425 lines
16 KiB
Python
425 lines
16 KiB
Python
import os
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import re
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import warnings
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from pathlib import Path
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from typing import Annotated, Any, Literal
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import yaml
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from pydantic import BaseModel, Field, PrivateAttr, SecretStr, model_validator, ValidationError
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from tht.config_compat import translate_legacy_config
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_ENV_RE = re.compile(r"\$\{([A-Za-z_][A-Za-z0-9_]*)\}")
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class ConfigError(Exception):
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"""Errore di configurazione, con messaggio leggibile per l'utente."""
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def local_tht_home() -> Path:
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"""Return the private local ThothII home, honoring the explicit override."""
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return Path(os.environ.get("THT_HOME", "~/.thothii")).expanduser()
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def _expand_env(value: Any) -> Any:
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if isinstance(value, str):
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def repl(m: re.Match) -> str:
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var = m.group(1)
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if var not in os.environ:
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raise ConfigError(
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f"Variabile d'ambiente non definita: {var} "
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f"(definiscila nel file .env o nell'ambiente)"
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)
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return os.environ[var]
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return _ENV_RE.sub(repl, value)
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if isinstance(value, dict):
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return {k: _expand_env(v) for k, v in value.items()}
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if isinstance(value, list):
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return [_expand_env(v) for v in value]
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return value
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def _resolve_secret_files(value: Any) -> Any:
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if isinstance(value, dict):
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resolved = {key: _resolve_secret_files(item) for key, item in value.items()}
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for secret_name in ("password", "access_key", "secret_key", "session_token"):
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file_name = f"{secret_name}_file"
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if file_name not in resolved:
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continue
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if secret_name in resolved:
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raise ConfigError(f"{secret_name} and {file_name} are mutually exclusive")
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path = Path(resolved.pop(file_name))
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try:
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secret = path.read_text()
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except (OSError, UnicodeError) as exc:
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raise ConfigError(f"Cannot read secret file: {path}") from exc
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if not secret or any(char.isspace() for char in secret) or "\x00" in secret:
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raise ConfigError(f"Invalid secret file: {path}")
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resolved[secret_name] = secret
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return resolved
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if isinstance(value, list):
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return [_resolve_secret_files(item) for item in value]
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return value
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class DatabaseConfig(BaseModel):
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host: str = "localhost"
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port: int = 5432
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database: str
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db_schema: str = Field(alias="schema")
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user: str
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password: str
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# transport: `direct` (Postgres via SQLAlchemy) o `rest` (Supabase/PostgREST).
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# In `rest` deve esistere la sezione `rest` (validato a livello di Config).
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transport: Literal["direct", "rest"] = "direct"
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model_config = {"populate_by_name": True}
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class RestConfig(BaseModel):
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"""Accesso al DWH via Supabase/PostgREST. base_url es. https://host/dwh/ ."""
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base_url: str
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api_key: str
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timeout: int = 30
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connect_timeout: int = 5
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ssl_ca: str | None = None # path al certificato CA (per server con CA interna)
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class DatabaseIdentityConfig(BaseModel):
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database: str
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db_schema: str = Field(alias="schema")
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model_config = {"populate_by_name": True}
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class PostgresDwhConfig(BaseModel):
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type: Literal["postgres_direct"]
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connection: DatabaseConfig
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class ThothRestDwhConfig(BaseModel):
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type: Literal["thoth_rest"]
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database: DatabaseIdentityConfig
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endpoint: RestConfig
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DwhResourceConfig = Annotated[
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PostgresDwhConfig | ThothRestDwhConfig,
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Field(discriminator="type"),
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]
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class PgvectorDirectConfig(BaseModel):
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type: Literal["pgvector_direct"]
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reader: DatabaseConfig | None = None
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writer: DatabaseConfig | None = None
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# Deprecated compatibility: a single direct connection historically meant read-only.
