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job-chat / config.py

ocr, email writing, rag

d7d27a3 9 days ago

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"""Application configuration, loaded once from the environment."""

import os
from dataclasses import dataclass
from functools import lru_cache
from pathlib import Path

from dotenv import load_dotenv

load_dotenv()

PROJECT_ROOT = Path(__file__).parent

DEFAULT_MODEL = "openrouter/free"
OPENROUTER_BASE_URL = "https://openrouter.ai/api/v1"
DEFAULT_TEMPERATURE = 0.0
# Drafting a cover letter is writing, not analysis: a little sampling gives
# natural prose. Kept low so it does not start inventing detail.
DEFAULT_DRAFTING_TEMPERATURE = 0.4
# The preset actions (ATS keyword tables, detailed reviews) run long, so 2048
# truncated them mid-answer. This leaves room for the profile, job description,
# and conversation history while avoiding an unnecessarily large response cap.
DEFAULT_MAX_TOKENS = 20000
# Prose skill output gets its own response cap.
DEFAULT_SKILL_MAX_TOKENS = 6500
# ATS returns a structured classification for every keyword, so it needs more
# output room than the prose skills.
DEFAULT_ATS_MAX_TOKENS = 12000
DEFAULT_LANGFUSE_HOST = "https://cloud.langfuse.com"
DEFAULT_CHECKPOINT_DB = "checkpoints.sqlite"
# Turns of conversation replayed to the model. Older turns stay in the
# checkpoint (nothing is deleted) but are not resent.
DEFAULT_MAX_HISTORY_TURNS = 10
# Routing and retrieval. ONNX runtime, so no torch dependency.
DEFAULT_EMBEDDING_MODEL = "sentence-transformers/all-MiniLM-L6-v2"
DEFAULT_RETRIEVAL_TOP_K = 10


class ConfigError(RuntimeError):
    """Raised when the environment is missing or misconfigured."""


@dataclass(frozen=True)
class Settings:
    openrouter_api_key: str
    candidate_name: str
    model: str
    temperature: float
    drafting_temperature: float
    max_tokens: int
    skill_max_tokens: int
    ats_max_tokens: int
    max_history_turns: int
    embedding_model: str
    retrieval_top_k: int
    checkpoint_db: Path
    langfuse_public_key: str
    langfuse_secret_key: str
    langfuse_host: str

    @property
    def tracing_enabled(self) -> bool:
        """Tracing turns itself on only when both Langfuse keys are present."""
        return bool(self.langfuse_public_key and self.langfuse_secret_key)


def _get_float(name, default):
    raw = os.getenv(name)
    if raw is None or not raw.strip():
        return default
    try:
        return float(raw)
    except ValueError:
        raise ConfigError(f"{name} must be a number, got {raw!r}")


def _get_int(name, default):
    raw = os.getenv(name)
    if raw is None or not raw.strip():
        return default
    try:
        return int(raw)
    except ValueError:
        raise ConfigError(f"{name} must be an integer, got {raw!r}")


@lru_cache(maxsize=2)
def get_settings(require_api_key=True) -> Settings:
    api_key = os.getenv("OPENROUTER_API_KEY", "").strip()
    if require_api_key and not api_key:
        raise ConfigError("OPENROUTER_API_KEY is not set. Add it to your .env file.")

    return Settings(
        openrouter_api_key=api_key,
        candidate_name=os.getenv("CANDIDATE_NAME", "").strip() or "the candidate",
        model=os.getenv("OPENROUTER_MODEL", "").strip() or DEFAULT_MODEL,
        temperature=_get_float("LLM_TEMPERATURE", DEFAULT_TEMPERATURE),
        drafting_temperature=_get_float("LLM_DRAFTING_TEMPERATURE", DEFAULT_DRAFTING_TEMPERATURE),
        max_tokens=_get_int("LLM_MAX_TOKENS", DEFAULT_MAX_TOKENS),
        skill_max_tokens=_get_int("SKILL_MAX_TOKENS", DEFAULT_SKILL_MAX_TOKENS),
        ats_max_tokens=_get_int("ATS_MAX_TOKENS", DEFAULT_ATS_MAX_TOKENS),
        max_history_turns=_get_int("MAX_HISTORY_TURNS", DEFAULT_MAX_HISTORY_TURNS),
        embedding_model=os.getenv("EMBEDDING_MODEL", "").strip() or DEFAULT_EMBEDDING_MODEL,
        retrieval_top_k=_get_int("RETRIEVAL_TOP_K", DEFAULT_RETRIEVAL_TOP_K),
        checkpoint_db=PROJECT_ROOT / (
            os.getenv("CHECKPOINT_DB", "").strip() or DEFAULT_CHECKPOINT_DB
        ),
        langfuse_public_key=os.getenv("LANGFUSE_PUBLIC_KEY", "").strip(),
        langfuse_secret_key=os.getenv("LANGFUSE_SECRET_KEY", "").strip(),
        # LANGFUSE_HOST is the SDK's own name; LANGFUSE_BASE_URL is accepted as an alias.
        langfuse_host=(
            os.getenv("LANGFUSE_HOST", "").strip()
            or os.getenv("LANGFUSE_BASE_URL", "").strip()
            or DEFAULT_LANGFUSE_HOST
        ),
    )

