pryscraper/llm_providers/base.py
cryptorugmunch 8d25702eca chore(license): re-license to dual MIT (core) + BSL 1.1 (stealth)
Squashed from chore/license-relicense. Full message preserved in the
original branch commit bb77eb5. See ADR-0002 for the decision rationale.

Refs: ADR-0002, commit bb77eb5
2026-07-02 19:59:18 +02:00

72 lines
2.3 KiB
Python

"""Pry — LLM Provider abstraction with referral revenue tracking.
Supports pluggable providers: OpenAI, Anthropic, Google, Cohere, Mistral, Ollama, OpenRouter.
Includes referral/affiliate link tracking for revenue sharing."""
# SPDX-License-Identifier: MIT
# Copyright (c) 2026 Rug Munch Media LLC
#
# Part of Pry — https://git.rugmunch.io/RugMunchMedia/pryscraper
# Licensed under MIT. See LICENSE.
import logging
from abc import ABC, abstractmethod
from dataclasses import dataclass, field
from typing import Any
logger = logging.getLogger(__name__)
@dataclass
class LLMResponse:
"""Standard response from any LLM provider."""
text: str
model: str
provider: str
input_tokens: int = 0
output_tokens: int = 0
cost_usd: float = 0.0
referral_id: str = ""
latency_ms: int = 0
raw: dict[str, Any] = field(default_factory=dict)
@dataclass
class ReferralConfig:
"""Referral/affiliate config for revenue sharing."""
enabled: bool = True
program_id: str = "pry-default"
# Provider-specific referral links (with our affiliate ID)
referral_links: dict[str, str] = field(default_factory=dict)
# NEW: link to the full provider catalog
catalog: dict = field(default_factory=dict)
def __post_init__(self):
if not self.referral_links:
from referrals import PROVIDER_CATALOG
for _category, providers in PROVIDER_CATALOG.items():
for p in providers:
self.referral_links[p["tag"]] = p["url"]
self.catalog = PROVIDER_CATALOG
class LLMProvider(ABC):
"""Abstract base class for LLM providers."""
name: str = ""
cost_per_1k_input: float = 0.0
cost_per_1k_output: float = 0.0
referral_url: str = ""
@abstractmethod
async def complete(self, prompt: str, system: str = "", max_tokens: int = 1024,
temperature: float = 0.7, model: str = "") -> LLMResponse:
"""Send completion request to provider."""
raise NotImplementedError
@abstractmethod
async def embed(self, text: str, model: str = "") -> list[float]:
"""Generate embedding for text."""
raise NotImplementedError
def estimate_cost(self, input_tokens: int, output_tokens: int) -> float:
return (input_tokens / 1000) * self.cost_per_1k_input + (output_tokens / 1000) * self.cost_per_1k_output