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feat(closes OPEN-7559): add callbacks and offline buffering for platform tracing
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‎examples/tracing/offline_buffering.ipynb‎

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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "intro",
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"metadata": {},
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"source": [
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"[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openlayer-ai/openlayer-python/blob/main/examples/tracing/offline_buffering.ipynb)\n",
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"\n",
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"\n",
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"# <a id=\"top\">Offline buffering for tracing</a>\n",
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"\n",
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"This notebook shows how to use offline buffering to handle network failures gracefully when tracing with Openlayer."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "install",
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"metadata": {},
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"outputs": [],
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"source": [
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"!pip install openlayer"
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]
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},
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{
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"cell_type": "markdown",
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"id": "setup",
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"metadata": {},
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"source": [
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"## 1. Configure with offline buffering"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "config",
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"metadata": {},
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"outputs": [],
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"source": [
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"from openlayer.lib import trace, configure\n",
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"\n",
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"\n",
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"# Define a callback for when traces fail to send\n",
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"def on_failure(trace_data, config, error): # noqa: ARG001\n",
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" # Failed traces are automatically buffered when offline_buffer_enabled=True\n",
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" pass\n",
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"\n",
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"# Configure tracer with offline buffering\n",
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"configure(\n",
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" api_key=\"your_api_key\",\n",
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" inference_pipeline_id=\"your_pipeline_id\",\n",
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" on_flush_failure=on_failure,\n",
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" offline_buffer_enabled=True,\n",
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" offline_buffer_path=\"./buffer\",\n",
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" max_buffer_size=100\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "usage",
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"metadata": {},
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"source": [
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"## 2. Use tracing normally"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "trace",
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"metadata": {},
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"outputs": [],
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"source": [
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"@trace()\n",
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"def process_query(query: str) -> str:\n",
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" return f\"Processed: {query}\"\n",
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"\n",
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"# If network fails, traces are automatically buffered\n",
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"result = process_query(\"What is AI?\")\n",
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"result"
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]
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},
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{
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"cell_type": "markdown",
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"id": "status",
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"metadata": {},
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"source": [
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"## 3. Check buffer status"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "check",
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"metadata": {},
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"outputs": [],
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"source": [
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"from openlayer.lib.tracing import tracer\n",
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"\n",
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"status = tracer.get_buffer_status()\n",
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"status"
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]
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},
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{
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"cell_type": "markdown",
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"id": "replay",
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"metadata": {},
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"source": [
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"## 4. Replay buffered traces"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "replay-code",
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"metadata": {},
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"outputs": [],
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"source": [
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"# When connectivity is restored, replay failed traces\n",
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"result = tracer.replay_buffered_traces()\n",
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"result"
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]
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},
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{
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"cell_type": "markdown",
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"id": "summary",
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"metadata": {},
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"source": [
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"## Summary\n",
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"\n",
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"With offline buffering:\n",
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"\n",
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"- ✅ Failed traces are automatically saved locally\n",
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"- ✅ No data loss during network outages \n",
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"- ✅ Easy replay when connectivity returns\n",
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"- ✅ Custom failure callbacks for monitoring"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.9.18"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

‎src/openlayer/lib/__init__.py‎

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__all__ = [
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"configure",
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"trace",
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"trace_anthropic",
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"trace_anthropic",
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"trace_openai",
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"trace_openai_assistant_thread_run",
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"trace_mistral",
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"trace_litellm",
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"update_current_trace",
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"update_current_step",
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# Offline buffer management functions
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"replay_buffered_traces",
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"get_buffer_status",
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"clear_offline_buffer",
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# User and session context functions
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"set_user_session_context",
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"update_trace_user_session",
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update_current_trace = tracer.update_current_trace
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update_current_step = tracer.update_current_step
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# Offline buffer management functions
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replay_buffered_traces = tracer.replay_buffered_traces
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get_buffer_status = tracer.get_buffer_status
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clear_offline_buffer = tracer.clear_offline_buffer
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def trace_anthropic(client):
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"""Trace Anthropic chat completions."""
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try:
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import boto3
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except ImportError:
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raise ImportError(
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"boto3 is required for Bedrock tracing. Install with: pip install boto3"
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)
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raise ImportError("boto3 is required for Bedrock tracing. Install with: pip install boto3")
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from .integrations import bedrock_tracer
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# Check if it's a boto3 client for bedrock-runtime service
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if (
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not hasattr(client, "_service_model")
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or client._service_model.service_name != "bedrock-runtime"
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):
129-
raise ValueError(
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"Invalid client. Please provide a boto3 bedrock-runtime client."
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)
132+
if not hasattr(client, "_service_model") or client._service_model.service_name != "bedrock-runtime":
133+
raise ValueError("Invalid client. Please provide a boto3 bedrock-runtime client.")
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return bedrock_tracer.trace_bedrock(client)
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def trace_oci_genai(client, estimate_tokens: bool = True):
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"""Trace OCI GenAI chat completions.
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Args:
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client: OCI GenAI client.
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estimate_tokens: Whether to estimate tokens when not available. Defaults to True.
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# --------------------------------- LiteLLM ---------------------------------- #
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def trace_litellm():
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"""Enable tracing for LiteLLM completions.
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This function patches litellm.completion to automatically trace all completions
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made through the LiteLLM library, which provides a unified interface to 100+ LLM APIs.
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Example:
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>>> import litellm
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>>> from openlayer.lib import trace_litellm
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>>>
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>>> # Enable tracing
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>>> trace_litellm()
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>>>
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>>> # Use LiteLLM normally - tracing happens automatically
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>>> response = litellm.completion(
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... model="gpt-3.5-turbo",
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... messages=[{"role": "user", "content": "Hello!"}],
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... inference_id="custom-id-123" # Optional Openlayer parameter
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... inference_id="custom-id-123", # Optional Openlayer parameter
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... )
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"""
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# pylint: disable=import-outside-toplevel
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try:
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import litellm
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except ImportError:
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raise ImportError(
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"litellm is required for LiteLLM tracing. Install with: pip install litellm"
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)
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raise ImportError("litellm is required for LiteLLM tracing. Install with: pip install litellm")
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from .integrations import litellm_tracer
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