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