Files
markitect-main/markitect/llm/factory.py
tegwick 41773f1320 feat(llm): add OpenAI adapter, entity archive policy, process chapters 5-7
Add OpenAIAdapter for the OpenAI chat completions API (apikey-chatgpt.txt
or OPENAI_API_KEY). Set default model to arcee-ai/trinity-large-preview:free
for the infospace pipeline and increase max_tokens from 4096 to 8192.

Reprocess chapter 05 with Trinity Large (was Gemini: 1 truncated entity,
now 19 complete entities). Process chapters 06 (Aurora Alpha, 10 entities)
and 07 (Trinity Large, 15 entities including regenerated violent-policy.md).
Canonical set now at 85 unique entities.

Add entity archive policy: entities are never silently deleted. Retired
entities move to output/entities/archive/ with a dated reason header.
New CLI option: --archive-entity <slug> --reason "...". The --list
output shows the archive count alongside the canonical set.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-02-11 23:39:44 +01:00

61 lines
2.1 KiB
Python

"""
Factory for creating LLM adapters by provider name.
"""
from typing import Optional, Dict, Any
from markitect.prompts.execution.llm_adapter import LLMAdapter
from markitect.llm.exceptions import LLMConfigurationError
# Lazy imports to avoid pulling in every adapter at module load time.
_PROVIDERS: Dict[str, str] = {
"openrouter": "markitect.llm.openrouter.OpenRouterAdapter",
"claude-code": "markitect.llm.claude_code.ClaudeCodeAdapter",
"gemini": "markitect.llm.gemini.GeminiAdapter",
"openai": "markitect.llm.openai.OpenAIAdapter",
}
def create_adapter(
provider: str = "openrouter",
model: Optional[str] = None,
api_key: Optional[str] = None,
system_prompt: Optional[str] = None,
**kwargs: Any,
) -> LLMAdapter:
"""Instantiate an :class:`LLMAdapter` for the given *provider*.
Args:
provider: ``"openrouter"``, ``"claude-code"``, ``"gemini"``, or ``"openai"``.
model: Model name (passed to the adapter constructor).
api_key: Explicit API key (OpenRouter / Gemini / OpenAI).
system_prompt: Optional system prompt (OpenRouter / Gemini / OpenAI).
**kwargs: Extra keyword arguments forwarded to the adapter.
Returns:
A ready-to-use :class:`LLMAdapter` instance.
Raises:
LLMConfigurationError: If *provider* is not recognised.
"""
if provider not in _PROVIDERS:
known = ", ".join(sorted(_PROVIDERS))
raise LLMConfigurationError(
f"Unknown LLM provider {provider!r}. Choose from: {known}",
context={"provider": provider},
)
# Lazy import
fqn = _PROVIDERS[provider]
module_path, class_name = fqn.rsplit(".", 1)
import importlib
mod = importlib.import_module(module_path)
cls = getattr(mod, class_name)
if provider in ("openrouter", "gemini", "openai"):
return cls(model=model, api_key=api_key, system_prompt=system_prompt, **kwargs)
elif provider == "claude-code":
return cls(model=model, **kwargs)
else:
return cls(**kwargs) # pragma: no cover