Explainability SDK for tracing, graphing, and policy auditing of AI agents
Project description
AISquare Explainability SDK
Lightweight Python SDK for tracing, graphing, and policy auditing of AI agents. Captures execution traces from any Python agent (Agno, LangChain, plain Python) and delivers them to the AISquare Explainability Gateway.
Installation
pip install aisquare[explainability]
For Agno auto-instrumentation:
pip install aisquare[explainability,agno]
Quick start
Every trace needs an agent identity on its root span — agent_name is the key
the gateway routes traces by. Name your agent explicitly and pre-register it:
# .env: EXPLAINABILITY_GATEWAY_URL, EXPLAINABILITY_API_KEY,
# EXPLAINABILITY_AGENTS=support-bot <- pre-registers; must equal agent_name below
import aisquare.explainability as sdk
sdk.init_from_env()
with sdk.AgentRunTracer(agent_name="support-bot"):
with sdk.LLMCallTracer(model="gpt-4o", provider="openai") as llm:
... # your agent logic — nested spans inherit the run's routing identity
# IMPORTANT for short-lived scripts: flush ensures traces reach the gateway
# before the process exits. Long-running services don't need this.
sdk.flush()
Using a framework instead of manual tracers? The identity contract is the
same — the agent's explicit name becomes agent.name on the root span: Agno
Agent(name="support-bot"), LangChain metadata={"agent_name": "support-bot"},
or GovernedAgent(..., agent_name="support-bot").
What the SDK captures
The SDK collects two layers of signal:
Auto-instrumentation (zero tracing code): The AgnoAdapter installs openinference-instrumentation-agno, which automatically wraps every Agno agent run, LLM call, and tool invocation as an OTel span. The Agno Agent(name=...) becomes the trace's routing identity — always name your agents.
Manual tracers (governance-grade): Nine context-manager tracers you can add to any Python code — framework-agnostic:
| Tracer | Purpose |
|---|---|
AgentRunTracer |
Wraps a full agent run as the root span |
LLMCallTracer |
Records an LLM inference call with I/O and token counts |
ToolCallTracer |
Records a tool invocation with parameters, result, and errors |
RetrievalTracer |
Records a RAG retrieval with documents and scores |
HumanInterventionTracer |
Records a human-in-the-loop review or correction |
RoutingTracer |
Records a routing/delegation decision with selected and rejected paths |
DecisionTracer |
Records a general decision point with options, selected, and rejected paths |
PolicyGateTracer |
Records a policy-gate evaluation with the policies checked and the allow/deny outcome |
MemoryTracer |
Records memory read/write operations |
Decorators are also available: @trace_tool and @trace_retrieval.
Manual instrumentation (any framework)
Leaf tracers (LLM, tool, routing, ...) always run nested inside an
AgentRunTracer — its agent_name is stamped as agent.name on the root
span, the attribute the gateway routes the trace by. A trace with no agent
identity is rejected at ingest (409 no_agent_identity).
import aisquare.explainability as sdk
sdk.init_from_env()
with sdk.AgentRunTracer(agent_name="MyAgent", run_id="abc-123") as run:
run.set_input("User query")
with sdk.LLMCallTracer(model="gpt-4o-mini", provider="openai") as llm:
response = call_openai(...)
llm.set_input_messages([{"role": "user", "content": "..."}])
llm.set_output_messages([{"role": "assistant", "content": response}])
llm.set_token_counts(prompt=100, completion=50)
with sdk.RoutingTracer(decision_type="tool_selection") as rt:
rt.set_selected("web_search", reason="Query requires fresh data")
rt.set_rejected([{"name": "cached_search", "reason": "Cache is stale"}])
run.set_output("Agent final answer")
sdk.flush()
Environment variables
| Variable | Description |
|---|---|
EXPLAINABILITY_GATEWAY_URL |
Gateway base URL for trace ingest |
EXPLAINABILITY_API_KEY |
API key for trace ingest |
EXPLAINABILITY_AGENTS |
Comma-separated agent names registered at init; must match your AgentRunTracer / framework agent names |
AISQUARE_AGENT_NAME |
The SDK's default agent identity, in two roles: the identity used for policy checks, and (since 1.0.6) the fallback trace identity stamped on spans that would otherwise be rootless so the trace still routes. Keep it equal to your agent_name. |
Multiple agents: name each agent in code (AgentRunTracer(agent_name=...)
or the framework equivalent) — that per-run name is what routes each trace.
AISQUARE_AGENT_NAME holds a single name and is a single-agent convenience
only; it cannot distinguish between agents in the same process.
Diagnostics
The SDK ships a built-in health checker:
explainability-doctor
Its agent_identity check warns when no agent identity is configured (the
classic precondition for 409 no_agent_identity ingest rejections), and its
delivery_backlog check surfaces traces stuck in the local inbox after
gateway 409s — with the remediation for each rejection code.
License
MIT
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