chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
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from constants.llm import OPENAI_URL
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from enums.image_provider import ImageProvider
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from enums.llm_provider import LLMProvider
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from utils.available_models import (
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list_available_anthropic_models,
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list_available_google_models,
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list_available_openai_compatible_models,
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normalize_openai_compatible_base_url,
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)
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from utils.get_env import (
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get_azure_openai_api_key_env,
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get_azure_openai_api_version_env,
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get_azure_openai_base_url_env,
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get_azure_openai_endpoint_env,
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get_anthropic_api_key_env,
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get_anthropic_model_env,
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get_bedrock_api_key_env,
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get_bedrock_aws_access_key_id_env,
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get_bedrock_aws_secret_access_key_env,
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get_bedrock_model_env,
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get_can_change_keys_env,
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get_cerebras_api_key_env,
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get_fireworks_api_key_env,
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get_fireworks_base_url_env,
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get_fireworks_model_env,
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get_google_model_env,
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get_litellm_base_url_env,
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get_litellm_model_env,
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get_lmstudio_api_key_env,
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get_lmstudio_base_url_env,
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get_lmstudio_model_env,
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get_openai_api_key_env,
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get_openai_model_env,
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get_openrouter_api_key_env,
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get_together_api_key_env,
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get_together_base_url_env,
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get_together_model_env,
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get_pixabay_api_key_env,
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get_pexels_api_key_env,
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get_vertex_api_key_env,
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get_vertex_location_env,
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get_vertex_project_env,
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get_comfyui_url_env,
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get_comfyui_workflow_env,
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get_deepseek_api_key_env,
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get_deepseek_base_url_env,
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get_deepseek_model_env,
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)
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from utils.get_env import get_google_api_key_env
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from utils.get_env import get_ollama_model_env
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from utils.get_env import get_custom_llm_api_key_env
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from utils.get_env import get_custom_llm_url_env
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from utils.get_env import get_custom_model_env
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from utils.llm_provider import (
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get_llm_provider,
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is_custom_llm_selected,
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is_ollama_selected,
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)
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from utils.ollama import list_available_ollama_models
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from utils.image_provider import (
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get_selected_image_provider,
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is_image_generation_disabled,
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)
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def _check_image_provider_configuration() -> None:
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selected_image_provider = get_selected_image_provider()
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if not selected_image_provider:
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raise Exception("IMAGE_PROVIDER must be provided")
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if selected_image_provider == ImageProvider.PEXELS:
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pexels_api_key = get_pexels_api_key_env()
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if not pexels_api_key:
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raise Exception("PEXELS_API_KEY must be provided")
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elif selected_image_provider == ImageProvider.PIXABAY:
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pixabay_api_key = get_pixabay_api_key_env()
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if not pixabay_api_key:
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raise Exception("PIXABAY_API_KEY must be provided")
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elif (
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selected_image_provider == ImageProvider.GEMINI_FLASH
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or selected_image_provider == ImageProvider.NANOBANANA_PRO
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):
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google_api_key = get_google_api_key_env()
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if not google_api_key:
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raise Exception("GOOGLE_API_KEY must be provided")
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elif (
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selected_image_provider == ImageProvider.DALLE3
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or selected_image_provider == ImageProvider.GPT_IMAGE_1_5
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):
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openai_api_key = get_openai_api_key_env()
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if not openai_api_key:
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raise Exception("OPENAI_API_KEY must be provided")
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elif selected_image_provider == ImageProvider.COMFYUI:
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comfyui_url = get_comfyui_url_env()
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if not comfyui_url:
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raise Exception("COMFYUI_URL must be provided")
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workflow_json = get_comfyui_workflow_env()
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if not workflow_json:
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raise Exception("COMFYUI_WORKFLOW must be provided")
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async def check_llm_and_image_provider_api_or_model_availability():
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can_change_keys = get_can_change_keys_env() != "false"