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connection: DatabaseConfig | None = None
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@model_validator(mode="after")
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def validate_connections(self):
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if self.reader is None and self.writer is None and self.connection is None:
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raise ValueError("pgvector_direct requires a reader or writer connection")
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return self
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class ThothVectorHttpConfig(BaseModel):
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type: Literal["thoth_vector_http"]
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reader: RestConfig | None = None
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writer: RestConfig | None = None
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# Transitional direct loading path used by the server profile.
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direct: DatabaseConfig | None = None
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VectorResourceConfig = Annotated[
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PgvectorDirectConfig | ThothVectorHttpConfig,
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Field(discriminator="type"),
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]
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class PathsConfig(BaseModel):
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artifacts: Path = Path("artifacts")
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indexes: Path = Path("indexes")
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sessions: Path = Path("sessions")
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class WorkspaceRoots(PathsConfig):
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pass
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class ExamplesConfig(BaseModel):
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max_per_column: int = 10
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class LshSkipConfig(BaseModel):
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# DEPRECATO: l'euristica di lunghezza (skip_column vendored) non è più usata. La
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# selezione delle colonne da indicizzare segue il principio di column eligibility
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# (sezione `eligibility`). Mantenuto solo per compatibilità con tht.yaml esistenti.
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max_total_chars: int = 50000
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max_avg_length: int = 20
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class LshConfig(BaseModel):
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signature_size: int = 64
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n_gram: int = 3
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threshold: float = 0.5
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max_values_per_column: int = 1000
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skip: LshSkipConfig = LshSkipConfig()
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class EligibilityConfig(BaseModel):
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# Soglie del principio di column eligibility (testo ampio ignorato ovunque).
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max_declared_len: int = 128 # char/varchar dichiarati <= soglia: eligible senza campionare
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max_avg_length: int = 40 # fallback data-driven: lunghezza media valori campionati
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max_sampled_len: int = 200 # fallback data-driven: lunghezza massima valore campionato
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# Colonne di servizio sempre ignorate per nome (match case-insensitive), a prescindere
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# dal tipo: metadati ETL/audit non analitici (es. timestamp di ultimo aggiornamento).
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ignore_columns: list[str] = ["etl_last_update"]
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class FilesystemEvidenceSourceConfig(BaseModel):
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type: Literal["filesystem"]
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root: Path
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patterns: list[str] = ["**/*.md"]
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max_bytes: int = Field(default=10 * 1024 * 1024, gt=0)
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class HttpEvidenceSourceConfig(BaseModel):
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type: Literal["http"]
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# Manifest URLs may contain signed query parameters. Treat the complete transport URL as
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# secret-bearing configuration; adapters derive a query-free provenance URI from it.
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urls: list[SecretStr] = Field(min_length=1)
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connect_timeout: float = Field(default=5, gt=0)
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read_timeout: float = Field(default=30, gt=0)
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max_bytes: int = Field(default=10 * 1024 * 1024, gt=0)
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max_redirects: int = Field(default=5, ge=0)
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allow_private_hosts: bool = False
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max_cache_bytes: int = Field(default=64 * 1024 * 1024, gt=0)
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class S3EvidenceSourceConfig(BaseModel):
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type: Literal["s3"]
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bucket: str = Field(min_length=1)
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prefix: str = ""
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endpoint_url: str | None = None
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region: str | None = None
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access_key: SecretStr | None = None
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secret_key: SecretStr | None = None
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session_token: SecretStr | None = None
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trusted_endpoint: bool = False
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allow_private_endpoint: bool = False
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allow_insecure_endpoint: bool = False
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max_bytes: int = Field(default=10 * 1024 * 1024, gt=0)
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max_objects: int = Field(default=10_000, gt=0)
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max_pages: int = Field(default=100, gt=0)
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page_size: int = Field(default=1000, gt=0, le=1000)
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EvidenceSourceConfig = Annotated[
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FilesystemEvidenceSourceConfig | HttpEvidenceSourceConfig | S3EvidenceSourceConfig,
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Field(discriminator="type"),
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]
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class EvidenceSourcesConfig(BaseModel):
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# Legacy curated-tree configuration remains accepted during migration.
