_history = "
".join(["`"+hide_cwd(f)+"`" for f in glob.glob(f'{get_log_folder()}/**/chatGPT对话历史*.html', recursive=True)])
- for f in glob.glob(f'{get_log_folder()}/**/chatGPT对话历史*.html', recursive=True):
+ local_history = "
".join([
+ "`"+hide_cwd(f)+"`"
+ for f in glob.glob(
+ f'{get_log_folder(get_user(chatbot), plugin_name="chat_history")}/**/{f_prefix}*.html', recursive=True
+ )])
+ for f in glob.glob(f'{get_log_folder(get_user(chatbot), plugin_name="chat_history")}/**/{f_prefix}*.html', recursive=True):
os.remove(f)
chatbot.append([f"删除所有历史对话文件", f"已删除
{local_history}"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
diff --git "a/crazy_functions/\346\200\273\347\273\223word\346\226\207\346\241\243.py" "b/crazy_functions/\346\200\273\347\273\223word\346\226\207\346\241\243.py"
index 4ea753cbdf7149c77910c1cf217be9eb5bfa3e56..b39230715488ddffcdd25cd7783251cde14c81cf 100644
--- "a/crazy_functions/\346\200\273\347\273\223word\346\226\207\346\241\243.py"
+++ "b/crazy_functions/\346\200\273\347\273\223word\346\226\207\346\241\243.py"
@@ -1,5 +1,5 @@
from toolbox import update_ui
-from toolbox import CatchException, report_execption
+from toolbox import CatchException, report_exception
from toolbox import write_history_to_file, promote_file_to_downloadzone
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
fast_debug = False
@@ -32,7 +32,7 @@ def 解析docx(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot
print(file_content)
# private_upload里面的文件名在解压zip后容易出现乱码（rar和7z格式正常），故可以只分析文章内容，不输入文件名
from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
- from request_llm.bridge_all import model_info
+ from request_llms.bridge_all import model_info
max_token = model_info[llm_kwargs['llm_model']]['max_token']
TOKEN_LIMIT_PER_FRAGMENT = max_token * 3 // 4
paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
@@ -97,7 +97,7 @@ def 总结word文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pr
try:
from docx import Document
except:
- report_execption(chatbot, history,
+ report_exception(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 python-docx pywin32```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
@@ -111,7 +111,7 @@ def 总结word文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pr
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
@@ -124,7 +124,7 @@ def 总结word文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pr
# 如果没找到任何文件
if len(file_manifest) == 0:
- report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何.docx或doc文件: {txt}")
+ report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何.docx或doc文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
diff --git "a/crazy_functions/\346\200\273\347\273\223\351\237\263\350\247\206\351\242\221.py" "b/crazy_functions/\346\200\273\347\273\223\351\237\263\350\247\206\351\242\221.py"
index 7c113f476adbecdeb0d9c78e28547a095d020b2e..b27bcce06c4c83d491dd5bae445be957436204f9 100644
--- "a/crazy_functions/\346\200\273\347\273\223\351\237\263\350\247\206\351\242\221.py"
+++ "b/crazy_functions/\346\200\273\347\273\223\351\237\263\350\247\206\351\242\221.py"
@@ -1,4 +1,4 @@
-from toolbox import CatchException, report_execption, select_api_key, update_ui, get_conf
+from toolbox import CatchException, report_exception, select_api_key, update_ui, get_conf
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
from toolbox import write_history_to_file, promote_file_to_downloadzone, get_log_folder
@@ -41,7 +41,7 @@ def split_audio_file(filename, split_duration=1000):
def AnalyAudio(parse_prompt, file_manifest, llm_kwargs, chatbot, history):
import os, requests
from moviepy.editor import AudioFileClip
- from request_llm.bridge_all import model_info
+ from request_llms.bridge_all import model_info
# 设置OpenAI密钥和模型
api_key = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model'])
@@ -79,7 +79,7 @@ def AnalyAudio(parse_prompt, file_manifest, llm_kwargs, chatbot, history):
chatbot.append([f"将 {i} 发送到openai音频解析终端 (whisper)，当前参数：{parse_prompt}", "正在处理 ..."])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
- proxies, = get_conf('proxies')
+ proxies = get_conf('proxies')
response = requests.post(url, headers=headers, files=files, data=data, proxies=proxies).text
chatbot.append(["音频解析结果", response])
@@ -144,7 +144,7 @@ def 总结音视频(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
try:
from moviepy.editor import AudioFileClip
except:
- report_execption(chatbot, history,
+ report_exception(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 moviepy```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
@@ -158,7 +158,7 @@ def 总结音视频(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
@@ -174,7 +174,7 @@ def 总结音视频(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
# 如果没找到任何文件
if len(file_manifest) == 0:
- report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何音频或视频文件: {txt}")
+ report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何音频或视频文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
diff --git "a/crazy_functions/\346\211\271\351\207\217Markdown\347\277\273\350\257\221.py" "b/crazy_functions/\346\211\271\351\207\217Markdown\347\277\273\350\257\221.py"
index 9485b1ec187e9ab73b30f3450cd7bb96c46a659d..12b4ef091681860f096b670b6068ba5cae6d119d 100644
--- "a/crazy_functions/\346\211\271\351\207\217Markdown\347\277\273\350\257\221.py"
+++ "b/crazy_functions/\346\211\271\351\207\217Markdown\347\277\273\350\257\221.py"
@@ -1,6 +1,6 @@
import glob, time, os, re, logging
from toolbox import update_ui, trimmed_format_exc, gen_time_str, disable_auto_promotion
-from toolbox import CatchException, report_execption, get_log_folder
+from toolbox import CatchException, report_exception, get_log_folder
from toolbox import write_history_to_file, promote_file_to_downloadzone
fast_debug = False
@@ -13,7 +13,7 @@ class PaperFileGroup():
self.sp_file_tag = []
# count_token
- from request_llm.bridge_all import model_info
+ from request_llms.bridge_all import model_info
enc = model_info["gpt-3.5-turbo"]['tokenizer']
def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
self.get_token_num = get_token_num
@@ -118,7 +118,7 @@ def get_files_from_everything(txt, preference=''):
if txt.startswith('http'):
import requests
from toolbox import get_conf
- proxies, = get_conf('proxies')
+ proxies = get_conf('proxies')
# 网络的远程文件
if preference == 'Github':
logging.info('正在从github下载资源 ...')
@@ -165,7 +165,7 @@ def Markdown英译中(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
try:
import tiktoken
except:
- report_execption(chatbot, history,
+ report_exception(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 tiktoken```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
@@ -177,12 +177,12 @@ def Markdown英译中(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
if not success:
# 什么都没有
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
if len(file_manifest) == 0:
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md文件: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
@@ -205,7 +205,7 @@ def Markdown中译英(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
try:
import tiktoken
except:
- report_execption(chatbot, history,
+ report_exception(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 tiktoken```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
@@ -215,11 +215,11 @@ def Markdown中译英(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
if not success:
# 什么都没有
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
if len(file_manifest) == 0:
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md文件: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
yield from 多文件翻译(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, language='zh->en')
@@ -238,7 +238,7 @@ def Markdown翻译指定语言(txt, llm_kwargs, plugin_kwargs, chatbot, history,
try:
import tiktoken
except:
- report_execption(chatbot, history,
+ report_exception(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 tiktoken```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
@@ -248,11 +248,11 @@ def Markdown翻译指定语言(txt, llm_kwargs, plugin_kwargs, chatbot, history,
if not success:
# 什么都没有
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
if len(file_manifest) == 0:
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md文件: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.md文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
diff --git "a/crazy_functions/\346\211\271\351\207\217\346\200\273\347\273\223PDF\346\226\207\346\241\243.py" "b/crazy_functions/\346\211\271\351\207\217\346\200\273\347\273\223PDF\346\226\207\346\241\243.py"
index b87d482585aee762331973ba26e50c60d14cfb44..7fc3e415c3e5881f9271bd2fc9f4e46f448551cb 100644
--- "a/crazy_functions/\346\211\271\351\207\217\346\200\273\347\273\223PDF\346\226\207\346\241\243.py"
+++ "b/crazy_functions/\346\211\271\351\207\217\346\200\273\347\273\223PDF\346\226\207\346\241\243.py"
@@ -1,5 +1,5 @@
from toolbox import update_ui, promote_file_to_downloadzone, gen_time_str
-from toolbox import CatchException, report_execption
+from toolbox import CatchException, report_exception
from toolbox import write_history_to_file, promote_file_to_downloadzone
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
from .crazy_utils import read_and_clean_pdf_text
@@ -21,7 +21,7 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
TOKEN_LIMIT_PER_FRAGMENT = 2500
from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
- from request_llm.bridge_all import model_info
+ from request_llms.bridge_all import model_info
enc = model_info["gpt-3.5-turbo"]['tokenizer']
def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
@@ -119,7 +119,7 @@ def 批量总结PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
try:
import fitz
except:
- report_execption(chatbot, history,
+ report_exception(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 pymupdf```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
@@ -133,7 +133,7 @@ def 批量总结PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
@@ -142,7 +142,7 @@ def 批量总结PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
# 如果没找到任何文件
if len(file_manifest) == 0:
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex或.pdf文件: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex或.pdf文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
diff --git "a/crazy_functions/\346\211\271\351\207\217\346\200\273\347\273\223PDF\346\226\207\346\241\243pdfminer.py" "b/crazy_functions/\346\211\271\351\207\217\346\200\273\347\273\223PDF\346\226\207\346\241\243pdfminer.py"
index 213d8bb26446683fdb87e06e20004dc3861eb087..a729efaa40cc12197c566c1a6fa59c1804bd8707 100644
--- "a/crazy_functions/\346\211\271\351\207\217\346\200\273\347\273\223PDF\346\226\207\346\241\243pdfminer.py"
+++ "b/crazy_functions/\346\211\271\351\207\217\346\200\273\347\273\223PDF\346\226\207\346\241\243pdfminer.py"
@@ -1,5 +1,5 @@
from toolbox import update_ui
-from toolbox import CatchException, report_execption
+from toolbox import CatchException, report_exception
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
from toolbox import write_history_to_file, promote_file_to_downloadzone
@@ -138,7 +138,7 @@ def 批量总结PDF文档pdfminer(txt, llm_kwargs, plugin_kwargs, chatbot, histo
try:
import pdfminer, bs4
except:
- report_execption(chatbot, history,
+ report_exception(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 pdfminer beautifulsoup4```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
@@ -147,7 +147,7 @@ def 批量总结PDF文档pdfminer(txt, llm_kwargs, plugin_kwargs, chatbot, histo
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)] + \
@@ -155,7 +155,7 @@ def 批量总结PDF文档pdfminer(txt, llm_kwargs, plugin_kwargs, chatbot, histo
# [f for f in glob.glob(f'{project_folder}/**/*.cpp', recursive=True)] + \
# [f for f in glob.glob(f'{project_folder}/**/*.c', recursive=True)]
if len(file_manifest) == 0:
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex或pdf文件: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex或pdf文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
yield from 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
diff --git "a/crazy_functions/\346\211\271\351\207\217\347\277\273\350\257\221PDF\346\226\207\346\241\243_NOUGAT.py" "b/crazy_functions/\346\211\271\351\207\217\347\277\273\350\257\221PDF\346\226\207\346\241\243_NOUGAT.py"
index c0961c14936ed0aa2d40d2c7bb2459513899e776..97170d0eddac7b55c6ce1d1aa96c1ec16b98cc7d 100644
--- "a/crazy_functions/\346\211\271\351\207\217\347\277\273\350\257\221PDF\346\226\207\346\241\243_NOUGAT.py"
+++ "b/crazy_functions/\346\211\271\351\207\217\347\277\273\350\257\221PDF\346\226\207\346\241\243_NOUGAT.py"
@@ -1,4 +1,4 @@
-from toolbox import CatchException, report_execption, get_log_folder, gen_time_str
+from toolbox import CatchException, report_exception, get_log_folder, gen_time_str
from toolbox import update_ui, promote_file_to_downloadzone, update_ui_lastest_msg, disable_auto_promotion
from toolbox import write_history_to_file, promote_file_to_downloadzone
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
@@ -57,30 +57,35 @@ 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_exception(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'
# 如果没找到任何文件
if len(file_manifest) == 0:
- report_execption(chatbot, history,
- a=f"解析项目: {txt}", b=f"找不到任何.tex或.pdf文件: {txt}")
+ report_exception(chatbot, history,
+ a=f"解析项目: {txt}", b=f"找不到任何.pdf拓展名的文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
@@ -97,12 +102,17 @@ def 解析PDF_基于NOUGAT(file_manifest, project_folder, llm_kwargs, plugin_kwa
generated_conclusion_files = []
generated_html_files = []
DST_LANG = "中文"
- from crazy_functions.crazy_utils import nougat_interface, construct_html
+ from crazy_functions.crazy_utils import nougat_interface
+ 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)
diff --git "a/crazy_functions/\346\211\271\351\207\217\347\277\273\350\257\221PDF\346\226\207\346\241\243_\345\244\232\347\272\277\347\250\213.py" "b/crazy_functions/\346\211\271\351\207\217\347\277\273\350\257\221PDF\346\226\207\346\241\243_\345\244\232\347\272\277\347\250\213.py"
index 0f60a90aed033fa7fdb328f22e91c77ba2e14c00..73cf59200c1f0daab3d75aae93d2910edee0a388 100644
--- "a/crazy_functions/\346\211\271\351\207\217\347\277\273\350\257\221PDF\346\226\207\346\241\243_\345\244\232\347\272\277\347\250\213.py"
+++ "b/crazy_functions/\346\211\271\351\207\217\347\277\273\350\257\221PDF\346\226\207\346\241\243_\345\244\232\347\272\277\347\250\213.py"
@@ -1,4 +1,4 @@
-from toolbox import CatchException, report_execption, get_log_folder, gen_time_str
+from toolbox import CatchException, report_exception, get_log_folder, gen_time_str, check_packages
from toolbox import update_ui, promote_file_to_downloadzone, update_ui_lastest_msg, disable_auto_promotion
from toolbox import write_history_to_file, promote_file_to_downloadzone
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
@@ -6,9 +6,8 @@ from .crazy_utils import request_gpt_model_multi_threads_with_very_awesome_ui_an
from .crazy_utils import read_and_clean_pdf_text
from .pdf_fns.parse_pdf import parse_pdf, get_avail_grobid_url, translate_pdf
from colorful import *
-import copy
import os
-import math
+
@CatchException
def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
@@ -22,11 +21,9 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
# 尝试导入依赖，如果缺少依赖，则给出安装建议
try:
- import fitz
- import tiktoken
- import scipdf
+ check_packages(["fitz", "tiktoken", "scipdf"])
except:
- report_execption(chatbot, history,
+ report_exception(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 pymupdf tiktoken scipdf_parser```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
@@ -43,8 +40,8 @@ def 批量翻译PDF文档(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
# 如果没找到任何文件
if len(file_manifest) == 0:
- report_execption(chatbot, history,
- a=f"解析项目: {txt}", b=f"找不到任何.tex或.pdf文件: {txt}")
+ report_exception(chatbot, history,
+ a=f"解析项目: {txt}", b=f"找不到任何.pdf拓展名的文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
@@ -63,7 +60,7 @@ def 解析PDF_基于GROBID(file_manifest, project_folder, llm_kwargs, plugin_kwa
generated_conclusion_files = []
generated_html_files = []
DST_LANG = "中文"
- from crazy_functions.crazy_utils import construct_html
+ from crazy_functions.pdf_fns.report_gen_html import construct_html
for index, fp in enumerate(file_manifest):
chatbot.append(["当前进度：", f"正在连接GROBID服务，请稍候: {grobid_url}\n如果等待时间过长，请修改config中的GROBID_URL，可修改成本地GROBID服务。"]); yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
article_dict = parse_pdf(fp, grobid_url)
@@ -86,7 +83,7 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
TOKEN_LIMIT_PER_FRAGMENT = 1024
generated_conclusion_files = []
generated_html_files = []
- from crazy_functions.crazy_utils import construct_html
+ from crazy_functions.pdf_fns.report_gen_html import construct_html
for index, fp in enumerate(file_manifest):
# 读取PDF文件
file_content, page_one = read_and_clean_pdf_text(fp)
@@ -95,7 +92,7 @@ def 解析PDF(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot,
# 递归地切割PDF文件
from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
- from request_llm.bridge_all import model_info
+ from request_llms.bridge_all import model_info
enc = model_info["gpt-3.5-turbo"]['tokenizer']
def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
diff --git "a/crazy_functions/\347\220\206\350\247\243PDF\346\226\207\346\241\243\345\206\205\345\256\271.py" "b/crazy_functions/\347\220\206\350\247\243PDF\346\226\207\346\241\243\345\206\205\345\256\271.py"
index f1a89a7ec94f30a00b58ad85661a876efc0ac4d2..ef9678896f210b072149c701a852d06655761ba4 100644
--- "a/crazy_functions/\347\220\206\350\247\243PDF\346\226\207\346\241\243\345\206\205\345\256\271.py"
+++ "b/crazy_functions/\347\220\206\350\247\243PDF\346\226\207\346\241\243\345\206\205\345\256\271.py"
@@ -1,5 +1,5 @@
from toolbox import update_ui
-from toolbox import CatchException, report_execption
+from toolbox import CatchException, report_exception
from .crazy_utils import read_and_clean_pdf_text
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
fast_debug = False
@@ -19,7 +19,7 @@ def 解析PDF(file_name, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
TOKEN_LIMIT_PER_FRAGMENT = 2500
from .crazy_utils import breakdown_txt_to_satisfy_token_limit_for_pdf
- from request_llm.bridge_all import model_info
+ from request_llms.bridge_all import model_info
enc = model_info["gpt-3.5-turbo"]['tokenizer']
def get_token_num(txt): return len(enc.encode(txt, disallowed_special=()))
paper_fragments = breakdown_txt_to_satisfy_token_limit_for_pdf(
@@ -49,7 +49,7 @@ def 解析PDF(file_name, llm_kwargs, plugin_kwargs, chatbot, history, system_pro
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(i_say, i_say_show_user, # i_say=真正给chatgpt的提问， i_say_show_user=给用户看的提问
llm_kwargs, chatbot,
history=["The main idea of the previous section is?", last_iteration_result], # 迭代上一次的结果
- sys_prompt="Extract the main idea of this section." # 提示
+ sys_prompt="Extract the main idea of this section, answer me with Chinese." # 提示
)
iteration_results.append(gpt_say)
last_iteration_result = gpt_say
@@ -81,7 +81,7 @@ def 理解PDF文档内容标准文件输入(txt, llm_kwargs, plugin_kwargs, chat
try:
import fitz
except:
- report_execption(chatbot, history,
+ report_exception(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 pymupdf```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
@@ -96,7 +96,7 @@ def 理解PDF文档内容标准文件输入(txt, llm_kwargs, plugin_kwargs, chat
else:
if txt == "":
txt = '空空如也的输入栏'
- report_execption(chatbot, history,
+ report_exception(chatbot, history,
a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
