diff --git a/backend/app/api/deps.py b/backend/app/api/deps.py index cf3b28d..8298c4c 100644 --- a/backend/app/api/deps.py +++ b/backend/app/api/deps.py @@ -10,6 +10,8 @@ from app.core.db import get_session from app.integrations.mailer.base import Mailer from app.integrations.mailer.console import ConsoleMailer from app.integrations.mailer.smtp import SMTPMailer +from app.integrations.models.base import EmbeddingProvider, LLMProvider +from app.integrations.models.null import NullEmbeddingProvider, NullLLMProvider from app.integrations.objectstore.base import ObjectStore from app.integrations.objectstore.s3 import S3ObjectStore from app.models.user import User @@ -67,3 +69,28 @@ def get_objectstore() -> ObjectStore: ObjectStoreDep = Annotated[ObjectStore, Depends(get_objectstore)] + + +def get_llm_provider() -> LLMProvider: + settings = get_settings() + if settings.model_provider == "anthropic" and settings.anthropic_api_key: + from app.integrations.models.anthropic_provider import AnthropicLLMProvider + + return AnthropicLLMProvider( + api_key=settings.anthropic_api_key, + model=settings.llm_model, + max_tokens=settings.llm_max_tokens, + ) + return NullLLMProvider() + + +LLMProviderDep = Annotated[LLMProvider, Depends(get_llm_provider)] + + +def get_embedding_provider() -> EmbeddingProvider: + # Only the null provider exists today; concrete embedders (Ollama/Voyage) + # implement the same interface and are selected here by settings.embedding_provider. + return NullEmbeddingProvider() + + +EmbeddingProviderDep = Annotated[EmbeddingProvider, Depends(get_embedding_provider)] diff --git a/backend/app/core/config.py b/backend/app/core/config.py index 74ea306..edbba4f 100644 --- a/backend/app/core/config.py +++ b/backend/app/core/config.py @@ -60,6 +60,14 @@ class Settings(BaseSettings): smtp_password: str | None = None smtp_from: str = "Provenance " + # --- Model providers (AI assistant + match-ranking embeddings) --- + # Separate because Anthropic has no embeddings endpoint; either can be off. + model_provider: str = "null" # null | anthropic + anthropic_api_key: str | None = None + llm_model: str = "claude-opus-4-8" + llm_max_tokens: int = 4096 + embedding_provider: str = "null" # null | (future: ollama, voyage, …) + @lru_cache def get_settings() -> Settings: diff --git a/backend/app/integrations/models/__init__.py b/backend/app/integrations/models/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/backend/app/integrations/models/anthropic_provider.py b/backend/app/integrations/models/anthropic_provider.py new file mode 100644 index 0000000..b5fbff5 --- /dev/null +++ b/backend/app/integrations/models/anthropic_provider.py @@ -0,0 +1,24 @@ +"""Anthropic LLM provider (official SDK). Self-hosters who want everything to +stay on their own metal would configure a local provider instead (e.g. Ollama) — +that's a future implementation of the same LLMProvider interface.""" + +from anthropic import AsyncAnthropic + +from app.integrations.models.base import LLMProvider + + +class AnthropicLLMProvider(LLMProvider): + def __init__(self, *, api_key: str, model: str, max_tokens: int = 4096) -> None: + self._client = AsyncAnthropic(api_key=api_key) + self._model = model + self._max_tokens = max_tokens + + async def complete(self, *, prompt: str, system: str | None = None) -> str: + resp = await self._client.messages.create( + model=self._model, + max_tokens=self._max_tokens, + system=system or "", + messages=[{"role": "user", "content": prompt}], + ) + # content is a list of blocks; concatenate the text ones. + return "".join(b.text for b in resp.content if b.type == "text") diff --git a/backend/app/integrations/models/base.py b/backend/app/integrations/models/base.py new file mode 100644 index 0000000..aad37e7 --- /dev/null +++ b/backend/app/integrations/models/base.py @@ -0,0 +1,36 @@ +"""Model-provider interfaces — the seam the AI assistant and match ranking plug +into. LLM (text) and embeddings are *separate* abstractions: Anthropic offers no +embeddings endpoint, so the two are configured independently (twelve-factor, +CLAUDE.md #7) and a deployment may run one without the other. + +These providers are read-only text/vector producers. They MUST NOT mutate tree +data — the assistant's writes go through a ChangeProposal a human approves +(CLAUDE.md #1). Nothing here touches the database. +""" + +from abc import ABC, abstractmethod + + +class LLMProvider(ABC): + """Text in, text out. Implementations wrap a chat/completion