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b2931f4 a8bc5d0 b2931f4 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 | # src/finrag/config.py
from pydantic_settings import BaseSettings, SettingsConfigDict
from pathlib import Path
REPO_ROOT = Path(__file__).resolve().parents[3]
# config.py → finrag/ → src/ → backend/ → REPO_ROOT
class Settings(BaseSettings):
# Both provider keys are optional: the active one is decided by
# `llm_provider`, and we validate presence lazily at call time so a
# Gemini-only setup doesn't need an Anthropic key (and vice versa).
anthropic_api_key: str | None = None
gemini_api_key: str | None = None
cohere_api_key: str
# Vector store location. Two mutually exclusive modes:
# • qdrant_path set → EMBEDDED Qdrant (in-process, on-disk at this path).
# The public deploy uses this: the vector store is baked into the Docker
# image alongside DuckDB + BM25, so there is no external cluster to idle-
# wipe and no QDRANT_URL/KEY secret. Relative paths resolve from REPO_ROOT.
# • qdrant_path empty → REMOTE Qdrant at qdrant_url (local docker-compose in
# dev, or a managed cluster). The original behaviour, unchanged.
qdrant_path: str | None = None
qdrant_url: str = "http://localhost:6333"
qdrant_api_key: str | None = None
duckdb_path: str = "./data/duckdb/finrag.duckdb"
llm_mode: str = "cloud"
# Which backend the finrag.llm dispatchers use: "anthropic" | "gemini" | "local".
llm_provider: str = "anthropic"
# Anthropic model. Default = the eval-validated Sonnet; the public demo deploy
# overrides this to Haiku (CLAUDE_MODEL=claude-haiku-4-5-20251001) to cut the
# per-question cost ~10x behind the guardrails below.
claude_model: str = "claude-sonnet-4-6"
# ── Public-deploy guardrails (only bite when a real client calls) ──
# CORS allow-list, comma-separated. Dev defaults to the Next.js dev server;
# the prod deploy sets this to the exact Vercel origin (see docs/deploy.md).
allowed_origins: str = "http://localhost:3000,http://127.0.0.1:3000"
# Per-IP sliding-window limit on the PAID endpoints (/answer,/agent[,/stream]).
rate_limit_per_min: int = 8
# Global hard ceiling on paid questions per UTC day — the cost circuit-breaker.
# 300 Haiku agent-questions ≈ a couple of dollars worst case; past it the API
# returns 429 until midnight UTC instead of burning the key.
daily_question_cap: int = 300
@property
def allowed_origins_list(self) -> list[str]:
return [o.strip() for o in self.allowed_origins.split(",") if o.strip()]
# ── Local / edge provider (Ollama, OpenAI-compatible API on :11434) ──
# Used only when llm_provider == "local". base_url is the OpenAI-compat
# endpoint, so the same backend would target vLLM/llama.cpp/LM Studio by
# swapping this one value. local_use_tools is the kill-switch: True runs the
# real agentic tool-loop (tests whether a 3B model can drive it); False runs
# degraded synthesis-only over retrieved context (the documented fallback for
# small models whose tool-calling is unreliable — see docs/handoff.md Day 5).
local_model: str = "llama3.2:3b"
local_base_url: str = "http://localhost:11434/v1"
local_use_tools: bool = True
model_config = SettingsConfigDict(env_file=REPO_ROOT / ".env", extra="ignore")
settings = Settings() # validates at import time |