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Deprecate gpt-4-vision-preview model #630

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Deprecate gpt-4-vision-preview model #630

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2 changes: 1 addition & 1 deletion .env.example
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Original file line number Diff line number Diff line change
Expand Up @@ -54,4 +54,4 @@ ALLOWED_TELEGRAM_USER_IDS=USER_ID_1,USER_ID_2
# TTS_PRICES=0.015,0.030
# BOT_LANGUAGE=en
# ENABLE_VISION_FOLLOW_UP_QUESTIONS="true"
# VISION_MODEL="gpt-4-vision-preview"
# VISION_MODEL="gpt-4o"
4 changes: 2 additions & 2 deletions README.md
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Expand Up @@ -99,8 +99,8 @@ Check out the [Budget Manual](https://github.com/n3d1117/chatgpt-telegram-bot/di
| `SHOW_USAGE` | Whether to show OpenAI token usage information after each response | `false` |
| `STREAM` | Whether to stream responses. **Note**: incompatible, if enabled, with `N_CHOICES` higher than 1 | `true` |
| `MAX_TOKENS` | Upper bound on how many tokens the ChatGPT API will return | `1200` for GPT-3, `2400` for GPT-4 |
| `VISION_MAX_TOKENS` | Upper bound on how many tokens vision models will return | `300` for gpt-4-vision-preview |
| `VISION_MODEL` | The Vision to Speech model to use. Allowed values: `gpt-4-vision-preview` | `gpt-4-vision-preview` |
| `VISION_MAX_TOKENS` | Upper bound on how many tokens vision models will return | `300` for gpt-4o |
| `VISION_MODEL` | The Vision to Speech model to use. Allowed values: `gpt-4o` | `gpt-4o` |
| `ENABLE_VISION_FOLLOW_UP_QUESTIONS` | If true, once you send an image to the bot, it uses the configured VISION_MODEL until the conversation ends. Otherwise, it uses the OPENAI_MODEL to follow the conversation. Allowed values: `true` or `false` | `true` |
| `MAX_HISTORY_SIZE` | Max number of messages to keep in memory, after which the conversation will be summarised to avoid excessive token usage | `15` |
| `MAX_CONVERSATION_AGE_MINUTES` | Maximum number of minutes a conversation should live since the last message, after which the conversation will be reset | `180` |
Expand Down
2 changes: 1 addition & 1 deletion bot/main.py
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Expand Up @@ -53,7 +53,7 @@ def main():
'bot_language': os.environ.get('BOT_LANGUAGE', 'en'),
'show_plugins_used': os.environ.get('SHOW_PLUGINS_USED', 'false').lower() == 'true',
'whisper_prompt': os.environ.get('WHISPER_PROMPT', ''),
'vision_model': os.environ.get('VISION_MODEL', 'gpt-4-vision-preview'),
'vision_model': os.environ.get('VISION_MODEL', 'gpt-4o'),
'enable_vision_follow_up_questions': os.environ.get('ENABLE_VISION_FOLLOW_UP_QUESTIONS', 'true').lower() == 'true',
'vision_prompt': os.environ.get('VISION_PROMPT', 'What is in this image'),
'vision_detail': os.environ.get('VISION_DETAIL', 'auto'),
Expand Down
58 changes: 31 additions & 27 deletions bot/openai_helper.py
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Expand Up @@ -26,8 +26,9 @@
GPT_3_16K_MODELS = ("gpt-3.5-turbo-16k", "gpt-3.5-turbo-16k-0613", "gpt-3.5-turbo-1106", "gpt-3.5-turbo-0125")
GPT_4_MODELS = ("gpt-4", "gpt-4-0314", "gpt-4-0613", "gpt-4-turbo-preview")
GPT_4_32K_MODELS = ("gpt-4-32k", "gpt-4-32k-0314", "gpt-4-32k-0613")
GPT_4_VISION_MODELS = ("gpt-4-vision-preview",)
GPT_4_128K_MODELS = ("gpt-4-1106-preview","gpt-4-0125-preview","gpt-4-turbo-preview", "gpt-4-turbo", "gpt-4-turbo-2024-04-09")
GPT_4_VISION_MODELS = ("gpt-4o",)
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gpt-4o-mini is also recommended here

GPT_4_128K_MODELS = (
"gpt-4-1106-preview", "gpt-4-0125-preview", "gpt-4-turbo-preview", "gpt-4-turbo", "gpt-4-turbo-2024-04-09")
GPT_4O_MODELS = ("gpt-4o",)
GPT_ALL_MODELS = GPT_3_MODELS + GPT_3_16K_MODELS + GPT_4_MODELS + GPT_4_32K_MODELS + GPT_4_VISION_MODELS + GPT_4_128K_MODELS + GPT_4O_MODELS

