singleaxis-fabric 0.2.0

Open-source observability and control plane for AI agents — decision-span tracing, fail-loud guardrails, and human-in-the-loop, OpenTelemetry-native.

singleaxis-fabric (Python SDK)

Native Python SDK that tenant agents import in-process. Provides the decision-span contract, guardrail/escalation types, OTel plumbing, and optional adapters for LangGraph, Microsoft Agent Framework, and CrewAI (installed via extras — the core SDK stays framework-neutral).

Authoritative specs

• ../../specs/002-architecture.md
• ../../specs/005-guardrails-inline.md
• ../../specs/003-context-graph.md (retrieval audit)
• ../../specs/007-escalation-workflow.md (pause primitive)

Status

Beta — Phase 1a shipping.

Shipping now

• Fabric client (Fabric.from_env, FabricConfig, close())

• Decision context manager — opens an OTel span per agent call and tags it with the Fabric-standard attributes:

  • fabric.tenant_id, fabric.agent_id, fabric.profile
  • fabric.session_id, fabric.request_id, fabric.user_id
  • fabric.blocked, fabric.blocked.policies (on block)

• Guardrail types: GuardrailResult, EntitySummary, GuardrailBlocked, GuardrailNotConfiguredError

• Presidio rail via UDS sidecar: UDSPresidioClient, RedactionResult, RedactionError. Decision.guard_input, guard_output_chunk, and guard_output_final route through the chain and emit fabric.guardrail span events (phase, latency_ms, blocked, entities, policies).

• NeMo Colang rail via UDS sidecar: UDSNemoClient, NemoResult, NemoError. Wired into the same chain; runs after Presidio so the Colang / LLM checks never see raw PII. May block (action == "block"), with the canned response surfaced on the GuardrailResult.

• LLM-call instrumentation: Decision.llm_call(system=..., model=...) opens a fabric.llm_call child span (kind=CLIENT) populated with the OpenTelemetry GenAI semantic conventions (gen_ai.system, gen_ai.request.model, gen_ai.usage.input_tokens, gen_ai.usage.output_tokens, gen_ai.response.finish_reasons) alongside fabric.llm.* mirrors. Phoenix LLM views, Langfuse cost dashboards, and any backend keying off either namespace render Fabric traces natively. The returned context manager exposes set_usage(...), set_response_model(...), and set_attribute(...) for attaching response data on exit.

• Tool-call instrumentation: Decision.tool_call(name, call_id=...) follows the same pattern with gen_ai.tool.* + fabric.tool.* conventions. Helpful for instrumenting function/tool invocations that happen inside an agent turn.

• OTel helpers: get_tracer, install_default_provider

• Decision-level block recording (record_block, raise_for_block)

• Retrieval recording: RetrievalSource, RetrievalRecord, Decision.record_retrieval(source, query=..., result_count=..., ...). Hashes the query with SHA-256 locally (raw text never hits the span), emits a fabric.retrieval span event with allowlisted attributes, and maintains rolling fabric.retrieval_count and fabric.retrieval_sources on the decision span so the Telemetry Bridge can fold them into the DecisionSummary wire event. Maps onto the Context Graph's Retrieval node (spec 003).

• Escalation pause primitive: EscalationSummary, EscalationRequested, Decision.request_escalation, Decision.raise_for_escalation. Records fabric.escalated, fabric.escalation.reason/rubric_id/ mode/triggering_score on the span and emits a fabric.escalation span event. EscalationSummary.to_payload() returns the framework-agnostic dict tenants hand to whatever interrupt primitive their orchestrator exposes (LangGraph interrupt(), Agent Framework checkpoints, a bespoke queue). The SDK owns the local signal only; the downstream SASF review + signed-verdict resume lives in the escalation service (spec 007).

• Memory write recording: MemoryKind, MemoryRecord, Decision.remember(kind=..., content=..., key=..., tags=..., ttl_seconds=...). Tenants perform the actual write against their own memory store; the SDK SHA-256s the content locally (raw text never hits the span) and emits a fabric.memory span event with the allowlisted metadata, plus rolling fabric.memory_write_count and fabric.memory_kinds attributes the Telemetry Bridge folds into the DecisionSummary wire event. Symmetric to record_retrieval — the Context Graph materializes the write as a Retrieval node with source=memory tied to the owning Decision.

  from fabric import MemoryKind
  
  with fabric.decision(session_id=sess, request_id=req) as decision:
      answer = my_agent.run(user_input)
      my_memory_store.write(key="last_answer", value=answer)
      decision.remember(
          kind=MemoryKind.EPISODIC,
          key="last_answer",
          content=answer,
          tags=("turn", "assistant"),
      )
  

When no rails are configured, guard_input / guard_output_* raise GuardrailNotConfiguredError. This is a deliberate fail-loud posture — a silently passing guardrail is a compliance footgun.

Framework adapters (optional)

The core SDK is framework-neutral. Adapters live under fabric.adapters.* and are each gated behind an install extra so the core install does not pull in any orchestration package.

