Claude 24f816b6a3
Consolidate 22 sibling repos into layered organism structure
Place useful parts of the surrounding repos into sica-fondt by layer, per the
body model (Ada = membrane; brain/endocrine/capabilities/knowledge non-Ada):

- brain/        LLM reasoning + providers (dapr, hermes, MoMoA)
- capabilities/ REPRAG sidecars: hermes tools/skills, dapr tools, parallel
                dispatch, A51 channels, and the OSINT cluster
- knowledge/    LORAG corpus: 754 cyber-skills, agency personas, secure-coding,
                MITRE ATT&CK data
- reference/    defensive threat-reference (C3, shhbruh doc) + AdaYaml parser

License handling: AGPL sources (worldosint, advanced_evolution, mercury,
Reticulum) and GPL DeTTECT are SPEC-only clean-room/port descriptions — no
copyleft code copied. MIT/Apache/data parts copied as working trees.

Safety: shhbruh escape/persistence material and C3 covert-C2 kept as reference
only, not wired into the running organism. See CONSOLIDATION.md.

https://claude.ai/code/session_01UehUqEXXJJCsHoA4voCU5c
2026-06-10 06:53:01 +00:00

66 lines
1.9 KiB
Python

#
# Copyright 2026 The Dapr Authors
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
#
from pydantic import BaseModel, PrivateAttr, Field
from abc import ABC, abstractmethod
from typing import Any, Optional
from dapr_agents.prompt.base import PromptTemplateBase
class LLMClientBase(BaseModel, ABC):
"""
Abstract base class for LLM models.
"""
_provider: str = PrivateAttr()
_api: str = PrivateAttr()
_config: Any = PrivateAttr()
_client: Any = PrivateAttr()
prompt_template: Optional[PromptTemplateBase] = Field(
default=None, description="Prompt template for rendering (optional)."
)
@property
def provider(self) -> str:
return self._provider
@property
def api(self) -> str:
return self._api
@property
def config(self) -> Any:
return self._config
@property
def client(self) -> Any:
return self._client
@abstractmethod
def get_client(self) -> Any:
"""Abstract method to get the client for the LLM model."""
pass
@abstractmethod
def get_config(self) -> Any:
"""Abstract method to get the configuration for the LLM model."""
pass
def refresh_client(self) -> None:
"""
Public method to refresh the client by regenerating the config and client.
"""
# Refresh config and client using the current state
self._config = self.get_config()
self._client = self.get_client()