mirror of
https://github.com/aljazceru/chatgpt-telegram-bot.git
synced 2025-12-20 22:24:57 +01:00
Merge branch 'main' into main
This commit is contained in:
ned
@@ -17,10 +17,12 @@ ALLOWED_TELEGRAM_USER_IDS=USER_ID_1,USER_ID_2
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# TOKEN_PRICE=0.002
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# IMAGE_PRICES=0.016,0.018,0.02
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# TRANSCRIPTION_PRICE=0.006
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# VISION_TOKEN_PRICE=0.01
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# ENABLE_QUOTING=true
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# ENABLE_IMAGE_GENERATION=true
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# ENABLE_TTS_GENERATION=true
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# ENABLE_TRANSCRIPTION=true
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# ENABLE_VISION=true
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# PROXY=http://localhost:8080
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# OPENAI_MODEL=gpt-3.5-turbo
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# OPENAI_BASE_URL=https://example.com/v1/
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@@ -28,10 +30,12 @@ ALLOWED_TELEGRAM_USER_IDS=USER_ID_1,USER_ID_2
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# SHOW_USAGE=false
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# STREAM=true
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# MAX_TOKENS=1200
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# VISION_MAX_TOKENS=300
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# MAX_HISTORY_SIZE=15
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# MAX_CONVERSATION_AGE_MINUTES=180
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# VOICE_REPLY_WITH_TRANSCRIPT_ONLY=true
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# VOICE_REPLY_PROMPTS="Hi bot;Hey bot;Hi chat;Hey chat"
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# VISION_PROMPT="What is in this image"
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# N_CHOICES=1
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# TEMPERATURE=1.0
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# PRESENCE_PENALTY=0.0
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@@ -41,9 +45,13 @@ ALLOWED_TELEGRAM_USER_IDS=USER_ID_1,USER_ID_2
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# IMAGE_STYLE=natural
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# IMAGE_SIZE=1024x1024
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# IMAGE_FORMAT=document
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# VISION_DETAIL="low"
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# GROUP_TRIGGER_KEYWORD=""
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# IGNORE_GROUP_TRANSCRIPTIONS=true
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# IGNORE_GROUP_VISION=true
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# TTS_MODEL="tts-1"
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# TTS_VOICE="alloy"
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# TTS_PRICES=0.015,0.030
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# BOT_LANGUAGE=en
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# ENABLE_VISION_FOLLOW_UP_QUESTIONS="true"
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# VISION_MODEL="gpt-4-vision-preview"
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@@ -75,6 +75,7 @@ The following parameters are optional and can be set in the `.env` file:
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| `TOKEN_PRICE` | $-price per 1000 tokens used to compute cost information in usage statistics. Source: https://openai.com/pricing | `0.002` |
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| `IMAGE_PRICES` | A comma-separated list with 3 elements of prices for the different image sizes: `256x256`, `512x512` and `1024x1024`. Source: https://openai.com/pricing | `0.016,0.018,0.02` |
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| `TRANSCRIPTION_PRICE` | USD-price for one minute of audio transcription. Source: https://openai.com/pricing | `0.006` |
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| `VISION_TOKEN_PRICE` | USD-price per 1K tokens of image interpretation. Source: https://openai.com/pricing | `0.01` |
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| `TTS_PRICES` | A comma-separated list with prices for the tts models: `tts-1`, `tts-1-hd`. Source: https://openai.com/pricing | `0.015,0.030` |
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Check out the [Budget Manual](https://github.com/n3d1117/chatgpt-telegram-bot/discussions/184) for possible budget configurations.
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@@ -86,6 +87,7 @@ Check out the [Budget Manual](https://github.com/n3d1117/chatgpt-telegram-bot/di
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| `ENABLE_IMAGE_GENERATION` | Whether to enable image generation via the `/image` command | `true` |
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| `ENABLE_TRANSCRIPTION` | Whether to enable transcriptions of audio and video messages | `true` |
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| `ENABLE_TTS_GENERATION` | Whether to enable text to speech generation via the `/tts` | `true` |
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| `ENABLE_VISION` | Whether to enable vision capabilities in supported models | `true` |
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| `PROXY` | Proxy to be used for OpenAI and Telegram bot (e.g. `http://localhost:8080`) | - |
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| `OPENAI_PROXY` | Proxy to be used only for OpenAI (e.g. `http://localhost:8080`) | - |
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| `TELEGRAM_PROXY` | Proxy to be used only for Telegram bot (e.g. `http://localhost:8080`) | - |
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@@ -95,10 +97,14 @@ Check out the [Budget Manual](https://github.com/n3d1117/chatgpt-telegram-bot/di
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| `SHOW_USAGE` | Whether to show OpenAI token usage information after each response | `false` |
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| `STREAM` | Whether to stream responses. **Note**: incompatible, if enabled, with `N_CHOICES` higher than 1 | `true` |
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| `MAX_TOKENS` | Upper bound on how many tokens the ChatGPT API will return | `1200` for GPT-3, `2400` for GPT-4 |
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| `VISION_MAX_TOKENS` | Upper bound on how many tokens vision models will return | `300` for gpt-4-vision-preview |
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| `VISION_MODEL` | The Vision to Speech model to use. Allowed values: `gpt-4-vision-preview` | `gpt-4-vision-preview` |
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| `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` |
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| `MAX_HISTORY_SIZE` | Max number of messages to keep in memory, after which the conversation will be summarised to avoid excessive token usage | `15` |
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| `MAX_CONVERSATION_AGE_MINUTES` | Maximum number of minutes a conversation should live since the last message, after which the conversation will be reset | `180` |
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| `VOICE_REPLY_WITH_TRANSCRIPT_ONLY` | Whether to answer to voice messages with the transcript only or with a ChatGPT response of the transcript | `false` |
