jpmschweitzerandClaude Fable 5
1769ec2803
One choke point in the sanitized client: the flavor is probed once (the boilerroom wrapper names itself on /health, a bare llama-server serves /props, Ollama answers neither) and every completion adapts. The agents' tool_choice "required" survives only on Ollama — advisory there, enforced by llama-server, an unbreakable tool loop through the wrapper. Through the wrapper every completion carries webber's session identity: session webber, eviction_order 20 in the decided ranking, configurable via settings. The wrapper's balancing and compaction signals are read from the response body's extra fields — an httpx event-hook variant was tried and never fires under the openai SDK. The enabling fix: the sanitized client was never in the request path. The provider assigned self._openai_client, an attribute nobody reads — OllamaProvider.client serves self._client — so every completion has bypassed the null-content sanitizer since the class was introduced. Exposed when the wrapper 503'd a session-less request the choke point should have named; the client now goes through the constructor's official openai_client parameter, and a wiring test pins provider.client to the sanitized type. The same bug exists in tatlock (its T-6, filed). Verified against the live wrapper from the dev server: flavor boilerroom detected, a tool-using explore run answered in 4.8 s with no tool loop, webber resident at rank 20, and the wrapper parked librarian and tatlock-experts to seat it — the ranking doing exactly its job. Six new tests (227 green), five mutation-checked: the rank default, the strip condition, the session-add condition, the no-cache-on-failure rule, and the client wiring. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
122 lines
3.8 KiB
Python
122 lines
3.8 KiB
Python
"""
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Application configuration via Pydantic Settings.
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All settings loaded from environment variables or .env file.
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Project metadata (name, version, description) sourced from pyproject.toml.
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"""
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import tomllib
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from dataclasses import dataclass
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from functools import lru_cache
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from pathlib import Path
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from pydantic_settings import BaseSettings, SettingsConfigDict
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@dataclass(frozen=True)
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class ProjectMeta:
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"""Project metadata from pyproject.toml (single source of truth)."""
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name: str
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version: str
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description: str
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def _load_project_meta() -> ProjectMeta:
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"""Load project metadata from pyproject.toml."""
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pyproject_path = Path(__file__).parent.parent.parent / "pyproject.toml"
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try:
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with open(pyproject_path, "rb") as f:
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data = tomllib.load(f)
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project = data.get("project", {})
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return ProjectMeta(
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name=str(project.get("name", "webber")).title(),
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version=str(project.get("version", "0.0.0")),
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description=str(project.get("description", "")),
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)
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except FileNotFoundError:
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return ProjectMeta(name="Webber", version="0.0.0", description="")
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PROJECT = _load_project_meta()
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__version__ = PROJECT.version
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class Settings(BaseSettings):
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"""Application settings loaded from environment."""
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# Application (from pyproject.toml)
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app_name: str = PROJECT.name
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app_version: str = PROJECT.version
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app_description: str = PROJECT.description
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debug: bool = False
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# Server
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host: str = "0.0.0.0"
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port: int = 8086
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# Logging
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log_level: str = "INFO"
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# CORS
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cors_origins: list[str] = ["http://localhost:3000", "http://localhost:8080"]
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cors_credentials: bool = True
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cors_methods: list[str] = ["*"]
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cors_headers: list[str] = ["*"]
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# LLM - Ollama (always hot in VRAM on tower-of-joy)
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ollama_url: str = "http://192.168.86.149:11434"
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ollama_agent_model: str = "gemma4:e2b"
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ollama_embed_model: str = "nomic-embed-text:latest"
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# Session identity through the boilerroom wrapper (workspace T-137):
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# rank 20 in the decided ordering — tatlock phases 40, experts 35,
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# librarian 30, webber 20; lower parks sooner. The fields only mean
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# something to the wrapper; Ollama and a bare llama-server ignore them.
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backend_session_name: str = "webber"
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backend_session_rank: int = 20
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# Auth - Tatlock integration
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tatlock_api_url: str | None = "http://tatlock:8000"
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internal_api_key: str | None = None
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# Web search - SearXNG (use SEARXNG_URL env var to override)
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searxng_url: str = "http://searxng:8080"
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searxng_timeout: int = 10
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# Tool execution
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tool_timeout_seconds: int = 120
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sandbox_enabled: bool = True
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allowed_paths: list[str] | None = None
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# Database
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database_url: str = "sqlite+aiosqlite:///./webber.db"
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# Sessions & Context
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session_ttl_hours: int = 24
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max_context_tokens: int = 128000
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summarization_threshold: float = 0.8 # Summarize at 80% of max tokens
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summarization_target_tokens: int = 500 # Target summary size
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keep_recent_messages: int = 6 # Messages to keep unsummarized (3 turns)
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# Retry logic
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retry_max_attempts: int = 3 # Max retry attempts for transient failures
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retry_base_delay: float = 1.0 # Base delay in seconds
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retry_max_delay: float = 30.0 # Maximum delay in seconds
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model_config = SettingsConfigDict(
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env_file=".env",
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case_sensitive=False,
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extra="ignore",
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env_parse_none_str="", # Treat empty string as None
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)
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@property
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def effective_allowed_paths(self) -> list[str]:
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"""Return allowed_paths or empty list if None."""
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return self.allowed_paths or []
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@lru_cache
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def get_settings() -> Settings:
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"""Cached settings singleton."""
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return Settings()
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