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feat: add skills example notebook #21

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korikuzma merged 1 commit into from
Jun 24, 2026
Merged

feat: add skills example notebook #21

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223 changes: 223 additions & 0 deletions notebooks/skills.ipynb
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{
"cells": [
{
"cell_type": "markdown",
"id": "b1bed39d",
"metadata": {},
"source": [
"# Skills Example\n",
"\n",
"This notebook demonstrates how to use a `SKILL.md` file with Wags-LLM."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "e9161ef9",
"metadata": {},
"outputs": [],
"source": [
"import logging\n",
"import sys\n",
"from collections.abc import Mapping\n",
"from pathlib import Path\n",
"from typing import Any\n",
"\n",
"from pydantic import BaseModel, ConfigDict\n",
"\n",
"from wags_llm.client.bedrock import BedrockClaudeJsonClient\n",
"from wags_llm.services.structured_task import StructuredTaskRunner\n",
"from wags_llm.skills.base import BaseSkillTemplate\n",
"from wags_llm.skills.registry import SkillRegistry\n",
"\n",
"logging.basicConfig(\n",
" stream=sys.stdout,\n",
" level=logging.WARNING,\n",
" format=\"%(name)s - %(levelname)s - %(message)s\",\n",
")\n",
"logging.getLogger(\"wags_llm\").setLevel(logging.DEBUG)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "1e9131aa",
"metadata": {},
"outputs": [],
"source": [
"class VariantCurationSkill(BaseSkillTemplate):\n",
" skill_path = Path(\"skills/variant_curation_0.1.0.md\")\n",
"\n",
" def build_user_prompt(self, payload: Mapping[str, Any]) -> str:\n",
" variant = payload[\"variant\"]\n",
" disease = payload.get(\"disease\", \"cancer\")\n",
"\n",
" return f\"\"\"Curate the following variant for {disease}.\n",
"Variant:\n",
"{variant}\n",
"\n",
"Return concise JSON matching the provided schema:\n",
"- clinical_significance: one short sentence\n",
"- evidence_level: short label\n",
"- supporting_rationale: 2-3 short sentences maximum\n",
"\"\"\"\n",
"\n",
"\n",
"class VariantCurationResult(BaseModel):\n",
" model_config = ConfigDict(extra=\"forbid\", use_enum_values=True) # Required\n",
"\n",
" clinical_significance: str | None = None\n",
" evidence_level: str | None = None\n",
" supporting_rationale: str | None = None\n",
" error_message: str | None = None"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "3c719fca",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"('variant_curation', '0.1.0')"
]
},
"execution_count": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"skill = VariantCurationSkill()\n",
"skill.name, skill.version"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "c44eeb11",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"wags_llm.skills.registry - DEBUG - Registering skill: name='variant_curation', version='0.1.0'\n",
"wags_llm.client.bedrock - DEBUG - BedrockClaudeJsonClient config: model_id='us.anthropic.claude-sonnet-4-6', region_name='us-east-1', profile_name='dev-account', max_tokens=350, temperature=0.000000\n",
"wags_llm.client.bedrock - INFO - BedrockClaudeJsonClient successfully initialized for model_id='us.anthropic.claude-sonnet-4-6'\n"
]
}
],
"source": [
"registry = SkillRegistry()\n",
"registry.register(skill)\n",
"\n",
"MODEL_ID = \"us.anthropic.claude-sonnet-4-6\"\n",
"REGION_NAME = \"us-east-1\"\n",
"PROFILE_NAME = \"dev-account\"\n",
"MAX_TOKENS = 350\n",
"\n",
"llm_client = BedrockClaudeJsonClient(\n",
" model_id=MODEL_ID,\n",
" region_name=REGION_NAME,\n",
" profile_name=PROFILE_NAME,\n",
" max_tokens=MAX_TOKENS,\n",
" temperature=0,\n",
")\n",
"\n",
"task_runner = StructuredTaskRunner(\n",
" client=llm_client,\n",
" skill_registry=registry,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "d045cf30",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"wags_llm.skills.base - DEBUG - Loading skill from path: skills/variant_curation_0.1.0.md\n",
"wags_llm.skills.base - INFO - Loaded skill from path: skills/variant_curation_0.1.0.md\n",