Expand Down Expand Up @@ -64,13 +65,13 @@ def are_functions_available(model: str) -> bool:
if model in ("gpt-3.5-turbo-0301", "gpt-4-0314", "gpt-4-32k-0314"):
return False
# Stable models will be updated to support functions on June 27, 2023
if model in ("gpt-3.5-turbo", "gpt-3.5-turbo-1106", "gpt-4", "gpt-4-32k","gpt-4-1106-preview","gpt-4-0125-preview","gpt-4-turbo-preview"):
if model in (
"gpt-3.5-turbo", "gpt-3.5-turbo-1106", "gpt-4", "gpt-4-32k", "gpt-4-1106-preview", "gpt-4-0125-preview",
"gpt-4-turbo-preview", "gpt-4o"):
return datetime.date.today() > datetime.date(2023, 6, 27)
# Models gpt-3.5-turbo-0613 and gpt-3.5-turbo-16k-0613 will be deprecated on June 13, 2024
if model in ("gpt-3.5-turbo-0613", "gpt-3.5-turbo-16k-0613"):
return datetime.date.today() < datetime.date(2024, 6, 13)
if model == 'gpt-4-vision-preview':
return False
return True


Expand Down Expand Up @@ -249,7 +250,8 @@ async def __common_get_chat_response(self, chat_id: int, query: str, stream=Fals
self.conversations[chat_id] = self.conversations[chat_id][-self.config['max_history_size']:]

common_args = {
'model': self.config['model'] if not self.conversations_vision[chat_id] else self.config['vision_model'],
'model': self.config['model'] if not self.conversations_vision[chat_id] else self.config[
'vision_model'],
'messages': self.conversations[chat_id],
'temperature': self.config['temperature'],
'n': self.config['n_choices'],
Expand Down Expand Up @@ -385,7 +387,8 @@ async def transcribe(self, filename):
try:
with open(filename, "rb") as audio:
prompt_text = self.config['whisper_prompt']
result = await self.client.audio.transcriptions.create(model="whisper-1", file=audio, prompt=prompt_text)
result = await self.client.audio.transcriptions.create(model="whisper-1", file=audio,
prompt=prompt_text)
return result.text
except Exception as e:
logging.exception(e)
Expand Down Expand Up @@ -429,7 +432,7 @@ async def __common_get_chat_response_vision(self, chat_id: int, content: list, s
if exceeded_max_tokens or exceeded_max_history_size:
logging.info(f'Chat history for chat ID {chat_id} is too long. Summarising...')
try:

last = self.conversations[chat_id][-1]
summary = await self.__summarise(self.conversations[chat_id][:-1])
logging.debug(f'Summary: {summary}')
Expand All @@ -440,28 +443,27 @@ async def __common_get_chat_response_vision(self, chat_id: int, content: list, s
logging.warning(f'Error while summarising chat history: {str(e)}. Popping elements instead...')
self.conversations[chat_id] = self.conversations[chat_id][-self.config['max_history_size']:]

message = {'role':'user', 'content':content}
message = {'role': 'user', 'content': content}

common_args = {
'model': self.config['vision_model'],
'messages': self.conversations[chat_id][:-1] + [message],
'temperature': self.config['temperature'],
'n': 1, # several choices is not implemented yet
'n': 1, # several choices is not implemented yet
'max_tokens': self.config['vision_max_tokens'],
'presence_penalty': self.config['presence_penalty'],
'frequency_penalty': self.config['frequency_penalty'],
'stream': stream
}


# vision model does not yet support functions

# if self.config['enable_functions']:
# functions = self.plugin_manager.get_functions_specs()
# if len(functions) > 0:
# common_args['functions'] = self.plugin_manager.get_functions_specs()
# common_args['function_call'] = 'auto'

return await self.client.chat.completions.create(**common_args)

except openai.RateLimitError as e:
Expand All @@ -473,23 +475,21 @@ async def __common_get_chat_response_vision(self, chat_id: int, content: list, s
except Exception as e:
raise Exception(f"⚠️ _{localized_text('error', bot_language)}._ ⚠️\n{str(e)}") from e


async def interpret_image(self, chat_id, fileobj, prompt=None):
"""
Interprets a given PNG image file using the Vision model.
"""
image = encode_image(fileobj)
prompt = self.config['vision_prompt'] if prompt is None else prompt

content = [{'type':'text', 'text':prompt}, {'type':'image_url', \
'image_url': {'url':image, 'detail':self.config['vision_detail'] } }]
content = [{'type': 'text', 'text': prompt}, {'type': 'image_url', \
'image_url': {'url': image,
'detail': self.config['vision_detail']}}]

response = await self.__common_get_chat_response_vision(chat_id, content)