@@ -105,7 +105,7 @@ def 理解PDF文档内容标准文件输入(txt, llm_kwargs, plugin_kwargs, chat
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.pdf', recursive=True)]
# 如果没找到任何文件
if len(file_manifest) == 0:
- report_execption(chatbot, history,
+ report_exception(chatbot, history,
a=f"解析项目: {txt}", b=f"找不到任何.tex或.pdf文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
diff --git "a/crazy_functions/\347\224\237\346\210\220\345\207\275\346\225\260\346\263\250\351\207\212.py" "b/crazy_functions/\347\224\237\346\210\220\345\207\275\346\225\260\346\263\250\351\207\212.py"
index bf3da6a4b973b311a19757d4b5e6cc4127542e8b..d71a568053e5db18c58a9beddf35d7981592d1c2 100644
--- "a/crazy_functions/\347\224\237\346\210\220\345\207\275\346\225\260\346\263\250\351\207\212.py"
+++ "b/crazy_functions/\347\224\237\346\210\220\345\207\275\346\225\260\346\263\250\351\207\212.py"
@@ -1,5 +1,5 @@
from toolbox import update_ui
-from toolbox import CatchException, report_execption
+from toolbox import CatchException, report_exception
from toolbox import write_history_to_file, promote_file_to_downloadzone
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
fast_debug = False
@@ -43,14 +43,14 @@ def 批量生成函数注释(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.py', recursive=True)] + \
[f for f in glob.glob(f'{project_folder}/**/*.cpp', recursive=True)]
if len(file_manifest) == 0:
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
yield from 生成函数注释(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
diff --git "a/crazy_functions/\350\201\224\347\275\221\347\232\204ChatGPT.py" "b/crazy_functions/\350\201\224\347\275\221\347\232\204ChatGPT.py"
index 4ed9aebf97834418d145ab1dd5b22ca7f4f9b214..6fa50ec2e39939371639076e508a0dce996e31ca 100644
--- "a/crazy_functions/\350\201\224\347\275\221\347\232\204ChatGPT.py"
+++ "b/crazy_functions/\350\201\224\347\275\221\347\232\204ChatGPT.py"
@@ -2,7 +2,7 @@ from toolbox import CatchException, update_ui
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, input_clipping
import requests
from bs4 import BeautifulSoup
-from request_llm.bridge_all import model_info
+from request_llms.bridge_all import model_info
def google(query, proxies):
query = query # 在此处替换您要搜索的关键词
@@ -72,7 +72,7 @@ def 连接网络回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
# ------------- < 第1步：爬取搜索引擎的结果 > -------------
from toolbox import get_conf
- proxies, = get_conf('proxies')
+ proxies = get_conf('proxies')
urls = google(txt, proxies)
history = []
if len(urls) == 0:
diff --git "a/crazy_functions/\350\201\224\347\275\221\347\232\204ChatGPT_bing\347\211\210.py" "b/crazy_functions/\350\201\224\347\275\221\347\232\204ChatGPT_bing\347\211\210.py"
index db5adb7992f765db3e5b0e7ecea7e71e44dbe855..009ebdce52dde5d0d85c6a31cf42fc62ae2a163e 100644
--- "a/crazy_functions/\350\201\224\347\275\221\347\232\204ChatGPT_bing\347\211\210.py"
+++ "b/crazy_functions/\350\201\224\347\275\221\347\232\204ChatGPT_bing\347\211\210.py"
@@ -2,7 +2,7 @@ from toolbox import CatchException, update_ui
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, input_clipping
import requests
from bs4 import BeautifulSoup
-from request_llm.bridge_all import model_info
+from request_llms.bridge_all import model_info
def bing_search(query, proxies=None):
@@ -72,7 +72,7 @@ def 连接bing搜索回答问题(txt, llm_kwargs, plugin_kwargs, chatbot, histor
# ------------- < 第1步：爬取搜索引擎的结果 > -------------
from toolbox import get_conf
- proxies, = get_conf('proxies')
+ proxies = get_conf('proxies')
urls = bing_search(txt, proxies)
history = []
if len(urls) == 0:
diff --git "a/crazy_functions/\350\231\232\347\251\272\347\273\210\347\253\257.py" "b/crazy_functions/\350\231\232\347\251\272\347\273\210\347\253\257.py"
index 5f33249e3e77d8fc92ce09f692d34f1e9ea3e559..439e71ca3d2b815d7964bf792d157202a4e8aa9d 100644
--- "a/crazy_functions/\350\231\232\347\251\272\347\273\210\347\253\257.py"
+++ "b/crazy_functions/\350\231\232\347\251\272\347\273\210\347\253\257.py"
@@ -48,7 +48,7 @@ from pydantic import BaseModel, Field
from typing import List
from toolbox import CatchException, update_ui, is_the_upload_folder
from toolbox import update_ui_lastest_msg, disable_auto_promotion
-from request_llm.bridge_all import predict_no_ui_long_connection
+from request_llms.bridge_all import predict_no_ui_long_connection
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
from crazy_functions.crazy_utils import input_clipping
from crazy_functions.json_fns.pydantic_io import GptJsonIO, JsonStringError
diff --git "a/crazy_functions/\350\247\243\346\236\220JupyterNotebook.py" "b/crazy_functions/\350\247\243\346\236\220JupyterNotebook.py"
index d4a3b49e69ea16235375371a4f51f87af1103a21..eeccadf7e6fa52c080a86baeecf98b3edaddb543 100644
--- "a/crazy_functions/\350\247\243\346\236\220JupyterNotebook.py"
+++ "b/crazy_functions/\350\247\243\346\236\220JupyterNotebook.py"
@@ -1,5 +1,5 @@
from toolbox import update_ui
-from toolbox import CatchException, report_execption
+from toolbox import CatchException, report_exception
from toolbox import write_history_to_file, promote_file_to_downloadzone
fast_debug = True
@@ -13,7 +13,7 @@ class PaperFileGroup():
self.sp_file_tag = []
# count_token
- from request_llm.bridge_all import model_info
+ from request_llms.bridge_all import model_info
enc = model_info["gpt-3.5-turbo"]['tokenizer']
def get_token_num(txt): return len(
enc.encode(txt, disallowed_special=()))
@@ -131,7 +131,7 @@ def 解析ipynb文件(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
else:
if txt == "":
txt = '空空如也的输入栏'
- report_execption(chatbot, history,
+ report_exception(chatbot, history,
a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
@@ -141,7 +141,7 @@ def 解析ipynb文件(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_p
file_manifest = [f for f in glob.glob(
f'{project_folder}/**/*.ipynb', recursive=True)]
if len(file_manifest) == 0:
- report_execption(chatbot, history,
+ report_exception(chatbot, history,
a=f"解析项目: {txt}", b=f"找不到任何.ipynb文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
diff --git "a/crazy_functions/\350\247\243\346\236\220\351\241\271\347\233\256\346\272\220\344\273\243\347\240\201.py" "b/crazy_functions/\350\247\243\346\236\220\351\241\271\347\233\256\346\272\220\344\273\243\347\240\201.py"
index f17a584d4e277050e59c3b9b6b0b16b0c168fbdf..e319d5a87435a1cbb410dffe823787a887e924b5 100644
--- "a/crazy_functions/\350\247\243\346\236\220\351\241\271\347\233\256\346\272\220\344\273\243\347\240\201.py"
+++ "b/crazy_functions/\350\247\243\346\236\220\351\241\271\347\233\256\346\272\220\344\273\243\347\240\201.py"
@@ -1,5 +1,5 @@
from toolbox import update_ui, promote_file_to_downloadzone, disable_auto_promotion
-from toolbox import CatchException, report_execption, write_history_to_file
+from toolbox import CatchException, report_exception, write_history_to_file
from .crazy_utils import input_clipping
def 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
@@ -113,7 +113,7 @@ def 解析项目本身(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
[f for f in glob.glob('./*/*.py')]
project_folder = './'
if len(file_manifest) == 0:
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何python文件: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何python文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
@@ -126,12 +126,12 @@ def 解析一个Python项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.py', recursive=True)]
if len(file_manifest) == 0:
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何python文件: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何python文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
@@ -144,12 +144,12 @@ def 解析一个Matlab项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a = f"解析Matlab项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a = f"解析Matlab项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.m', recursive=True)]
if len(file_manifest) == 0:
- report_execption(chatbot, history, a = f"解析Matlab项目: {txt}", b = f"找不到任何`.m`源文件: {txt}")
+ report_exception(chatbot, history, a = f"解析Matlab项目: {txt}", b = f"找不到任何`.m`源文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
@@ -162,14 +162,14 @@ def 解析一个C项目的头文件(txt, llm_kwargs, plugin_kwargs, chatbot, his
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.h', recursive=True)] + \
[f for f in glob.glob(f'{project_folder}/**/*.hpp', recursive=True)] #+ \
# [f for f in glob.glob(f'{project_folder}/**/*.c', recursive=True)]
if len(file_manifest) == 0:
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.h头文件: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.h头文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
@@ -182,7 +182,7 @@ def 解析一个C项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.h', recursive=True)] + \
@@ -190,7 +190,7 @@ def 解析一个C项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, system
[f for f in glob.glob(f'{project_folder}/**/*.hpp', recursive=True)] + \
[f for f in glob.glob(f'{project_folder}/**/*.c', recursive=True)]
if len(file_manifest) == 0:
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.h头文件: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.h头文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
@@ -204,7 +204,7 @@ def 解析一个Java项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.java', recursive=True)] + \
@@ -212,7 +212,7 @@ def 解析一个Java项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys
[f for f in glob.glob(f'{project_folder}/**/*.xml', recursive=True)] + \
[f for f in glob.glob(f'{project_folder}/**/*.sh', recursive=True)]
if len(file_manifest) == 0:
- report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何java文件: {txt}")
+ report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何java文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
@@ -226,7 +226,7 @@ def 解析一个前端项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.ts', recursive=True)] + \
@@ -241,7 +241,7 @@ def 解析一个前端项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
[f for f in glob.glob(f'{project_folder}/**/*.css', recursive=True)] + \
[f for f in glob.glob(f'{project_folder}/**/*.jsx', recursive=True)]
if len(file_manifest) == 0:
- report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何前端相关文件: {txt}")
+ report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何前端相关文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
@@ -255,7 +255,7 @@ def 解析一个Golang项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.go', recursive=True)] + \
@@ -263,7 +263,7 @@ def 解析一个Golang项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
[f for f in glob.glob(f'{project_folder}/**/go.sum', recursive=True)] + \
[f for f in glob.glob(f'{project_folder}/**/go.work', recursive=True)]
if len(file_manifest) == 0:
- report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何golang文件: {txt}")
+ report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何golang文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
@@ -276,14 +276,14 @@ def 解析一个Rust项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.rs', recursive=True)] + \
[f for f in glob.glob(f'{project_folder}/**/*.toml', recursive=True)] + \
[f for f in glob.glob(f'{project_folder}/**/*.lock', recursive=True)]
if len(file_manifest) == 0:
- report_execption(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何golang文件: {txt}")
+ report_exception(chatbot, history, a=f"解析项目: {txt}", b=f"找不到任何golang文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
@@ -296,7 +296,7 @@ def 解析一个Lua项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.lua', recursive=True)] + \
@@ -304,7 +304,7 @@ def 解析一个Lua项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
[f for f in glob.glob(f'{project_folder}/**/*.json', recursive=True)] + \
[f for f in glob.glob(f'{project_folder}/**/*.toml', recursive=True)]
if len(file_manifest) == 0:
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何lua文件: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何lua文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
@@ -318,13 +318,13 @@ def 解析一个CSharp项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, s
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.cs', recursive=True)] + \
[f for f in glob.glob(f'{project_folder}/**/*.csproj', recursive=True)]
if len(file_manifest) == 0:
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何CSharp文件: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何CSharp文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
@@ -352,7 +352,7 @@ def 解析任意code项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
# 若上传压缩文件, 先寻找到解压的文件夹路径, 从而避免解析压缩文件
@@ -365,7 +365,7 @@ def 解析任意code项目(txt, llm_kwargs, plugin_kwargs, chatbot, history, sys
file_manifest = [f for pattern in pattern_include for f in glob.glob(f'{extract_folder_path}/**/{pattern}', recursive=True) if "" != extract_folder_path and \
os.path.isfile(f) and (not re.search(pattern_except, f) or pattern.endswith('.' + re.search(pattern_except, f).group().split('.')[-1]))]
if len(file_manifest) == 0:
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何文件: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
yield from 解析源代码新(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
\ No newline at end of file
diff --git "a/crazy_functions/\350\257\242\351\227\256\345\244\232\344\270\252\345\244\247\350\257\255\350\250\200\346\250\241\345\236\213.py" "b/crazy_functions/\350\257\242\351\227\256\345\244\232\344\270\252\345\244\247\350\257\255\350\250\200\346\250\241\345\236\213.py"
index 8fdf5915d303a54cc7859e9df77ac9acf5311ced..4210fb2136751da6b6d20a7381c4cd60eb8e8649 100644
--- "a/crazy_functions/\350\257\242\351\227\256\345\244\232\344\270\252\345\244\247\350\257\255\350\250\200\346\250\241\345\236\213.py"
+++ "b/crazy_functions/\350\257\242\351\227\256\345\244\232\344\270\252\345\244\247\350\257\255\350\250\200\346\250\241\345\236\213.py"
@@ -1,4 +1,4 @@
-from toolbox import CatchException, update_ui
+from toolbox import CatchException, update_ui, get_conf
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
import datetime
@CatchException
@@ -13,11 +13,12 @@ def 同时问询(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
web_port 当前软件运行的端口号
"""
history = [] # 清空历史，以免输入溢出
- chatbot.append((txt, "正在同时咨询gpt-3.5和gpt-4……"))
+ MULTI_QUERY_LLM_MODELS = get_conf('MULTI_QUERY_LLM_MODELS')
+ chatbot.append((txt, "正在同时咨询" + MULTI_QUERY_LLM_MODELS))
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
# llm_kwargs['llm_model'] = 'chatglm&gpt-3.5-turbo&api2d-gpt-3.5-turbo' # 支持任意数量的llm接口，用&符号分隔
- llm_kwargs['llm_model'] = 'gpt-3.5-turbo&gpt-4' # 支持任意数量的llm接口，用&符号分隔
+ llm_kwargs['llm_model'] = MULTI_QUERY_LLM_MODELS # 支持任意数量的llm接口，用&符号分隔
gpt_say = yield from request_gpt_model_in_new_thread_with_ui_alive(
inputs=txt, inputs_show_user=txt,
llm_kwargs=llm_kwargs, chatbot=chatbot, history=history,
diff --git "a/crazy_functions/\350\257\255\351\237\263\345\212\251\346\211\213.py" "b/crazy_functions/\350\257\255\351\237\263\345\212\251\346\211\213.py"
index b1c8c41e63f3cedc97affb66d5ea124f9c5d4837..3e93ceaed536e3cf1fe5129a0c5c379047d4ff3b 100644
--- "a/crazy_functions/\350\257\255\351\237\263\345\212\251\346\211\213.py"
+++ "b/crazy_functions/\350\257\255\351\237\263\345\212\251\346\211\213.py"
@@ -1,47 +1,35 @@
from toolbox import update_ui
from toolbox import CatchException, get_conf, markdown_convertion
from crazy_functions.crazy_utils import input_clipping
-from request_llm.bridge_all import predict_no_ui_long_connection
+from crazy_functions.agent_fns.watchdog import WatchDog
+from request_llms.bridge_all import predict_no_ui_long_connection
import threading, time
import numpy as np
from .live_audio.aliyunASR import AliyunASR
import json
+import re
-class WatchDog():
- def __init__(self, timeout, bark_fn, interval=3, msg="") -> None:
- self.last_feed = None
- self.timeout = timeout
- self.bark_fn = bark_fn
- self.interval = interval
- self.msg = msg
- self.kill_dog = False
-
- def watch(self):
- while True:
- if self.kill_dog: break
- if time.time() - self.last_feed > self.timeout:
- if len(self.msg) > 0: print(self.msg)
- self.bark_fn()
- break
- time.sleep(self.interval)
-
- def begin_watch(self):
- self.last_feed = time.time()
- th = threading.Thread(target=self.watch)
- th.daemon = True
- th.start()
-
- def feed(self):
- self.last_feed = time.time()
def chatbot2history(chatbot):
history = []
for c in chatbot:
for q in c:
- if q not in ["[请讲话]", "[等待GPT响应]", "[正在等您说完问题]"]:
+ if q in ["[ 请讲话 ]", "[ 等待GPT响应 ]", "[ 正在等您说完问题 ]"]:
+ continue
+ elif q.startswith("[ 正在等您说完问题 ]"):
+ continue
+ else:
history.append(q.strip('').strip('
').strip('').strip('
'))
return history
+def visualize_audio(chatbot, audio_shape):
+ if len(chatbot) == 0: chatbot.append(["[ 请讲话 ]", "[ 正在等您说完问题 ]"])
+ chatbot[-1] = list(chatbot[-1])
+ p1 = '「'
+ p2 = '」'
+ chatbot[-1][-1] = re.sub(p1+r'(.*)'+p2, '', chatbot[-1][-1])
+ chatbot[-1][-1] += (p1+f"`{audio_shape}`"+p2)
+
class AsyncGptTask():
def __init__(self) -> None:
self.observe_future = []
@@ -81,8 +69,9 @@ class InterviewAssistant(AliyunASR):
self.capture_interval = 0.5 # second
self.stop = False
self.parsed_text = "" # 下个句子中已经说完的部分, 由 test_on_result_chg() 写入
- self.parsed_sentence = "" # 某段话的整个句子,由 test_on_sentence_end() 写入
+ self.parsed_sentence = "" # 某段话的整个句子, 由 test_on_sentence_end() 写入
self.buffered_sentence = "" #
+ self.audio_shape = "" # 音频的可视化表现, 由 audio_convertion_thread() 写入
self.event_on_result_chg = threading.Event()
self.event_on_entence_end = threading.Event()
self.event_on_commit_question = threading.Event()
@@ -117,7 +106,7 @@ class InterviewAssistant(AliyunASR):
def begin(self, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt):
# main plugin function
self.init(chatbot)
- chatbot.append(["[请讲话]", "[正在等您说完问题]"])
+ chatbot.append(["[ 请讲话 ]", "[ 正在等您说完问题 ]"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
self.plugin_wd.begin_watch()
self.agt = AsyncGptTask()
@@ -157,14 +146,18 @@ class InterviewAssistant(AliyunASR):
self.commit_wd.begin_watch()
chatbot[-1] = list(chatbot[-1])
- chatbot[-1] = [self.buffered_sentence, "[等待GPT响应]"]
+ chatbot[-1] = [self.buffered_sentence, "[ 等待GPT响应 ]"]
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
# add gpt task 创建子线程请求gpt，避免线程阻塞
history = chatbot2history(chatbot)
self.agt.add_async_gpt_task(self.buffered_sentence, len(chatbot)-1, llm_kwargs, history, system_prompt)
self.buffered_sentence = ""
- chatbot.append(["[请讲话]", "[正在等您说完问题]"])
+ chatbot.append(["[ 请讲话 ]", "[ 正在等您说完问题 ]"])
+ yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
+
+ if not self.event_on_result_chg.is_set() and not self.event_on_entence_end.is_set() and not self.event_on_commit_question.is_set():
+ visualize_audio(chatbot, self.audio_shape)
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
if len(self.stop_msg) != 0:
@@ -183,7 +176,7 @@ def 语音助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
import nls
from scipy import io
except:
- chatbot.append(["导入依赖失败", "使用该模块需要额外依赖, 安装方法:```pip install --upgrade aliyun-python-sdk-core==2.13.3 pyOpenSSL scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git```"])
+ chatbot.append(["导入依赖失败", "使用该模块需要额外依赖, 安装方法:```pip install --upgrade aliyun-python-sdk-core==2.13.3 pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git```"])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
diff --git "a/crazy_functions/\350\257\273\346\226\207\347\253\240\345\206\231\346\221\230\350\246\201.py" "b/crazy_functions/\350\257\273\346\226\207\347\253\240\345\206\231\346\221\230\350\246\201.py"
index acdf632c3ba44d0a20424d29e6c9718c999f20f2..a43b6aa29af0157e6b8eac8ed92770679b0f044e 100644
--- "a/crazy_functions/\350\257\273\346\226\207\347\253\240\345\206\231\346\221\230\350\246\201.py"
