# =========== Copyright 2023 @ CAMEL-AI.org. All Rights Reserved. ===========
# Licensed under the Apache License, Version 2.0 (the “License”);
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an “AS IS” BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# =========== Copyright 2023 @ CAMEL-AI.org. All Rights Reserved. ===========
import re
from enum import Enum, EnumMeta
[docs]
class RoleType(Enum):
ASSISTANT = "assistant"
USER = "user"
CRITIC = "critic"
EMBODIMENT = "embodiment"
DEFAULT = "default"
[docs]
class ModelType(Enum):
GPT_3_5_TURBO = "gpt-3.5-turbo"
GPT_4 = "gpt-4"
GPT_4_TURBO = "gpt-4-turbo"
GPT_4O = "gpt-4o"
GPT_4O_MINI = "gpt-4o-mini"
O1_PREVIEW = "o1-preview"
O1_MINI = "o1-mini"
GLM_4 = "glm-4"
GLM_4_OPEN_SOURCE = "glm-4-open-source"
GLM_4V = 'glm-4v'
GLM_3_TURBO = "glm-3-turbo"
GROQ_LLAMA_3_1_8B = "llama-3.1-8b-instant"
GROQ_LLAMA_3_1_70B = "llama-3.1-70b-versatile"
GROQ_LLAMA_3_1_405B = "llama-3.1-405b-reasoning"
GROQ_LLAMA_3_8B = "llama3-8b-8192"
GROQ_LLAMA_3_70B = "llama3-70b-8192"
GROQ_MIXTRAL_8_7B = "mixtral-8x7b-32768"
GROQ_GEMMA_7B_IT = "gemma-7b-it"
GROQ_GEMMA_2_9B_IT = "gemma2-9b-it"
STUB = "stub"
LLAMA_2 = "llama-2"
LLAMA_3 = "llama-3"
VICUNA = "vicuna"
VICUNA_16K = "vicuna-16k"
QWEN_2 = "qwen-2"
# Legacy anthropic models
# NOTE: anthropic legacy models only Claude 2.1 has system prompt support
CLAUDE_2_1 = "claude-2.1"
CLAUDE_2_0 = "claude-2.0"
CLAUDE_INSTANT_1_2 = "claude-instant-1.2"
# Claude3 models
CLAUDE_3_OPUS = "claude-3-opus-20240229"
CLAUDE_3_SONNET = "claude-3-sonnet-20240229"
CLAUDE_3_HAIKU = "claude-3-haiku-20240307"
CLAUDE_3_5_SONNET = "claude-3-5-sonnet-20240620"
# Nvidia models
NEMOTRON_4_REWARD = "nvidia/nemotron-4-340b-reward"
# Gemini models
GEMINI_1_5_FLASH = "gemini-1.5-flash"
GEMINI_1_5_PRO = "gemini-1.5-pro"
# Mistral AI models
MISTRAL_LARGE = "mistral-large-latest"
MISTRAL_NEMO = "open-mistral-nemo"
MISTRAL_CODESTRAL = "codestral-latest"
MISTRAL_7B = "open-mistral-7b"
MISTRAL_MIXTRAL_8x7B = "open-mixtral-8x7b"
MISTRAL_MIXTRAL_8x22B = "open-mixtral-8x22b"
MISTRAL_CODESTRAL_MAMBA = "open-codestral-mamba"
# Reka models
REKA_CORE = "reka-core"
REKA_FLASH = "reka-flash"
REKA_EDGE = "reka-edge"
@property
def value_for_tiktoken(self) -> str:
if self.is_openai:
return self.value
return "gpt-4o-mini"
@property
def supports_tool_calling(self) -> bool:
return any([self.is_openai, self.is_gemini, self.is_mistral])
@property
def is_openai(self) -> bool:
r"""Returns whether this type of models is an OpenAI-released model."""
return self in {
ModelType.GPT_3_5_TURBO,
ModelType.GPT_4,
ModelType.GPT_4_TURBO,
ModelType.GPT_4O,
ModelType.GPT_4O_MINI,
ModelType.O1_PREVIEW,
ModelType.O1_MINI,
}
@property
def is_azure_openai(self) -> bool:
r"""Returns whether this type of models is an OpenAI-released model
from Azure.