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skip_image_validation = is_image_generation_disabled()
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if not can_change_keys:
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if get_llm_provider() == LLMProvider.OPENAI:
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openai_api_key = get_openai_api_key_env()
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if not openai_api_key:
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raise Exception("OPENAI_API_KEY must be provided")
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openai_model = get_openai_model_env()
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if openai_model:
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available_models = await list_available_openai_compatible_models(
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OPENAI_URL, openai_api_key
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)
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if openai_model not in available_models:
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print("-" * 50)
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print("Available models: ", available_models)
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raise Exception(f"Model {openai_model} is not available")
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elif get_llm_provider() == LLMProvider.GOOGLE:
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google_api_key = get_google_api_key_env()
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if not google_api_key:
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raise Exception("GOOGLE_API_KEY must be provided")
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google_model = get_google_model_env()
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if google_model:
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available_models = await list_available_google_models(google_api_key)
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if google_model not in available_models:
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print("-" * 50)
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print("Available models: ", available_models)
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raise Exception(f"Model {google_model} is not available")
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elif get_llm_provider() == LLMProvider.DEEPSEEK:
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deepseek_api_key = (get_deepseek_api_key_env() or "").strip()
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deepseek_model = (get_deepseek_model_env() or "").strip()
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if not deepseek_api_key:
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raise Exception("DEEPSEEK_API_KEY must be provided")
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if not deepseek_model:
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raise Exception("DEEPSEEK_MODEL must be provided")
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deepseek_base_url = normalize_openai_compatible_base_url(
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get_deepseek_base_url_env() or "https://api.deepseek.com/v1"
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)
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available_models = await list_available_openai_compatible_models(
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deepseek_base_url, deepseek_api_key
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)
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print("-" * 50)
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print("Available models: ", available_models)
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if deepseek_model not in available_models:
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raise Exception(f"Model {deepseek_model} is not available")
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elif get_llm_provider() == LLMProvider.VERTEX:
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vertex_api_key = get_vertex_api_key_env()
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vertex_project = get_vertex_project_env()
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vertex_location = get_vertex_location_env()
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if not vertex_api_key and not vertex_project:
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raise Exception(
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"Configure VERTEX_API_KEY or VERTEX_PROJECT for Vertex AI"
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)
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if vertex_api_key and (vertex_project or vertex_location):
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raise Exception(
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"Vertex config is ambiguous. Use either VERTEX_API_KEY or "
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"VERTEX_PROJECT/VERTEX_LOCATION, not both."
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)
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elif get_llm_provider() == LLMProvider.AZURE:
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azure_api_key = get_azure_openai_api_key_env()
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azure_endpoint = get_azure_openai_endpoint_env()
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azure_base_url = get_azure_openai_base_url_env()
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azure_api_version = get_azure_openai_api_version_env()
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if not azure_api_key:
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raise Exception("AZURE_OPENAI_API_KEY must be provided")
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if not azure_api_version:
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raise Exception("AZURE_OPENAI_API_VERSION must be provided")
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if not azure_endpoint and not azure_base_url:
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raise Exception(
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"AZURE_OPENAI_ENDPOINT or AZURE_OPENAI_BASE_URL must be provided"
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)
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elif get_llm_provider() == LLMProvider.BEDROCK:
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bedrock_model = (get_bedrock_model_env() or "").strip()
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if not bedrock_model:
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raise Exception("BEDROCK_MODEL must be provided")
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has_api_key = bool((get_bedrock_api_key_env() or "").strip())
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has_access_key = bool((get_bedrock_aws_access_key_id_env() or "").strip())
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has_secret_key = bool((get_bedrock_aws_secret_access_key_env() or "").strip())
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if not has_api_key and not (has_access_key and has_secret_key):
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raise Exception(
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"Set BEDROCK_API_KEY, or set BEDROCK_AWS_ACCESS_KEY_ID and "
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"BEDROCK_AWS_SECRET_ACCESS_KEY"
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)
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elif get_llm_provider() == LLMProvider.OPENROUTER:
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if not get_openrouter_api_key_env():
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raise Exception("OPENROUTER_API_KEY must be provided")
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elif get_llm_provider() == LLMProvider.FIREWORKS:
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fireworks_api_key = (get_fireworks_api_key_env() or "").strip()
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fireworks_model = (get_fireworks_model_env() or "").strip()
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if not fireworks_api_key:
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raise Exception("FIREWORKS_API_KEY must be provided")