+++ "b/crazy_functions/\350\257\273\346\226\207\347\253\240\345\206\231\346\221\230\350\246\201.py"
@@ -1,5 +1,5 @@
from toolbox import update_ui
-from toolbox import CatchException, report_execption
+from toolbox import CatchException, report_exception
from toolbox import write_history_to_file, promote_file_to_downloadzone
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
@@ -51,14 +51,14 @@ def 读文章写摘要(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_
project_folder = txt
else:
if txt == "": txt = '空空如也的输入栏'
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到本地项目或无权访问: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
file_manifest = [f for f in glob.glob(f'{project_folder}/**/*.tex', recursive=True)] # + \
# [f for f in glob.glob(f'{project_folder}/**/*.cpp', recursive=True)] + \
# [f for f in glob.glob(f'{project_folder}/**/*.c', recursive=True)]
if len(file_manifest) == 0:
- report_execption(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
+ report_exception(chatbot, history, a = f"解析项目: {txt}", b = f"找不到任何.tex文件: {txt}")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
return
yield from 解析Paper(file_manifest, project_folder, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt)
diff --git "a/crazy_functions/\350\260\267\346\255\214\346\243\200\347\264\242\345\260\217\345\212\251\346\211\213.py" "b/crazy_functions/\350\260\267\346\255\214\346\243\200\347\264\242\345\260\217\345\212\251\346\211\213.py"
index 05e80d2c8432cd3db46b8ca5a30b045ca9f5c7ca..14b21bfcd000803d8bb06164069d5096209d135c 100644
--- "a/crazy_functions/\350\260\267\346\255\214\346\243\200\347\264\242\345\260\217\345\212\251\346\211\213.py"
+++ "b/crazy_functions/\350\260\267\346\255\214\346\243\200\347\264\242\345\260\217\345\212\251\346\211\213.py"
@@ -1,5 +1,5 @@
from .crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
-from toolbox import CatchException, report_execption, promote_file_to_downloadzone
+from toolbox import CatchException, report_exception, promote_file_to_downloadzone
from toolbox import update_ui, update_ui_lastest_msg, disable_auto_promotion, write_history_to_file
import logging
import requests
@@ -17,7 +17,7 @@ def get_meta_information(url, chatbot, history):
from urllib.parse import urlparse
session = requests.session()
- proxies, = get_conf('proxies')
+ proxies = get_conf('proxies')
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/116.0.0.0 Safari/537.36',
'Accept-Encoding': 'gzip, deflate, br',
@@ -26,7 +26,13 @@ def get_meta_information(url, chatbot, history):
'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7',
'Connection': 'keep-alive'
}
- session.proxies.update(proxies)
+ try:
+ session.proxies.update(proxies)
+ except:
+ report_exception(chatbot, history,
+ a=f"获取代理失败 无代理状态下很可能无法访问OpenAI家族的模型及谷歌学术 建议：检查USE_PROXY选项是否修改。",
+ b=f"尝试直接连接")
+ yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
session.headers.update(headers)
response = session.get(url)
@@ -140,7 +146,7 @@ def 谷歌检索小助手(txt, llm_kwargs, plugin_kwargs, chatbot, history, syst
import math
from bs4 import BeautifulSoup
except:
- report_execption(chatbot, history,
+ report_exception(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 beautifulsoup4 arxiv```。")
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
diff --git "a/crazy_functions/\350\276\205\345\212\251\345\212\237\350\203\275.py" "b/crazy_functions/\350\276\205\345\212\251\345\212\237\350\203\275.py"
index 16854e087eec27f4990aaafcf1b2e9f8ee9e1e30..c5f874026c3319b9c191c92a3de592cf0e5db1e8 100644
--- "a/crazy_functions/\350\276\205\345\212\251\345\212\237\350\203\275.py"
+++ "b/crazy_functions/\350\276\205\345\212\251\345\212\237\350\203\275.py"
@@ -2,9 +2,12 @@
# @Time : 2023/4/19
# @Author : Spike
# @Descr :
-from toolbox import update_ui, get_conf
+from toolbox import update_ui, get_conf, get_user
from toolbox import CatchException
+from toolbox import default_user_name
from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive
+import shutil
+import os
@CatchException
@@ -33,10 +36,19 @@ def 清除缓存(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt
chatbot.append(['清除本地缓存数据', '执行中. 删除数据'])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
- import shutil, os
- PATH_PRIVATE_UPLOAD, PATH_LOGGING = get_conf('PATH_PRIVATE_UPLOAD', 'PATH_LOGGING')
- shutil.rmtree(PATH_LOGGING, ignore_errors=True)
- shutil.rmtree(PATH_PRIVATE_UPLOAD, ignore_errors=True)
+ def _get_log_folder(user=default_user_name):
+ PATH_LOGGING = get_conf('PATH_LOGGING')
+ _dir = os.path.join(PATH_LOGGING, user)
+ if not os.path.exists(_dir): os.makedirs(_dir)
+ return _dir
+
+ def _get_upload_folder(user=default_user_name):
+ PATH_PRIVATE_UPLOAD = get_conf('PATH_PRIVATE_UPLOAD')
+ _dir = os.path.join(PATH_PRIVATE_UPLOAD, user)
+ return _dir
+
+ shutil.rmtree(_get_log_folder(get_user(chatbot)), ignore_errors=True)
+ shutil.rmtree(_get_upload_folder(get_user(chatbot)), ignore_errors=True)
chatbot.append(['清除本地缓存数据', '执行完成'])
yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
\ No newline at end of file
diff --git a/docker-compose.yml b/docker-compose.yml
index 2bf9dfe4b45a26307e70c489df0157bf948a0119..9472a0f9411a7cfcb9640d3db2e2962145bc49f1 100644
--- a/docker-compose.yml
+++ b/docker-compose.yml
@@ -32,10 +32,10 @@ services:
gpt_academic_full_capability:
image: ghcr.io/binary-husky/gpt_academic_with_all_capacity:master
environment:
- # 请查阅 `config.py`或者 github wiki 以查看所有的配置信息
+ # 请查阅 `config.py`或者 github wiki 以查看所有的配置信息
API_KEY: ' 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 '
- # USE_PROXY: ' True '
- # proxies: ' { "http": "http://localhost:10881", "https": "http://localhost:10881", } '
+ # USE_PROXY: ' True '
+ # proxies: ' { "http": "http://localhost:10881", "https": "http://localhost:10881", } '
LLM_MODEL: ' gpt-3.5-turbo '
AVAIL_LLM_MODELS: ' ["gpt-3.5-turbo", "gpt-4", "qianfan", "sparkv2", "spark", "chatglm"] '
BAIDU_CLOUD_API_KEY : ' bTUtwEAveBrQipEowUvDwYWq '
@@ -51,7 +51,7 @@ services:
THEME: ' Chuanhu-Small-and-Beautiful '
ALIYUN_ACCESSKEY: ' LTAI5t6BrFUzxRXVGUWnekh1 '
ALIYUN_SECRET: ' eHmI20SVWIwQZxCiTD2bGQVspP9i68 '
- # LOCAL_MODEL_DEVICE: ' cuda '
+ # LOCAL_MODEL_DEVICE: ' cuda '
# 加载英伟达显卡运行时
# runtime: nvidia
@@ -137,7 +137,7 @@ services:
# P.S. 通过对 command 进行微调，可以便捷地安装额外的依赖
# command: >
- # bash -c "pip install -r request_llm/requirements_qwen.txt && python3 -u main.py"
+ # bash -c "pip install -r request_llms/requirements_qwen.txt && python3 -u main.py"
### ===================================================
### 【方案三】 如果需要运行ChatGPT + LLAMA + 盘古 + RWKV本地模型
diff --git a/docs/GithubAction+AllCapacity b/docs/GithubAction+AllCapacity
index 5e50b40114fd8f6201aacdfd94122e4173b99c5f..4ba0e31a9e1e7858059e179e97ff2648dd898c58 100644
--- a/docs/GithubAction+AllCapacity
+++ b/docs/GithubAction+AllCapacity
@@ -14,18 +14,18 @@ RUN python3 -m pip install colorama Markdown pygments pymupdf
RUN python3 -m pip install python-docx moviepy pdfminer
RUN python3 -m pip install zh_langchain==0.2.1 pypinyin
RUN python3 -m pip install rarfile py7zr
-RUN python3 -m pip install aliyun-python-sdk-core==2.13.3 pyOpenSSL scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
+RUN python3 -m pip install aliyun-python-sdk-core==2.13.3 pyOpenSSL webrtcvad scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
# 下载分支
WORKDIR /gpt
RUN git clone --depth=1 https://github.com/binary-husky/gpt_academic.git
WORKDIR /gpt/gpt_academic
-RUN git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llm/moss
+RUN git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss
RUN python3 -m pip install -r requirements.txt
-RUN python3 -m pip install -r request_llm/requirements_moss.txt
-RUN python3 -m pip install -r request_llm/requirements_qwen.txt
-RUN python3 -m pip install -r request_llm/requirements_chatglm.txt
-RUN python3 -m pip install -r request_llm/requirements_newbing.txt
+RUN python3 -m pip install -r request_llms/requirements_moss.txt
+RUN python3 -m pip install -r request_llms/requirements_qwen.txt
+RUN python3 -m pip install -r request_llms/requirements_chatglm.txt
+RUN python3 -m pip install -r request_llms/requirements_newbing.txt
RUN python3 -m pip install nougat-ocr
diff --git a/docs/GithubAction+ChatGLM+Moss b/docs/GithubAction+ChatGLM+Moss
index 3087d5513c646759c33f08d29d62ed68602eaa93..3212dc2f4d17425696e0a67a35e90cb81b6a99e5 100644
--- a/docs/GithubAction+ChatGLM+Moss
+++ b/docs/GithubAction+ChatGLM+Moss
@@ -14,12 +14,12 @@ RUN python3 -m pip install torch --extra-index-url https://download.pytorch.org/
WORKDIR /gpt
RUN git clone --depth=1 https://github.com/binary-husky/gpt_academic.git
WORKDIR /gpt/gpt_academic
-RUN git clone https://github.com/OpenLMLab/MOSS.git request_llm/moss
+RUN git clone https://github.com/OpenLMLab/MOSS.git request_llms/moss
RUN python3 -m pip install -r requirements.txt
-RUN python3 -m pip install -r request_llm/requirements_moss.txt
-RUN python3 -m pip install -r request_llm/requirements_qwen.txt
-RUN python3 -m pip install -r request_llm/requirements_chatglm.txt
-RUN python3 -m pip install -r request_llm/requirements_newbing.txt
+RUN python3 -m pip install -r request_llms/requirements_moss.txt
+RUN python3 -m pip install -r request_llms/requirements_qwen.txt
+RUN python3 -m pip install -r request_llms/requirements_chatglm.txt
+RUN python3 -m pip install -r request_llms/requirements_newbing.txt
diff --git a/docs/GithubAction+JittorLLMs b/docs/GithubAction+JittorLLMs
index dc883bcfcc393dcafed8010e15894e53f4b6cfc2..189eb24431e4778367e08d359949a260e9426194 100644
--- a/docs/GithubAction+JittorLLMs
+++ b/docs/GithubAction+JittorLLMs
@@ -16,12 +16,12 @@ WORKDIR /gpt
RUN git clone --depth=1 https://github.com/binary-husky/gpt_academic.git
WORKDIR /gpt/gpt_academic
RUN python3 -m pip install -r requirements.txt
-RUN python3 -m pip install -r request_llm/requirements_chatglm.txt
-RUN python3 -m pip install -r request_llm/requirements_newbing.txt
-RUN python3 -m pip install -r request_llm/requirements_jittorllms.txt -i https://pypi.jittor.org/simple -I
+RUN python3 -m pip install -r request_llms/requirements_chatglm.txt
+RUN python3 -m pip install -r request_llms/requirements_newbing.txt
+RUN python3 -m pip install -r request_llms/requirements_jittorllms.txt -i https://pypi.jittor.org/simple -I
# 下载JittorLLMs
-RUN git clone https://github.com/binary-husky/JittorLLMs.git --depth 1 request_llm/jittorllms
+RUN git clone https://github.com/binary-husky/JittorLLMs.git --depth 1 request_llms/jittorllms
# 禁用缓存，确保更新代码
ADD "https://www.random.org/cgi-bin/randbyte?nbytes=10&format=h" skipcache
diff --git a/docs/GithubAction+NoLocal+Latex b/docs/GithubAction+NoLocal+Latex
index 516eb8fde31f98331913b6b7c8900fb77ab748c9..6335ee72d4ede9e6f57164ec6fc56baa204bcdcb 100644
--- a/docs/GithubAction+NoLocal+Latex
+++ b/docs/GithubAction+NoLocal+Latex
@@ -4,6 +4,11 @@
# - 3 运行 docker run -v /home/fuqingxu/arxiv_cache:/root/arxiv_cache --rm -it --net=host gpt-academic-nolocal-latex
FROM fuqingxu/python311_texlive_ctex:latest
+ENV PATH "$PATH:/usr/local/texlive/2022/bin/x86_64-linux"
+ENV PATH "$PATH:/usr/local/texlive/2023/bin/x86_64-linux"
+ENV PATH "$PATH:/usr/local/texlive/2024/bin/x86_64-linux"
+ENV PATH "$PATH:/usr/local/texlive/2025/bin/x86_64-linux"
+ENV PATH "$PATH:/usr/local/texlive/2026/bin/x86_64-linux"
# 删除文档文件以节约空间
RUN rm -rf /usr/local/texlive/2023/texmf-dist/doc
@@ -11,12 +16,10 @@ RUN rm -rf /usr/local/texlive/2023/texmf-dist/doc
# 指定路径
WORKDIR /gpt
-RUN pip3 install gradio openai numpy arxiv rich
+RUN pip3 install openai numpy arxiv rich
RUN pip3 install colorama Markdown pygments pymupdf
-RUN pip3 install python-docx moviepy pdfminer
-RUN pip3 install zh_langchain==0.2.1
+RUN pip3 install python-docx pdfminer
RUN pip3 install nougat-ocr
-RUN pip3 install aliyun-python-sdk-core==2.13.3 pyOpenSSL scipy git+https://github.com/aliyun/alibabacloud-nls-python-sdk.git
# 装载项目文件
COPY . .
diff --git a/docs/README.Arabic.md b/docs/README.Arabic.md
new file mode 100644
index 0000000000000000000000000000000000000000..791fb69a03cd6502d01f72cdae0a61c23502442d
--- /dev/null
+++ b/docs/README.Arabic.md
@@ -0,0 +1,344 @@
+
+
+
+> **ملحوظة**
+>
+> تمت ترجمة هذا الملف README باستخدام GPT (بواسطة المكون الإضافي لهذا المشروع) وقد لا تكون الترجمة 100٪ موثوقة، يُرجى التمييز بعناية بنتائج الترجمة.
+>
+> 2023.11.7: عند تثبيت التبعيات، يُرجى اختيار الإصدار المُحدد في `requirements.txt`. الأمر للتثبيت: `pip install -r requirements.txt`.
+
+# 
GPT الأكاديمي
+
+الوظائف (⭐= وظائف مُضافة حديثًا) | الوصف
+--- | ---
+⭐[التوصل لنموذج جديد](https://github.com/binary-husky/gpt_academic/wiki/%E5%A6%82%E4%BD%95%E5%88%87%E6%8D%A2%E6%A8%A1%E5%9E%8B)! | بحث بيدو[تشيان فان](https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Nlks5zkzu) ووينسين[جينرال](https://modelscope.cn/models/qwen/Qwen-7B-Chat/summary)، مختبرات شنغهاي للذكاء الصناعي[شو شينغ](https://github.com/InternLM/InternLM)، إكسنفلام[زينغهو]https://xinghuo.xfyun.cn/)، [LLaMa2](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf)، واجهة بيانية ذكية و3 خدمات إضافية [DALLE3]
+الجودة الفائقة، الترجمة، شرح الكود | الإصلاح الفوري للاخطاء النحوية في الأبحاث وترجمة وتحسين التصريف اللغوي للأكواد
+[اختصارات مخصصة](https://www.bilibili.com/video/BV14s4y1E7jN) | دعم الاختصارات المخصصة
+تصميم قابل للتوسيع | دعم الإضافات القوية المخصصة (الوظائف)، الإضافات قابلة للتحديث بشكل فوري
+[تحليل البرنامج](https://www.bilibili.com/video/BV1cj411A7VW) | [وظائف] التحليل الشجري بناءً على البرنامج من Python/C/C++/Java/Lua/..., أو [التحليل الذاتي](https://www.bilibili.com/video/BV1cj411A7VW)
+قراءة وترجمة الأبحاث | [وظائف] فك تشفير كامل لأوراق البحث بتنسيق LaTeX/PDF وإنشاء مستخلص
+ترجمة وتحسين أوراق اللاتكس | [وظائف] ترجمة أو تحسين الأوراق المكتوبة بلاتكس
+إنشاء تعليقات الدوال دفعة واحدة | [وظائف] إنشاء تعليقات الدوال بدفعة واحدة
+ترجمة Markdown بين اللغتين العربية والإنجليزية | [وظائف] هل رأيت الـ 5 لغات المستخدمة في منشور [README](https://github.com/binary-husky/gpt_academic/blob/master/docs/README_EN.md) ؟
+إنشاء تقرير تحليل الدردشة | [وظائف] إنشاء تقرير ملخص بعد تشغيله
+ترجمة كاملة لأوراق PDF | [وظائف] تحليل الأوراق بتنسيق PDF لتحديد العنوان وملخصها وترجمتها (متعدد الخيوط)
+مساعدة Arxiv | [وظائف] قم بإدخال رابط مقال Arxiv لترجمة الملخص وتحميل ملف PDF
+تصحيح لاتكس بضغطة زر واحدة | [وظائف] إكمال تصحيح لاتكس بناءً على التركيبة النحوية، إخراج همز المقابل للمقارنة PDF
+مساعد بحث Google بنسخة محلية | [وظائف] قم بتقديم رابط لصفحة بحث Google Scholar العشوائي حتى يساعدك GPT في كتابة [الأبحاث المتعلقة](https://www.bilibili.com/video/BV1GP411U7Az/)
+تجميع معلومات الويب + GPT | [وظائف] جمع المعلومات من الويب بشكل سهل للرد على الأسئلة لجعل المعلومات محدثة باستمرار
+⭐ترجمة دقيقة لأوراق Arxiv ([Docker](https://github.com/binary-husky/gpt_academic/pkgs/container/gpt_academic_with_latex)) | [وظائف] ترجمة مقالات Arxiv عالية الجودة بنقرة واحدة، أفضل أداة حاليا للترجمة
+⭐[إدخال الصوت الفوري](https://github.com/binary-husky/gpt_academic/blob/master/docs/use_audio.md) | [وظائف] (غير متزامن) استماع الصوت وقطعه تلقائيًا وتحديد وقت الإجابة تلقائيًا
+عرض الصيغ/الصور/الجداول | يمكن عرض الصيغ بشكل [TEX](https://user-images.githubusercontent.com/96192199/230598842-1d7fcddd-815d-40ee-af60-baf488a199df.png) وأيضًا بتنسيق رسومي، يدعم عرض الصيغ وإبراز الكود
+⭐إضغط على وكيل "شارلوت الذكي" | [وظائف] استكمال الذكاء للكأس الأول للذكاء المكتسب من مايكروسوفت، اكتشاف وتطوير عالمي العميل
+تبديل الواجهة المُظلمة | يمكنك التبديل إلى الواجهة المظلمة بإضافة ```/?__theme=dark``` إلى نهاية عنوان URL في المتصفح
+دعم المزيد من نماذج LLM | دعم لجميع GPT3.5 وGPT4 و[ChatGLM2 في جامعة ثوه في لين](https://github.com/THUDM/ChatGLM2-6B) و[MOSS في جامعة فودان](https://github.com/OpenLMLab/MOSS)
+⭐تحوي انطباعة "ChatGLM2" | يدعم استيراد "ChatGLM2" ويوفر إضافة المساعدة في تعديله
+دعم المزيد من نماذج "LLM"، دعم [نشر الحديس](https://huggingface.co/spaces/qingxu98/gpt-academic) | انضم إلى واجهة "Newbing" (Bing الجديدة)،نقدم نماذج Jittorllms الجديدة تؤيدهم [LLaMA](https://github.com/facebookresearch/llama) و [盘古α](https://openi.org.cn/pangu/)
+⭐حزمة "void-terminal" للشبكة (pip) | قم بطلب كافة وظائف إضافة هذا المشروع في python بدون واجهة رسومية (قيد التطوير)
+⭐PCI-Express لإعلام (PCI) | [وظائف] باللغة الطبيعية، قم بتنفيذ المِهام الأخرى في المشروع
+المزيد من العروض (إنشاء الصور وغيرها)……| شاهد أكثر في نهاية هذا المستند ...
+
+
+
+- شكل جديد (عن طريق تعديل الخيار LAYOUT في `config.py` لقانون التوزيع "اليمين أو اليسار" أو "الأعلى أو الأسفل")
+
+
+
+
+
+
+
+
+
+
+
+
+
إذا كنت بحاجة إلى دعم ChatGLM2 من الجامعة الصينية للاقتصاد وإدارة الأعمال وموس من جامعة فودان كخادم وجودة عالية لطرح الأسئلة، انقر هنا للعرض
+
+
+【خطوات اختيارية】إذا كنت بحاجة إلى دعم جودة عالية لتشات جامعة تسينهوا (ChatGLM2) الصينية وجامعة فودان (MOSS)، يتعين عليك تثبيت تبعيات إضافية (شرط مسبق: التعامل مع Python واستخدام Pytorch وتوفر الحاسوب الشخصي بمواصفات قوية):
+```sh
+# 【خطوات اختيارية 1】دعم جودة عالية لتشات جامعة تسينهوا (ChatGLM2)
+python -m pip install -r request_llms/requirements_chatglm.txt
+
+# 【خطوات اختيارية 2】دعم جودة عالية لتشات جامعة فودان (MOSS)
+python -m pip install -r request_llms/requirements_moss.txt
+git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss # عند تنفيذ هذا الأمر، يجب أن تكون في مسار المشروع الرئيسي
+
+# 【خطوات اختيارية 3】دعم RWKV Runner
+راجع الويكي: https://github.com/binary-husky/gpt_academic/wiki/دليل-تكوين-RWKV
+
+# 【خطوات اختيارية 4】تأكد من أن ملف التكوين config.py يحتوي على النماذج المرجوة، وهناك النماذج المدعومة حاليًا التالية (توجد خطط لتشغيل "jittorllms" في docker فقط):
+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"]
+```
+
+
+
+
+
+
+
+
===>
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
===>
+
+
+
+
GPT Academic Optimization
+
+Feature (⭐ = Recently Added) | Description
+--- | ---
+⭐[Integrate New Models](https://github.com/binary-husky/gpt_academic/wiki/%E5%A6%82%E4%BD%95%E5%88%87%E6%8D%A2%E6%A8%A1%E5%9E%8B) | Baidu [Qianfan](https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Nlks5zkzu) and Wenxin Yiyu, [Tongyi Qianwen](https://modelscope.cn/models/qwen/Qwen-7B-Chat/summary), Shanghai AI-Lab [Shusheng](https://github.com/InternLM/InternLM), Xunfei [Xinghuo](https://xinghuo.xfyun.cn/), [LLaMa2](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf), Zhifu API, DALLE3
+Proofreading, Translation, Code Explanation | One-click proofreading, translation, searching for grammar errors in papers, explaining code
+[Custom Shortcuts](https://www.bilibili.com/video/BV14s4y1E7jN) | Support for custom shortcuts
+Modular Design | Support for powerful [plugins](https://github.com/binary-husky/gpt_academic/tree/master/crazy_functions), plugins support [hot updates](https://github.com/binary-husky/gpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97)
+[Program Profiling](https://www.bilibili.com/video/BV1cj411A7VW) | [Plugin] One-click to profile Python/C/C++/Java/Lua/... project trees or [self-profiling](https://www.bilibili.com/video/BV1cj411A7VW)
+Read Papers, [Translate](https://www.bilibili.com/video/BV1KT411x7Wn) Papers | [Plugin] One-click to interpret full-text latex/pdf papers and generate abstracts
+Full-text Latex [Translation](https://www.bilibili.com/video/BV1nk4y1Y7Js/), [Proofreading](https://www.bilibili.com/video/BV1FT411H7c5/) | [Plugin] One-click translation or proofreading of latex papers
+Batch Comment Generation | [Plugin] One-click batch generation of function comments
+Markdown [Translation](https://www.bilibili.com/video/BV1yo4y157jV/) | [Plugin] Did you see the [README](https://github.com/binary-husky/gpt_academic/blob/master/docs/README_EN.md) in the top five languages?
