> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pandaprobe.com/llms.txt
> Use this file to discover all available pages before exploring further.
# Python SDK
> Release notes for the PandaProbe Python SDK
Release history for the **PandaProbe Python SDK**.
Current version: `v0.4.0`
### Mistral AI and AWS Bedrock wrappers
* Added `pandaprobe.wrappers.wrap_mistral` for the official `mistralai>=1.0.0` client. Instruments `chat.complete` / `chat.complete_async` (blocking) and `chat.stream` / `chat.stream_async` (streaming) — every call automatically produces an LLM span with input, output, model, model parameters, and token usage. Mistral's native `prompt_tokens` / `completion_tokens` / `total_tokens` map directly onto PandaProbe's canonical names; `UNSET` sentinel kwargs are stripped before logging.
* Added `pandaprobe.wrappers.wrap_bedrock` *(beta)* for the AWS `bedrock-runtime` client (`boto3` and `aioboto3`). Instruments the recommended **Converse** API (`converse`, `converse_stream`) end-to-end — system blocks are hoisted into the universal-schema messages list, text-only `content` blocks are flattened, the streaming response dict (`{"stream": ..., "ResponseMetadata": ...}`) shape is preserved with only the inner iterator wrapped, time-to-first-token is captured on the first `contentBlockDelta`, and final usage (`inputTokens` / `outputTokens` / `totalTokens` and cache-read / cache-write counts) is read from the trailing `metadata` event.
* Bedrock legacy **InvokeModel** path is also instrumented (`invoke_model`, `invoke_model_with_response_stream`) with best-effort body parsing across Anthropic-on-Bedrock, Mistral, Llama, Titan, and Cohere body shapes.
* Async support for Bedrock is opportunistic — `aioboto3` is detected at runtime via `inspect.iscoroutinefunction` plus client-class-module heuristics, so you can use it without listing it as a dependency.
* New optional dependencies: `pip install "pandaprobe[mistral]"` and `pip install "pandaprobe[bedrock]"`.
* New examples in `examples/mistral/` (chat completion, streaming, multi-turn with sessions) and `examples/bedrock/` (Converse, Converse streaming, legacy InvokeModel with the Anthropic Claude body shape).
`wrap_bedrock` ships as **beta**.
### DeepAgents integration
* Added `pandaprobe.integrations.deepagents.DeepAgentsCallbackHandler` for tracing deep agents built with `create_deep_agent`. A single handler captures the parent agent **and** every sub-agent dispatched via the built-in `task` tool — sub-agent invocations forward `callbacks` / `tags` / `configurable` automatically, so the entire nested run is one trace.
* Span tree faithfully records the `task (TOOL) → (AGENT)` nesting, preserving the LangChain universal schema across the dispatcher boundary.
* Trace name remap: DeepAgents wraps a LangGraph compiled graph (root reports `name="LangGraph"`); rewritten to `"DeepAgents"` while custom user-given graph names pass through.
* New optional dependency: `pip install "pandaprobe[deepagents]"` (requires Python ≥3.11).
* New examples in `examples/deepagents/`: simple agent, sub-agent dispatch via the `task` tool, and multi-turn with sessions.
### Test infrastructure
* Test suite is now hermetic: a session-level fixture in `tests/conftest.py` pins `PANDAPROBE_ENDPOINT` to a fake host and clears every `PANDAPROBE_*` config var, so developer-machine env exports cannot leak into tests or accidentally hit production. Pinned by a regression-test class.
### LangChain integration
* Added `pandaprobe.integrations.langchain.LangChainCallbackHandler` for tracing LangChain agents built with `langchain.agents.create_agent` and plain LCEL pipelines (`prompt | model | parser`).
* Refactored shared callback logic into a private `pandaprobe.integrations._langchain_core` package. `LangGraphCallbackHandler` is now a thin subclass — behavior is unchanged for existing users; future LangChain-family integrations share the same base.
* Trace name remap: `create_agent`'s root reports `name="LangGraph"`, LCEL chains report `name="RunnableSequence"` — both rewritten to `"LangChain"` while custom user-given names pass through.
* Improved `safe_output` to faithfully serialize `@dataclass` instances (e.g. LangGraph `Command` objects) into structured JSON instead of `repr()` strings, preserving routing fields.
* Diagnostic-label fix: error logs in `_finalize_trace` now correctly reflect the active integration's name (`PandaProbe LangChain callback failed…` vs `PandaProbe LangGraph callback failed…`).
* New optional dependency: `pip install "pandaprobe[langchain]"`.
* New examples in `examples/langchain/`: simple agent, LCEL chain, multi-turn with sessions.
* Fixed installation of optional dependency extras (e.g. `pandaprobe[openai]`, `pandaprobe[gemini]`) by quoting glob-pattern extras to avoid shell unmatched-glob errors on common shells.
* Minor example and documentation corrections.
* Documentation polish: page titles and copy fixes across the SDK reference.
* Updated and expanded Python SDK documentation.
### Initial public release of the Python SDK
* **Tracing core**: `pandaprobe.init`, `pandaprobe.trace`, `pandaprobe.span` decorators, `TraceContext`/`SpanContext` context managers, background-batched transport with retry/backoff and atexit flushing.
* **Provider wrappers**: OpenAI, Anthropic, and Google Gemini — automatic LLM span capture without code changes.
* **Framework integrations**: LangGraph, Google ADK, Claude Agent SDK, CrewAI, and OpenAI Agents SDK.
* **Session and user context**: `pandaprobe.session(...)` / `pandaprobe.user(...)` ContextVar-based propagation across decorators, wrappers, and integrations.
* **Programmatic scoring**: `Client.score(trace_id, name, value, ...)` for trace-level evaluation signals.
* **Auto-init from environment**: `PANDAPROBE_API_KEY` + `PANDAPROBE_PROJECT_NAME` env vars trigger lazy client creation; `PANDAPROBE_ENABLED=false` disables silently.