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Install

pip install nexus-library

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Get your Nexus API key

Create or sign in to the Nexus platform and copy your nexus_api_key: In examples below, nexus_key means your nexus_api_key.

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Run your first manual trace

The source tree exports NexusClient from nexus_library.nexus_core. 
from nexus_library.nexus_core import NexusClient

nexus_key = "your_nexus_api_key"
client = NexusClient(api_key=nexus_key)

with client.span("root-workflow", event_type="chain", input_data={"question": "What is Nexus?"}) as root:
    with client.span("lookup-tool", event_type="tool", input_data={"query": "nexus-library"}) as tool_span:
        tool_span.set_output({"result": "Tracing library for AI systems"})

    root.set_output({"status": "ok"})

client.flush()

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Add LangChain callback tracing

from nexus_library.nexus_core import NexusClient
from nexus_library.langchain import PrintingHandler

nexus_key = "your_nexus_api_key"
nexus_client = NexusClient(api_key=nexus_key)
callback_handler = PrintingHandler(nexus_client)

# Attach `callback_handler` to your LangChain runnable / agent callbacks

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Verify the trace exists

After your run finishes:
  • use client.get_all_events() to fetch stored rows
  • use client.print_tree_structure() to inspect hierarchy in terminal
  • use client.get_trace_tree_string() to get an LLM-readable tree dump

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Next steps

Manual tracing guide

Deep dive into span nesting and flush semantics.

LangChain guide

Understand callback lifecycle and event categories.

Configuration

Set DB URLs and trigger endpoints safely.

Python reference

Review method-level behavior for NexusClient.
nexus_key should be your Nexus platform nexus_api_key. Keep it secret and load it from environment variables in production.