+Chat Analysis Report Generation | [Plugin] Automatically generates summary reports after running
+[PDF Paper Full-text Translation](https://www.bilibili.com/video/BV1KT411x7Wn) | [Plugin] Extract title & abstract of PDF papers + translate full-text (multi-threaded)
+[Arxiv Helper](https://www.bilibili.com/video/BV1LM4y1279X) | [Plugin] Enter the arxiv article URL to translate the abstract + download PDF with one click
+One-click Proofreading of Latex Papers | [Plugin] Syntax and spelling correction of Latex papers similar to Grammarly + output side-by-side PDF
+[Google Scholar Integration Helper](https://www.bilibili.com/video/BV19L411U7ia) | [Plugin] Given any Google Scholar search page URL, let GPT help you [write related works](https://www.bilibili.com/video/BV1GP411U7Az/)
+Internet Information Aggregation + GPT | [Plugin] One-click to let GPT retrieve information from the Internet to answer questions and keep the information up to date
+⭐Arxiv Paper Fine Translation ([Docker](https://github.com/binary-husky/gpt_academic/pkgs/container/gpt_academic_with_latex)) | [Plugin] One-click [high-quality translation of arxiv papers](https://www.bilibili.com/video/BV1dz4y1v77A/), the best paper translation tool at present
+⭐[Real-time Speech Input](https://github.com/binary-husky/gpt_academic/blob/master/docs/use_audio.md) | [Plugin] Asynchronously [listen to audio](https://www.bilibili.com/video/BV1AV4y187Uy/), automatically segment sentences, and automatically find the best time to answer
+Formula/Image/Table Display | Can simultaneously display formulas in [TeX form and rendered form](https://user-images.githubusercontent.com/96192199/230598842-1d7fcddd-815d-40ee-af60-baf488a199df.png), support formula and code highlighting
+⭐AutoGen Multi-Agent Plugin | [Plugin] Explore the emergence of multi-agent intelligence with Microsoft AutoGen!
+Start Dark [Theme](https://github.com/binary-husky/gpt_academic/issues/173) | Add ```/?__theme=dark``` to the end of the browser URL to switch to the dark theme
+[More LLM Model Support](https://www.bilibili.com/video/BV1wT411p7yf) | It must be great to be served by GPT3.5, GPT4, [THU ChatGLM2](https://github.com/THUDM/ChatGLM2-6B), and [Fudan MOSS](https://github.com/OpenLMLab/MOSS) at the same time, right?
+⭐ChatGLM2 Fine-tuning Model | Support for loading ChatGLM2 fine-tuning models and providing ChatGLM2 fine-tuning assistant plugins
+More LLM Model Access, support for [huggingface deployment](https://huggingface.co/spaces/qingxu98/gpt-academic) | Join NewBing interface (New Bing), introduce Tsinghua [JittorLLMs](https://github.com/Jittor/JittorLLMs) to support [LLaMA](https://github.com/facebookresearch/llama) and [Pangu](https://openi.org.cn/pangu/)
+⭐[void-terminal](https://github.com/binary-husky/void-terminal) pip package | Use this project's all function plugins directly in Python without GUI (under development)
+⭐Void Terminal Plugin | [Plugin] Schedule other plugins of this project directly in natural language
+More New Feature Demonstrations (Image Generation, etc.)...... | See the end of this document ........
+
+
+
+- New interface (modify the LAYOUT option in `config.py` to switch between "left-right layout" and "top-bottom layout")
+
+
+
+
+
+
+
+
+
+
+
+
+
If you need to support THU ChatGLM2, Fudan MOSS, or RWKV Runner as backends, click here to expand
+
+
+【Optional Step】If you need to support THU ChatGLM2 or Fudan MOSS as backends, you need to install additional dependencies (Prerequisites: Familiar with Python + Familiar with Pytorch + Sufficient computer configuration):
+```sh
+# 【Optional Step I】Support THU ChatGLM2. Note: If you encounter the "Call ChatGLM fail unable to load ChatGLM parameters" error, refer to the following: 1. The default installation above is for torch+cpu version. To use cuda, uninstall torch and reinstall torch+cuda; 2. If the model cannot be loaded due to insufficient local configuration, you can modify the model accuracy in request_llm/bridge_chatglm.py. Change AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) to AutoTokenizer.from_pretrained("THUDM/chatglm-6b-int4", trust_remote_code=True)
+python -m pip install -r request_llms/requirements_chatglm.txt
+
+# 【Optional Step II】Support Fudan MOSS
+python -m pip install -r request_llms/requirements_moss.txt
+git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss # When executing this line of code, make sure you are in the root directory of the project
+
+# 【Optional Step III】Support RWKV Runner
+Refer to wiki: https://github.com/binary-husky/gpt_academic/wiki/%E9%80%82%E9%85%8DRWKV-Runner
+
+# 【Optional Step IV】Make sure that the AVAIL_LLM_MODELS in the config.py configuration file includes the expected models. The currently supported models are as follows (jittorllms series currently only supports the docker solution):
+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"]
+```
+
+
+
+
+
+
+
+
===>
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
===>
+
+
+
+
Optimisation académique GPT (GPT Academic)
+
+Fonctionnalités (⭐ = fonctionnalité récemment ajoutée) | Description
+--- | ---
+⭐[Modèles acquis](https://github.com/binary-husky/gpt_academic/wiki/如何切换模型)！ | Baidu [Qianfan](https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Nlks5zkzu) et Wenxin Yiyuan, [Tongyi Qianwen](https://modelscope.cn/models/qwen/Qwen-7B-Chat/summary), Shanghai AI-Lab [Shusheng](https://github.com/InternLM/InternLM), Xunfei [Xinghuo](https://xinghuo.xfyun.cn/), [LLaMa2](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf), Zhifu API, DALLE3
+Amélioration, traduction, explication du code | Correction, traduction, recherche d'erreurs de syntaxe dans les articles, explication du code
+[Raccourcis personnalisés](https://www.bilibili.com/video/BV14s4y1E7jN) | Prise en charge de raccourcis personnalisés
+Conception modulaire | Prise en charge de plugins puissants personnalisables, prise en charge de la [mise à jour à chaud](https://github.com/binary-husky/gpt_academic/wiki/函数插件指南) des plugins
+[Analyse de programme](https://www.bilibili.com/video/BV1cj411A7VW) | [Plugin] Analyse en profondeur d'un arbre de projets Python/C/C++/Java/Lua/... d'un simple clic ou [auto-analyse](https://www.bilibili.com/video/BV1cj411A7VW)
+Lecture d'articles, traduction d'articles | [Plugin] Lecture automatique des articles LaTeX/PDF et génération du résumé
+Traduction complète de [LaTeX](https://www.bilibili.com/video/BV1nk4y1Y7Js/) ou amélioration de leur qualité | [Plugin] Traduction ou amélioration rapide des articles LaTeX
+Génération de commentaires en masse | [Plugin] Génération facile de commentaires de fonctions
+Traduction [chinois-anglais](https://www.bilibili.com/video/BV1yo4y157jV/) du Markdown | [Plugin] Avez-vous vu le [README](https://github.com/binary-husky/gpt_academic/blob/master/docs/README_EN.md) dans les cinq langues ci-dessus ?
+Génération de rapports d'analyse du chat | [Plugin] Génération automatique d'un rapport récapitulatif après l'exécution du chat
+[Fonction de traduction complète des articles PDF](https://www.bilibili.com/video/BV1KT411x7Wn) | [Plugin] Extraction du titre et du résumé d'un article PDF, ainsi que traduction intégrale (multithreading)
+Assistant Arxiv | [Plugin] Saisissez l'URL d'un article Arxiv pour traduire automatiquement le résumé et télécharger le PDF
+Correction automatique d'articles LaTeX | [Plugin] Correction de la grammaire, de l'orthographe et comparaison avec le PDF correspondant, à la manière de Grammarly
+Assistant Google Scholar | [Plugin] Donner l'URL d'une page de recherche Google Scholar pour obtenir de l'aide sur l'écriture des références
+Agrégation d'informations sur Internet + GPT | [Plugin] Obtenez les informations de l'Internet pour répondre aux questions à l'aide de GPT, afin que les informations ne soient jamais obsolètes
+⭐Traduction détaillée des articles Arxiv ([Docker](https://github.com/binary-husky/gpt_academic/pkgs/container/gpt_academic_with_latex)) | [Plugin] Traduction de haute qualité d'articles Arxiv en un clic, le meilleur outil de traduction d'articles à ce jour
+⭐[Saisie orale en temps réel](https://github.com/binary-husky/gpt_academic/blob/master/docs/use_audio.md) | [Plugin] Écoute asynchrone de l'audio, découpage automatique et recherche automatique du meilleur moment pour répondre
+Affichage des formules, images, tableaux | Affichage simultané de la forme [TeX et rendue](https://user-images.githubusercontent.com/96192199/230598842-1d7fcddd-815d-40ee-af60-baf488a199df.png) des formules, prise en charge de la mise en évidence des formules et du code
+⭐Plugin AutoGen multi-agents | [Plugin] Explorez les émergences intelligentes à plusieurs agents avec Microsoft AutoGen !
+Activation du [thème sombre](https://github.com/binary-husky/gpt_academic/issues/173) | Ajouter ```/?__theme=dark``` à l'URL du navigateur pour basculer vers le thème sombre
+Prise en charge de plusieurs modèles LLM | Expérimentez avec GPT 3.5, GPT4, [ChatGLM2 de Tsinghua](https://github.com/THUDM/ChatGLM2-6B), [MOSS de Fudan](https://github.com/OpenLMLab/MOSS) simultanément !
+⭐Modèle ChatGLM2 fine-tuned | Chargez et utilisez un modèle fine-tuned de ChatGLM2, disponible avec un plugin d'assistance
+Prise en charge de plus de modèles LLM, déploiement sur [Huggingface](https://huggingface.co/spaces/qingxu98/gpt-academic) | Ajout de l'interface de connaissance-API, support de [LLaMA](https://github.com/facebookresearch/llama) et [PanGuα](https://openi.org.cn/pangu/)
+⭐Paquet pip [void-terminal](https://github.com/binary-husky/void-terminal) | Accédez à toutes les fonctions et plugins de ce projet directement depuis Python (en cours de développement)
+⭐Plugin terminal du vide | [Plugin] Utilisez un langage naturel pour interagir avec les autres plugins du projet
+Affichage de nouvelles fonctionnalités (génération d'images, etc.) …… | Voir à la fin de ce document ……
+
+
+
+- Nouvelle interface (modifiez l'option LAYOUT dans `config.py` pour basculer entre la disposition "gauche-droite" et "haut-bas")
+
+
+
+
+
+
+
+
+
+
+
+
+
If you need to support Tsinghua ChatGLM2/Fudan MOSS/RWKV as backends, click here to expand
+
+
+[Optional Steps] If you need to support Tsinghua ChatGLM2/Fudan MOSS as backends, you need to install additional dependencies (Prerequisites: Familiar with Python + Have used PyTorch + Sufficient computer configuration):
+```sh
+# [Optional Step I] Support Tsinghua ChatGLM2. Comment on this note: If you encounter the error "Call ChatGLM generated an error and cannot load the parameters of ChatGLM", refer to the following: 1: The default installation is the torch+cpu version. To use cuda, you need to uninstall torch and reinstall torch+cuda; 2: If the model cannot be loaded due to insufficient computer configuration, you can modify the model precision in request_llm/bridge_chatglm.py. Change AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) to AutoTokenizer.from_pretrained("THUDM/chatglm-6b-int4", trust_remote_code=True).
+python -m pip install -r request_llms/requirements_chatglm.txt
+
+# [Optional Step II] Support Fudan MOSS
+python -m pip install -r request_llms/requirements_moss.txt
+git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss # Note: You need to be at the root directory of the project when executing this line of code
+
+# [Optional Step III] Support RWKV Runner
+Refer to the wiki: https://github.com/binary-husky/gpt_academic/wiki/%E9%80%82%E9%85%8DRWKV-Runner
+
+# [Optional Step IV] Make sure that the AVAIL_LLM_MODELS in the config.py configuration file contains the expected models. The currently supported models are as follows (jittorllms series currently only support the docker solution):
+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"]
+```
+
+
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+
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+
===>
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===>
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+
+
+
GPT Academic (GPT Akademisch)
+
+Funktionen (⭐= Kürzlich hinzugefügte Funktion) | Beschreibung
+--- | ---
+⭐[Neues Modell integrieren](https://github.com/binary-husky/gpt_academic/wiki/%E5%A6%82%E4%BD%95%E5%88%87%E6%8D%A2%E6%A8%A1%E5%9E%8B)! | Baidu [Qianfan](https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Nlks5zkzu) und Wenxin Yanyi, [Tongyi Qianwen](https://modelscope.cn/models/qwen/Qwen-7B-Chat/summary), Shanghai AI-Lab [Shusheng](https://github.com/InternLM/InternLM), Xunfei [Xinghuo](https://xinghuo.xfyun.cn/), [LLaMa2](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf), Cognitive Graph API, DALLE3
+Verfeinern, Übersetzen, Codierung erläutern | Ein-Klick-Verfeinerung, Übersetzung, Suche nach grammatikalischen Fehlern in wissenschaftlichen Arbeiten, Erklärung von Code
+[Eigene Tastenkombinationen](https://www.bilibili.com/video/BV14s4y1E7jN) definieren | Eigene Tastenkombinationen definieren
+Modulare Gestaltung | Ermöglicht die Verwendung benutzerdefinierter leistungsstarker [Plugins](https://github.com/binary-husky/gpt_academic/tree/master/crazy_functions), Plugins unterstützen [Hot-Reload](https://github.com/binary-husky/gpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97)
+[Programmanalyse](https://www.bilibili.com/video/BV1cj411A7VW) | [Plugin] Ermöglicht die Erstellung einer Projekthierarchie für Python/C/C++/Java/Lua/... mit nur einem Klick oder [Selbstanalyse](https://www.bilibili.com/video/BV1cj411A7VW)
+Lesen von Forschungsarbeiten, Übersetzen von Forschungsarbeiten | [Plugin] Ermöglicht eine Umwandlung des gesamten Latex-/PDF-Forschungspapiers mit nur einem Klick und generiert eine Zusammenfassung
+Latex-Übersetzung des vollständigen Textes, Ausbesserung | [Plugin] Ermöglicht eine Übersetzung oder Verbesserung der Latex-Forschungsarbeit mit nur einem Klick
+Erzeugen von Batch-Anmerkungen | [Plugin] Erzeugt Funktionserläuterungen in Stapeln
+Markdown- [En-De-Übersetzung](https://www.bilibili.com/video/BV1yo4y157jV/) | [Plugin] Haben Sie die [README](https://github.com/binary-husky/gpt_academic/blob/master/docs/README_EN.md) in den oben genannten 5 Sprachen gesehen?
+Erzeugen eines Chat-Analyseberichts | [Plugin] Generiert einen zusammenfassenden Bericht nach der Ausführung
+PDF-Textübersetzungsmerkmal | [Plugin] Extrahiert Titel und Zusammenfassung des PDF-Dokuments und übersetzt den vollständigen Text (mehrfädig)
+Arxiv-Assistent | [Plugin] Geben Sie die URL eines Arxiv-Artikels ein, um eine Zusammenfassung zu übersetzen und die PDF-Datei herunterzuladen
+Automatische Überprüfung von Latex-Artikeln | [Plugin] Überprüft die Grammatik und Rechtschreibung von Latex-Artikeln nach dem Vorbild von Grammarly und generiert eine PDF-Vergleichsdatei
+Google Scholar Integration Assistant | [Plugin] Geben Sie eine beliebige URL der Google Scholar-Suchseite ein und lassen Sie GPT Ihre [Verwandten Arbeiten](https://www.bilibili.com/video/BV1GP411U7Az/) schreiben
+Internetinformationsaggregation + GPT | [Plugin] Ermöglicht es GPT, Fragen durch das Durchsuchen des Internets zu beantworten und Informationen immer auf dem neuesten Stand zu halten
+⭐Feine Übersetzung von Arxiv-Artikeln ([Docker](https://github.com/binary-husky/gpt_academic/pkgs/container/gpt_academic_with_latex)) | [Plugin] Übersetzt Arxiv-Artikel [mit hoher Qualität](https://www.bilibili.com/video/BV1dz4y1v77A/) mit einem Klick - das beste Übersetzungstool für wissenschaftliche Artikel
+⭐[Echtzeit-Spracheingabe](https://github.com/binary-husky/gpt_academic/blob/master/docs/use_audio.md) | [Plugin] [Asynchrones Lauschen auf Audio-Eingabe](https://www.bilibili.com/video/BV1AV4y187Uy/), automatisches Zerschneiden des Textes, automatische Suche nach dem richtigen Zeitpunkt zur Beantwortung
+Darstellen von Formeln/Bildern/Tabellen | Zeigt Formeln sowohl in [TEX-](https://user-images.githubusercontent.com/96192199/230598842-1d7fcddd-815d-40ee-af60-baf488a199df.png)- als auch in gerenderten Formen an, unterstützt Formeln und Code-Hervorhebung
+⭐AutoGen Multi-Agent Plugin | [Plugin] Erforscht die Möglichkeiten des emergenten Verhaltens von Multi-Agent-Systemen mit Microsoft AutoGen!
+Start im Dark-Theme | Um das Dark-Theme zu aktivieren, fügen Sie ```/?__theme=dark``` am Ende der URL im Browser hinzu
+[Mehrsprachige LLM-Modelle](https://www.bilibili.com/video/BV1wT411p7yf) unterstützt | Es ist sicherlich beeindruckend, von GPT3.5, GPT4, [ChatGLM2 der Tsinghua University](https://github.com/THUDM/ChatGLM2-6B), [MOSS der Fudan University](https://github.com/OpenLMLab/MOSS) bedient zu werden, oder?
+⭐ChatGLM2 Feinabstimmungsmodell | Unterstützt das Laden von ChatGLM2-Feinabstimmungsmodellen und bietet Unterstützung für ChatGLM2-Feinabstimmungsassistenten
+Integration weiterer LLM-Modelle, Unterstützung von [Huggingface-Deployment](https://huggingface.co/spaces/qingxu98/gpt-academic) | Hinzufügen der Newbing-Schnittstelle (neues Bing), Einführung der [Jittorllms der Tsinghua University](https://github.com/Jittor/JittorLLMs) zur Unterstützung von LLaMA und PanGu Alpha
+⭐[void-terminal](https://github.com/binary-husky/void-terminal) Pip-Paket | Verwenden Sie das Projekt in Python direkt, indem Sie das gesamte Funktionsplugin verwenden (in Entwicklung)
+⭐Void-Terminal-Plugin | [Plugin] Verwenden Sie natürliche Sprache, um andere Funktionen dieses Projekts direkt zu steuern
+Weitere Funktionen anzeigen (z. B. Bildgenerierung) …… | Siehe das Ende dieses Dokuments ……
+
+
+
+- Neues Interface (Ändern Sie die LAYOUT-Option in der `config.py`, um zwischen "Links-Rechts-Layout" und "Oben-Unten-Layout" zu wechseln)
+
+
+
+
+
+
+
+
+
+
+
+
+
If you need support for Tsinghua ChatGLM2/Fudan MOSS/RWKV as backend, please click to expand.