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if not fireworks_model:
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raise Exception("FIREWORKS_MODEL must be provided")
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fireworks_base_url = normalize_openai_compatible_base_url(
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get_fireworks_base_url_env() or "https://api.fireworks.ai/inference/v1"
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)
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available_models = await list_available_openai_compatible_models(
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fireworks_base_url, fireworks_api_key
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)
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print("-" * 50)
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print("Available models: ", available_models)
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if fireworks_model not in available_models:
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raise Exception(f"Model {fireworks_model} is not available")
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elif get_llm_provider() == LLMProvider.TOGETHER:
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together_api_key = (get_together_api_key_env() or "").strip()
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together_model = (get_together_model_env() or "").strip()
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if not together_api_key:
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raise Exception("TOGETHER_API_KEY must be provided")
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if not together_model:
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raise Exception("TOGETHER_MODEL must be provided")
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together_base_url = normalize_openai_compatible_base_url(
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get_together_base_url_env() or "https://api.together.ai/v1"
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)
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available_models = await list_available_openai_compatible_models(
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together_base_url, together_api_key
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)
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print("-" * 50)
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print("Available models: ", available_models)
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if together_model not in available_models:
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raise Exception(f"Model {together_model} is not available")
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elif get_llm_provider() == LLMProvider.CEREBRAS:
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if not get_cerebras_api_key_env():
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raise Exception("CEREBRAS_API_KEY must be provided")
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elif get_llm_provider() == LLMProvider.LITELLM:
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if not (get_litellm_base_url_env() or "").strip():
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raise Exception("LITELLM_BASE_URL must be provided")
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if not (get_litellm_model_env() or "").strip():
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raise Exception("LITELLM_MODEL must be provided")
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elif get_llm_provider() == LLMProvider.LMSTUDIO:
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lmstudio_model = (get_lmstudio_model_env() or "").strip()
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if not lmstudio_model:
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raise Exception("LMSTUDIO_MODEL must be provided")
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lmstudio_base_url = normalize_openai_compatible_base_url(
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get_lmstudio_base_url_env() or "http://localhost:1234/v1"
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)
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available_models = await list_available_openai_compatible_models(
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lmstudio_base_url, get_lmstudio_api_key_env() or ""
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)
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print("-" * 50)
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print("Available models: ", available_models)
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if lmstudio_model not in available_models:
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raise Exception(f"Model {lmstudio_model} is not available")
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elif get_llm_provider() == LLMProvider.ANTHROPIC:
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anthropic_api_key = get_anthropic_api_key_env()
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if not anthropic_api_key:
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raise Exception("ANTHROPIC_API_KEY must be provided")
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anthropic_model = get_anthropic_model_env()
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if anthropic_model:
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available_models = await list_available_anthropic_models(
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anthropic_api_key
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)
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if anthropic_model not in available_models:
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print("-" * 50)
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print("Available models: ", available_models)
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raise Exception(f"Model {anthropic_model} is not available")
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elif is_ollama_selected():
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ollama_model = get_ollama_model_env()
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if not ollama_model:
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raise Exception("OLLAMA_MODEL must be provided")
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available_models = await list_available_ollama_models()
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if ollama_model not in {model.name for model in available_models}:
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raise Exception(
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f"Model {ollama_model} is not available in Ollama. "
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"Pull it in Ollama, then check models in Presenton."
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)
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elif is_custom_llm_selected():
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custom_model = get_custom_model_env()
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custom_llm_url = get_custom_llm_url_env()
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if not custom_model:
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raise Exception("CUSTOM_MODEL must be provided")
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if not custom_llm_url:
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raise Exception("CUSTOM_LLM_URL must be provided")
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available_models = await list_available_openai_compatible_models(
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custom_llm_url, get_custom_llm_api_key_env() or "null"
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)
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print("-" * 50)
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print("Available models: ", available_models)
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if custom_model not in available_models:
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raise Exception(f"Model {custom_model} is not available")
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if not skip_image_validation:
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_check_image_provider_configuration()
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