"""
return self in {
ModelType.GPT_3_5_TURBO,
ModelType.GPT_4,
ModelType.GPT_4_TURBO,
ModelType.GPT_4O,
}
@property
def is_zhipuai(self) -> bool:
r"""Returns whether this type of models is an ZhipuAI model."""
return self in {
ModelType.GLM_3_TURBO,
ModelType.GLM_4,
ModelType.GLM_4V,
}
@property
def is_open_source(self) -> bool:
r"""Returns whether this type of models is open-source."""
return self in {
ModelType.LLAMA_2,
ModelType.LLAMA_3,
ModelType.QWEN_2,
ModelType.GLM_4_OPEN_SOURCE,
ModelType.VICUNA,
ModelType.VICUNA_16K,
}
@property
def is_anthropic(self) -> bool:
r"""Returns whether this type of models is Anthropic-released model.
Returns:
bool: Whether this type of models is anthropic.
"""
return self in {
ModelType.CLAUDE_INSTANT_1_2,
ModelType.CLAUDE_2_0,
ModelType.CLAUDE_2_1,
ModelType.CLAUDE_3_OPUS,
ModelType.CLAUDE_3_SONNET,
ModelType.CLAUDE_3_HAIKU,
ModelType.CLAUDE_3_5_SONNET,
}
@property
def is_groq(self) -> bool:
r"""Returns whether this type of models is served by Groq."""
return self in {
ModelType.GROQ_LLAMA_3_1_8B,
ModelType.GROQ_LLAMA_3_1_70B,
ModelType.GROQ_LLAMA_3_1_405B,
ModelType.GROQ_LLAMA_3_8B,
ModelType.GROQ_LLAMA_3_70B,
ModelType.GROQ_MIXTRAL_8_7B,
ModelType.GROQ_GEMMA_7B_IT,
ModelType.GROQ_GEMMA_2_9B_IT,
}
@property
def is_mistral(self) -> bool:
r"""Returns whether this type of models is served by Mistral."""
return self in {
ModelType.MISTRAL_LARGE,
ModelType.MISTRAL_NEMO,
ModelType.MISTRAL_CODESTRAL,
ModelType.MISTRAL_7B,
ModelType.MISTRAL_MIXTRAL_8x7B,
ModelType.MISTRAL_MIXTRAL_8x22B,
ModelType.MISTRAL_CODESTRAL_MAMBA,
}
@property
def is_nvidia(self) -> bool:
r"""Returns whether this type of models is Nvidia-released model.
Returns:
bool: Whether this type of models is nvidia.
"""
return self in {
ModelType.NEMOTRON_4_REWARD,
}
@property
def is_gemini(self) -> bool:
r"""Returns whether this type of models is Gemini model.
Returns:
bool: Whether this type of models is gemini.
"""
return self in {ModelType.GEMINI_1_5_FLASH, ModelType.GEMINI_1_5_PRO}
@property
def is_reka(self) -> bool:
r"""Returns whether this type of models is Reka model.
Returns:
bool: Whether this type of models is Reka.
"""
return self in {
ModelType.REKA_CORE,
ModelType.REKA_EDGE,
ModelType.REKA_FLASH,
}
@property
def token_limit(self) -> int:
r"""Returns the maximum token limit for a given model.
Returns:
int: The maximum token limit for the given model.