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source_root: Path | None = None
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# cartella curata a mano nell'ETL (relativa a source_root): unica fonte delle
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# evidence. Niente piu' estrazione automatica dalle schede tabella: i documenti
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# qui dentro sono gia' evidence pronte (frontmatter + corpo), scelte e arricchite
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# dall'autore ETL e organizzate in sottocartelle per dominio.
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evidence_dir: str = "evidence"
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sources: list[EvidenceSourceConfig] = []
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@model_validator(mode="after")
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def require_a_source(self):
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if self.source_root is None and not self.sources:
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raise ValueError("evidence requires source_root or sources")
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return self
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class EmbeddingsConfig(BaseModel):
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base_url: str
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model: str = "nomic-embed-text-v2-moe"
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dim: int = 768
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batch_size: int = 32
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timeout: int = 30
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connect_timeout: int = 5
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bin: str = "ollama"
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start_cmd: list[str] | None = None
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class VectorConfig(BaseModel):
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max_chunk_chars: int = 4000
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# ACTIVE plus the two most recent rollback generations by default.
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retain_published_generations: int = Field(default=3, ge=1)
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class SearchConfig(BaseModel):
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rrf_k: int = 60
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top_schema_tables: int = 12 # default `--top` per `tht search --kind schema` (n. tabelle)
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schema_chunk_pool: int = 150 # chunk tabella/colonna fusi prima dell'aggregazione a tabella
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class ExecutionConfig(BaseModel):
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allow: list[str] = ["cte_test", "explain", "preview", "aggregate", "export"]
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max_preview_rows: int = 10
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statement_timeout_ms: int = 30000
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warn_execution_ms: int = 5000
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warn_plan_rows: int = 1_000_000
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max_aggregate_cells: int = 20
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max_export_rows: int = 100000
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forbidden_functions: list[str] = [
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"setval",
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"nextval",
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"pg_advisory_lock",
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"pg_advisory_xact_lock",
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"dblink",
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"dblink_exec",
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"pg_terminate_backend",
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"pg_cancel_backend",
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"lo_import",
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"lo_export",
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"pg_reload_conf",
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]
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class Config(BaseModel):
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_workspace_id: str = PrivateAttr(default="default")
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_config_source: str = PrivateAttr(default="direct")
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dwh: DwhResourceConfig
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vectors: VectorResourceConfig | None = None
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roots: WorkspaceRoots = WorkspaceRoots()
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# Compatibility views retained until all call sites consume typed resources.
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database: DatabaseConfig
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# Profilo dell'installazione, letto da THT_PROFILE (.env), non dallo yaml versionato.
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# server: ricostruisce i derivati (artefatti, LSH, vettori schema nel vectordb).
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# workstation: postazione locale che legge il vectordb via REST; gli upsert remoti
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# richiedono vector_write_rest, mentre init/clear/rebuild restano solo-server.
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profile: Literal["server", "workstation"] = "server"
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# Language in which table/column descriptions and evidence are written. The skill
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# instructions stay in English; only content/output follow this language. Default
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# 'en' so Thoth is not bound to any customer's language.
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language: str = "en"
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paths: PathsConfig = PathsConfig()
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examples: ExamplesConfig = ExamplesConfig()
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lsh: LshConfig = LshConfig()
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eligibility: EligibilityConfig = EligibilityConfig()
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evidence: EvidenceSourcesConfig | None = None
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embeddings: EmbeddingsConfig | None = None
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vector_db: DatabaseConfig | None = None
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vector: VectorConfig = VectorConfig()
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search: SearchConfig = SearchConfig()
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execution: ExecutionConfig = ExecutionConfig()
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rest: RestConfig | None = None
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# Endpoint REST dedicato per la similarity search del pgvector (rpc search_similar).
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# Se presente, `tht search` legge via REST; altrimenti legge in diretto (dev/test).
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vector_rest: RestConfig | None = None
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# Endpoint REST dedicato alle scritture controllate del pgvector. E' opzionale e usa
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# una API key separata dalla lettura; espone solo upsert/hash via RPC allowlist.
