mirror of
https://github.com/SHOGGOTH-SECTOR/sica-fondt.git
synced 2026-08-01 08:30:20 +00:00
24f816b6a3
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
65 lines
2.7 KiB
Python
65 lines
2.7 KiB
Python
#
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# Copyright 2026 The Dapr Authors
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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# http://www.apache.org/licenses/LICENSE-2.0
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import logging
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from typing import Any, Callable, Dict, Optional
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from dapr_agents.tool.base import AgentTool
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from dapr_agents.types import ToolError
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logger = logging.getLogger(__name__)
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class WorkflowContextInjectedTool(AgentTool):
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"""
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AgentTool variant that allows the *agent* to inject a Dapr workflow context
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into tool execution without exposing that context as part of the tool schema.
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The injected context is passed via a dedicated kwarg (default: "ctx").
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It is *not* validated by args_model and is omitted from args_schema.
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"""
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# Name of the kwarg used to pass the workflow context at execution time.
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context_kwarg: str = "ctx"
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def _validate_and_prepare_args(
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self, func: Callable, *args: Any, **kwargs: Any
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) -> Dict[str, Any]:
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"""
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Pop workflow context and any hidden runtime kwargs out of kwargs, validate
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the remaining args against args_model, then re-attach the hidden kwargs so
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the executor receives them without exposing them in the LLM tool schema.
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Hidden kwargs stripped here:
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- ``ctx`` — Dapr workflow context (required)
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- ``_source_agent`` — name of the calling agent, used for "on-behalf-of"
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labelling (optional)
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- ``_child_instance_id`` — explicit instance ID for child workflows
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(optional, used by AgentWorkflowTool)
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"""
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ctx = kwargs.pop(self.context_kwarg, None)
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if ctx is None:
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raise ToolError(
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f"Missing workflow context. Pass it as '{self.context_kwarg}=<DaprWorkflowContext>'."
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)
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source_agent = kwargs.pop("_source_agent", None)
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child_instance_id = kwargs.pop("_child_instance_id", None)
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validated = super()._validate_and_prepare_args(func, *args, **kwargs)
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validated[self.context_kwarg] = ctx
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if source_agent is not None:
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validated["_source_agent"] = source_agent
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if child_instance_id is not None:
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validated["_child_instance_id"] = child_instance_id
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return validated
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