+
+
+[Optional] If you need to support Tsinghua ChatGLM2/Fudan MOSS as the backend, you need to install additional dependencies (Prerequisites: Familiar with Python + Have used PyTorch + Strong computer configuration):
+```sh
+# [Optional Step I] Support Tsinghua ChatGLM2. Tsinghua ChatGLM note: If you encounter the error "Call ChatGLM fail cannot load ChatGLM parameters normally", refer to the following: 1: The default installation above is torch+cpu version. To use cuda, you need to uninstall torch and reinstall torch+cuda; 2: If you cannot load the model due to insufficient computer configuration, you can modify the model accuracy in request_llm/bridge_chatglm.py. Change AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) to AutoTokenizer.from_pretrained("THUDM/chatglm-6b-int4", trust_remote_code=True)
+python -m pip install -r request_llms/requirements_chatglm.txt
+
+# [Optional Step II] Support Fudan MOSS
+python -m pip install -r request_llms/requirements_moss.txt
+git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss # When executing this line of code, you must be in the root path of the project
+
+# [Optional Step III] Support RWKV Runner
+Refer to the wiki: https://github.com/binary-husky/gpt_academic/wiki/Support-RWKV-Runner
+
+# [Optional Step IV] Make sure the AVAIL_LLM_MODELS in config.py includes the expected models. The currently supported models are as follows (the jittorllms series only supports the docker solution at present):
+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"]
+```
+
+
+
+
+
+
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+
GPT Ottimizzazione Accademica (GPT Academic)
+
+Funzionalità (⭐ = Nuove funzionalità recenti) | Descrizione
+--- | ---
+⭐[Integrazione di nuovi modelli](https://github.com/binary-husky/gpt_academic/wiki/%E5%A6%82%E4%BD%95%E5%88%87%E6%8D%A2%E6%A8%A1%E5%9E%8B)！ | Baidu [Qianfan](https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Nlks5zkzu) e [Wenxin](https://cloud.baidu.com/doc/GUIDE/5268.9) Intelligence, [Tongyi Qianwen](https://modelscope.cn/models/qwen/Qwen-7B-Chat/summary), Shanghai AI-Lab [bookbrain](https://github.com/InternLM/InternLM), Xunfei [Xinghuo](https://xinghuo.xfyun.cn/), [LLaMa2](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf), Zhipu API, DALLE3
+Revisione, traduzione, spiegazione del codice | Revisione, traduzione, ricerca errori grammaticali nei documenti e spiegazione del codice con un clic
+[Tasti di scelta rapida personalizzati](https://www.bilibili.com/video/BV14s4y1E7jN) | Supporta tasti di scelta rapida personalizzati
+Design modulare | Supporto per plugin personalizzati potenti, i plugin supportano l'[aggiornamento in tempo reale](https://github.com/binary-husky/gpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97)
+[Analisi del codice](https://www.bilibili.com/video/BV1cj411A7VW) | [Plugin] Un clic per analizzare alberi di progetti Python/C/C++/Java/Lua/... o [autoanalisi](https://www.bilibili.com/video/BV1cj411A7VW)
+Lettura di documenti, traduzione di documenti | [Plugin] Un clic per interpretare documenti completi in latex/pdf e generare un riassunto
+Traduzione completa di testi in Latex, revisione completa di testi in Latex | [Plugin] Un clic per tradurre o correggere documenti in latex
+Generazione automatica di commenti in batch | [Plugin] Un clic per generare commenti di funzione in batch
+Traduzione [cinese-inglese](https://www.bilibili.com/video/BV1yo4y157jV/) in Markdown | [Plugin] Hai visto sopra i README in 5 lingue diverse ([Inglese](https://github.com/binary-husky/gpt_academic/blob/master/docs/README_EN.md))?
+Generazione di rapporti di analisi chat | [Plugin] Genera automaticamente un rapporto di sintesi dopo l'esecuzione
+Funzionalità di traduzione di testo completo in PDF | [Plugin] Estrai il titolo e il riassunto dei documenti PDF e traduci tutto il testo (multithreading)
+Aiutante per Arxiv | [Plugin] Inserisci l'URL dell'articolo Arxiv per tradurre riassunto e scaricare PDF in un clic
+Controllo completo dei documenti in Latex | [Plugin] Rileva errori grammaticali e ortografici nei documenti in Latex simile a Grammarly + Scarica un PDF per il confronto
+Assistente per Google Scholar | [Plugin] Dato qualsiasi URL della pagina di ricerca di Google Scholar, fai scrivere da GPT gli *articoli correlati* per te
+Concentrazione delle informazioni di Internet + GPT | [Plugin] [Recupera informazioni da Internet](https://www.bilibili.com/video/BV1om4y127ck) utilizzando GPT per rispondere alle domande e rendi le informazioni sempre aggiornate
+⭐Traduzione accurata di articoli Arxiv ([Docker](https://github.com/binary-husky/gpt_academic/pkgs/container/gpt_academic_with_latex)) | [Plugin] [Traduci articoli Arxiv ad alta qualità](https://www.bilibili.com/video/BV1dz4y1v77A/) con un clic, lo strumento di traduzione degli articoli migliore al mondo al momento
+⭐[Inserimento della conversazione vocale in tempo reale](https://github.com/binary-husky/gpt_academic/blob/master/docs/use_audio.md) | [Plugin] [Ascolta l'audio](https://www.bilibili.com/video/BV1AV4y187Uy/) in modo asincrono, taglia automaticamente le frasi e trova automaticamente il momento giusto per rispondere
+Visualizzazione di formule, immagini, tabelle | Mostra contemporaneamente formule in formato tex e renderizzato, supporta formule e evidenziazione del codice
+⭐Plugin multi-agente AutoGen | [Plugin] Esplora le possibilità dell'emergenza intelligence multi-agente con l'aiuto di Microsoft AutoGen!
+Attiva il tema scuro [qui](https://github.com/binary-husky/gpt_academic/issues/173) | Aggiungi ```/?__theme=dark``` alla fine dell'URL del browser per passare al tema scuro
+Supporto di più modelli LLM | Essere servito contemporaneamente da GPT3.5, GPT4, [ChatGLM2 di Tsinghua](https://github.com/THUDM/ChatGLM2-6B), [MOSS di Fudan](https://github.com/OpenLMLab/MOSS)
+⭐Modello di fine-tuning ChatGLM2 | Supporto per l'importazione del modello di fine-tuning di ChatGLM2, fornendo plug-in di assistenza per il fine tuning di ChatGLM2
+Più supporto per modelli LLM, supporto del [deploy di Huggingface](https://huggingface.co/spaces/qingxu98/gpt-academic) | Aggiungi interfaccia Newbing (Bing Translator), introduce il supporto di [JittorLLMs](https://github.com/Jittor/JittorLLMs) di Tsinghua, supporto per [LLaMA](https://github.com/facebookresearch/llama) e [Panguα](https://openi.org.cn/pangu/)
+⭐Pacchetto pip [void-terminal](https://github.com/binary-husky/void-terminal) | Fornisce funzionalità di tutti i plugin di questo progetto direttamente in Python senza GUI (in sviluppo)
+⭐Plugin terminale virtuale | [Plugin] Richiama altri plugin di questo progetto utilizzando linguaggio naturale
+Altre nuove funzionalità (come la generazione di immagini) ... | Vedi alla fine di questo documento ...
+
+
+
+
+- Nuovo layout (modifica l'opzione LAYOUT in `config.py` per passare tra "layout sinistra / destra" e "layout sopra / sotto")
+
+
+
+
+
+
+
+
+
+
+
+
+
Se desideri utilizzare il backend di ChatGLM2 di Tsinghua/Fudan MOSS/RWKV, fai clic per espandere
+
+
+[Optional] Se desideri utilizzare ChatGLM2 di Tsinghua/Fudan MOSS come backend, è necessario installare ulteriori dipendenze (Requisiti: conoscenza di Python + esperienza con Pytorch + hardware potente):
+```sh
+# [Optional Step I] Supporto per ChatGLM2 di Tsinghua. Note di ChatGLM di Tsinghua: Se si verifica l'errore "Call ChatGLM fail non può caricare i parametri di ChatGLM", fare riferimento a quanto segue: 1: L'installazione predefinita è la versione torch+cpu, per usare cuda è necessario disinstallare torch ed installare nuovamente la versione con torch+cuda; 2: Se il modello non può essere caricato a causa di una configurazione insufficiente, è possibile modificare la precisione del modello in request_llm/bridge_chatglm.py, sostituendo AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) con AutoTokenizer.from_pretrained("THUDM/chatglm-6b-int4", trust_remote_code=True)
+python -m pip install -r request_llms/requirements_chatglm.txt
+
+# [Optional Step II] Supporto per Fudan MOSS
+python -m pip install -r request_llms/requirements_moss.txt
+git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss # Attenzione: eseguire questo comando nella directory principale del progetto
+
+# [Optional Step III] Supporto per RWKV Runner
+Consulta il Wiki: https://github.com/binary-husky/gpt_academic/wiki/%E9%80%82%E9%85%8DRWKV-Runner
+
+# [Optional Step IV] Assicurati che il file di configurazione config.py includa i modelli desiderati. Di seguito sono elencati i modelli attualmente supportati (gli llm di jittorllms supportano solo la soluzione Docker):
+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"]
+```
+
+
+
+
+
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+
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+
===>
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+
GPT 学術最適化 (GPT Academic)
+
+機能（⭐= 最近追加された機能） | 説明
+--- | ---
+⭐[新しいモデルの追加](https://github.com/binary-husky/gpt_academic/wiki/%E5%A6%82%E4%BD%95%E5%88%87%E6%8D%A2%E6%A8%A1%E5%9E%8B)！ | Baidu [Qianfan](https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Nlks5zkzu)とWenxin Yiyu, [Tongyi Qianwen](https://modelscope.cn/models/qwen/Qwen-7B-Chat/summary), Shanghai AI-Lab [Shusheng](https://github.com/InternLM/InternLM), Xunfei [Xinghuo](https://xinghuo.xfyun.cn/), [LLaMa2](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf), Zhantu API, DALLE3
+校正、翻訳、コード解説 | 一括校正、翻訳、論文の文法エラーの検索、コードの解説
+[カスタムショートカットキー](https://www.bilibili.com/video/BV14s4y1E7jN) | カスタムショートカットキーのサポート
+モジュール化された設計 | カスタムでパワフルな[プラグイン](https://github.com/binary-husky/gpt_academic/tree/master/crazy_functions)のサポート、プラグインの[ホットリロード](https://github.com/binary-husky/gpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97)
+[プログラム解析](https://www.bilibili.com/video/BV1cj411A7VW) | [プラグイン] Python/C/C++/Java/Lua/...のプロジェクトツリーを簡単に解析するか、[自己解析](https://www.bilibili.com/video/BV1cj411A7VW)
+論文の読み込み、[翻訳](https://www.bilibili.com/video/BV1KT411x7Wn) | [プラグイン] LaTeX/PDFの論文全文を翻訳して要約を作成する
+LaTeX全文の[翻訳](https://www.bilibili.com/video/BV1nk4y1Y7Js/)、[校正](https://www.bilibili.com/video/BV1FT411H7c5/) | [プラグイン] LaTeX論文を翻訳や校正する
+一括コメント生成 | [プラグイン] 関数コメントを一括生成する
+Markdownの[日英翻訳](https://www.bilibili.com/video/BV1yo4y157jV/) | [プラグイン] 5つの言語（[英語](https://github.com/binary-husky/gpt_academic/blob/master/docs/README_EN.md)など）のREADMEをご覧になりましたか？
+チャット分析レポートの生成 | [プラグイン] 実行後にサマリーレポートを自動生成する
+[PDF論文全文の翻訳機能](https://www.bilibili.com/video/BV1KT411x7Wn) | [プラグイン] PDF論文のタイトルと要約を抽出し、全文を翻訳する（マルチスレッド）
+[Arxivアシスタント](https://www.bilibili.com/video/BV1LM4y1279X) | [プラグイン] arxiv論文のURLを入力すると、要約を翻訳してPDFをダウンロードできます
+LaTeX論文の一括校正 | [プラグイン] Grammarlyのように、LaTeX論文の文法とスペルを修正して対照PDFを出力する
+[Google Scholar統合アシスタント](https://www.bilibili.com/video/BV19L411U7ia) | [プラグイン] 任意のGoogle Scholar検索ページのURLを指定して、関連資料をGPTに書かせることができます
+インターネット情報の集約+GPT | [プラグイン] インターネットから情報を取得して質問に答え、情報が常に最新になるようにします
+⭐Arxiv論文の詳細な翻訳 ([Docker](https://github.com/binary-husky/gpt_academic/pkgs/container/gpt_academic_with_latex)) | [プラグイン] arxiv論文を超高品質で翻訳します。最高の論文翻訳ツールです
+⭐[リアルタイム音声入力](https://github.com/binary-husky/gpt_academic/blob/master/docs/use_audio.md) | [プラグイン] 非同期[音声をリッスン(https://www.bilibili.com/video/BV1AV4y187Uy/)し、自動で文章を区切り、回答のタイミングを自動で探します
+公式/画像/表の表示 | 公式の[tex形式とレンダリング形式](https://user-images.githubusercontent.com/96192199/230598842-1d7fcddd-815d-40ee-af60-baf488a199df.png)を同時に表示し、公式とコードのハイライトをサポートします
+⭐AutoGenマルチエージェントプラグイン | [プラグイン] Microsoft AutoGenを利用して、マルチエージェントのインテリジェントなエマージェンスを探索します
+ダーク[テーマ](https://github.com/binary-husky/gpt_academic/issues/173)を起動 | ブラウザのURLに```/?__theme=dark```を追加すると、ダークテーマに切り替えられます
+[複数のLLMモデル](https://www.bilibili.com/video/BV1wT411p7yf)のサポート | GPT3.5、GPT4、[Tsinghua ChatGLM2](https://github.com/THUDM/ChatGLM2-6B)、[Fudan MOSS](https://github.com/OpenLMLab/MOSS)などを同時に使えるのは最高の感じですよね？
+⭐ChatGLM2ファインチューニングモデル | ChatGLM2ファインチューニングモデルをロードして使用することができ、ChatGLM2ファインチューニングの補助プラグインが用意されています
+さらなるLLMモデルの導入、[HuggingFaceデプロイのサポート](https://huggingface.co/spaces/qingxu98/gpt-academic) | Newbingインターフェース（新しいBing）の追加、Tsinghua [Jittorllms](https://github.com/Jittor/JittorLLMs)の導入、[LLaMA](https://github.com/facebookresearch/llama)および[盤古α](https://openi.org.cn/pangu/)のサポート
+⭐[void-terminal](https://github.com/binary-husky/void-terminal) pipパッケージ | GUIから独立して、Pythonから直接このプロジェクトのすべての関数プラグインを呼び出せます（開発中）
+⭐Void Terminalプラグイン | [プラグイン] 自然言語で、このプロジェクトの他のプラグインを直接実行します
+その他の新機能の紹介（画像生成など）...... | 末尾をご覧ください ......
+
+
+
+
+- もし出力に数式が含まれている場合、TeX形式とレンダリング形式の両方で表示されます。これにより、コピーと読み取りが容易になります。
+
+
+
+
+
+
+
+
清華ChatGLM2/復旦MOSS/RWKVがバックエンドとしてサポートされている場合、ここをクリックして展開してください
+
+
+【オプションステップ】 清華ChatGLM2/復旦MOSSをバックエンドとしてサポートする場合は、さらに追加の依存関係をインストールする必要があります（前提条件：Pythonに精通していて、PytorchとNVIDIA GPUを使用したことがあり、十分なコンピュータの構成を持っていること）：
+
+```sh
+# 【オプションステップI】 清華ChatGLM2のサポートを追加する。 清華ChatGLM2に関する注意点： "Call ChatGLM fail 不能正常加载ChatGLM的参数" のエラーが発生した場合、次の手順を参照してください。 1: デフォルトでインストールされているのはtorch+cpu版です。CUDAを使用するにはtorchをアンインストールしてtorch+cuda版を再インストールする必要があります。 2: モデルをロードできない場合は、request_llm/bridge_chatglm.pyのモデル精度を変更できます。AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True)をAutoTokenizer.from_pretrained("THUDM/chatglm-6b-int4", trust_remote_code=True)に変更します。
+python -m pip install -r request_llms/requirements_chatglm.txt
+
+# 【オプションステップII】 復旦MOSSのサポートを追加する
+python -m pip install -r request_llms/requirements_moss.txt
+git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss # このコマンドを実行するときは、プロジェクトのルートパスである必要があります。
+
+# 【オプションステップIII】 RWKV Runnerのサポートを追加する
+Wikiを参照してください: https://github.com/binary-husky/gpt_academic/wiki/%E9%80%82%E9%85%8DRWKV-Runner
+
+# 【オプションステップIV】 config.py設定ファイルに、以下のすべてのモデルが含まれていることを確認します。以下のモデルがすべてサポートされています（jittorllmsはDockerのみサポートされています）：
+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"]
+```
+
+
+
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+
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+
===>
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+
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===>
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+
+
+
GPT 학술 최적화 (GPT Academic)
+
+기능 (⭐= 최근 추가 기능) | 설명
+--- | ---
+⭐[새 모델 추가](https://github.com/binary-husky/gpt_academic/wiki/%E5%A6%82%E4%BD%95%E5%88%87%E6%8D%A2%E6%A8%A1%E5%9E%8B)! | Baidu [Qianfan](https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Nlks5zkzu)와 Wenxin Yiyan, [Tongyi Qianwen](https://modelscope.cn/models/qwen/Qwen-7B-Chat/summary), Shanghai AI-Lab [Shusheng](https://github.com/InternLM/InternLM), Xunfei [Star](https://xinghuo.xfyun.cn/), [LLaMa2](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf), Zhipu API, DALLE3
+문체 개선, 번역, 코드 설명 | 일괄적인 문체 개선, 번역, 논문 문법 오류 탐색, 코드 설명
+[사용자 정의 단축키](https://www.bilibili.com/video/BV14s4y1E7jN) | 사용자 정의 단축키 지원
+모듈화 설계 | 사용자 정의 가능한 강력한 [플러그인](https://github.com/binary-husky/gpt_academic/tree/master/crazy_functions) 지원, 플러그인 지원 [핫 업데이트](https://github.com/binary-husky/gpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97)
+[프로그램 분석](https://www.bilibili.com/video/BV1cj411A7VW) | [플러그인] 한 번에 Python/C/C++/Java/Lua/... 프로젝트 트리를 분석하거나 [자체 분석](https://www.bilibili.com/video/BV1cj411A7VW)
+논문 읽기, 논문 [번역](https://www.bilibili.com/video/BV1KT411x7Wn) | [플러그인] LaTeX/PDF 논문 전문을 읽고 요약 생성
+LaTeX 전체 [번역](https://www.bilibili.com/video/BV1nk4y1Y7Js/), [개선](https://www.bilibili.com/video/BV1FT411H7c5/) | [플러그인] LaTeX 논문 번역 또는 개선
+일괄 주석 생성 | [플러그인] 함수 주석 일괄 생성
+Markdown [한 / 영 번역](https://www.bilibili.com/video/BV1yo4y157jV/) | 위의 5개 언어로 작성된 [README](https://github.com/binary-husky/gpt_academic/blob/master/docs/README_EN.md)를 살펴보셨나요?
+채팅 분석 보고서 생성 | [플러그인] 실행 후 요약 보고서 자동 생성
+[PDF 논문 전체 번역](https://www.bilibili.com/video/BV1KT411x7Wn) 기능 | [플러그인] PDF 논문 제목 및 요약 추출 + 전체 번역 (멀티 스레드)
+[Arxiv 도우미](https://www.bilibili.com/video/BV1LM4y1279X) | [플러그인] arxiv 논문 url 입력시 요약 번역 + PDF 다운로드
+LaTeX 논문 일괄 교정 | [플러그인] Grammarly를 모사하여 LaTeX 논문에 대한 문법 및 맞춤법 오류 교정 + 대조 PDF 출력
+[Google 학술 통합 도우미](https://www.bilibili.com/video/BV19L411U7ia) | 임의의 Google 학술 검색 페이지 URL을 지정하여 gpt가 [related works를 작성](https://www.bilibili.com/video/BV1GP411U7Az/)하게 해주세요.
+인터넷 정보 집계 + GPT | [플러그인] [인터넷에서 정보를 가져와서](https://www.bilibili.com/video/BV1om4y127ck) 질문에 대답하도록 GPT를 자동화하세요. 정보가 절대로 오래되지 않도록 해줍니다.
+⭐Arxiv 논문 세심한 번역 ([Docker](https://github.com/binary-husky/gpt_academic/pkgs/container/gpt_academic_with_latex)) | [플러그인] [arxiv 논문을 고품질 번역으로](https://www.bilibili.com/video/BV1dz4y1v77A/) 번역하는 최고의 도구
+⭐[실시간 음성 대화 입력](https://github.com/binary-husky/gpt_academic/blob/master/docs/use_audio.md) | [플러그인] 비동기적으로 [오디오를 모니터링](https://www.bilibili.com/video/BV1AV4y187Uy/)하여 문장을 자동으로 분절하고 대답 시기를 자동으로 찾습니다.