"wags_llm.client.bedrock - DEBUG - Bedrock Claude usage={'inputTokens': 576, 'outputTokens': 185, 'totalTokens': 761, 'cacheReadInputTokens': 0, 'cacheWriteInputTokens': 0}\n",
"wags_llm.client.bedrock - DEBUG - Bedrock Claude metrics={'latencyMs': 4014}\n",
"wags_llm.client.bedrock - DEBUG - Bedrock Claude content=[{'text': '{\"clinical_significance\":\"BRAF V600E is a pathogenic, therapeutically actionable variant in melanoma associated with sensitivity to BRAF and MEK inhibitors.\",\"evidence_level\":\"Level A (Validated association)\",\"supporting_rationale\":\"BRAF V600E is the most common activating mutation in melanoma, present in approximately 50% of cases, and constitutively activates the MAPK signaling pathway. FDA-approved targeted therapies including vemurafenib, dabrafenib (BRAF inhibitors), and trametinib (MEK inhibitor) demonstrate significant clinical benefit in BRAF V600E-positive melanoma patients. Multiple phase III clinical trials support improved progression-free and overall survival with BRAF/MEK inhibitor combinations compared to chemotherapy.\",\"error_message\":null}'}]\n"
]
},
{
"data": {
"text/plain": [
"VariantCurationResult(clinical_significance='BRAF V600E is a pathogenic, therapeutically actionable variant in melanoma associated with sensitivity to BRAF and MEK inhibitors.', evidence_level='Level A (Validated association)', supporting_rationale='BRAF V600E is the most common activating mutation in melanoma, present in approximately 50% of cases, and constitutively activates the MAPK signaling pathway. FDA-approved targeted therapies including vemurafenib, dabrafenib (BRAF inhibitors), and trametinib (MEK inhibitor) demonstrate significant clinical benefit in BRAF V600E-positive melanoma patients. Multiple phase III clinical trials support improved progression-free and overall survival with BRAF/MEK inhibitor combinations compared to chemotherapy.', error_message=None)"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"result = task_runner.execute_skill(\n",
" skill_name=\"variant_curation\",\n",
" skill_version=\"0.1.0\",\n",
" payload={\n",
" \"variant\": \"BRAF V600E\",\n",
" \"disease\": \"melanoma\",\n",
" },\n",
" response_model=VariantCurationResult,\n",
")\n",
"result"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "2ac3d498",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"{'clinical_significance': 'BRAF V600E is a pathogenic, therapeutically actionable variant in melanoma associated with sensitivity to BRAF and MEK inhibitors.',\n",
" 'evidence_level': 'Level A (Validated association)',\n",
" 'supporting_rationale': 'BRAF V600E is the most common activating mutation in melanoma, present in approximately 50% of cases, and constitutively activates the MAPK signaling pathway. FDA-approved targeted therapies including vemurafenib, dabrafenib (BRAF inhibitors), and trametinib (MEK inhibitor) demonstrate significant clinical benefit in BRAF V600E-positive melanoma patients. Multiple phase III clinical trials support improved progression-free and overall survival with BRAF/MEK inhibitor combinations compared to chemotherapy.',\n",
" 'error_message': None}"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"result.model_dump()"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "wags-llm (3.13.5)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.13.5"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
23 changes: 23 additions & 0 deletions notebooks/skills/variant_curation_0.1.0.md
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---
name: variant-curation
description: Assess clinical significance of a genomic variant in a specified disease context.
---

# Variant Curation

## Inputs
- variant
- disease

## Instructions
- Follow CIViC-style evidence reasoning.
- Be precise.
- Do not invent evidence.
- Flag uncertainty clearly.

## Output
Return a `VariantCurationResult` object containing:
- clinical_significance
- evidence_level
- supporting_rationale
- error_message
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