95358448e6
Replace hardwired Anthropic API calls with a pluggable provider system. Each deployment configures its AI provider in instance.yaml — switching between Anthropic, LiteLLM, OpenRouter, or any OpenAI-compatible proxy is a config change, not a code change. New connectors/llm/ module: - StructuredExtractor Protocol with extract_json() interface - AnthropicExtractor: direct Anthropic SDK with retry + backoff - OpenAICompatExtractor: any OpenAI-compatible proxy with three-layer structured output fallback (json_schema -> json_object -> prompt) - Configurable structured_output policy (strict/json/auto) - Custom exception hierarchy (auth/rate_limit/timeout/format/refusal) - Zero secrets in logs: no API keys, prompts, or responses logged Reviewed by: Google Gemini, Claude Sonnet, OpenAI GPT-5.4. Security audit passed with all critical findings resolved.
137 lines
4.5 KiB
Python
137 lines
4.5 KiB
Python
"""Factory for creating structured extractors from instance configuration.
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Reads the ai: section from instance.yaml (already resolved by config/loader.py)
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and creates the appropriate StructuredExtractor implementation.
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"""
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import logging
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from urllib.parse import urlparse
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from .anthropic_provider import AnthropicExtractor
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from .base import StructuredExtractor
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from .openai_compat import OpenAICompatExtractor
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logger = logging.getLogger(__name__)
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# Default model when not specified in config
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DEFAULT_MODEL = "claude-haiku-4-5-20251001"
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# Default structured output strategy
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DEFAULT_STRUCTURED_OUTPUT = "auto"
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def create_extractor(ai_config: dict) -> StructuredExtractor:
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"""Create a structured extractor from the ai: config section.
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Supports two configuration formats:
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New format (explicit provider):
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ai:
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provider: anthropic | openai_compat
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api_key: ${ANTHROPIC_API_KEY}
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model: claude-haiku-4-5-20251001
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base_url: https://api.example.com/v1 # required for openai_compat
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structured_output: auto # strict | json | auto
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Legacy format (backward compatible):
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ai:
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anthropic_api_key: ${ANTHROPIC_API_KEY}
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Args:
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ai_config: The ai: section dict from instance.yaml,
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already resolved by config/loader.py.
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Returns:
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A StructuredExtractor instance.
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Raises:
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ValueError: If configuration is invalid or incomplete.
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"""
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if not ai_config or not isinstance(ai_config, dict):
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raise ValueError(
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"ai: section in instance.yaml must be a non-empty dict. "
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"Example:\n ai:\n provider: anthropic\n api_key: ${ANTHROPIC_API_KEY}"
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)
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provider = ai_config.get("provider")
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# Legacy format detection: anthropic_api_key present, no provider
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if not provider and "anthropic_api_key" in ai_config:
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api_key = ai_config["anthropic_api_key"]
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_validate_api_key(api_key)
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model = ai_config.get("model", DEFAULT_MODEL)
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logger.info(
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"Creating AnthropicExtractor (legacy config), model=%s", model
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)
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return AnthropicExtractor(api_key=api_key, model=model)
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if not provider:
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raise ValueError(
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"ai.provider is required in instance.yaml. "
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"Supported: 'anthropic', 'openai_compat'. "
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"Hint: use ${ENV_VAR} syntax for secrets."
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)
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api_key = ai_config.get("api_key", "")
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_validate_api_key(api_key)
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model = ai_config.get("model", DEFAULT_MODEL)
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if provider == "anthropic":
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logger.info("Creating AnthropicExtractor, model=%s", model)
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return AnthropicExtractor(api_key=api_key, model=model)
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elif provider == "openai_compat":
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base_url = ai_config.get("base_url", "")
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if not base_url:
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raise ValueError(
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"ai.base_url is required when provider is 'openai_compat'. "
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"Example: base_url: https://api.openai.com/v1"
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)
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structured_output = ai_config.get(
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"structured_output", DEFAULT_STRUCTURED_OUTPUT,
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)
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if structured_output not in ("strict", "json", "auto"):
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raise ValueError(
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f"ai.structured_output must be 'strict', 'json', or 'auto', "
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f"got '{structured_output}'"
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)
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safe_url = _sanitize_url(base_url)
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logger.info(
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"Creating OpenAICompatExtractor, url=%s, model=%s, "
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"structured_output=%s",
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safe_url, model, structured_output,
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)
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return OpenAICompatExtractor(
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api_key=api_key,
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base_url=base_url,
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model=model,
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structured_output=structured_output,
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)
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else:
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raise ValueError(
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f"Unknown ai.provider '{provider}'. "
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f"Supported: 'anthropic', 'openai_compat'. "
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f"Hint: use ${{ENV_VAR}} syntax for secrets."
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)
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def _validate_api_key(api_key: str) -> None:
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"""Validate that an API key is present and non-empty.
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Raises:
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ValueError: If api_key is empty or missing.
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"""
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if not api_key or not api_key.strip():
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raise ValueError(
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"ai.api_key (or ai.anthropic_api_key) must not be empty. "
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"Check that the corresponding environment variable is set "
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"and referenced with ${ENV_VAR} syntax in instance.yaml."
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)
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def _sanitize_url(url: str) -> str:
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"""Extract scheme://host from a URL for safe logging."""
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parsed = urlparse(url)
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return f"{parsed.scheme}://{parsed.netloc}"
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