mirror of
https://github.com/tiennm99/DocsGPT.git
synced 2026-10-03 20:12:55 +00:00
Alex
574f96341e
The backend import package is now docsgpt, the name it will carry on PyPI; application was far too generic to install into anyone's site-packages. git mv plus a mechanical rewrite of every import, dotted string and path reference: 734 Python files, the compose files, Dockerfile, workflows, docs, setup scripts, devcontainer, k8s manifests, vscode config, pytest and coverage config, .gitignore. Behaviour is unchanged. Kept for one release: - A top-level application package whose meta-path finder resolves application.x.y to the already-imported docsgpt.x.y object, so old imports and entry points (celery -A application.app.celery, uvicorn application.asgi:asgi_app) keep working with a FutureWarning. - Celery registers every application.* task name as an alias of its docsgpt.* task on start-up, so messages queued by the previous release still run. The redbeat key prefix moves to redbeat:docsgpt:v2: so schedule entries the previous release wrote are left unread instead of firing twice. The backend image builds from the repository root (docker build -f docsgpt/Dockerfile .) so it can ship the alias package; a root .dockerignore allow-lists docsgpt/ and application/ and keeps caches, local data, .env files, the sample index files and the Dockerfile out. Compose and the image workflows point at the new context.
100 lines
3.8 KiB
Python
100 lines
3.8 KiB
Python
import logging
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from dataclasses import dataclass, field
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from enum import Enum
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from typing import Dict, List, Optional
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logger = logging.getLogger(__name__)
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# Re-exported here so existing call sites (and tests) that do
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# ``from docsgpt.core.model_settings import ModelRegistry`` keep
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# working. The implementation lives in ``docsgpt/core/model_registry.py``.
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# Imported lazily inside ``__getattr__`` to avoid an import cycle with
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# ``model_yaml`` → ``model_settings`` (this file).
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class ModelProvider(str, Enum):
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OPENAI = "openai"
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OPENAI_COMPATIBLE = "openai_compatible"
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OPENROUTER = "openrouter"
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ANTHROPIC = "anthropic"
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GROQ = "groq"
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GOOGLE = "google"
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HUGGINGFACE = "huggingface"
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LLAMA_CPP = "llama.cpp"
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DOCSGPT = "docsgpt"
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NOVITA = "novita"
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@dataclass
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class ModelCapabilities:
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supports_tools: bool = False
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supports_structured_output: bool = False
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supports_streaming: bool = True
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supported_attachment_types: List[str] = field(default_factory=list)
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context_window: int = 128000
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input_cost_per_token: Optional[float] = None
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output_cost_per_token: Optional[float] = None
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# OpenAI reasoning-model effort hint (none/minimal/low/medium/high/xhigh;
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# the accepted subset is model-dependent). Consumed by OpenAILLM — sent
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# top-level on Chat Completions and nested under ``reasoning`` on the
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# Responses path; ignored by providers that don't accept it.
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reasoning_effort: Optional[str] = None
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# Which OpenAI wire protocol the model speaks: "chat_completions"
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# (the default) or "responses" (the /v1/responses endpoint). Set per
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# model so only models that actually support the Responses API opt in.
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api_flavor: str = "chat_completions"
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@dataclass
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class AvailableModel:
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id: str
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provider: ModelProvider
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display_name: str
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description: str = ""
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capabilities: ModelCapabilities = field(default_factory=ModelCapabilities)
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enabled: bool = True
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base_url: Optional[str] = None
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# User-facing label distinct from dispatch provider (e.g. mistral
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# routed through openai_compatible).
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display_provider: Optional[str] = None
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# Sent in the API call's ``model`` field; falls back to ``self.id``
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# for built-ins where id IS the upstream name.
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upstream_model_id: Optional[str] = None
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# "builtin" for catalog YAMLs, "user" for BYOM records.
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source: str = "builtin"
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# Decrypted/resolved at registry-merge time. Never serialized.
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api_key: Optional[str] = field(default=None, repr=False, compare=False)
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def to_dict(self) -> Dict:
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result = {
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"id": self.id,
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"provider": self.display_provider or self.provider.value,
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"display_name": self.display_name,
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"description": self.description,
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"supported_attachment_types": self.capabilities.supported_attachment_types,
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"supports_tools": self.capabilities.supports_tools,
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"supports_structured_output": self.capabilities.supports_structured_output,
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"supports_streaming": self.capabilities.supports_streaming,
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"context_window": self.capabilities.context_window,
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"api_flavor": self.capabilities.api_flavor,
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"reasoning_effort": self.capabilities.reasoning_effort,
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"enabled": self.enabled,
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"source": self.source,
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}
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if self.base_url:
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result["base_url"] = self.base_url
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return result
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def __getattr__(name):
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"""Lazy re-export of ``ModelRegistry`` from ``model_registry.py``.
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Done lazily to avoid an import cycle: ``model_registry`` imports
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``model_yaml`` which imports the dataclasses from this file.
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"""
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if name == "ModelRegistry":
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from docsgpt.core.model_registry import ModelRegistry as _MR
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return _MR
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raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
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