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| `VOICE_REPLY_PROMPTS` | A semicolon separated list of phrases (i.e. `Hi bot;Hello chat`). If the transcript starts with any of them, it will be treated as a prompt even if `VOICE_REPLY_WITH_TRANSCRIPT_ONLY` is set to `true` | - |
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| `VISION_PROMPT` | A phrase (i.e. `What is in this image`). The vision models use it as prompt to interpret a given image. If there is caption in the image sent to the bot, that supersedes this parameter | `What is in this image` |
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| `N_CHOICES` | Number of answers to generate for each input message. **Note**: setting this to a number higher than 1 will not work properly if `STREAM` is enabled | `1` |
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| `TEMPERATURE` | Number between 0 and 2. Higher values will make the output more random | `1.0` |
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| `PRESENCE_PENALTY` | Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far | `0.0` |
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@@ -108,8 +114,10 @@ Check out the [Budget Manual](https://github.com/n3d1117/chatgpt-telegram-bot/di
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| `IMAGE_QUALITY` | Quality of DALL·E images, only available for `dall-e-3`-model. Possible options: `standard` or `hd`, beware of [pricing differences](https://openai.com/pricing#image-models). | `standard` |
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| `IMAGE_STYLE` | Style for DALL·E image generation, only available for `dall-e-3`-model. Possible options: `vivid` or `natural`. Check availbe styles [here](https://platform.openai.com/docs/api-reference/images/create). | `vivid` |
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| `IMAGE_SIZE` | The DALL·E generated image size. Must be `256x256`, `512x512`, or `1024x1024` for dall-e-2. Must be `1024x1024` for dall-e-3 models. | `512x512` |
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| `VISION_DETAIL` | The detail parameter for vision models, explained [Vision Guide](https://platform.openai.com/docs/guides/vision). Allowed values: `low` or `high` | `auto` |
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| `GROUP_TRIGGER_KEYWORD` | If set, the bot in group chats will only respond to messages that start with this keyword | - |
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| `IGNORE_GROUP_TRANSCRIPTIONS` | If set to true, the bot will not process transcriptions in group chats | `true` |
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| `IGNORE_GROUP_VISION` | If set to true, the bot will not process vision queries in group chats | `true` |
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| `BOT_LANGUAGE` | Language of general bot messages. Currently available: `en`, `de`, `ru`, `tr`, `it`, `fi`, `es`, `id`, `nl`, `zh-cn`, `zh-tw`, `vi`, `fa`, `pt-br`, `uk`, `ms`, `uz`. [Contribute with additional translations](https://github.com/n3d1117/chatgpt-telegram-bot/discussions/219) | `en` |
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| `WHISPER_PROMPT` | To improve the accuracy of Whisper's transcription service, especially for specific names or terms, you can set up a custom message. [Speech to text - Prompting](https://platform.openai.com/docs/guides/speech-to-text/prompting) | `-` |
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| `TTS_VOICE` | The Text to Speech voice to use. Allowed values: `alloy`, `echo`, `fable`, `onyx`, `nova`, or `shimmer` | `alloy` |
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@@ -53,6 +53,11 @@ def main():
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'bot_language': os.environ.get('BOT_LANGUAGE', 'en'),
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'show_plugins_used': os.environ.get('SHOW_PLUGINS_USED', 'false').lower() == 'true',
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'whisper_prompt': os.environ.get('WHISPER_PROMPT', ''),
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'vision_model': os.environ.get('VISION_MODEL', 'gpt-4-vision-preview'),
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'enable_vision_follow_up_questions': os.environ.get('ENABLE_VISION_FOLLOW_UP_QUESTIONS', 'true').lower() == 'true',
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'vision_prompt': os.environ.get('VISION_PROMPT', 'What is in this image'),
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'vision_detail': os.environ.get('VISION_DETAIL', 'auto'),
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'vision_max_tokens': int(os.environ.get('VISION_MAX_TOKENS', '300')),
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'tts_model': os.environ.get('TTS_MODEL', 'tts-1'),
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'tts_voice': os.environ.get('TTS_VOICE', 'alloy'),
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}
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@@ -75,6 +80,7 @@ def main():
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'enable_quoting': os.environ.get('ENABLE_QUOTING', 'true').lower() == 'true',
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'enable_image_generation': os.environ.get('ENABLE_IMAGE_GENERATION', 'true').lower() == 'true',
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'enable_transcription': os.environ.get('ENABLE_TRANSCRIPTION', 'true').lower() == 'true',
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'enable_vision': os.environ.get('ENABLE_VISION', 'true').lower() == 'true',
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'enable_tts_generation': os.environ.get('ENABLE_TTS_GENERATION', 'true').lower() == 'true',
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'budget_period': os.environ.get('BUDGET_PERIOD', 'monthly').lower(),
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'user_budgets': os.environ.get('USER_BUDGETS', os.environ.get('MONTHLY_USER_BUDGETS', '*')),
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@@ -84,9 +90,11 @@ def main():
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'voice_reply_transcript': os.environ.get('VOICE_REPLY_WITH_TRANSCRIPT_ONLY', 'false').lower() == 'true',
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'voice_reply_prompts': os.environ.get('VOICE_REPLY_PROMPTS', '').split(';'),
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'ignore_group_transcriptions': os.environ.get('IGNORE_GROUP_TRANSCRIPTIONS', 'true').lower() == 'true',
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'ignore_group_vision': os.environ.get('IGNORE_GROUP_VISION', 'true').lower() == 'true',
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'group_trigger_keyword': os.environ.get('GROUP_TRIGGER_KEYWORD', ''),
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'token_price': float(os.environ.get('TOKEN_PRICE', 0.002)),
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'image_prices': [float(i) for i in os.environ.get('IMAGE_PRICES', "0.016,0.018,0.02").split(",")],
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'vision_token_price': float(os.environ.get('VISION_TOKEN_PRICE', '0.01')),
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'image_receive_mode': os.environ.get('IMAGE_FORMAT', "photo"),
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'tts_model': os.environ.get('TTS_MODEL', 'tts-1'),
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'tts_prices': [float(i) for i in os.environ.get('TTS_PRICES', "0.015,0.030").split(",")],
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@@ -13,10 +13,11 @@ import httpx
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import io
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from datetime import date
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from calendar import monthrange
