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add LangSmith observability, partner endpoint callout, and QA fixes to getting started notebook (#137)
* feat: add LangSmith observability section, partner endpoint callout, and QA fixes to getting started notebook
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docs/notebooks/0_Getting_Started_with_AIQ.ipynb

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"cell_type": "markdown",
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"id": "mp3fa80d86",
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"metadata": {},
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"source": "**3. Add LangSmith tracing to your config**\n\nRun the cell below to automatically update `config_simple_researcher.yml` with LangSmith tracing:"
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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": "ls_config_writer",
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"metadata": {},
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"outputs": [],
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"source": [
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"**3. Add LangSmith tracing to your config**\n",
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"config_path = \"config_simple_researcher.yml\"\n",
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"\n",
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"Add the `tracing` block under `general.telemetry` in your config file (e.g. `config_simple_researcher.yml`):\n",
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"with open(config_path) as f:\n",
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" content = f.read()\n",
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"\n",
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"```yaml\n",
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"general:\n",
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" use_uvloop: true\n",
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" telemetry:\n",
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" logging:\n",
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" console:\n",
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" _type: console\n",
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" level: WARN\n",
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" tracing:\n",
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" langsmith:\n",
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" _type: langsmith\n",
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" project: langsmith-project\n",
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" api_key: ${LANGSMITH_API_KEY}\n",
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"```\n",
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"\n",
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"Then re-run the agent as before. Traces will appear in your LangSmith project dashboard at [smith.langchain.com](https://smith.langchain.com/)."
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"if \"tracing:\" not in content:\n",
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" content = content.replace(\n",
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" \" level: INFO\\n\",\n",
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" \" level: INFO\\n\\n\"\n",
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" \" tracing:\\n\"\n",
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" \" langsmith:\\n\"\n",
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" \" _type: langsmith\\n\"\n",
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" \" project: ${LANGSMITH_PROJECT}\\n\"\n",
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" \" api_key: ${LANGSMITH_API_KEY}\\n\",\n",
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" 1,\n",
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" )\n",
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" with open(config_path, \"w\") as f:\n",
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" f.write(content)\n",
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" print(f\"Tracing config added to {config_path}\")\n",
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"else:\n",
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" print(\"Tracing config already present — no changes made.\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "ls_verify_md",
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"metadata": {},
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"source": "**4. Run the agent and verify traces**\n\nRe-run the agent with the updated config:"
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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": "ls_run_agent",
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"metadata": {},
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"outputs": [],
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"source": [
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"!.venv/bin/nat run --config_file config_simple_researcher.yml --input \"What is NVIDIA Spectrum-X?\" | sed 's/\\\\n/\\n/g'"
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]
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},
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{
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"cell_type": "markdown",
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"id": "ls_check_md",
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"metadata": {},
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"source": "After the run completes, go to [smith.langchain.com](https://smith.langchain.com/), open your project, and you should see a new trace for the query above. Click into it to explore the agent's steps, LLM calls, and tool usage."
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},
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{
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"cell_type": "markdown",
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"id": "together_lightweight_md",
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"metadata": {},
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"source": "## (Optional) Use a Partner LLM Endpoint\n\nYou can swap the LLM provider in `config_simple_researcher.yml` with any OpenAI-compatible API.\n\nFor example, to use [Together.ai](https://www.together.ai/) with the [Nemotron model](https://www.together.ai/models/nvidia-nemotron-3-nano) — sign up at [together.ai](https://www.together.ai/), generate an API key, and update the three Nemotron LLM blocks (`nemotron_llm_intent`, `nemotron_llm`, `nemotron_llm_deep`) following this pattern:\n\n```yaml\nllms:\n nemotron_llm:\n _type: openai\n model_name: nvidia/NVIDIA-Nemotron-3-Nano-30B-A3B-BF16\n base_url: \"https://api.together.xyz/v1\"\n api_key: ${TOGETHER_API_KEY}\n temperature: 0.1\n top_p: 0.3\n max_tokens: 16384\n num_retries: 5\n```\n\nKey changes from the default NIM config:\n- `_type: nim` → `_type: openai`\n- `base_url` → partner endpoint URL\n- `api_key` → your `TOGETHER_API_KEY`\n- Remove `chat_template_kwargs: enable_thinking: true` (NIM-specific)\n\n> More provider guides coming soon."
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},
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{
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"cell_type": "markdown",
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"id": "ed4b4431",

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