model.""" + + @abstractmethod + async def complete(self, *, prompt: str, system: str | None = None) -> str: + """Return the model's text response to a single user prompt.""" + ... + + +class EmbeddingProvider(ABC): + """Text in, vectors out — for pgvector-backed match ranking.""" + + #: Dimensionality of the returned vectors (for the pgvector column). + dimensions: int + + @abstractmethod + async def embed(self, texts: list[str]) -> list[list[float]]: + """Return one embedding vector per input text, in order.""" + ... + + +class ModelProviderNotConfigured(RuntimeError): + """Raised when an AI capability is used but no provider is configured.""" diff --git a/backend/app/integrations/models/null.py b/backend/app/integrations/models/null.py new file mode 100644 index 0000000..9dc1543 --- /dev/null +++ b/backend/app/integrations/models/null.py @@ -0,0 +1,31 @@ +"""Default providers when no model backend is configured — AI features are off. + +They fail loudly (rather than silently doing nothing) so a caller that reaches +for an unconfigured capability gets a clear, actionable error. +""" + +from app.integrations.models.base import ( + EmbeddingProvider, + LLMProvider, + ModelProviderNotConfigured, +) + +_MSG = ( + "No model provider configured. Set MODEL_PROVIDER (e.g. 'anthropic') and the " + "provider's credentials to enable AI features." +) + + +class NullLLMProvider(LLMProvider): + async def complete(self, *, prompt: str, system: str | None = None) -> str: + raise ModelProviderNotConfigured(_MSG) + + +class NullEmbeddingProvider(EmbeddingProvider): + dimensions = 0 + + async def embed(self, texts: list[str]) -> list[list[float]]: + raise ModelProviderNotConfigured( + "No embedding provider configured. Set EMBEDDING_PROVIDER and its " + "credentials to enable match ranking." + ) diff --git a/backend/pyproject.toml b/backend/pyproject.toml index 0fabe8d..1281776 100644 --- a/backend/pyproject.toml +++ b/backend/pyproject.toml @@ -14,6 +14,7 @@ dependencies = [ "argon2-cffi>=23.1", "boto3>=1.35", "python-multipart>=0.0.12", + "anthropic>=0.108.0", ] [dependency-groups] diff --git a/backend/tests/test_model_providers.py b/backend/tests/test_model_providers.py new file mode 100644 index 0000000..3705e11 --- /dev/null +++ b/backend/tests/test_model_providers.py @@ -0,0 +1,43 @@ +"""Model-provider selection + the null-provider fail-loud behavior. + +No network: we only assert which provider the factory returns and that the null +providers raise a clear error. (Live LLM/embedding calls aren't unit-tested.) +""" + +import pytest + +from app.api.deps import get_embedding_provider, get_llm_provider +from app.core.config import get_settings +from app.integrations.models.anthropic_provider import AnthropicLLMProvider +from app.integrations.models.base import ModelProviderNotConfigured +from app.integrations.models.null import NullEmbeddingProvider, NullLLMProvider + + +async def test_default_llm_is_null_and_fails_loud(monkeypatch): + monkeypatch.setattr(get_settings(), "model_provider", "null") + provider = get_llm_provider() + assert isinstance(provider, NullLLMProvider) + with pytest.raises(ModelProviderNotConfigured): + await provider.complete(prompt="hello") + + +async def test_anthropic_selected_when_configured(monkeypatch): + s = get_settings() + monkeypatch.setattr(s, "model_provider", "anthropic") + monkeypatch.setattr(s, "anthropic_api_key", "sk-ant-test-key") + monkeypatch.setattr(s, "llm_model", "claude-opus-4-8") + assert isinstance(get_llm_provider(), AnthropicLLMProvider) # no network call + + +async def test_anthropic_without_key_falls_back_to_null(monkeypatch): + s = get_settings() + monkeypatch.setattr(s, "model_provider", "anthropic") + monkeypatch.setattr(s, "anthropic_api_key", None) + assert isinstance(get_llm_provider(), NullLLMProvider) + + +async def test_embedding_default_is_null_and_fails_loud(): + provider = get_embedding_provider() + assert isinstance(provider, NullEmbeddingProvider) + with pytest.raises(ModelProviderNotConfigured): + await provider.embed(["text"]) diff --git a/backend/uv.lock b/backend/uv.lock index 5036127..62e742b 100644 --- a/backend/uv.lock +++ b/backend/uv.lock @@ -38,6 +38,25 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = 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+ANTHROPIC_API_KEY= +LLM_MODEL=claude-opus-4-8 +LLM_MAX_TOKENS=4096 +# Embeddings are separate (Anthropic has no embeddings endpoint). 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