	"""Application configuration, loaded once from the environment."""

	import os
	from dataclasses import dataclass
	from functools import lru_cache
	from pathlib import Path

	from dotenv import load_dotenv

	load_dotenv()

	PROJECT_ROOT = Path(__file__).parent

	DEFAULT_MODEL = "openrouter/free"
	OPENROUTER_BASE_URL = "https://openrouter.ai/api/v1"
	DEFAULT_TEMPERATURE = 0.0
	# Drafting a cover letter is writing, not analysis: a little sampling gives
	# natural prose. Kept low so it does not start inventing detail.
	DEFAULT_DRAFTING_TEMPERATURE = 0.4
	# The preset actions (ATS keyword tables, detailed reviews) run long, so 2048
	# truncated them mid-answer. This leaves room for the profile, job description,
	# and conversation history while avoiding an unnecessarily large response cap.
	DEFAULT_MAX_TOKENS = 20000
	# Prose skill output gets its own response cap.
	DEFAULT_SKILL_MAX_TOKENS = 6500
	# ATS returns a structured classification for every keyword, so it needs more
	# output room than the prose skills.
	DEFAULT_ATS_MAX_TOKENS = 12000
	DEFAULT_LANGFUSE_HOST = "https://cloud.langfuse.com"
	DEFAULT_CHECKPOINT_DB = "checkpoints.sqlite"
	# Turns of conversation replayed to the model. Older turns stay in the
	# checkpoint (nothing is deleted) but are not resent.
	DEFAULT_MAX_HISTORY_TURNS = 10
	# Routing and retrieval. ONNX runtime, so no torch dependency.
	DEFAULT_EMBEDDING_MODEL = "sentence-transformers/all-MiniLM-L6-v2"
	DEFAULT_RETRIEVAL_TOP_K = 10


	class ConfigError(RuntimeError):
	"""Raised when the environment is missing or misconfigured."""


	@dataclass(frozen=True)
	class Settings:
	openrouter_api_key: str
	candidate_name: str
	model: str
	temperature: float
	drafting_temperature: float
	max_tokens: int
	skill_max_tokens: int
	ats_max_tokens: int
	max_history_turns: int
	embedding_model: str
	retrieval_top_k: int
	checkpoint_db: Path
	langfuse_public_key: str
	langfuse_secret_key: str
	langfuse_host: str

	@property
	def tracing_enabled(self) -> bool:
	"""Tracing turns itself on only when both Langfuse keys are present."""
	return bool(self.langfuse_public_key and self.langfuse_secret_key)


	def _get_float(name, default):
	raw = os.getenv(name)
	if raw is None or not raw.strip():
	return default
	try:
	return float(raw)
	except ValueError:
	raise ConfigError(f"{name} must be a number, got {raw!r}")


	def _get_int(name, default):
	raw = os.getenv(name)
	if raw is None or not raw.strip():
	return default
	try:
	return int(raw)
	except ValueError:
	raise ConfigError(f"{name} must be an integer, got {raw!r}")


	@lru_cache(maxsize=2)
	def get_settings(require_api_key=True) -> Settings:
	api_key = os.getenv("OPENROUTER_API_KEY", "").strip()
	if require_api_key and not api_key:
	raise ConfigError("OPENROUTER_API_KEY is not set. Add it to your .env file.")

	return Settings(
	openrouter_api_key=api_key,
	candidate_name=os.getenv("CANDIDATE_NAME", "").strip() or "the candidate",
	model=os.getenv("OPENROUTER_MODEL", "").strip() or DEFAULT_MODEL,
	temperature=_get_float("LLM_TEMPERATURE", DEFAULT_TEMPERATURE),
	drafting_temperature=_get_float("LLM_DRAFTING_TEMPERATURE", DEFAULT_DRAFTING_TEMPERATURE),
	max_tokens=_get_int("LLM_MAX_TOKENS", DEFAULT_MAX_TOKENS),
	skill_max_tokens=_get_int("SKILL_MAX_TOKENS", DEFAULT_SKILL_MAX_TOKENS),
	ats_max_tokens=_get_int("ATS_MAX_TOKENS", DEFAULT_ATS_MAX_TOKENS),
	max_history_turns=_get_int("MAX_HISTORY_TURNS", DEFAULT_MAX_HISTORY_TURNS),
	embedding_model=os.getenv("EMBEDDING_MODEL", "").strip() or DEFAULT_EMBEDDING_MODEL,
	retrieval_top_k=_get_int("RETRIEVAL_TOP_K", DEFAULT_RETRIEVAL_TOP_K),
	checkpoint_db=PROJECT_ROOT / (
	os.getenv("CHECKPOINT_DB", "").strip() or DEFAULT_CHECKPOINT_DB
	),
	langfuse_public_key=os.getenv("LANGFUSE_PUBLIC_KEY", "").strip(),
	langfuse_secret_key=os.getenv("LANGFUSE_SECRET_KEY", "").strip(),
	# LANGFUSE_HOST is the SDK's own name; LANGFUSE_BASE_URL is accepted as an alias.
	langfuse_host=(
	os.getenv("LANGFUSE_HOST", "").strip()
	or os.getenv("LANGFUSE_BASE_URL", "").strip()
	or DEFAULT_LANGFUSE_HOST
	),
	)