# functions are not available for this model

# if self.config['enable_functions']:
# response, plugins_used = await self.__handle_function_call(chat_id, response)
# if is_direct_result(response):
Expand Down Expand Up @@ -532,13 +532,12 @@ async def interpret_image_stream(self, chat_id, fileobj, prompt=None):
image = encode_image(fileobj)
prompt = self.config['vision_prompt'] if prompt is None else prompt

content = [{'type':'text', 'text':prompt}, {'type':'image_url', \
'image_url': {'url':image, 'detail':self.config['vision_detail'] } }]
content = [{'type': 'text', 'text': prompt}, {'type': 'image_url', \
'image_url': {'url': image,
'detail': self.config['vision_detail']}}]

response = await self.__common_get_chat_response_vision(chat_id, content, stream=True)



# if self.config['enable_functions']:
# response, plugins_used = await self.__handle_function_call(chat_id, response, stream=True)
# if is_direct_result(response):
Expand All @@ -557,8 +556,8 @@ async def interpret_image_stream(self, chat_id, fileobj, prompt=None):
self.__add_to_history(chat_id, role="assistant", content=answer)
tokens_used = str(self.__count_tokens(self.conversations[chat_id]))

#show_plugins_used = len(plugins_used) > 0 and self.config['show_plugins_used']
#plugin_names = tuple(self.plugin_manager.get_plugin_source_name(plugin) for plugin in plugins_used)
# show_plugins_used = len(plugins_used) > 0 and self.config['show_plugins_used']
# plugin_names = tuple(self.plugin_manager.get_plugin_source_name(plugin) for plugin in plugins_used)
if self.config['show_usage']:
answer += f"\n\n---\n💰 {tokens_used} {localized_text('stats_tokens', self.config['bot_language'])}"
# if show_plugins_used:
Expand Down Expand Up @@ -651,7 +650,12 @@ def __count_tokens(self, messages) -> int:
"""
model = self.config['model']
try:
encoding = tiktoken.encoding_for_model(model)
# TODO this is a temporary workaround until tiktoken is updated
# https://github.com/n3d1117/chatgpt-telegram-bot/issues/577
if model in GPT_4O_MODELS:
encoding = tiktoken.get_encoding("p50k_base")
else:
encoding = tiktoken.encoding_for_model(model)
except KeyError:
encoding = tiktoken.get_encoding("gpt-3.5-turbo")

Expand Down Expand Up @@ -697,15 +701,15 @@ def __count_tokens_vision(self, image_bytes: bytes) -> int:
model = self.config['vision_model']
if model not in GPT_4_VISION_MODELS:
raise NotImplementedError(f"""count_tokens_vision() is not implemented for model {model}.""")

w, h = image.size
if w > h: w, h = h, w
# this computation follows https://platform.openai.com/docs/guides/vision and https://openai.com/pricing#gpt-4-turbo
base_tokens = 85
detail = self.config['vision_detail']
if detail == 'low':
return base_tokens
elif detail == 'high' or detail == 'auto': # assuming worst cost for auto
elif detail == 'high' or detail == 'auto': # assuming worst cost for auto
f = max(w / 768, h / 2048)
if f > 1:
w, h = int(w / f), int(h / f)
Expand Down
52 changes: 41 additions & 11 deletions requirements.txt
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@@ -1,14 +1,44 @@
python-dotenv~=1.0.0
pydub~=0.25.1
tiktoken==0.7.0
annotated-types==0.7.0
anyio==4.4.0
async-timeout==4.0.3
backports.tarfile==1.2.0
Brotli==1.1.0
certifi==2024.7.4
charset-normalizer==3.3.2
click==8.1.7
distro==1.9.0
duckduckgo_search==5.3.1b1
exceptiongroup==1.2.2
gTTS==2.5.3
h11==0.14.0
h2==4.1.0
hpack==4.0.0
httpcore==1.0.5
httpx==0.27.0
hyperframe==6.0.1
idna==3.8
jaraco.context==6.0.1
more-itertools==10.4.0
openai==1.29.0
pillow==10.3.0
pydantic==2.8.2
pydantic_core==2.20.1
pydub==0.25.1
python-dotenv==1.0.1
python-telegram-bot==21.1.1
requests~=2.31.0
pytube==15.0.0
redis==5.0.8
regex==2024.7.24
requests==2.31.0
six==1.16.0
sniffio==1.3.1
socksio==1.0.0
spotipy==2.23.0
tenacity==8.3.0
wolframalpha~=5.0.0
duckduckgo_search==5.3.1b1
spotipy~=2.23.0
pytube~=15.0.0
gtts~=2.5.1
whois~=0.9.27
Pillow~=10.3.0
tiktoken==0.7.0
tqdm==4.66.5
typing_extensions==4.12.2
urllib3==2.2.2
whois==0.9.27
wolframalpha==5.0.1
xmltodict==0.13.0