"""
if self is ModelType.GLM_4V:
return 1024
elif self is ModelType.VICUNA:
# reference: https://lmsys.org/blog/2023-03-30-vicuna/
return 2048
elif self in {
ModelType.LLAMA_2,
ModelType.NEMOTRON_4_REWARD,
ModelType.STUB,
ModelType.REKA_CORE,
ModelType.REKA_EDGE,
ModelType.REKA_FLASH,
}:
return 4_096
elif self in {
ModelType.GPT_4,
ModelType.GROQ_LLAMA_3_8B,
ModelType.GROQ_LLAMA_3_70B,
ModelType.GROQ_GEMMA_7B_IT,
ModelType.GROQ_GEMMA_2_9B_IT,
ModelType.LLAMA_3,
ModelType.GLM_3_TURBO,
ModelType.GLM_4,
ModelType.GLM_4_OPEN_SOURCE,
}:
return 8_192
elif self in {
ModelType.GPT_3_5_TURBO,
ModelType.VICUNA_16K,
}:
return 16_384
elif self in {
ModelType.MISTRAL_CODESTRAL,
ModelType.MISTRAL_7B,
ModelType.MISTRAL_MIXTRAL_8x7B,
ModelType.GROQ_MIXTRAL_8_7B,
}:
return 32_768
elif self in {ModelType.MISTRAL_MIXTRAL_8x22B}:
return 64_000
elif self in {ModelType.CLAUDE_2_0, ModelType.CLAUDE_INSTANT_1_2}:
return 100_000
elif self in {
ModelType.GPT_4O,
ModelType.GPT_4O_MINI,
ModelType.GPT_4_TURBO,
ModelType.O1_PREVIEW,
ModelType.O1_MINI,
ModelType.MISTRAL_LARGE,
ModelType.MISTRAL_NEMO,
ModelType.QWEN_2,
}:
return 128_000
elif self in {
ModelType.GROQ_LLAMA_3_1_8B,
ModelType.GROQ_LLAMA_3_1_70B,
ModelType.GROQ_LLAMA_3_1_405B,
}:
return 131_072
elif self in {
ModelType.CLAUDE_2_1,
ModelType.CLAUDE_3_OPUS,
ModelType.CLAUDE_3_SONNET,
ModelType.CLAUDE_3_HAIKU,
ModelType.CLAUDE_3_5_SONNET,
}:
return 200_000
elif self in {
ModelType.MISTRAL_CODESTRAL_MAMBA,
}:
return 256_000
elif self in {ModelType.GEMINI_1_5_FLASH, ModelType.GEMINI_1_5_PRO}:
return 1_048_576
else:
raise ValueError("Unknown model type")
[docs]
def validate_model_name(self, model_name: str) -> bool:
r"""Checks whether the model type and the model name matches.
Args:
model_name (str): The name of the model, e.g. "vicuna-7b-v1.5".
Returns:
bool: Whether the model type matches the model name.
"""
if self is ModelType.VICUNA:
pattern = r'^vicuna-\d+b-v\d+\.\d+$'
return bool(re.match(pattern, model_name))
elif self is ModelType.VICUNA_16K:
pattern = r'^vicuna-\d+b-v\d+\.\d+-16k$'
return bool(re.match(pattern, model_name))
elif self is ModelType.LLAMA_2:
return (
self.value in model_name.lower()
or "llama2" in model_name.lower()
)
elif self is ModelType.LLAMA_3:
return (
self.value in model_name.lower()
or "llama3" in model_name.lower()
)
elif self is ModelType.QWEN_2:
return (
self.value in model_name.lower()
or "qwen2" in model_name.lower()
)
elif self is ModelType.GLM_4_OPEN_SOURCE:
return (
'glm-4' in model_name.lower() or "glm4" in model_name.lower()
)
else:
return self.value in model_name.lower()
[docs]
class EmbeddingModelType(Enum):
TEXT_EMBEDDING_ADA_2 = "text-embedding-ada-002"
TEXT_EMBEDDING_3_SMALL = "text-embedding-3-small"
TEXT_EMBEDDING_3_LARGE = "text-embedding-3-large"
MISTRAL_EMBED = "mistral-embed"
@property
def is_openai(self) -> bool:
r"""Returns whether this type of models is an OpenAI-released model."""
return self in {
EmbeddingModelType.TEXT_EMBEDDING_ADA_2,
EmbeddingModelType.TEXT_EMBEDDING_3_SMALL,
EmbeddingModelType.TEXT_EMBEDDING_3_LARGE,
}
@property
def is_mistral(self) -> bool:
r"""Returns whether this type of models is an Mistral-released
model.
