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from __future__ import annotations
import requests
from ..config import DEFAULT_MODEL
from .template import OpenaiTemplate
class DeepInfra(OpenaiTemplate):
url = "https://deepinfra.com"
login_url = "https://deepinfra.com/dash/api_keys"
api_base = "https://api.deepinfra.com/v1/openai"
working = True
active_by_default = True
default_model = DEFAULT_MODEL
default_vision_model = DEFAULT_MODEL
vision_models = [
default_vision_model,
'meta-llama/Llama-3.2-90B-Vision-Instruct',
'openai/gpt-oss-120b',
'openai/gpt-oss-20b',
]
model_aliases = {
# cognitivecomputations
"dolphin-2.6": "cognitivecomputations/dolphin-2.6-mixtral-8x7b",
"dolphin-2.9": "cognitivecomputations/dolphin-2.9.1-llama-3-70b",
# deepinfra
"airoboros-70b": "deepinfra/airoboros-70b",
# deepseek-ai
"deepseek-prover-v2": "deepseek-ai/DeepSeek-Prover-V2-671B",
"deepseek-prover-v2-671b": "deepseek-ai/DeepSeek-Prover-V2-671B",
"deepseek-r1": ["deepseek-ai/DeepSeek-R1", "deepseek-ai/DeepSeek-R1-0528"],
"deepseek-r1-0528": "deepseek-ai/DeepSeek-R1-0528",
"deepseek-r1-0528-turbo": "deepseek-ai/DeepSeek-R1-0528-Turbo",
"deepseek-r1-distill-llama-70b": "deepseek-ai/DeepSeek-R1-Distill-Llama-70B",
"deepseek-r1-distill-qwen-32b": "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
"deepseek-r1-turbo": "deepseek-ai/DeepSeek-R1-Turbo",
"deepseek-v3": ["deepseek-ai/DeepSeek-V3", "deepseek-ai/DeepSeek-V3-0324"],
"deepseek-v3-0324": "deepseek-ai/DeepSeek-V3-0324",
"deepseek-v3-0324-turbo": "deepseek-ai/DeepSeek-V3-0324-Turbo",
# google
"codegemma-7b": "google/codegemma-7b-it",
"gemma-1.1-7b": "google/gemma-1.1-7b-it",
"gemma-2-27b": "google/gemma-2-27b-it",
"gemma-2-9b": "google/gemma-2-9b-it",
"gemma-3-4b": "google/gemma-3-4b-it",
"gemma-3-12b": "google/gemma-3-12b-it",
"gemma-3-27b": "google/gemma-3-27b-it",
# lizpreciatior
"lzlv-70b": "lizpreciatior/lzlv_70b_fp16_hf",
# meta-llama
"llama-3.1-8b": "meta-llama/Meta-Llama-3.1-8B-Instruct",
"llama-3.2-90b": "meta-llama/Llama-3.2-90B-Vision-Instruct",
"llama-3.3-70b": "meta-llama/Llama-3.3-70B-Instruct",
"llama-4-maverick": "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
"llama-4-scout": "meta-llama/Llama-4-Scout-17B-16E-Instruct",
# microsoft
"phi-4": "microsoft/phi-4",
"phi-4-multimodal": "microsoft/Phi-4-multimodal-instruct",
"phi-4-reasoning-plus": "microsoft/phi-4-reasoning-plus",
"wizardlm-2-7b": "microsoft/WizardLM-2-7B",
"wizardlm-2-8x22b": "microsoft/WizardLM-2-8x22B",
# mistralai
"mistral-small-3.1-24b": "mistralai/Mistral-Small-3.1-24B-Instruct-2503",
# Qwen
"qwen-3-14b": "Qwen/Qwen3-14B",
"qwen-3-30b": "Qwen/Qwen3-30B-A3B",
"qwen-3-32b": "Qwen/Qwen3-32B",
"qwen-3-235b": "Qwen/Qwen3-235B-A22B",
"qwq-32b": "Qwen/QwQ-32B",
}
@classmethod
def get_models(cls, **kwargs):
if not cls.models:
url = 'https://api.deepinfra.com/models/featured'
response = requests.get(url)
models = response.json()
cls.models = []
cls.image_models = []
for model in models:
if model["type"] == "text-generation":
cls.models.append(model['model_name'])
elif model["reported_type"] == "text-to-image":
cls.image_models.append(model['model_name'])
cls.models.extend(cls.image_models)
if models:
cls.live += 1
return cls.models
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