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from PIL import Image
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from tenacity import retry, stop_after_attempt, wait_fixed, retry_if_exception_type
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from utils import is_direct_result
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from utils import is_direct_result, encode_image, decode_image
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from plugin_manager import PluginManager
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# Models can be found here: https://platform.openai.com/docs/models/overview
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@@ -24,8 +25,9 @@ GPT_3_MODELS = ("gpt-3.5-turbo", "gpt-3.5-turbo-0301", "gpt-3.5-turbo-0613")
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GPT_3_16K_MODELS = ("gpt-3.5-turbo-16k", "gpt-3.5-turbo-16k-0613", "gpt-3.5-turbo-1106")
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GPT_4_MODELS = ("gpt-4", "gpt-4-0314", "gpt-4-0613")
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GPT_4_32K_MODELS = ("gpt-4-32k", "gpt-4-32k-0314", "gpt-4-32k-0613")
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GPT_4_VISION_MODELS = ("gpt-4-vision-preview",)
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GPT_4_128K_MODELS = ("gpt-4-1106-preview",)
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GPT_ALL_MODELS = GPT_3_MODELS + GPT_3_16K_MODELS + GPT_4_MODELS + GPT_4_32K_MODELS + GPT_4_128K_MODELS
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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
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def default_max_tokens(model: str) -> int:
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@@ -45,6 +47,8 @@ def default_max_tokens(model: str) -> int:
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return base * 4
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elif model in GPT_4_32K_MODELS:
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return base * 8
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elif model in GPT_4_VISION_MODELS:
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return 4096
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elif model in GPT_4_128K_MODELS:
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return 4096
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@@ -59,6 +63,8 @@ def are_functions_available(model: str) -> bool:
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# Stable models will be updated to support functions on June 27, 2023
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if model in ("gpt-3.5-turbo", "gpt-3.5-turbo-1106", "gpt-4", "gpt-4-32k","gpt-4-1106-preview"):
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return datetime.date.today() > datetime.date(2023, 6, 27)
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if model == 'gpt-4-vision-preview':
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return False
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return True
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@@ -103,6 +109,7 @@ class OpenAIHelper:
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self.config = config
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self.plugin_manager = plugin_manager
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self.conversations: dict[int: list] = {} # {chat_id: history}
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self.conversations_vision: dict[int: bool] = {} # {chat_id: is_vision}
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self.last_updated: dict[int: datetime] = {} # {chat_id: last_update_timestamp}
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def get_conversation_stats(self, chat_id: int) -> tuple[int, int]:
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@@ -124,7 +131,7 @@ class OpenAIHelper:
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"""
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plugins_used = ()
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response = await self.__common_get_chat_response(chat_id, query)
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if self.config['enable_functions']:
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if self.config['enable_functions'] and not self.conversations_vision[chat_id]:
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response, plugins_used = await self.__handle_function_call(chat_id, response)
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if is_direct_result(response):
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return response, '0'
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@@ -167,7 +174,7 @@ class OpenAIHelper:
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"""
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plugins_used = ()
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response = await self.__common_get_chat_response(chat_id, query, stream=True)
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if self.config['enable_functions']:
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if self.config['enable_functions'] and not self.conversations_vision[chat_id]:
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response, plugins_used = await self.__handle_function_call(chat_id, response, stream=True)
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if is_direct_result(response):
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yield response, '0'
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@@ -236,7 +243,7 @@ class OpenAIHelper:
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self.conversations[chat_id] = self.conversations[chat_id][-self.config['max_history_size']:]
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|
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common_args = {
|
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'model': self.config['model'],
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'model': self.config['model'] if not self.conversations_vision[chat_id] else self.config['vision_model'],
|
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'messages': self.conversations[chat_id],
|
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'temperature': self.config['temperature'],
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'n': self.config['n_choices'],
|
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@@ -246,7 +253,7 @@ class OpenAIHelper:
|
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'stream': stream
|
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}
|
||||
|
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if self.config['enable_functions']:
|
||||
if self.config['enable_functions'] and not self.conversations_vision[chat_id]:
|
||||
functions = self.plugin_manager.get_functions_specs()
|
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if len(functions) > 0:
|
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common_args['functions'] = self.plugin_manager.get_functions_specs()
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@@ -378,6 +385,183 @@ class OpenAIHelper:
|
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logging.exception(e)
|
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raise Exception(f"⚠️ _{localized_text('error', self.config['bot_language'])}._ ⚠️\n{str(e)}") from e
|
||||
|
||||
@retry(
|
||||
reraise=True,
|
||||
retry=retry_if_exception_type(openai.RateLimitError),
|
||||
wait=wait_fixed(20),
|
||||
stop=stop_after_attempt(3)
|
||||
)
|
||||
async def __common_get_chat_response_vision(self, chat_id: int, content: list, stream=False):
|
||||
"""
|
||||
Request a response from the GPT model.