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vector_write_rest: RestConfig | None = None
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@model_validator(mode="before")
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@classmethod
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def accept_legacy_constructor_fields(cls, value: Any) -> Any:
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if not isinstance(value, dict) or "dwh" in value:
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return value
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translated, _ = translate_legacy_config(value)
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_populate_legacy_views(translated)
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return translated
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def workspace_id_from_path(path: Path) -> str:
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"""Return the stable workspace identity, resolving deployment aliases first."""
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return path.resolve().stem.lower().replace(".", "-").replace("_", "-")
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def load_config(path: Path) -> Config:
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if not path.exists():
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raise ConfigError(f"File di configurazione non trovato: {path}")
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raw = yaml.safe_load(path.read_text())
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if not isinstance(raw, dict):
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raise ConfigError(f"Configurazione non valida (atteso un mapping YAML): {path}")
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expanded = _resolve_secret_files(_expand_env(raw))
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translated, used_legacy = translate_legacy_config(expanded)
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_populate_legacy_views(translated)
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try:
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cfg = Config.model_validate(translated)
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except ValidationError as e:
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raise ConfigError(f"Configurazione non valida in {path}:\n{e}") from e
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env_profile = os.environ.get("THT_PROFILE")
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if env_profile is not None:
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if env_profile not in ("server", "workstation"):
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raise ConfigError(
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f"THT_PROFILE non valido: {env_profile!r} (atteso 'server' o 'workstation')."
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)
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cfg = cfg.model_copy(update={"profile": env_profile})
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if cfg.database.transport == "rest" and cfg.rest is None:
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raise ConfigError(
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f"transport: rest richiede la sezione `rest` (base_url, api_key) in {path}."
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)
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# THT_HOME is the local-user storage root. Retain THT_DATA_ROOT as the
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# portable-deployment compatibility name until all callers use repositories.
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data_root = os.environ.get("THT_HOME") or os.environ.get("THT_DATA_ROOT")
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if data_root:
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# Import locally: paths owns resolution, while ConfigError remains the public
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# configuration exception callers already handle.
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from tht.paths import resolve_workspace_paths
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resolved = resolve_workspace_paths(path, cfg, Path(data_root))
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cfg = cfg.model_copy(
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update={
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"paths": PathsConfig(
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sessions=resolved.sessions,
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artifacts=resolved.artifacts,
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indexes=resolved.indexes,
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)
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}
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)
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elif not used_legacy:
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# Modern `roots` replace `paths`; without a mounted data root retain the old
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# working-directory-relative behavior used by local development.
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cfg = cfg.model_copy(update={"paths": PathsConfig(**cfg.roots.model_dump())})
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if used_legacy:
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warnings.warn(
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"DEPRECATION: legacy workspace resource keys are deprecated; "
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"use dwh, vectors, and roots.",
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FutureWarning,
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stacklevel=2,
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)
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cfg._workspace_id = workspace_id_from_path(path)
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cfg._config_source = path.resolve().as_posix()
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return cfg
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def _populate_legacy_views(raw: dict[str, Any]) -> None:
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"""Populate old Config attributes for command compatibility during migration."""
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dwh = raw.get("dwh")
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if "database" not in raw and isinstance(dwh, dict):
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if dwh.get("type") == "postgres_direct":
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raw["database"] = {**dwh["connection"], "transport": "direct"}
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elif dwh.get("type") == "thoth_rest":
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raw["database"] = {
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**dwh["database"],
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"user": "rest",
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"password": "",
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"transport": "rest",
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}
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raw["rest"] = dwh["endpoint"]
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vectors = raw.get("vectors")
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if isinstance(vectors, dict):
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if vectors.get("type") == "pgvector_direct":
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raw.setdefault(
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"vector_db",
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vectors.get("writer") or vectors.get("reader") or vectors.get("connection"),
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)
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elif vectors.get("type") == "thoth_vector_http":
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raw.setdefault("vector_rest", vectors.get("reader"))
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raw.setdefault("vector_write_rest", vectors.get("writer"))
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raw.setdefault("vector_db", vectors.get("direct"))
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raw.setdefault("paths", raw.get("roots", {}))
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