+수식/이미지/표 표시 | [tex 형식 및 렌더링 형식](https://user-images.githubusercontent.com/96192199/230598842-1d7fcddd-815d-40ee-af60-baf488a199df.png)의 수식을 동시에 표시하며, 수식 및 코드 하이라이트 지원
+⭐AutoGen multi-agent 플러그인 | [플러그인] Microsoft AutoGen을 활용하여 여러 개의 에이전트가 지능적으로 발생하는 가능성을 탐색하세요!
+다크 모드 주제 지원 | 브라우저의 URL 뒤에 ```/?__theme=dark```를 추가하여 다크 모드로 전환하세요.
+[다양한 LLM 모델](https://www.bilibili.com/video/BV1wT411p7yf) 지원 | GPT3.5, GPT4, [Tsinghua ChatGLM2](https://github.com/THUDM/ChatGLM2-6B), [Fudan MOSS](https://github.com/OpenLMLab/MOSS)을 함께 사용하는 느낌은 좋을 것입니다, 그렇지 않습니까?
+⭐ChatGLM2 fine-tuned 모델 | ChatGLM2 fine-tuned 모델 로드를 지원하며, ChatGLM2 fine-tuned 보조 플러그인 제공
+더 많은 LLM 모델 연결, [huggingface 배포](https://huggingface.co/spaces/qingxu98/gpt-academic) 지원 | Newbing 인터페이스(신 밍), Tsinghua [Jittorllms](https://github.com/Jittor/JittorLLMs) 도입, [LLaMA](https://github.com/facebookresearch/llama)와 [Pangu-alpha](https://openi.org.cn/pangu/)를 지원합니다.
+⭐[void-terminal](https://github.com/binary-husky/void-terminal) 패키지 | GUI에서 독립, Python에서 이 프로젝트의 모든 함수 플러그인을 직접 호출 (개발 중)
+⭐Void 터미널 플러그인 | [플러그인] 자연어로 이 프로젝트의 다른 플러그인을 직접 영속합니다.
+기타 새로운 기능 소개 (이미지 생성 등) …… | 본 문서 맨 끝 참조 ……
+
+
+
+- 새로운 인터페이스(`config.py`의 LAYOUT 옵션 수정으로 "왼쪽-오른쪽 레이아웃"과 "위-아래 레이아웃"을 전환할 수 있음)
+
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+
Click here to expand if you need support for Tsinghua ChatGLM2/Fudan MOSS/RWKV backend
+
+
+[Optional Step] If you need support for Tsinghua ChatGLM2/Fudan MOSS as the backend, you need to install additional dependencies (Prerequisites: Familiar with Python + Have used Pytorch + Sufficient computer configuration):
+```sh
+# [Optional Step I] Support for Tsinghua ChatGLM2. Note for Tsinghua ChatGLM: If you encounter the error "Call ChatGLM fail cannot load ChatGLM parameters", refer to the following: 1: The default installation above is torch+cpu version. To use cuda, uninstall torch and reinstall torch+cuda; 2: If you cannot load the model due to insufficient computer configuration, you can modify the model precision in request_llm/bridge_chatglm.py, change AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) to AutoTokenizer.from_pretrained("THUDM/chatglm-6b-int4", trust_remote_code=True)
+python -m pip install -r request_llms/requirements_chatglm.txt
+
+# [Optional Step II] Support for Fudan MOSS
+python -m pip install -r request_llms/requirements_moss.txt
+git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss # When executing this line of code, make sure you are in the project root path
+
+# [Optional Step III] Support for RWKV Runner
+Refer to the wiki: https://github.com/binary-husky/gpt_academic/wiki/%E9%80%82%E9%85%8DRWKV-Runner
+
+# [Optional Step IV] Make sure that the AVAIL_LLM_MODELS in the config.py configuration file includes the expected models. The currently supported models are as follows (the jittorllms series only supports the docker solution):
+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"]
+```
+
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GPT Acadêmico
+
+Funcionalidades (⭐= funcionalidade recentemente adicionada) | Descrição
+--- | ---
+⭐[Integração com novos modelos](https://github.com/binary-husky/gpt_academic/wiki/%E5%A6%82%E4%BD%95%E5%88%87%E6%8D%A2%E6%A8%A1%E5%9E%8B)！ | [Qianfan](https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Nlks5zkzu) da Baidu, Wenxin e [Tongyi Qianwen](https://modelscope.cn/models/qwen/Qwen-7B-Chat/summary), [Shusheng](https://github.com/InternLM/InternLM) da Shanghai AI-Lab, [Xinghuo](https://xinghuo.xfyun.cn/) da Iflytek, [LLaMa2](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf), Zhipu API, DALLE3
+Aprimoramento, tradução, explicação de códigos | Aprimoramento com um clique, tradução, busca de erros gramaticais em artigos e explicação de códigos
+[Atalhos de teclado personalizados](https://www.bilibili.com/video/BV14s4y1E7jN) | Suporte para atalhos de teclado personalizados
+Design modular | Suporte a plugins poderosos e personalizáveis, plugins com suporte a [atualização a quente](https://github.com/binary-husky/gpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97)
+[Análise de código](https://www.bilibili.com/video/BV1cj411A7VW) | [Plugin] Análise instantânea da estrutura de projetos em Python/C/C++/Java/Lua/... ou [autoanálise](https://www.bilibili.com/video/BV1cj411A7VW)
+Leitura de artigos, [tradução](https://www.bilibili.com/video/BV1KT411x7Wn) de artigos | [Plugin] Interpretação instantânea de artigos completos em latex/pdf e geração de resumos
+Tradução completa de artigos em latex [PDF](https://www.bilibili.com/video/BV1nk4y1Y7Js/), [aprimoramento](https://www.bilibili.com/video/BV1FT411H7c5/) | [Plugin] Tradução completa ou aprimoramento de artigos em latex com um clique
+Geração em lote de comentários | [Plugin] Geração em lote de comentários de funções com um clique
+Tradução (inglês-chinês) de Markdown | [Plugin] Você já viu o [README](https://github.com/binary-husky/gpt_academic/blob/master/docs/README_EN.md) nas 5 línguas acima?
+Criação de relatório de análise de bate-papo | [Plugin] Geração automática de relatório de resumo após a execução
+Tradução [completa de artigos em PDF](https://www.bilibili.com/video/BV1KT411x7Wn) | [Plugin] Extração de título e resumo de artigos em PDF + tradução completa (multithreading)
+Auxiliar Arxiv | [Plugin] Insira o URL de um artigo Arxiv para traduzir o resumo + baixar o PDF com um clique
+Correção automática de artigos em latex | [Plugin] Correções gramaticais e ortográficas de artigos em latex semelhante ao Grammarly + saída PDF comparativo
+Auxiliar Google Scholar | [Plugin] Insira qualquer URL da busca do Google Acadêmico e deixe o GPT [escrever trabalhos relacionados](https://www.bilibili.com/video/BV1GP411U7Az/) para você
+Agregação de informações da Internet + GPT | [Plugin] Capturar informações da Internet e obter respostas de perguntas com o GPT em um clique, para que as informações nunca fiquem desatualizadas
+⭐Tradução refinada de artigos do Arxiv ([Docker](https://github.com/binary-husky/gpt_academic/pkgs/container/gpt_academic_with_latex)) | [Plugin] Tradução de alta qualidade de artigos do Arxiv com um clique, a melhor ferramenta de tradução de artigos atualmente
+⭐Entrada de conversa de voz em tempo real | [Plugin] Monitoramento de áudio [assíncrono](https://www.bilibili.com/video/BV1AV4y187Uy/), segmentação automática de frases, detecção automática de momentos de resposta
+Exibição de fórmulas, imagens e tabelas | Exibição de fórmulas em formato tex e renderizadas simultaneamente, suporte a fórmulas e destaque de código
+⭐Plugin AutoGen para vários agentes | [Plugin] Explore a emergência de múltiplos agentes com o AutoGen da Microsoft!
+Ativar o tema escuro | Adicione ```/?__theme=dark``` ao final da URL para alternar para o tema escuro
+Suporte a múltiplos modelos LLM | Ser atendido simultaneamente pelo GPT3.5, GPT4, [ChatGLM2](https://github.com/THUDM/ChatGLM2-6B) do Tsinghua University e [MOSS](https://github.com/OpenLMLab/MOSS) da Fudan University se sente incrível, não é mesmo?
+⭐Modelo de ajuste fino ChatGLM2 | Suporte para carregar o modelo ChatGLM2 ajustado e fornecer plugins de assistência ao ajuste fino do ChatGLM2
+Mais modelos LLM e suporte para [implantação pela HuggingFace](https://huggingface.co/spaces/qingxu98/gpt-academic) | Integração com a interface Newbing (Bing novo), introdução do [Jittorllms](https://github.com/Jittor/JittorLLMs) da Tsinghua University com suporte a [LLaMA](https://github.com/facebookresearch/llama) e [Panguα](https://openi.org.cn/pangu/)
+⭐Pacote pip [void-terminal](https://github.com/binary-husky/void-terminal) | Chame todas as funções plugins deste projeto diretamente em Python, sem a GUI (em desenvolvimento)
+⭐Plugin Terminal do Vácuo | [Plugin] Chame outros plugins deste projeto diretamente usando linguagem natural
+Apresentação de mais novas funcionalidades (geração de imagens, etc.) ... | Veja no final deste documento ...
+
+
+
+
+- Nova interface (altere a opção LAYOUT em `config.py` para alternar entre os "Layouts de lado a lado" e "Layout de cima para baixo")
+
+
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+
Se você quiser suporte para o ChatGLM2 do THU/ MOSS do Fudan/RWKV como backend, clique para expandir
+
+
+[Opcional] Se você quiser suporte para o ChatGLM2 do THU/ MOSS do Fudan, precisará instalar dependências extras (pré-requisitos: familiarizado com o Python + já usou o PyTorch + o computador tem configuração suficiente):
+```sh
+# [Opcional Passo I] Suporte para ChatGLM2 do THU. Observações sobre o ChatGLM2 do THU: Se você encontrar o erro "Call ChatGLM fail 不能正常加载ChatGLM的参数" (Falha ao chamar o ChatGLM, não é possível carregar os parâmetros do ChatGLM), consulte o seguinte: 1: A versão instalada por padrão é a versão torch+cpu. Se você quiser usar a versão cuda, desinstale o torch e reinstale uma versão com torch+cuda; 2: Se a sua configuração não for suficiente para carregar o modelo, você pode modificar a precisão do modelo em request_llm/bridge_chatglm.py, alterando todas as ocorrências de AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) para AutoTokenizer.from_pretrained("THUDM/chatglm-6b-int4", trust_remote_code=True)
+python -m pip install -r request_llms/requirements_chatglm.txt
+
+# [Opcional Passo II] Suporte para MOSS do Fudan
+python -m pip install -r request_llms/requirements_moss.txt
+git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss # Observe que você deve estar no diretório raiz do projeto ao executar este comando
+
+# [Opcional Passo III] Suporte para RWKV Runner
+Consulte a página Wiki: https://github.com/binary-husky/gpt_academic/wiki/%E9%80%82%E9%85%8DRWKV-Runner
+
+# [Opcional Passo IV] Verifique se o arquivo de configuração config.py contém os modelos desejados, os modelos compatíveis são os seguintes (a série jittorllms suporta apenas a solução Docker):
+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"]
+```
+
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+
GPT Academic (GPT Академический)
+
+Функции (⭐= Недавно добавленные функции) | Описание
+--- | ---
+⭐[Подключение новой модели](https://github.com/binary-husky/gpt_academic/wiki/%E5%A6%82%E4%BD%95%E5%88%87%E6%8D%A2%E6%A8%A1%E5%9E%8B)！ | Baidu [QianFan](https://cloud.baidu.com/doc/WENXINWORKSHOP/s/Nlks5zkzu) и WenxinYiYan, [TongYiQianWen](https://modelscope.cn/models/qwen/Qwen-7B-Chat/summary), Shanghai AI-Lab [ShuSheng](https://github.com/InternLM/InternLM), Xunfei [XingHuo](https://xinghuo.xfyun.cn/), [LLaMa2](https://huggingface.co/meta-llama/Llama-2-7b-chat-hf), ZhiPu API, DALLE3
+Улучшение, перевод, объяснение кода | Одним нажатием выполнить поиск синтаксических ошибок в научных статьях, переводить, объяснять код
+[Настройка горячих клавиш](https://www.bilibili.com/video/BV14s4y1E7jN) | Поддержка настройки горячих клавиш
+Модульный дизайн | Поддержка настраиваемых мощных [плагинов](https://github.com/binary-husky/gpt_academic/tree/master/crazy_functions), плагины поддерживают [горячую замену](https://github.com/binary-husky/gpt_academic/wiki/%E5%87%BD%E6%95%B0%E6%8F%92%E4%BB%B6%E6%8C%87%E5%8D%97)
+[Профилирование кода](https://www.bilibili.com/video/BV1cj411A7VW) | [Плагин] Одним нажатием можно профилировать дерево проекта Python/C/C++/Java/Lua/... или [проанализировать самого себя](https://www.bilibili.com/video/BV1cj411A7VW)
+Просмотр статей, перевод статей | [Плагин] Одним нажатием прочитать полный текст статьи в формате LaTeX/PDF и сгенерировать аннотацию
+Перевод LaTeX статей, [улучшение](https://www.bilibili.com/video/BV1FT411H7c5/)| [Плагин] Одним нажатием перевести или улучшить статьи в формате LaTeX
+Генерация пакетного комментария | [Плагин] Одним нажатием сгенерировать многострочный комментарий к функции
+Перевод Markdown на английский и китайский | [Плагин] Вы видели документацию на сверху на пяти языках? [README](https://github.com/binary-husky/gpt_academic/blob/master/docs/README_EN.md)`
+Анализ и создание отчета в формате чата | [Плагин] Автоматически генерируйте сводный отчет после выполнения
+Функция перевода полноценной PDF статьи | [Плагин] Изъять название и аннотацию статьи из PDF + переводить полный текст (многопоточно)
+[Arxiv помощник](https://www.bilibili.com/video/BV1LM4y1279X) | [Плагин] Просто введите URL статьи на arXiv, чтобы одним нажатием выполнить перевод аннотации + загрузить PDF
+Одним кликом проверить статью на LaTeX | [Плагин] Проверка грамматики и правописания статьи LaTeX, добавление PDF в качестве справки
+[Помощник Google Scholar](https://www.bilibili.com/video/BV19L411U7ia) | [Плагин] Создайте "related works" с помощью Google Scholar URL по вашему выбору.
+Агрегирование интернет-информации + GPT | [Плагин] [GPT получает информацию из интернета](https://www.bilibili.com/video/BV1om4y127ck) и отвечает на вопросы, чтобы информация никогда не устаревала
+⭐Точный перевод статей Arxiv ([Docker](https://github.com/binary-husky/gpt_academic/pkgs/container/gpt_academic_with_latex)) | [Плагин] [Переводите статьи Arxiv наивысшего качества](https://www.bilibili.com/video/BV1dz4y1v77A/) всего одним нажатием. Сейчас это лучший инструмент для перевода научных статей
+⭐[Реальное время ввода голосом](https://github.com/binary-husky/gpt_academic/blob/master/docs/use_audio.md) | [Плагин] Асинхронно [слушать аудио](https://www.bilibili.com/video/BV1AV4y187Uy/), автоматически разбивать на предложения, автоматически находить момент для ответа
+Отображение формул/изображений/таблиц | Поддержка отображения формул в форме [tex и рендеринга](https://user-images.githubusercontent.com/96192199/230598842-1d7fcddd-815d-40ee-af60-baf488a199df.png), поддержка подсветки синтаксиса формул и кода
+⭐Плагин AutoGen для множества интеллектуальных агентов | [Плагин] Используйте Microsoft AutoGen для исследования возможностей интеллектуального всплытия нескольких агентов!
+Запуск [темной темы](https://github.com/binary-husky/gpt_academic/issues/173) | Добавьте `/?__theme=dark` в конец URL в браузере, чтобы переключиться на темную тему
+[Поддержка нескольких моделей LLM](https://www.bilibili.com/video/BV1wT411p7yf) | Быть обслуживаемым GPT3.5, GPT4, [ChatGLM2 из Цинхуа](https://github.com/THUDM/ChatGLM2-6B), [MOSS из Фуданя](https://github.com/OpenLMLab/MOSS) одновременно должно быть очень приятно, не так ли?
+⭐Модель ChatGLM2 Fine-tune | Поддержка загрузки модели ChatGLM2 Fine-tune, предоставляет вспомогательный плагин ChatGLM2 Fine-tune
+Больше моделей LLM, поддержка [развертывания huggingface](https://huggingface.co/spaces/qingxu98/gpt-academic) | Включение интерфейса Newbing (новый Bing), введение поддержки китайских [Jittorllms](https://github.com/Jittor/JittorLLMs) для поддержки [LLaMA](https://github.com/facebookresearch/llama) и [Panguα](https://openi.org.cn/pangu/)
+⭐Пакет pip [void-terminal](https://github.com/binary-husky/void-terminal) | Без GUI вызывайте все функциональные плагины этого проекта прямо из Python (разрабатывается)
+⭐Плагин пустого терминала | [Плагин] Используя естественный язык, напрямую распоряжайтесь другими плагинами этого проекта
+Больше новых функций (генерация изображений и т. д.) ... | Смотрите в конце этого документа ...