"""
return self in {
EmbeddingModelType.MISTRAL_EMBED,
}
@property
def output_dim(self) -> int:
if self is EmbeddingModelType.TEXT_EMBEDDING_ADA_2:
return 1536
elif self is EmbeddingModelType.TEXT_EMBEDDING_3_SMALL:
return 1536
elif self is EmbeddingModelType.TEXT_EMBEDDING_3_LARGE:
return 3072
elif self is EmbeddingModelType.MISTRAL_EMBED:
return 1024
else:
raise ValueError(f"Unknown model type {self}.")
[docs]
class TaskType(Enum):
AI_SOCIETY = "ai_society"
CODE = "code"
MISALIGNMENT = "misalignment"
TRANSLATION = "translation"
EVALUATION = "evaluation"
SOLUTION_EXTRACTION = "solution_extraction"
ROLE_DESCRIPTION = "role_description"
GENERATE_TEXT_EMBEDDING_DATA = "generate_text_embedding_data"
OBJECT_RECOGNITION = "object_recognition"
IMAGE_CRAFT = "image_craft"
MULTI_CONDITION_IMAGE_CRAFT = "multi_condition_image_craft"
DEFAULT = "default"
VIDEO_DESCRIPTION = "video_description"
[docs]
class VectorDistance(Enum):
r"""Distance metrics used in a vector database."""
DOT = "dot"
r"""Dot product. https://en.wikipedia.org/wiki/Dot_product"""
COSINE = "cosine"
r"""Cosine similarity. https://en.wikipedia.org/wiki/Cosine_similarity"""
EUCLIDEAN = "euclidean"
r"""Euclidean distance. https://en.wikipedia.org/wiki/Euclidean_distance"""
[docs]
class OpenAIBackendRole(Enum):
ASSISTANT = "assistant"
SYSTEM = "system"
USER = "user"
FUNCTION = "function"
TOOL = "tool"
[docs]
class TerminationMode(Enum):
ANY = "any"
ALL = "all"
[docs]
class OpenAIImageType(Enum, metaclass=OpenAIImageTypeMeta):
r"""Image types supported by OpenAI vision model."""
# https://platform.openai.com/docs/guides/vision
PNG = "png"
JPEG = "jpeg"
JPG = "jpg"
WEBP = "webp"
GIF = "gif"
[docs]
class OpenAIVisionDetailType(Enum):
AUTO = "auto"
LOW = "low"
HIGH = "high"
[docs]
class StorageType(Enum):
MILVUS = "milvus"
QDRANT = "qdrant"
[docs]
class OpenAPIName(Enum):
COURSERA = "coursera"
KLARNA = "klarna"
SPEAK = "speak"
NASA_APOD = "nasa_apod"
BIZTOC = "biztoc"
CREATE_QR_CODE = "create_qr_code"
OUTSCHOOL = "outschool"
WEB_SCRAPER = "web_scraper"
[docs]
class AudioModelType(Enum):
TTS_1 = "tts-1"
TTS_1_HD = "tts-1-hd"
@property
def is_openai(self) -> bool:
r"""Returns whether this type of audio models is an OpenAI-released
model."""
return self in {
AudioModelType.TTS_1,
AudioModelType.TTS_1_HD,
}
[docs]
class VoiceType(Enum):
ALLOY = "alloy"
ECHO = "echo"
FABLE = "fable"
ONYX = "onyx"
NOVA = "nova"
SHIMMER = "shimmer"
@property
def is_openai(self) -> bool:
r"""Returns whether this type of voice is an OpenAI-released voice."""
return self in {
VoiceType.ALLOY,
VoiceType.ECHO,
VoiceType.FABLE,
VoiceType.ONYX,
VoiceType.NOVA,
VoiceType.SHIMMER,
}