• fabric.adapters.langgraph.escalate(decision, summary) — records the Fabric escalation on the decision span and calls langgraph.types.interrupt(payload). Returns whatever the host resumes the graph with (typically the signed verdict).
• fabric.adapters.agent_framework.request_escalation(ctx, decision, summary, *, response_type=...) — records on span, then await ctx.request_info(request_data=..., response_type=...). The resumed response is routed to a MAF @response_handler method (dispatch-based, per MAF design).
• fabric.adapters.crewai.attach_callbacks(decision) returns CrewCallbacks (step + task callbacks that record CrewAI lifecycle events on the decision span). fabric.adapters.crewai.request_escalation(decision, summary) records on span and returns the canonical payload — the tenant pairs it with their chosen CrewAI HITL channel (@human_feedback Flow, Task(human_input=True), or enterprise /resume).

Install

pip install singleaxis-fabric                         # core
pip install "singleaxis-fabric[otlp]"                 # + OTLP/HTTP exporter
pip install "singleaxis-fabric[langgraph]"            # + LangGraph adapter
pip install "singleaxis-fabric[agent-framework]"      # + MAF adapter
pip install "singleaxis-fabric[crewai]"               # + CrewAI adapter

Quick start

import os
from fabric import Fabric, install_default_provider
from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter

# Host chooses how to export — typically an OTLP endpoint pointing at
# the Fabric OTel Collector. install_default_provider is a convenience
# for small agents; production hosts wire the provider themselves.
install_default_provider(
    service_name="support-bot",
    exporter=OTLPSpanExporter(endpoint=os.environ["OTEL_EXPORTER_OTLP_ENDPOINT"]),
)

fabric = Fabric.from_env()

with fabric.decision(
    session_id=session.id,
    request_id=req.id,
    user_id=user.id,
) as decision:
    # real work happens here; the decision span wraps it all
    safe_input = decision.guard_input(req.body)
    output = llm.complete(prompt=safe_input)
    final = decision.guard_output_final(output)
    decision.set_attribute("llm.model", "claude-opus-4-7")

guard_input / guard_output_* are no-ops that raise GuardrailNotConfiguredError unless FABRIC_PRESIDIO_UNIX_SOCKET is set (or a PresidioClient is passed to Fabric(...) directly).

Environment variables

Variable	Required	Purpose
FABRIC_TENANT_ID	yes	Tenant scope for all emitted events.
FABRIC_AGENT_ID	yes	Which agent in the tenant is running.
FABRIC_PROFILE	no	Regulatory profile (default permissive-dev).
FABRIC_PRESIDIO_UNIX_SOCKET	no	Unix socket path to the Presidio sidecar (/v1/redact). If unset, the Presidio rail is not installed.
FABRIC_PRESIDIO_TIMEOUT_SECONDS	no	Per-call timeout for the sidecar (float, default 0.5).
FABRIC_NEMO_UNIX_SOCKET	no	Unix socket path to the NeMo Colang sidecar (/v1/check). If unset, the NeMo rail is not installed.
FABRIC_NEMO_TIMEOUT_SECONDS	no	Per-call timeout for the NeMo sidecar (float, default 1.0).

Module layout

sdk/python/
├── pyproject.toml
├── src/fabric/
│   ├── __init__.py
│   ├── client.py          # Fabric, FabricConfig, from_env
│   ├── decision.py        # Decision context manager
│   ├── guardrails.py      # result + error types
│   ├── escalation.py      # EscalationSummary + EscalationRequested
│   ├── presidio.py        # PresidioClient protocol + UDS impl
│   ├── nemo.py            # NemoClient protocol + UDS impl
│   ├── retrieval.py       # RetrievalSource + RetrievalRecord
│   ├── memory.py          # MemoryKind + MemoryRecord
│   ├── _chain.py          # GuardrailChain (internal)
│   ├── _uds.py            # HTTP-over-unix-socket transport
│   ├── _version.py        # version sourced from git tag (hatch-vcs)
│   ├── tracing.py         # OTel helpers
│   ├── adapters/          # framework adapters (extras-gated)
│   │   ├── langgraph.py
│   │   ├── agent_framework.py
│   │   └── crewai.py
│   └── py.typed
└── tests/
    ├── conftest.py
    ├── _fake_sidecar.py
    ├── test_client.py
    ├── test_decision.py
    ├── test_guardrail_chain.py
    ├── test_escalation.py
    ├── test_nemo.py
    ├── test_presidio.py
    ├── test_retrieval.py
    └── test_tracing.py

Tests

python -m venv .venv && . .venv/bin/activate
pip install -e '.[dev]'
pytest

Coverage threshold is 85% at the pyproject level. Current baseline is ~98% because the Phase 1a surface is narrow; as guardrails and memory land, keep the 85% floor honest rather than moving it.

Versioning

Independent of the Fabric umbrella version pre-1.0.0. Tenant agents pin the SDK; the Control Plane advertises compatibility ranges.

License

Apache-2.0. See LICENSE.