|
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:param chat_id: The chat ID
|
||||
:param query: The query to send to the model
|
||||
:return: The answer from the model and the number of tokens used
|
||||
"""
|
||||
bot_language = self.config['bot_language']
|
||||
try:
|
||||
if chat_id not in self.conversations or self.__max_age_reached(chat_id):
|
||||
self.reset_chat_history(chat_id)
|
||||
|
||||
self.last_updated[chat_id] = datetime.datetime.now()
|
||||
|
||||
if self.config['enable_vision_follow_up_questions']:
|
||||
self.conversations_vision[chat_id] = True
|
||||
self.__add_to_history(chat_id, role="user", content=content)
|
||||
else:
|
||||
for message in content:
|
||||
if message['type'] == 'text':
|
||||
query = message['text']
|
||||
break
|
||||
self.__add_to_history(chat_id, role="user", content=query)
|
||||
|
||||
# Summarize the chat history if it's too long to avoid excessive token usage
|
||||
token_count = self.__count_tokens(self.conversations[chat_id])
|
||||
exceeded_max_tokens = token_count + self.config['max_tokens'] > self.__max_model_tokens()
|
||||
exceeded_max_history_size = len(self.conversations[chat_id]) > self.config['max_history_size']
|
||||
|
||||
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}')
|
||||
self.reset_chat_history(chat_id, self.conversations[chat_id][0]['content'])
|
||||
self.__add_to_history(chat_id, role="assistant", content=summary)
|
||||
self.conversations[chat_id] += [last]
|
||||
except Exception as e:
|
||||
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}
|
||||
|
||||
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
|
||||
'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:
|
||||
raise e
|
||||
|
||||
except openai.BadRequestError as e:
|
||||
raise Exception(f"⚠️ _{localized_text('openai_invalid', bot_language)}._ ⚠️\n{str(e)}") from e
|
||||
|
||||
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'] } }]
|
||||
|
||||
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):
|
||||
# return response, '0'
|
||||
|
||||
answer = ''
|
||||
|
||||
if len(response.choices) > 1 and self.config['n_choices'] > 1:
|
||||
for index, choice in enumerate(response.choices):
|
||||
content = choice.message.content.strip()
|
||||
if index == 0:
|
||||
self.__add_to_history(chat_id, role="assistant", content=content)
|
||||
answer += f'{index + 1}\u20e3\n'
|
||||
answer += content
|
||||
answer += '\n\n'
|
||||
else:
|
||||
answer = response.choices[0].message.content.strip()
|
||||
self.__add_to_history(chat_id, role="assistant", content=answer)
|
||||
|
||||
bot_language = self.config['bot_language']
|
||||
# Plugins are not enabled either
|
||||
# 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 += "\n\n---\n" \
|
||||
f"💰 {str(response.usage.total_tokens)} {localized_text('stats_tokens', bot_language)}" \
|
||||
f" ({str(response.usage.prompt_tokens)} {localized_text('prompt', bot_language)}," \
|
||||
f" {str(response.usage.completion_tokens)} {localized_text('completion', bot_language)})"
|
||||
# if show_plugins_used:
|
||||
# answer += f"\n🔌 {', '.join(plugin_names)}"
|
||||
# elif show_plugins_used:
|
||||
# answer += f"\n\n---\n🔌 {', '.join(plugin_names)}"
|
||||
|
||||
return answer, response.usage.total_tokens
|
||||
|
||||
async def interpret_image_stream(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'] } }]
|
||||
|
||||
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):
|
||||
# yield response, '0'
|
||||
# return
|
||||
|
||||
answer = ''
|
||||
async for chunk in response:
|
||||
if len(chunk.choices) == 0:
|
||||
continue
|
||||
delta = chunk.choices[0].delta
|
||||
if delta.content:
|
||||
answer += delta.content
|
||||
yield answer, 'not_finished'
|
||||
answer = answer.strip()
|
||||
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)
|
||||
if self.config['show_usage']:
|
||||
answer += f"\n\n---\n💰 {tokens_used} {localized_text('stats_tokens', self.config['bot_language'])}"
|
||||
# if show_plugins_used:
|
||||
# answer += f"\n🔌 {', '.join(plugin_names)}"
|
||||
# elif show_plugins_used:
|
||||
# answer += f"\n\n---\n🔌 {', '.join(plugin_names)}"
|
||||
|
||||
yield answer, tokens_used
|
||||
|
||||
def reset_chat_history(self, chat_id, content=''):
|
||||
"""
|
||||
Resets the conversation history.
|
||||
@@ -385,6 +569,7 @@ class OpenAIHelper:
|
||||
if content == '':
|
||||
content = self.config['assistant_prompt']
|
||||
self.conversations[chat_id] = [{"role": "system", "content": content}]
|
||||
self.conversations_vision[chat_id] = False
|
||||
|
||||
def __max_age_reached(self, chat_id) -> bool:
|
||||
"""
|
||||
@@ -441,6 +626,8 @@ class OpenAIHelper:
|
||||
return base * 2
|
||||
if self.config['model'] in GPT_4_32K_MODELS:
|
||||
return base * 8
|
||||
if self.config['model'] in GPT_4_VISION_MODELS:
|
||||
return base * 31
|
||||
if self.config['model'] in GPT_4_128K_MODELS:
|
||||
return base * 31
|
||||
raise NotImplementedError(
|
||||
@@ -463,7 +650,7 @@ class OpenAIHelper:
|
||||
if model in GPT_3_MODELS + GPT_3_16K_MODELS:
|
||||
tokens_per_message = 4 # every message follows <|start|>{role/name}\n{content}<|end|>\n
|
||||
tokens_per_name = -1 # if there's a name, the role is omitted
|
||||
elif model in GPT_4_MODELS + GPT_4_32K_MODELS + GPT_4_128K_MODELS:
|
||||
elif model in GPT_4_MODELS + GPT_4_32K_MODELS + GPT_4_VISION_MODELS + GPT_4_128K_MODELS:
|
||||
tokens_per_message = 3
|
||||
tokens_per_name = 1
|
||||
else:
|
||||
@@ -472,12 +659,55 @@ class OpenAIHelper:
|
||||
for message in messages:
|
||||
num_tokens += tokens_per_message
|
||||
for key, value in message.items():
|
||||
if key == 'content':
|
||||
if isinstance(value, str):
|
||||
num_tokens += len(encoding.encode(value))
|
||||
else:
|
||||
for message1 in value:
|
||||
if message1['type'] == 'image_url':
|
||||
image = decode_image(message1['image_url']['url'])
|
||||
num_tokens += self.__count_tokens_vision(image)
|
||||
else:
|
||||
num_tokens += len(encoding.encode(message1['text']))
|
||||
else:
|
||||
num_tokens += len(encoding.encode(value))
|
||||
if key == "name":
|
||||
num_tokens += tokens_per_name
|
||||
num_tokens += 3 # every reply is primed with <|start|>assistant<|message|>
|
||||
return num_tokens
|
||||
|
||||
# no longer needed
|
||||
|
||||
def __count_tokens_vision(self, image_bytes: bytes) -> int:
|
||||
"""
|
||||
Counts the number of tokens for interpreting an image.