+
+
+
+- Новый интерфейс (изменение опции LAYOUT в `config.py` позволяет переключиться между "расположением слева и справа" и "расположением сверху и снизу")
+
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+
Если вам нужна поддержка ChatGLM2 от Цинхуа/MOSS от Фуданя/Раннера RWKV как бэкенда, нажмите, чтобы развернуть
+
+
+【Опциональный шаг】Если вам нужна поддержка ChatGLM2 от Цинхуа/Сервиса MOSS от Фуданя, вам понадобится дополнительно установить дополнительные зависимости (предполагается, что вы знакомы с Python + PyTorch + у вас достаточно мощный компьютер):
+```sh
+# 【Опциональный шаг I】Поддержка ChatGLM2 от Цинхуа. Примечание к ChatGLM от Цинхуа: Если вы столкнулись с ошибкой "Call ChatGLM fail 不能正常加载ChatGLM的参数", обратите внимание на следующее: 1: По умолчанию установлена версия torch+cpu, для использования cuda необходимо удалить torch и установить версию torch+cuda; 2: Если вы не можете загрузить модель из-за недостаточной мощности компьютера, вы можете изменить точность модели в файле request_llm/bridge_chatglm.py, заменив AutoTokenizer.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True) на AutoTokenizer.from_pretrained("THUDM/chatglm-6b-int4", trust_remote_code=True)
+python -m pip install -r request_llms/requirements_chatglm.txt
+
+# 【Опциональный шаг II】Поддержка MOSS от Фуданя
+python -m pip install -r request_llms/requirements_moss.txt
+git clone --depth=1 https://github.com/OpenLMLab/MOSS.git request_llms/moss # Обратите внимание, что когда вы запускаете эту команду, вы должны находиться в корневой папке проекта
+
+# 【Опциональный шаг III】Поддержка RWKV Runner
+Смотрите вики: https://github.com/binary-husky/gpt_academic/wiki/Поддержка-RWKV-Runner
+
+# 【Опциональный шаг IV】Убедитесь, что config.py содержит все нужные вам модели. Пример:
+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"]
+```
+
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+
\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
+ return_string_collect.append( f"【{str(models[i])} 说】: {future.result()} " )
+
+ window_mutex[-1] = False # stop mutex thread
+ res = '
\n\n---\n\n'.join(return_string_collect)
+ return res
+
+
+def predict(inputs, llm_kwargs, *args, **kwargs):
+ """
+ 发送至LLM，流式获取输出。
+ 用于基础的对话功能。
+ inputs 是本次问询的输入
+ top_p, temperature是LLM的内部调优参数
+ history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
+ chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
+ additional_fn代表点击的哪个按钮，按钮见functional.py
+ """
+
+ 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
+ yield from method(inputs, llm_kwargs, *args, **kwargs)
+
diff --git a/request_llms/bridge_chatglm.py b/request_llms/bridge_chatglm.py
new file mode 100644
index 0000000000000000000000000000000000000000..c58495dccfc7d64f194b5f6904b6660141c41cad
--- /dev/null
+++ b/request_llms/bridge_chatglm.py
@@ -0,0 +1,78 @@
+model_name = "ChatGLM"
+cmd_to_install = "`pip install -r request_llms/requirements_chatglm.txt`"
+
+
+from toolbox import get_conf, ProxyNetworkActivate
+from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns
+
+
+
+# ------------------------------------------------------------------------------------------------------------------------
+# 🔌💻 Local Model
+# ------------------------------------------------------------------------------------------------------------------------
+class GetGLM2Handle(LocalLLMHandle):
+
+ def load_model_info(self):
+ # 🏃♂️🏃♂️🏃♂️ 子进程执行
+ self.model_name = model_name
+ self.cmd_to_install = cmd_to_install
+
+ def load_model_and_tokenizer(self):
+ # 🏃♂️🏃♂️🏃♂️ 子进程执行
+ import os, glob
+ import os
+ import platform
+ from transformers import AutoModel, AutoTokenizer
+ LOCAL_MODEL_QUANT, device = get_conf('LOCAL_MODEL_QUANT', 'LOCAL_MODEL_DEVICE')
+
+ if LOCAL_MODEL_QUANT == "INT4": # INT4
+ _model_name_ = "THUDM/chatglm2-6b-int4"
+ elif LOCAL_MODEL_QUANT == "INT8": # INT8
+ _model_name_ = "THUDM/chatglm2-6b-int8"
+ else:
+ _model_name_ = "THUDM/chatglm2-6b" # FP16
+
+ with ProxyNetworkActivate('Download_LLM'):
+ chatglm_tokenizer = AutoTokenizer.from_pretrained(_model_name_, trust_remote_code=True)
+ if device=='cpu':
+ chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True).float()
+ else:
+ chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True).half().cuda()
+ chatglm_model = chatglm_model.eval()
+
+ self._model = chatglm_model
+ self._tokenizer = chatglm_tokenizer
+ return self._model, self._tokenizer
+
+ def llm_stream_generator(self, **kwargs):
+ # 🏃♂️🏃♂️🏃♂️ 子进程执行
+ def adaptor(kwargs):
+ query = kwargs['query']
+ max_length = kwargs['max_length']
+ top_p = kwargs['top_p']
+ temperature = kwargs['temperature']
+ history = kwargs['history']
+ return query, max_length, top_p, temperature, history
+
+ query, max_length, top_p, temperature, history = adaptor(kwargs)
+
+ for response, history in self._model.stream_chat(self._tokenizer,
+ query,
+ history,
+ max_length=max_length,
+ top_p=top_p,
+ temperature=temperature,
+ ):
+ yield response
+
+ def try_to_import_special_deps(self, **kwargs):
+ # import something that will raise error if the user does not install requirement_*.txt
+ # 🏃♂️🏃♂️🏃♂️ 主进程执行
+ import importlib
+ # importlib.import_module('modelscope')
+
+
+# ------------------------------------------------------------------------------------------------------------------------
+# 🔌💻 GPT-Academic Interface
+# ------------------------------------------------------------------------------------------------------------------------
+predict_no_ui_long_connection, predict = get_local_llm_predict_fns(GetGLM2Handle, model_name)
\ No newline at end of file
diff --git a/request_llms/bridge_chatglm3.py b/request_llms/bridge_chatglm3.py
new file mode 100644
index 0000000000000000000000000000000000000000..3caa4769d39ae8f56780caf43ddff6373600410d
--- /dev/null
+++ b/request_llms/bridge_chatglm3.py
@@ -0,0 +1,77 @@
+model_name = "ChatGLM3"
+cmd_to_install = "`pip install -r request_llms/requirements_chatglm.txt`"
+
+
+from toolbox import get_conf, ProxyNetworkActivate
+from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns
+
+
+
+# ------------------------------------------------------------------------------------------------------------------------
+# 🔌💻 Local Model
+# ------------------------------------------------------------------------------------------------------------------------
+class GetGLM3Handle(LocalLLMHandle):
+
+ def load_model_info(self):
+ # 🏃♂️🏃♂️🏃♂️ 子进程执行
+ self.model_name = model_name
+ self.cmd_to_install = cmd_to_install
+
+ def load_model_and_tokenizer(self):
+ # 🏃♂️🏃♂️🏃♂️ 子进程执行
+ from transformers import AutoModel, AutoTokenizer
+ import os, glob
+ import os
+ import platform
+ LOCAL_MODEL_QUANT, device = get_conf('LOCAL_MODEL_QUANT', 'LOCAL_MODEL_DEVICE')
+
+ if LOCAL_MODEL_QUANT == "INT4": # INT4
+ _model_name_ = "THUDM/chatglm3-6b-int4"
+ elif LOCAL_MODEL_QUANT == "INT8": # INT8
+ _model_name_ = "THUDM/chatglm3-6b-int8"
+ else:
+ _model_name_ = "THUDM/chatglm3-6b" # FP16
+ with ProxyNetworkActivate('Download_LLM'):
+ chatglm_tokenizer = AutoTokenizer.from_pretrained(_model_name_, trust_remote_code=True)
+ if device=='cpu':
+ chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True, device='cpu').float()
+ else:
+ chatglm_model = AutoModel.from_pretrained(_model_name_, trust_remote_code=True, device='cuda')
+ chatglm_model = chatglm_model.eval()
+
+ self._model = chatglm_model
+ self._tokenizer = chatglm_tokenizer
+ return self._model, self._tokenizer
+
+ def llm_stream_generator(self, **kwargs):
+ # 🏃♂️🏃♂️🏃♂️ 子进程执行
+ def adaptor(kwargs):
+ query = kwargs['query']
+ max_length = kwargs['max_length']
+ top_p = kwargs['top_p']
+ temperature = kwargs['temperature']
+ history = kwargs['history']
+ return query, max_length, top_p, temperature, history
+
+ query, max_length, top_p, temperature, history = adaptor(kwargs)
+
+ for response, history in self._model.stream_chat(self._tokenizer,
+ query,
+ history,
+ max_length=max_length,
+ top_p=top_p,
+ temperature=temperature,
+ ):
+ yield response
+
+ def try_to_import_special_deps(self, **kwargs):
+ # import something that will raise error if the user does not install requirement_*.txt
+ # 🏃♂️🏃♂️🏃♂️ 主进程执行
+ import importlib
+ # importlib.import_module('modelscope')
+
+
+# ------------------------------------------------------------------------------------------------------------------------
+# 🔌💻 GPT-Academic Interface
+# ------------------------------------------------------------------------------------------------------------------------
+predict_no_ui_long_connection, predict = get_local_llm_predict_fns(GetGLM3Handle, model_name, history_format='chatglm3')
\ No newline at end of file
diff --git a/request_llms/bridge_chatglmft.py b/request_llms/bridge_chatglmft.py
new file mode 100644
index 0000000000000000000000000000000000000000..d812bae3c36dc22e6c40e78b54e0fbbda665e989
--- /dev/null
+++ b/request_llms/bridge_chatglmft.py
@@ -0,0 +1,207 @@
+
+from transformers import AutoModel, AutoTokenizer
+import time
+import os
+import json
+import threading
+import importlib
+from toolbox import update_ui, get_conf
+from multiprocessing import Process, Pipe
+
+load_message = "ChatGLMFT尚未加载，加载需要一段时间。注意，取决于`config.py`的配置，ChatGLMFT消耗大量的内存（CPU）或显存（GPU），也许会导致低配计算机卡死 ……"
+
+def string_to_options(arguments):
+ import argparse
+ import shlex
+ # Create an argparse.ArgumentParser instance
+ parser = argparse.ArgumentParser()
+ # Add command-line arguments
+ parser.add_argument("--llm_to_learn", type=str, help="LLM model to learn", default="gpt-3.5-turbo")
+ parser.add_argument("--prompt_prefix", type=str, help="Prompt prefix", default='')
+ parser.add_argument("--system_prompt", type=str, help="System prompt", default='')
+ parser.add_argument("--batch", type=int, help="System prompt", default=50)
+ # Parse the arguments
+ args = parser.parse_args(shlex.split(arguments))
+ return args
+
+
+#################################################################################
+class GetGLMFTHandle(Process):
+ def __init__(self):
+ super().__init__(daemon=True)
+ self.parent, self.child = Pipe()
+ self.chatglmft_model = None
+ self.chatglmft_tokenizer = None
+ self.info = ""
+ self.success = True
+ self.check_dependency()
+ self.start()
+ self.threadLock = threading.Lock()
+
+ def check_dependency(self):
+ try:
+ import sentencepiece
+ self.info = "依赖检测通过"
+ self.success = True
+ except:
+ self.info = "缺少ChatGLMFT的依赖，如果要使用ChatGLMFT，除了基础的pip依赖以外，您还需要运行`pip install -r request_llms/requirements_chatglm.txt`安装ChatGLM的依赖。"
+ self.success = False
+
+ def ready(self):
+ return self.chatglmft_model is not None
+
+ def run(self):
+ # 子进程执行
+ # 第一次运行，加载参数
+ retry = 0
+ while True:
+ try:
+ if self.chatglmft_model is None:
+ from transformers import AutoConfig
+ import torch
+ # conf = 'request_llms/current_ptune_model.json'
+ # if not os.path.exists(conf): raise RuntimeError('找不到微调模型信息')
+ # with open(conf, 'r', encoding='utf8') as f:
+ # model_args = json.loads(f.read())
+ CHATGLM_PTUNING_CHECKPOINT = get_conf('CHATGLM_PTUNING_CHECKPOINT')
+ assert os.path.exists(CHATGLM_PTUNING_CHECKPOINT), "找不到微调模型检查点"
+ conf = os.path.join(CHATGLM_PTUNING_CHECKPOINT, "config.json")
+ with open(conf, 'r', encoding='utf8') as f:
+ model_args = json.loads(f.read())
+ if 'model_name_or_path' not in model_args:
+ model_args['model_name_or_path'] = model_args['_name_or_path']
+ self.chatglmft_tokenizer = AutoTokenizer.from_pretrained(
+ model_args['model_name_or_path'], trust_remote_code=True)
+ config = AutoConfig.from_pretrained(
+ model_args['model_name_or_path'], trust_remote_code=True)
+
+ config.pre_seq_len = model_args['pre_seq_len']
+ config.prefix_projection = model_args['prefix_projection']
+
+ print(f"Loading prefix_encoder weight from {CHATGLM_PTUNING_CHECKPOINT}")
+ model = AutoModel.from_pretrained(model_args['model_name_or_path'], config=config, trust_remote_code=True)
+ prefix_state_dict = torch.load(os.path.join(CHATGLM_PTUNING_CHECKPOINT, "pytorch_model.bin"))
+ new_prefix_state_dict = {}
+ for k, v in prefix_state_dict.items():
+ if k.startswith("transformer.prefix_encoder."):
+ new_prefix_state_dict[k[len("transformer.prefix_encoder."):]] = v
+ model.transformer.prefix_encoder.load_state_dict(new_prefix_state_dict)
+
+ if model_args['quantization_bit'] is not None and model_args['quantization_bit'] != 0:
+ print(f"Quantized to {model_args['quantization_bit']} bit")
+ model = model.quantize(model_args['quantization_bit'])
+ model = model.cuda()
+ if model_args['pre_seq_len'] is not None:
+ # P-tuning v2
+ model.transformer.prefix_encoder.float()
+ self.chatglmft_model = model.eval()
+
+ break
+ else:
+ break
+ except Exception as e:
+ retry += 1
+ if retry > 3:
+ self.child.send('[Local Message] Call ChatGLMFT fail 不能正常加载ChatGLMFT的参数。')
+ raise RuntimeError("不能正常加载ChatGLMFT的参数！")
+
+ while True:
+ # 进入任务等待状态
+ kwargs = self.child.recv()
+ # 收到消息，开始请求
+ try:
+ for response, history in self.chatglmft_model.stream_chat(self.chatglmft_tokenizer, **kwargs):
+ self.child.send(response)
+ # # 中途接收可能的终止指令（如果有的话）
+ # if self.child.poll():
+ # command = self.child.recv()
+ # if command == '[Terminate]': break
+ except:
+ from toolbox import trimmed_format_exc
+ self.child.send('[Local Message] Call ChatGLMFT fail.' + '\n```\n' + trimmed_format_exc() + '\n```\n')
+ # 请求处理结束，开始下一个循环
+ self.child.send('[Finish]')
+
+ def stream_chat(self, **kwargs):
+ # 主进程执行
+ self.threadLock.acquire()
+ self.parent.send(kwargs)
+ while True:
+ res = self.parent.recv()
+ if res != '[Finish]':
+ yield res
+ else:
+ break
+ self.threadLock.release()
+
+global glmft_handle
+glmft_handle = None
+#################################################################################
+def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=[], console_slience=False):
+ """
+ 多线程方法
+ 函数的说明请见 request_llms/bridge_all.py
+ """
+ global glmft_handle
+ if glmft_handle is None:
+ glmft_handle = GetGLMFTHandle()
+ if len(observe_window) >= 1: observe_window[0] = load_message + "\n\n" + glmft_handle.info
+ if not glmft_handle.success:
+ error = glmft_handle.info
+ glmft_handle = None
+ raise RuntimeError(error)
+
+ # chatglmft 没有 sys_prompt 接口，因此把prompt加入 history
+ history_feedin = []
+ history_feedin.append(["What can I do?", sys_prompt])
+ for i in range(len(history)//2):
+ history_feedin.append([history[2*i], history[2*i+1]] )
+
+ watch_dog_patience = 5 # 看门狗 (watchdog) 的耐心, 设置5秒即可
+ response = ""
+ for response in glmft_handle.stream_chat(query=inputs, history=history_feedin, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
+ if len(observe_window) >= 1: observe_window[0] = response
+ if len(observe_window) >= 2:
+ if (time.time()-observe_window[1]) > watch_dog_patience:
+ raise RuntimeError("程序终止。")
+ return response
+
+
+
+def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
+ """
+ 单线程方法
+ 函数的说明请见 request_llms/bridge_all.py
+ """
+ chatbot.append((inputs, ""))
+
+ global glmft_handle
+ if glmft_handle is None:
+ glmft_handle = GetGLMFTHandle()
+ chatbot[-1] = (inputs, load_message + "\n\n" + glmft_handle.info)
+ yield from update_ui(chatbot=chatbot, history=[])
+ if not glmft_handle.success:
+ glmft_handle = None
+ return
+
+ if additional_fn is not None:
+ from core_functional import handle_core_functionality
+ inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
+
+ # 处理历史信息
+ history_feedin = []
+ history_feedin.append(["What can I do?", system_prompt] )
+ for i in range(len(history)//2):
+ history_feedin.append([history[2*i], history[2*i+1]] )
+
+ # 开始接收chatglmft的回复
+ response = "[Local Message] 等待ChatGLMFT响应中 ..."
+ for response in glmft_handle.stream_chat(query=inputs, history=history_feedin, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
+ chatbot[-1] = (inputs, response)
+ yield from update_ui(chatbot=chatbot, history=history)
+
+ # 总结输出
+ if response == "[Local Message] 等待ChatGLMFT响应中 ...":
+ response = "[Local Message] ChatGLMFT响应异常 ..."
+ history.extend([inputs, response])
+ yield from update_ui(chatbot=chatbot, history=history)
diff --git a/request_llms/bridge_chatglmonnx.py b/request_llms/bridge_chatglmonnx.py
new file mode 100644
index 0000000000000000000000000000000000000000..4b905718f63089c1355d244d61c67df07c3dc521
--- /dev/null
+++ b/request_llms/bridge_chatglmonnx.py
@@ -0,0 +1,72 @@
+model_name = "ChatGLM-ONNX"
+cmd_to_install = "`pip install -r request_llms/requirements_chatglm_onnx.txt`"
+
+
+from transformers import AutoModel, AutoTokenizer
+import time
+import threading
+import importlib
+from toolbox import update_ui, get_conf
+from multiprocessing import Process, Pipe
+from .local_llm_class import LocalLLMHandle, get_local_llm_predict_fns
+
+from .chatglmoonx import ChatGLMModel, chat_template
+
+
+
+# ------------------------------------------------------------------------------------------------------------------------
+# 🔌💻 Local Model
+# ------------------------------------------------------------------------------------------------------------------------
+class GetONNXGLMHandle(LocalLLMHandle):
+
+ def load_model_info(self):
+ # 🏃♂️🏃♂️🏃♂️ 子进程执行
+ self.model_name = model_name
+ self.cmd_to_install = cmd_to_install
+
+ def load_model_and_tokenizer(self):
+ # 🏃♂️🏃♂️🏃♂️ 子进程执行
+ import os, glob
+ if not len(glob.glob("./request_llms/ChatGLM-6b-onnx-u8s8/chatglm-6b-int8-onnx-merged/*.bin")) >= 7: # 该模型有七个 bin 文件
+ from huggingface_hub import snapshot_download
+ snapshot_download(repo_id="K024/ChatGLM-6b-onnx-u8s8", local_dir="./request_llms/ChatGLM-6b-onnx-u8s8")
+ def create_model():
+ return ChatGLMModel(
+ tokenizer_path = "./request_llms/ChatGLM-6b-onnx-u8s8/chatglm-6b-int8-onnx-merged/sentencepiece.model",
+ onnx_model_path = "./request_llms/ChatGLM-6b-onnx-u8s8/chatglm-6b-int8-onnx-merged/chatglm-6b-int8.onnx"
+ )
+ self._model = create_model()
+ return self._model, None
+
+ def llm_stream_generator(self, **kwargs):
+ # 🏃♂️🏃♂️🏃♂️ 子进程执行
+ def adaptor(kwargs):
+ query = kwargs['query']
+ max_length = kwargs['max_length']
+ top_p = kwargs['top_p']
+ temperature = kwargs['temperature']
+ history = kwargs['history']
+ return query, max_length, top_p, temperature, history
+
+ query, max_length, top_p, temperature, history = adaptor(kwargs)
+
+ prompt = chat_template(history, query)
+ for answer in self._model.generate_iterate(
+ prompt,
+ max_generated_tokens=max_length,
+ top_k=1,
+ top_p=top_p,
+ temperature=temperature,
+ ):
+ yield answer
+
+ def try_to_import_special_deps(self, **kwargs):
+ # import something that will raise error if the user does not install requirement_*.txt
+ # 🏃♂️🏃♂️🏃♂️ 子进程执行
+ pass
+
+
+# ------------------------------------------------------------------------------------------------------------------------
+# 🔌💻 GPT-Academic Interface
