Framework adapters

import pandaprobe
from pandaprobe_harness import Harness
from pandaprobe_harness.agent_tools.native import as_langchain_tools

harness = Harness.for_langgraph()
handler = harness.adapter.make_callback()          # the turn detector

graph = build_graph(
    system=harness.system_context() + PROMPT,
    tools=my_tools + as_langchain_tools(harness.toolset),
)

with pandaprobe.session(session_id):               # harness + SDK traces share the session
    await graph.ainvoke(
        state,
        config={"callbacks": [handler],
                "configurable": {"thread_id": session_id}},
    )

import pandaprobe
from pandaprobe_harness import Harness

harness = Harness.for_crewai()      # instruments Crew.kickoff automatically

crew = build_crew(
    system=harness.system_context() + PROMPT,
    # deliver the toolset via the companion CLI + harness.shell,
    # or wrap harness.toolset ops as CrewAI tools
)

with pandaprobe.session(session_id):
    crew.kickoff(inputs=...)        # each kickoff = one evaluated turn

import pandaprobe
from pandaprobe_harness import Harness
from pandaprobe_harness.agent_tools.native import as_anthropic_tools

harness = Harness.for_claude_agent_sdk()   # instruments receive_response

specs, dispatch = as_anthropic_tools(harness.toolset)

with pandaprobe.session(session_id):
    async with ClaudeSDKClient(options) as client:
        await client.query(user_input)
        async for message in client.receive_response():   # stream end = turn end
            ...

import pandaprobe
from pandaprobe_harness import Harness
from pandaprobe_harness.agent_tools.native import as_openai_function_tools

harness = Harness.for_openai_agents()      # registers the tracing processor

agent = Agent(
    instructions=harness.system_context() + PROMPT,
    tools=my_tools + as_openai_function_tools(harness.toolset),
)

with pandaprobe.session(session_id):
    result = await Runner.run(agent, user_input)   # one run = one evaluated turn