|
||||
:param image_bytes: image to interpret
|
||||
:return: the number of tokens required
|
||||
"""
|
||||
image_file = io.BytesIO(image_bytes)
|
||||
image = Image.open(image_file)
|
||||
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
|
||||
f = max(w / 768, h / 2048)
|
||||
if f > 1:
|
||||
w, h = int(w / f), int(h / f)
|
||||
tw, th = (w + 511) // 512, (h + 511) // 512
|
||||
tiles = tw * th
|
||||
num_tokens = base_tokens + tiles * 170
|
||||
return num_tokens
|
||||
else:
|
||||
raise NotImplementedError(f"""unknown parameter detail={detail} for model {model}.""")
|
||||
|
||||
# No longer works as of July 21st 2023, as OpenAI has removed the billing API
|
||||
# def get_billing_current_month(self):
|
||||
# """Gets billed usage for current month from OpenAI API.
|
||||
|
||||
@@ -3,16 +3,18 @@ from __future__ import annotations
|
||||
import asyncio
|
||||
import logging
|
||||
import os
|
||||
import io
|
||||
|
||||
from uuid import uuid4
|
||||
from telegram import BotCommandScopeAllGroupChats, Update, constants
|
||||
from telegram import InlineKeyboardMarkup, InlineKeyboardButton, InlineQueryResultArticle
|
||||
from telegram import InputTextMessageContent, BotCommand
|
||||
from telegram.error import RetryAfter, TimedOut
|
||||
from telegram.error import RetryAfter, TimedOut, BadRequest
|
||||
from telegram.ext import ApplicationBuilder, CommandHandler, MessageHandler, \
|
||||
filters, InlineQueryHandler, CallbackQueryHandler, Application, ContextTypes, CallbackContext
|
||||
|
||||
from pydub import AudioSegment
|
||||
from PIL import Image
|
||||
|
||||
from utils import is_group_chat, get_thread_id, message_text, wrap_with_indicator, split_into_chunks, \
|
||||
edit_message_with_retry, get_stream_cutoff_values, is_allowed, get_remaining_budget, is_admin, is_within_budget, \
|
||||
@@ -97,6 +99,7 @@ class ChatGPTTelegramBot:
|
||||
images_today, images_month = self.usage[user_id].get_current_image_count()
|
||||
(transcribe_minutes_today, transcribe_seconds_today, transcribe_minutes_month,
|
||||
transcribe_seconds_month) = self.usage[user_id].get_current_transcription_duration()
|
||||
vision_today, vision_month = self.usage[user_id].get_current_vision_tokens()
|
||||
characters_today, characters_month = self.usage[user_id].get_current_tts_usage()
|
||||
current_cost = self.usage[user_id].get_current_cost()
|
||||
|
||||
@@ -117,6 +120,10 @@ class ChatGPTTelegramBot:
|
||||
if self.config.get('enable_image_generation', False):
|
||||
text_today_images = f"{images_today} {localized_text('stats_images', bot_language)}\n"
|
||||
|
||||
text_today_vision = ""
|
||||
if self.config.get('enable_vision', False):
|
||||
text_today_vision = f"{vision_today} {localized_text('stats_vision', bot_language)}\n"
|
||||
|
||||
text_today_tts = ""
|
||||
if self.config.get('enable_tts_generation', False):
|
||||
text_today_tts = f"{characters_today} {localized_text('stats_tts', bot_language)}\n"
|
||||
@@ -125,6 +132,7 @@ class ChatGPTTelegramBot:
|
||||
f"*{localized_text('usage_today', bot_language)}:*\n"
|
||||
f"{tokens_today} {localized_text('stats_tokens', bot_language)}\n"
|
||||
f"{text_today_images}" # Include the image statistics for today if applicable
|
||||
f"{text_today_vision}"
|
||||
f"{text_today_tts}"
|
||||
f"{transcribe_minutes_today} {localized_text('stats_transcribe', bot_language)[0]} "
|
||||
f"{transcribe_seconds_today} {localized_text('stats_transcribe', bot_language)[1]}\n"
|
||||
@@ -136,6 +144,10 @@ class ChatGPTTelegramBot:
|
||||
if self.config.get('enable_image_generation', False):
|
||||
text_month_images = f"{images_month} {localized_text('stats_images', bot_language)}\n"
|
||||
|
||||
text_month_vision = ""
|
||||
if self.config.get('enable_vision', False):
|
||||
text_month_vision = f"{vision_month} {localized_text('stats_vision', bot_language)}\n"
|
||||
|
||||
text_month_tts = ""
|
||||
if self.config.get('enable_tts_generation', False):
|
||||
text_month_tts = f"{characters_month} {localized_text('stats_tts', bot_language)}\n"
|
||||
@@ -145,6 +157,7 @@ class ChatGPTTelegramBot:
|
||||
f"*{localized_text('usage_month', bot_language)}:*\n"
|
||||
f"{tokens_month} {localized_text('stats_tokens', bot_language)}\n"
|
||||
f"{text_month_images}" # Include the image statistics for the month if applicable
|
||||
f"{text_month_vision}"
|
||||
f"{text_month_tts}"
|
||||
f"{transcribe_minutes_month} {localized_text('stats_transcribe', bot_language)[0]} "
|
||||
f"{transcribe_seconds_month} {localized_text('stats_transcribe', bot_language)[1]}\n"
|
||||
@@ -438,6 +451,198 @@ class ChatGPTTelegramBot:
|
||||
|
||||
await wrap_with_indicator(update, context, _execute, constants.ChatAction.TYPING)
|
||||
|
||||
async def vision(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
|
||||
"""
|
||||
Interpret image using vision model.