+# ------------------------------------------------------------------------------------------------------------------------
+predict_no_ui_long_connection, predict = get_local_llm_predict_fns(GetONNXGLMHandle, model_name)
\ No newline at end of file
diff --git a/request_llms/bridge_chatgpt.py b/request_llms/bridge_chatgpt.py
new file mode 100644
index 0000000000000000000000000000000000000000..e55ad37ae78ac9897dd90794ca18a9ad0370c6a5
--- /dev/null
+++ b/request_llms/bridge_chatgpt.py
@@ -0,0 +1,376 @@
+# 借鉴了 https://github.com/GaiZhenbiao/ChuanhuChatGPT 项目
+
+"""
+ 该文件中主要包含三个函数
+
+ 不具备多线程能力的函数：
+ 1. predict: 正常对话时使用，具备完备的交互功能，不可多线程
+
+ 具备多线程调用能力的函数
+ 2. predict_no_ui_long_connection：支持多线程
+"""
+
+import json
+import time
+import gradio as gr
+import logging
+import traceback
+import requests
+import importlib
+import random
+
+# config_private.py放自己的秘密如API和代理网址
+# 读取时首先看是否存在私密的config_private配置文件（不受git管控），如果有，则覆盖原config文件
+from toolbox import get_conf, update_ui, is_any_api_key, select_api_key, what_keys, clip_history, trimmed_format_exc, is_the_upload_folder
+proxies, TIMEOUT_SECONDS, MAX_RETRY, API_ORG, AZURE_CFG_ARRAY = \
+ get_conf('proxies', 'TIMEOUT_SECONDS', 'MAX_RETRY', 'API_ORG', 'AZURE_CFG_ARRAY')
+
+timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check proxy settings in config.py.' + \
+ '网络错误，检查代理服务器是否可用，以及代理设置的格式是否正确，格式须是[协议]://[地址]:[端口]，缺一不可。'
+
+def get_full_error(chunk, stream_response):
+ """
+ 获取完整的从Openai返回的报错
+ """
+ while True:
+ try:
+ chunk += next(stream_response)
+ except:
+ break
+ return chunk
+
+def decode_chunk(chunk):
+ # 提前读取一些信息 （用于判断异常）
+ chunk_decoded = chunk.decode()
+ chunkjson = None
+ has_choices = False
+ choice_valid = False
+ has_content = False
+ has_role = False
+ try:
+ chunkjson = json.loads(chunk_decoded[6:])
+ has_choices = 'choices' in chunkjson
+ if has_choices: choice_valid = (len(chunkjson['choices']) > 0)
+ if has_choices and choice_valid: has_content = "content" in chunkjson['choices'][0]["delta"]
+ if has_choices and choice_valid: has_role = "role" in chunkjson['choices'][0]["delta"]
+ except:
+ pass
+ return chunk_decoded, chunkjson, has_choices, choice_valid, has_content, has_role
+
+from functools import lru_cache
+@lru_cache(maxsize=32)
+def verify_endpoint(endpoint):
+ """
+ 检查endpoint是否可用
+ """
+ if "你亲手写的api名称" in endpoint:
+ raise ValueError("Endpoint不正确, 请检查AZURE_ENDPOINT的配置! 当前的Endpoint为:" + endpoint)
+ return endpoint
+
+def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
+ """
+ 发送至chatGPT，等待回复，一次性完成，不显示中间过程。但内部用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：
+ chatGPT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
+ """
+ watch_dog_patience = 5 # 看门狗的耐心, 设置5秒即可
+ headers, payload = generate_payload(inputs, llm_kwargs, history, system_prompt=sys_prompt, stream=True)
+ retry = 0
+ while True:
+ try:
+ # make a POST request to the API endpoint, stream=False
+ from .bridge_all import model_info
+ endpoint = verify_endpoint(model_info[llm_kwargs['llm_model']]['endpoint'])
+ response = requests.post(endpoint, headers=headers, proxies=proxies,
+ json=payload, stream=True, timeout=TIMEOUT_SECONDS); break
+ except requests.exceptions.ReadTimeout as e:
+ retry += 1
+ traceback.print_exc()
+ if retry > MAX_RETRY: raise TimeoutError
+ if MAX_RETRY!=0: print(f'请求超时，正在重试 ({retry}/{MAX_RETRY}) ……')
+
+ stream_response = response.iter_lines()
+ result = ''
+ json_data = None
+ while True:
+ try: chunk = next(stream_response).decode()
+ except StopIteration:
+ break
+ except requests.exceptions.ConnectionError:
+ chunk = next(stream_response).decode() # 失败了，重试一次？再失败就没办法了。
+ if len(chunk)==0: continue
+ if not chunk.startswith('data:'):
+ error_msg = get_full_error(chunk.encode('utf8'), stream_response).decode()
+ if "reduce the length" in error_msg:
+ raise ConnectionAbortedError("OpenAI拒绝了请求:" + error_msg)
+ else:
+ raise RuntimeError("OpenAI拒绝了请求：" + error_msg)
+ if ('data: [DONE]' in chunk): break # api2d 正常完成
+ json_data = json.loads(chunk.lstrip('data:'))['choices'][0]
+ delta = json_data["delta"]
+ if len(delta) == 0: break
+ if "role" in delta: continue
+ if "content" in delta:
+ result += delta["content"]
+ if not console_slience: print(delta["content"], end='')
+ if observe_window is not None:
+ # 观测窗，把已经获取的数据显示出去
+ if len(observe_window) >= 1:
+ observe_window[0] += delta["content"]
+ # 看门狗，如果超过期限没有喂狗，则终止
+ if len(observe_window) >= 2:
+ if (time.time()-observe_window[1]) > watch_dog_patience:
+ raise RuntimeError("用户取消了程序。")
+ else: raise RuntimeError("意外Json结构："+delta)
+ if json_data and json_data['finish_reason'] == 'content_filter':
+ raise RuntimeError("由于提问含不合规内容被Azure过滤。")
+ if json_data and json_data['finish_reason'] == 'length':
+ raise ConnectionAbortedError("正常结束，但显示Token不足，导致输出不完整，请削减单次输入的文本量。")
+ return result
+
+
+def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
+ """
+ 发送至chatGPT，流式获取输出。
+ 用于基础的对话功能。
+ inputs 是本次问询的输入
+ top_p, temperature是chatGPT的内部调优参数
+ history 是之前的对话列表（注意无论是inputs还是history，内容太长了都会触发token数量溢出的错误）
+ chatbot 为WebUI中显示的对话列表，修改它，然后yeild出去，可以直接修改对话界面内容
+ additional_fn代表点击的哪个按钮，按钮见functional.py
+ """
+ if is_any_api_key(inputs):
+ chatbot._cookies['api_key'] = inputs
+ chatbot.append(("输入已识别为openai的api_key", what_keys(inputs)))
+ yield from update_ui(chatbot=chatbot, history=history, msg="api_key已导入") # 刷新界面
+ return
+ elif not is_any_api_key(chatbot._cookies['api_key']):
+ chatbot.append((inputs, "缺少api_key。\n\n1. 临时解决方案：直接在输入区键入api_key，然后回车提交。\n\n2. 长效解决方案：在config.py中配置。"))
+ yield from update_ui(chatbot=chatbot, history=history, msg="缺少api_key") # 刷新界面
+ return
+
+ user_input = inputs
+ if additional_fn is not None:
+ from core_functional import handle_core_functionality
+ inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
+
+ raw_input = inputs
+ logging.info(f'[raw_input] {raw_input}')
+ chatbot.append((inputs, ""))
+ yield from update_ui(chatbot=chatbot, history=history, msg="等待响应") # 刷新界面
+
+ # check mis-behavior
+ if is_the_upload_folder(user_input):
+ chatbot[-1] = (inputs, f"[Local Message] 检测到操作错误！当您上传文档之后，需点击“**函数插件区**”按钮进行处理，请勿点击“提交”按钮或者“基础功能区”按钮。")
+ yield from update_ui(chatbot=chatbot, history=history, msg="正常") # 刷新界面
+ time.sleep(2)
+
+ try:
+ headers, payload = generate_payload(inputs, llm_kwargs, history, system_prompt, stream)
+ except RuntimeError as e:
+ chatbot[-1] = (inputs, f"您提供的api-key不满足要求，不包含任何可用于{llm_kwargs['llm_model']}的api-key。您可能选择了错误的模型或请求源。")
+ yield from update_ui(chatbot=chatbot, history=history, msg="api-key不满足要求") # 刷新界面
+ return
+
+ # 检查endpoint是否合法
+ try:
+ from .bridge_all import model_info
+ endpoint = verify_endpoint(model_info[llm_kwargs['llm_model']]['endpoint'])
+ except:
+ tb_str = '```\n' + trimmed_format_exc() + '```'
+ chatbot[-1] = (inputs, tb_str)
+ yield from update_ui(chatbot=chatbot, history=history, msg="Endpoint不满足要求") # 刷新界面
+ return
+
+ history.append(inputs); history.append("")
+
+ retry = 0
+ while True:
+ try:
+ # make a POST request to the API endpoint, stream=True
+ response = requests.post(endpoint, headers=headers, proxies=proxies,
+ json=payload, stream=True, timeout=TIMEOUT_SECONDS);break
+ except:
+ retry += 1
+ chatbot[-1] = ((chatbot[-1][0], timeout_bot_msg))
+ retry_msg = f"，正在重试 ({retry}/{MAX_RETRY}) ……" if MAX_RETRY > 0 else ""
+ yield from update_ui(chatbot=chatbot, history=history, msg="请求超时"+retry_msg) # 刷新界面
+ if retry > MAX_RETRY: raise TimeoutError
+
+ gpt_replying_buffer = ""
+
+ is_head_of_the_stream = True
+ if stream:
+ stream_response = response.iter_lines()
+ while True:
+ try:
+ chunk = next(stream_response)
+ except StopIteration:
+ # 非OpenAI官方接口的出现这样的报错，OpenAI和API2D不会走这里
+ chunk_decoded = chunk.decode()
+ error_msg = chunk_decoded
+ # 首先排除一个one-api没有done数据包的第三方Bug情形
+ if len(gpt_replying_buffer.strip()) > 0 and len(error_msg) == 0:
+ yield from update_ui(chatbot=chatbot, history=history, msg="检测到有缺陷的非OpenAI官方接口，建议选择更稳定的接口。")
+ break
+ # 其他情况，直接返回报错
+ chatbot, history = handle_error(inputs, llm_kwargs, chatbot, history, chunk_decoded, error_msg)
+ yield from update_ui(chatbot=chatbot, history=history, msg="非OpenAI官方接口返回了错误:" + chunk.decode()) # 刷新界面
+ return
+
+ # 提前读取一些信息 （用于判断异常）
+ chunk_decoded, chunkjson, has_choices, choice_valid, has_content, has_role = decode_chunk(chunk)
+
+ if is_head_of_the_stream and (r'"object":"error"' not in chunk_decoded) and (r"content" not in chunk_decoded):
+ # 数据流的第一帧不携带content
+ is_head_of_the_stream = False; continue
+
+ if chunk:
+ try:
+ if has_choices and not choice_valid:
+ # 一些垃圾第三方接口的出现这样的错误
+ continue
+ # 前者是API2D的结束条件，后者是OPENAI的结束条件
+ if ('data: [DONE]' in chunk_decoded) or (len(chunkjson['choices'][0]["delta"]) == 0):
+ # 判定为数据流的结束，gpt_replying_buffer也写完了
+ logging.info(f'[response] {gpt_replying_buffer}')
+ break
+ # 处理数据流的主体
+ status_text = f"finish_reason: {chunkjson['choices'][0].get('finish_reason', 'null')}"
+ # 如果这里抛出异常，一般是文本过长，详情见get_full_error的输出
+ if has_content:
+ # 正常情况
+ gpt_replying_buffer = gpt_replying_buffer + chunkjson['choices'][0]["delta"]["content"]
+ elif has_role:
+ # 一些第三方接口的出现这样的错误，兼容一下吧
+ continue
+ else:
+ # 一些垃圾第三方接口的出现这样的错误
+ gpt_replying_buffer = gpt_replying_buffer + chunkjson['choices'][0]["delta"]["content"]
+
+ history[-1] = gpt_replying_buffer
+ chatbot[-1] = (history[-2], history[-1])
+ yield from update_ui(chatbot=chatbot, history=history, msg=status_text) # 刷新界面
+ except Exception as e:
+ yield from update_ui(chatbot=chatbot, history=history, msg="Json解析不合常规") # 刷新界面
+ chunk = get_full_error(chunk, stream_response)
+ chunk_decoded = chunk.decode()
+ error_msg = chunk_decoded
+ chatbot, history = handle_error(inputs, llm_kwargs, chatbot, history, chunk_decoded, error_msg)
+ yield from update_ui(chatbot=chatbot, history=history, msg="Json异常" + error_msg) # 刷新界面
+ print(error_msg)
+ return
+
+def handle_error(inputs, llm_kwargs, chatbot, history, chunk_decoded, error_msg):
+ from .bridge_all import model_info
+ openai_website = ' 请登录OpenAI查看详情 https://platform.openai.com/signup'
+ if "reduce the length" in error_msg:
+ if len(history) >= 2: history[-1] = ""; history[-2] = "" # 清除当前溢出的输入：history[-2] 是本次输入, history[-1] 是本次输出
+ history = clip_history(inputs=inputs, history=history, tokenizer=model_info[llm_kwargs['llm_model']]['tokenizer'],
+ max_token_limit=(model_info[llm_kwargs['llm_model']]['max_token'])) # history至少释放二分之一
+ chatbot[-1] = (chatbot[-1][0], "[Local Message] Reduce the length. 本次输入过长, 或历史数据过长. 历史缓存数据已部分释放, 您可以请再次尝试. (若再次失败则更可能是因为输入过长.)")
+ elif "does not exist" in error_msg:
+ chatbot[-1] = (chatbot[-1][0], f"[Local Message] Model {llm_kwargs['llm_model']} does not exist. 模型不存在, 或者您没有获得体验资格.")
+ elif "Incorrect API key" in error_msg:
+ chatbot[-1] = (chatbot[-1][0], "[Local Message] Incorrect API key. OpenAI以提供了不正确的API_KEY为由, 拒绝服务. " + openai_website)
+ elif "exceeded your current quota" in error_msg:
+ chatbot[-1] = (chatbot[-1][0], "[Local Message] You exceeded your current quota. OpenAI以账户额度不足为由, 拒绝服务." + openai_website)
+ elif "account is not active" in error_msg:
+ chatbot[-1] = (chatbot[-1][0], "[Local Message] Your account is not active. OpenAI以账户失效为由, 拒绝服务." + openai_website)
+ elif "associated with a deactivated account" in error_msg:
+ chatbot[-1] = (chatbot[-1][0], "[Local Message] You are associated with a deactivated account. OpenAI以账户失效为由, 拒绝服务." + openai_website)
+ elif "API key has been deactivated" in error_msg:
+ chatbot[-1] = (chatbot[-1][0], "[Local Message] API key has been deactivated. OpenAI以账户失效为由, 拒绝服务." + openai_website)
+ elif "bad forward key" in error_msg:
+ chatbot[-1] = (chatbot[-1][0], "[Local Message] Bad forward key. API2D账户额度不足.")
+ elif "Not enough point" in error_msg:
+ chatbot[-1] = (chatbot[-1][0], "[Local Message] Not enough point. API2D账户点数不足.")
+ else:
+ from toolbox import regular_txt_to_markdown
+ tb_str = '```\n' + trimmed_format_exc() + '```'
+ chatbot[-1] = (chatbot[-1][0], f"[Local Message] 异常 \n\n{tb_str} \n\n{regular_txt_to_markdown(chunk_decoded)}")
+ return chatbot, history
+
+def generate_payload(inputs, llm_kwargs, history, system_prompt, stream):
+ """
+ 整合所有信息，选择LLM模型，生成http请求，为发送请求做准备
+ """
+ if not is_any_api_key(llm_kwargs['api_key']):
+ raise AssertionError("你提供了错误的API_KEY。\n\n1. 临时解决方案：直接在输入区键入api_key，然后回车提交。\n\n2. 长效解决方案：在config.py中配置。")
+
+ api_key = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model'])
+
+ headers = {
+ "Content-Type": "application/json",
+ "Authorization": f"Bearer {api_key}"
+ }
+ if API_ORG.startswith('org-'): headers.update({"OpenAI-Organization": API_ORG})
+ if llm_kwargs['llm_model'].startswith('azure-'):
+ headers.update({"api-key": api_key})
+ if llm_kwargs['llm_model'] in AZURE_CFG_ARRAY.keys():
+ azure_api_key_unshared = AZURE_CFG_ARRAY[llm_kwargs['llm_model']]["AZURE_API_KEY"]
+ headers.update({"api-key": azure_api_key_unshared})
+
+ conversation_cnt = len(history) // 2
+
+ messages = [{"role": "system", "content": system_prompt}]
+ if conversation_cnt:
+ for index in range(0, 2*conversation_cnt, 2):
+ what_i_have_asked = {}
+ what_i_have_asked["role"] = "user"
+ what_i_have_asked["content"] = history[index]
+ what_gpt_answer = {}
+ what_gpt_answer["role"] = "assistant"
+ what_gpt_answer["content"] = history[index+1]
+ if what_i_have_asked["content"] != "":
+ if what_gpt_answer["content"] == "": continue
+ if what_gpt_answer["content"] == timeout_bot_msg: continue
+ messages.append(what_i_have_asked)
+ messages.append(what_gpt_answer)
+ else:
+ messages[-1]['content'] = what_gpt_answer['content']
+
+ what_i_ask_now = {}
+ what_i_ask_now["role"] = "user"
+ what_i_ask_now["content"] = inputs
+ messages.append(what_i_ask_now)
+ model = llm_kwargs['llm_model']
+ if llm_kwargs['llm_model'].startswith('api2d-'):
+ model = llm_kwargs['llm_model'][len('api2d-'):]
+
+ if model == "gpt-3.5-random": # 随机选择, 绕过openai访问频率限制
+ 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",
+ ])
+ logging.info("Random select model:" + model)
+
+ payload = {
+ "model": model,
+ "messages": messages,
+ "temperature": llm_kwargs['temperature'], # 1.0,
+ "top_p": llm_kwargs['top_p'], # 1.0,
+ "n": 1,
+ "stream": stream,
+ "presence_penalty": 0,
+ "frequency_penalty": 0,
+ }
+ try:
+ print(f" {llm_kwargs['llm_model']} : {conversation_cnt} : {inputs[:100]} ..........")
+ except:
+ print('输入中可能存在乱码。')
+ return headers,payload
+
+
diff --git a/request_llms/bridge_chatgpt_vision.py b/request_llms/bridge_chatgpt_vision.py
new file mode 100644
index 0000000000000000000000000000000000000000..e84bc0b717102cac12ac169898665e3402f12e36
--- /dev/null
+++ b/request_llms/bridge_chatgpt_vision.py
@@ -0,0 +1,329 @@
+"""
+ 该文件中主要包含三个函数
+
+ 不具备多线程能力的函数：
+ 1. predict: 正常对话时使用，具备完备的交互功能，不可多线程
+
+ 具备多线程调用能力的函数
+ 2. predict_no_ui_long_connection：支持多线程
+"""
+
+import json
+import time
+import logging
+import requests
+import base64
+import os
+import glob
+
+from toolbox import get_conf, update_ui, is_any_api_key, select_api_key, what_keys, clip_history, trimmed_format_exc, is_the_upload_folder, update_ui_lastest_msg, get_max_token
+proxies, TIMEOUT_SECONDS, MAX_RETRY, API_ORG, AZURE_CFG_ARRAY = \
+ get_conf('proxies', 'TIMEOUT_SECONDS', 'MAX_RETRY', 'API_ORG', 'AZURE_CFG_ARRAY')
+
+timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check proxy settings in config.py.' + \
+ '网络错误，检查代理服务器是否可用，以及代理设置的格式是否正确，格式须是[协议]://[地址]:[端口]，缺一不可。'
+
+def have_any_recent_upload_image_files(chatbot):
+ _5min = 5 * 60
+ if chatbot is None: return False, None # chatbot is None
+ most_recent_uploaded = chatbot._cookies.get("most_recent_uploaded", None)
+ if not most_recent_uploaded: return False, None # most_recent_uploaded is None
+ if time.time() - most_recent_uploaded["time"] < _5min:
+ most_recent_uploaded = chatbot._cookies.get("most_recent_uploaded", None)
+ path = most_recent_uploaded['path']
+ file_manifest = [f for f in glob.glob(f'{path}/**/*.jpg', recursive=True)]
+ file_manifest += [f for f in glob.glob(f'{path}/**/*.jpeg', recursive=True)]
+ file_manifest += [f for f in glob.glob(f'{path}/**/*.png', recursive=True)]
+ if len(file_manifest) == 0: return False, None
+ return True, file_manifest # most_recent_uploaded is new
+ else:
+ return False, None # most_recent_uploaded is too old
+
+def report_invalid_key(key):
+ if get_conf("BLOCK_INVALID_APIKEY"):
+ # 实验性功能，自动检测并屏蔽失效的KEY，请勿使用
+ from request_llms.key_manager import ApiKeyManager
+ api_key = ApiKeyManager().add_key_to_blacklist(key)
+
+def get_full_error(chunk, stream_response):
+ """
+ 获取完整的从Openai返回的报错
+ """
+ while True:
+ try:
+ chunk += next(stream_response)
+ except:
+ break
+ return chunk
+
+def decode_chunk(chunk):
+ # 提前读取一些信息 （用于判断异常）
+ chunk_decoded = chunk.decode()
+ chunkjson = None
+ has_choices = False
+ choice_valid = False
+ has_content = False
+ has_role = False
+ try:
+ chunkjson = json.loads(chunk_decoded[6:])
+ has_choices = 'choices' in chunkjson
+ if has_choices: choice_valid = (len(chunkjson['choices']) > 0)
+ if has_choices and choice_valid: has_content = "content" in chunkjson['choices'][0]["delta"]
+ if has_choices and choice_valid: has_role = "role" in chunkjson['choices'][0]["delta"]
+ except:
+ pass
+ return chunk_decoded, chunkjson, has_choices, choice_valid, has_content, has_role
+
+from functools import lru_cache
+@lru_cache(maxsize=32)
+def verify_endpoint(endpoint):
+ """
+ 检查endpoint是否可用
+ """
+ return endpoint
+
+def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None, console_slience=False):
+ raise NotImplementedError
+
+
+def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_prompt='', stream = True, additional_fn=None):
+
+ have_recent_file, image_paths = have_any_recent_upload_image_files(chatbot)
+
+ if is_any_api_key(inputs):
+ chatbot._cookies['api_key'] = inputs
+ chatbot.append(("输入已识别为openai的api_key", what_keys(inputs)))
+ yield from update_ui(chatbot=chatbot, history=history, msg="api_key已导入") # 刷新界面
+ return
+ elif not is_any_api_key(chatbot._cookies['api_key']):
+ chatbot.append((inputs, "缺少api_key。\n\n1. 临时解决方案：直接在输入区键入api_key，然后回车提交。\n\n2. 长效解决方案：在config.py中配置。"))
+ yield from update_ui(chatbot=chatbot, history=history, msg="缺少api_key") # 刷新界面
+ return
+ if not have_recent_file:
+ chatbot.append((inputs, "没有检测到任何近期上传的图像文件，请上传jpg格式的图片，此外，请注意拓展名需要小写"))
+ yield from update_ui(chatbot=chatbot, history=history, msg="等待图片") # 刷新界面
+ return
+ if os.path.exists(inputs):
+ chatbot.append((inputs, "已经接收到您上传的文件，您不需要再重复强调该文件的路径了，请直接输入您的问题。"))
+ yield from update_ui(chatbot=chatbot, history=history, msg="等待指令") # 刷新界面
+ return
+
+
+ user_input = inputs
+ if additional_fn is not None:
+ from core_functional import handle_core_functionality
+ inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
+
+ raw_input = inputs
+ logging.info(f'[raw_input] {raw_input}')
+ def make_media_input(inputs, image_paths):
+ for image_path in image_paths:
+ inputs = inputs + f'
})
GPT 学术优化 (GPT Academic)
+
-