qixinbo
62 lines
1.8 KiB
Python
62 lines
1.8 KiB
Python
from typing import Optional, Dict
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from nanobot.providers.azure_openai_provider import AzureOpenAIProvider
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from nanobot.providers.openai_codex_provider import OpenAICodexProvider
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from nanobot.providers.registry import find_by_name
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from app.core.patched_openai_compat_provider import PatchedOpenAICompatProvider
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def normalize_provider_name(provider: Optional[str]) -> Optional[str]:
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if not provider:
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return None
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normalized = provider.strip().lower()
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alias_map = {
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"azure": "azure_openai",
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"local": "vllm",
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}
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return alias_map.get(normalized, normalized)
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def build_llm_provider(
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*,
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model: str,
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provider: Optional[str] = None,
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api_key: Optional[str] = None,
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api_base: Optional[str] = None,
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extra_headers: Optional[Dict[str, str]] = None,
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):
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provider_name = normalize_provider_name(provider)
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spec = find_by_name(provider_name) if provider_name else None
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backend = spec.backend if spec else "openai_compat"
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if backend == "openai_codex" or model.startswith("openai-codex/"):
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return OpenAICodexProvider(default_model=model)
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if backend == "azure_openai":
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if not api_key or not api_base:
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raise ValueError("Azure OpenAI requires api_key and api_base.")
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return AzureOpenAIProvider(
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api_key=api_key,
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api_base=api_base,
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default_model=model,
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)
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if backend == "anthropic":
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from nanobot.providers.anthropic_provider import AnthropicProvider
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return AnthropicProvider(
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api_key=api_key,
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api_base=api_base,
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default_model=model,
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extra_headers=extra_headers,
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)
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return PatchedOpenAICompatProvider(
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api_key=api_key,
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api_base=api_base,
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default_model=model,
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extra_headers=extra_headers,
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spec=spec,
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)
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