|
||||
"""
|
||||
if not self.config['enable_vision'] or not await self.check_allowed_and_within_budget(update, context):
|
||||
return
|
||||
|
||||
chat_id = update.effective_chat.id
|
||||
prompt = update.message.caption
|
||||
|
||||
if is_group_chat(update):
|
||||
if self.config['ignore_group_vision']:
|
||||
logging.info(f'Vision coming from group chat, ignoring...')
|
||||
return
|
||||
else:
|
||||
trigger_keyword = self.config['group_trigger_keyword']
|
||||
if (prompt is None and trigger_keyword != '') or \
|
||||
(prompt is not None and not prompt.lower().startswith(trigger_keyword.lower())):
|
||||
logging.info(f'Vision coming from group chat with wrong keyword, ignoring...')
|
||||
return
|
||||
|
||||
image = update.message.effective_attachment[-1]
|
||||
|
||||
|
||||
async def _execute():
|
||||
bot_language = self.config['bot_language']
|
||||
try:
|
||||
media_file = await context.bot.get_file(image.file_id)
|
||||
temp_file = io.BytesIO(await media_file.download_as_bytearray())
|
||||
except Exception as e:
|
||||
logging.exception(e)
|
||||
await update.effective_message.reply_text(
|
||||
message_thread_id=get_thread_id(update),
|
||||
reply_to_message_id=get_reply_to_message_id(self.config, update),
|
||||
text=(
|
||||
f"{localized_text('media_download_fail', bot_language)[0]}: "
|
||||
f"{str(e)}. {localized_text('media_download_fail', bot_language)[1]}"
|
||||
),
|
||||
parse_mode=constants.ParseMode.MARKDOWN
|
||||
)
|
||||
return
|
||||
|
||||
# convert jpg from telegram to png as understood by openai
|
||||
|
||||
temp_file_png = io.BytesIO()
|
||||
|
||||
try:
|
||||
original_image = Image.open(temp_file)
|
||||
|
||||
original_image.save(temp_file_png, format='PNG')
|
||||
logging.info(f'New vision request received from user {update.message.from_user.name} '
|
||||
f'(id: {update.message.from_user.id})')
|
||||
|
||||
except Exception as e:
|
||||
logging.exception(e)
|
||||
await update.effective_message.reply_text(
|
||||
message_thread_id=get_thread_id(update),
|
||||
reply_to_message_id=get_reply_to_message_id(self.config, update),
|
||||
text=localized_text('media_type_fail', bot_language)
|
||||
)
|
||||
|
||||
|
||||
|
||||
user_id = update.message.from_user.id
|
||||
if user_id not in self.usage:
|
||||
self.usage[user_id] = UsageTracker(user_id, update.message.from_user.name)
|
||||
|
||||
if self.config['stream']:
|
||||
|
||||
stream_response = self.openai.interpret_image_stream(chat_id=chat_id, fileobj=temp_file_png, prompt=prompt)
|
||||
i = 0
|
||||
prev = ''
|
||||
sent_message = None
|
||||
backoff = 0
|
||||
stream_chunk = 0
|
||||
|
||||
async for content, tokens in stream_response:
|
||||
if is_direct_result(content):
|
||||
return await handle_direct_result(self.config, update, content)
|
||||
|
||||
if len(content.strip()) == 0:
|
||||
continue
|
||||
|
||||
stream_chunks = split_into_chunks(content)
|
||||
if len(stream_chunks) > 1:
|
||||
content = stream_chunks[-1]
|
||||
if stream_chunk != len(stream_chunks) - 1:
|
||||
stream_chunk += 1
|
||||
try:
|
||||
await edit_message_with_retry(context, chat_id, str(sent_message.message_id),
|
||||
stream_chunks[-2])
|
||||
except:
|
||||
pass
|
||||
try:
|
||||
sent_message = await update.effective_message.reply_text(
|
||||
message_thread_id=get_thread_id(update),
|
||||
text=content if len(content) > 0 else "..."
|
||||
)
|
||||
except:
|
||||
pass
|
||||
continue
|
||||
|
||||
cutoff = get_stream_cutoff_values(update, content)
|
||||
cutoff += backoff
|
||||
|
||||
if i == 0:
|
||||
try:
|
||||
if sent_message is not None:
|
||||
await context.bot.delete_message(chat_id=sent_message.chat_id,
|
||||
message_id=sent_message.message_id)
|
||||
sent_message = await update.effective_message.reply_text(
|
||||
message_thread_id=get_thread_id(update),
|
||||
reply_to_message_id=get_reply_to_message_id(self.config, update),
|
||||
text=content,
|
||||
)
|
||||
except:
|
||||
continue
|
||||
|
||||
elif abs(len(content) - len(prev)) > cutoff or tokens != 'not_finished':
|
||||
prev = content
|
||||
|
||||
try:
|
||||
use_markdown = tokens != 'not_finished'
|
||||
await edit_message_with_retry(context, chat_id, str(sent_message.message_id),
|
||||
text=content, markdown=use_markdown)
|
||||
|
||||
except RetryAfter as e:
|
||||
backoff += 5
|
||||
await asyncio.sleep(e.retry_after)
|
||||
continue
|
||||
|
||||
except TimedOut:
|
||||
backoff += 5
|
||||
await asyncio.sleep(0.5)
|
||||
continue
|
||||
|
||||
except Exception:
|
||||
backoff += 5
|
||||
continue
|
||||
|
||||
await asyncio.sleep(0.01)
|
||||
|
||||
i += 1
|
||||
if tokens != 'not_finished':
|
||||
total_tokens = int(tokens)
|
||||
|
||||
|
||||
else:
|
||||
|
||||
try:
|
||||
interpretation, total_tokens = await self.openai.interpret_image(chat_id, temp_file_png, prompt=prompt)
|
||||
|
||||
|
||||
try:
|
||||
await update.effective_message.reply_text(
|
||||
message_thread_id=get_thread_id(update),
|
||||
reply_to_message_id=get_reply_to_message_id(self.config, update),
|
||||
text=interpretation,
|
||||
parse_mode=constants.ParseMode.MARKDOWN
|
||||
)
|
||||
except BadRequest:
|
||||
try:
|
||||
await update.effective_message.reply_text(
|
||||
message_thread_id=get_thread_id(update),
|
||||
reply_to_message_id=get_reply_to_message_id(self.config, update),
|
||||
text=interpretation
|
||||
)
|
||||
except Exception as e:
|
||||
logging.exception(e)
|
||||
await update.effective_message.reply_text(
|
||||
message_thread_id=get_thread_id(update),
|
||||
reply_to_message_id=get_reply_to_message_id(self.config, update),
|
||||
text=f"{localized_text('vision_fail', bot_language)}: {str(e)}",
|
||||
parse_mode=constants.ParseMode.MARKDOWN
|
||||
)
|
||||
except Exception as e:
|
||||
logging.exception(e)
|
||||
await update.effective_message.reply_text(
|
||||
message_thread_id=get_thread_id(update),
|
||||
reply_to_message_id=get_reply_to_message_id(self.config, update),
|
||||
text=f"{localized_text('vision_fail', bot_language)}: {str(e)}",
|
||||
parse_mode=constants.ParseMode.MARKDOWN
|
||||
)
|
||||
vision_token_price = self.config['vision_token_price']
|
||||
self.usage[user_id].add_vision_tokens(total_tokens, vision_token_price)
|
||||
|
||||
allowed_user_ids = self.config['allowed_user_ids'].split(',')
|
||||
if str(user_id) not in allowed_user_ids and 'guests' in self.usage:
|
||||
self.usage["guests"].add_vision_tokens(total_tokens, vision_token_price)
|
||||
|
||||
await wrap_with_indicator(update, context, _execute, constants.ChatAction.TYPING)
|
||||
|
||||
async def prompt(self, update: Update, context: ContextTypes.DEFAULT_TYPE):
|
||||
"""
|
||||
React to incoming messages and respond accordingly.
|
||||
@@ -861,6 +1066,9 @@ class ChatGPTTelegramBot:
|
||||
application.add_handler(CommandHandler(
|
||||
'chat', self.prompt, filters=filters.ChatType.GROUP | filters.ChatType.SUPERGROUP)
|
||||
)
|
||||
application.add_handler(MessageHandler(
|
||||
filters.PHOTO | filters.Document.IMAGE,
|
||||
self.vision))
|
||||
application.add_handler(MessageHandler(
|
||||
filters.AUDIO | filters.VOICE | filters.Document.AUDIO |
|
||||
filters.VIDEO | filters.VIDEO_NOTE | filters.Document.VIDEO,
|
||||
|
||||
@@ -56,6 +56,8 @@ class UsageTracker:
|
||||
if os.path.isfile(self.user_file):
|
||||
with open(self.user_file, "r") as file:
|
||||
self.usage = json.load(file)
|
||||
if 'vision_tokens' not in self.usage['usage_history']:
|
||||
self.usage['usage_history']['vision_tokens'] = {}
|
||||
if 'tts_characters' not in self.usage['usage_history']:
|
||||
self.usage['usage_history']['tts_characters'] = {}
|
||||
else:
|
||||
@@ -65,7 +67,7 @@ class UsageTracker:
|
||||
self.usage = {
|
||||
"user_name": user_name,
|
||||
"current_cost": {"day": 0.0, "month": 0.0, "all_time": 0.0, "last_update": str(date.today())},
|
||||
"usage_history": {"chat_tokens": {}, "transcription_seconds": {}, "number_images": {}, "tts_characters": {}}
|
||||
"usage_history": {"chat_tokens": {}, "transcription_seconds": {}, "number_images": {}, "tts_characters": {}, "vision_tokens":{}}
|
||||
}
|
||||
|
||||
# token usage functions:
|
||||
@@ -153,6 +155,47 @@ class UsageTracker:
|
||||
usage_month += sum(images)
|
||||
return usage_day, usage_month
|
||||
|
||||
|
||||
# vision usage functions
|
||||
def add_vision_tokens(self, tokens, vision_token_price=0.01):
|
||||
"""
|
||||
Adds requested vision tokens to a users usage history and updates current cost.
|
||||
:param tokens: total tokens used in last request
|
||||
:param vision_token_price: price per 1K tokens transcription, defaults to 0.01
|
||||
"""
|
||||
today = date.today()
|
||||
token_price = round(tokens * vision_token_price / 1000, 2)
|
||||
self.add_current_costs(token_price)
|
||||
|
||||
# update usage_history
|
||||
if str(today) in self.usage["usage_history"]["vision_tokens"]:
|
||||
# add requested seconds to existing date
|
||||
self.usage["usage_history"]["vision_tokens"][str(today)] += tokens
|
||||
else:
|
||||
# create new entry for current date
|
||||
self.usage["usage_history"]["vision_tokens"][str(today)] = tokens
|
||||
|
||||
# write updated token usage to user file
|
||||
with open(self.user_file, "w") as outfile:
|
||||
json.dump(self.usage, outfile)
|
||||
|
||||
def get_current_vision_tokens(self):
|
||||
"""Get vision tokens for today and this month.
|
||||
|
||||
:return: total amount of vision tokens per day and per month
|
||||
"""
|
||||
today = date.today()
|
||||
if str(today) in self.usage["usage_history"]["vision_tokens"]:
|
||||
tokens_day = self.usage["usage_history"]["vision_tokens"][str(today)]
|
||||
else:
|
||||
tokens_day = 0
|
||||
month = str(today)[:7] # year-month as string
|
||||
tokens_month = 0
|
||||
for today, tokens in self.usage["usage_history"]["vision_tokens"].items():
|
||||
if today.startswith(month):
|
||||
tokens_month += tokens
|
||||
return tokens_day, tokens_month
|
||||
|
||||
# tts usage functions:
|
||||
|
||||
def add_tts_request(self, text_length, tts_model, tts_prices):
|
||||
@@ -289,14 +332,15 @@ class UsageTracker:
|
||||
cost_all_time = self.usage["current_cost"].get("all_time", self.initialize_all_time_cost())
|
||||
return {"cost_today": cost_day, "cost_month": cost_month, "cost_all_time": cost_all_time}
|
||||
|
||||
def initialize_all_time_cost(self, tokens_price=0.002, image_prices="0.016,0.018,0.02", minute_price=0.006, tts_prices='0.015,0.030'):
|
||||
def initialize_all_time_cost(self, tokens_price=0.002, image_prices="0.016,0.018,0.02", minute_price=0.006, vision_token_price=0.01, tts_prices='0.015,0.030'):
|
||||
"""Get total USD amount of all requests in history
|
||||
|
||||
:param tokens_price: price per 1000 tokens, defaults to 0.002
|
||||
:param image_prices: prices for images of sizes ["256x256", "512x512", "1024x1024"],
|
||||
defaults to [0.016, 0.018, 0.02]
|
||||
:param minute_price: price per minute transcription, defaults to 0.006
|
||||
:param character_price: price per character tts per model ['tts-1', 'tts-1-hd'], defaults to [0.015, 0.030]
|
||||
:param vision_token_price: price per 1K vision token interpretation, defaults to 0.01
|
||||
:param tts_prices: price per 1K characters tts per model ['tts-1', 'tts-1-hd'], defaults to [0.015, 0.030]
|
||||
:return: total cost of all requests
|
||||
"""
|
||||
total_tokens = sum(self.usage['usage_history']['chat_tokens'].values())
|
||||
@@ -309,9 +353,12 @@ class UsageTracker:
|
||||
total_transcription_seconds = sum(self.usage['usage_history']['transcription_seconds'].values())
|
||||
transcription_cost = round(total_transcription_seconds * minute_price / 60, 2)
|
||||
|
||||
total_vision_tokens = sum(self.usage['usage_history']['vision_tokens'].values())
|
||||
vision_cost = round(total_vision_tokens * vision_token_price / 1000, 2)
|
||||
|
||||
total_characters = [sum(tts_model.values()) for tts_model in self.usage['usage_history']['tts_characters'].values()]
|
||||
tts_prices_list = [float(x) for x in tts_prices.split(',')]
|
||||
tts_cost = round(sum([count * price / 1000 for count, price in zip(total_characters, tts_prices_list)]), 2)
|
||||
|
||||
all_time_cost = token_cost + transcription_cost + image_cost + tts_cost
|
||||
all_time_cost = token_cost + transcription_cost + image_cost + vision_cost + tts_cost
|
||||
return all_time_cost
|
||||
|
||||
11
bot/utils.py
11
bot/utils.py
@@ -5,6 +5,7 @@ import itertools
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import base64
|
||||
|
||||
import telegram
|
||||
from telegram import Message, MessageEntity, Update, ChatMember, constants
|
||||
@@ -377,3 +378,13 @@ def cleanup_intermediate_files(response: any):
|
||||
if format == 'path':
|
||||
if os.path.exists(value):
|
||||
os.remove(value)
|
||||
|
||||
|
||||
# Function to encode the image
|
||||
def encode_image(fileobj):
|
||||
image = base64.b64encode(fileobj.getvalue()).decode('utf-8')
|
||||
return f'data:image/jpeg;base64,{image}'
|
||||
|
||||
def decode_image(imgbase64):
|
||||
image = imgbase64[len('data:image/jpeg;base64,'):]
|
||||
return base64.b64decode(image)
|
||||
|
||||
@@ -11,3 +11,4 @@ spotipy~=2.23.0
|
||||
pytube~=15.0.0
|
||||
gtts~=2.3.2
|
||||
whois~=0.9.27
|
||||
Pillow~=10.1.0
|
||||
|
||||
@@ -15,6 +15,7 @@
|
||||
"usage_month":"Usage this month",
|
||||
"stats_tokens":"tokens",
|
||||
"stats_images":"images generated",
|
||||
"stats_vision":"image tokens interpreted",
|
||||
"stats_tts":"characters converted to speech",
|
||||
"stats_transcribe":["minutes and", "seconds transcribed"],
|
||||
"stats_total":"💰 For a total amount of $",
|
||||
@@ -27,6 +28,7 @@
|
||||
"reset_done":"Done!",
|
||||
"image_no_prompt":"Please provide a prompt! (e.g. /image cat)",
|
||||
"image_fail":"Failed to generate image",
|
||||
"vision_fail":"Failed to interpret image",
|
||||
"tts_no_prompt":"Please provide text! (e.g. /tts my house)",
|
||||
"tts_fail":"Failed to generate speech",
|
||||
"media_download_fail":["Failed to download audio file", "Make sure the file is not too large. (max 20MB)"],
|
||||
|
||||
Reference in New Issue
Block a user