|
|
|
|
|
|
|
|
| FAKE_WEATHER = {
|
| "mumbai": "32 C, sunny, humid",
|
| "london": "14 C, cloudy, light rain",
|
| "tokyo": "21 C, clear skies",
|
| "new york": "18 C, partly cloudy",
|
| "paris": "16 C, overcast",
|
| }
|
|
|
|
|
| def add(a: float, b: float) -> str:
|
| return f"{a + b}"
|
|
|
|
|
| def multiply(a: float, b: float) -> str:
|
| return f"{a * b}"
|
|
|
|
|
| def get_weather(city: str) -> str:
|
| return FAKE_WEATHER.get(
|
| city.lower(),
|
| f"Weather for {city}: 25 C, partly cloudy (demo data)",
|
| )
|
|
|
|
|
|
|
|
|
|
|
|
|
| from examples import search_examples, get_paper_info, list_papers
|
|
|
|
|
| def search_ml_examples(query: str) -> str:
|
| """Search the ML paper sentence catalog by keyword."""
|
| matches = search_examples(query)
|
| if not matches:
|
| return f"No sentences matching '{query}'."
|
| lines = [f"Found {len(matches)} match(es):"]
|
| for m in matches[:5]:
|
| lines.append(
|
| f"- [{m['label']}] \"{m['sentence']}\" "
|
| f"({m['paper_title']}, {m['year']})"
|
| )
|
| return "\n".join(lines)
|
|
|
|
|
| def ml_paper_info(paper_id: str) -> str:
|
| """Look up metadata for a specific paper by its id."""
|
| info = get_paper_info(paper_id)
|
| if not info:
|
| return f"No paper with id '{paper_id}'."
|
| return (
|
| f"{info['title']} ({info['year']}) — "
|
| f"id: {info['paper_id']}, sentences in catalog: {info['sentence_count']}"
|
| )
|
|
|
|
|
| def list_ml_papers() -> str:
|
| """List every paper in the catalog."""
|
| papers = list_papers()
|
| lines = [f"{len(papers)} papers in catalog:"]
|
| for p in papers:
|
| lines.append(
|
| f"- {p['paper_id']}: {p['title']} ({p['year']}) "
|
| f"— {p['sentence_count']} sentences"
|
| )
|
| return "\n".join(lines)
|
|
|
|
|
| TOOL_FUNCTIONS = {
|
| "add": add,
|
| "multiply": multiply,
|
| "get_weather": get_weather,
|
| "search_ml_examples": search_ml_examples,
|
| "ml_paper_info": ml_paper_info,
|
| "list_ml_papers": list_ml_papers,
|
| }
|
|
|
|
|
| TOOL_SCHEMAS = [
|
| {
|
| "type": "function",
|
| "function": {
|
| "name": "add",
|
| "description": "Add two numbers and return the result.",
|
| "parameters": {
|
| "type": "object",
|
| "properties": {
|
| "a": {"type": "number", "description": "First number"},
|
| "b": {"type": "number", "description": "Second number"},
|
| },
|
| "required": ["a", "b"],
|
| },
|
| },
|
| },
|
| {
|
| "type": "function",
|
| "function": {
|
| "name": "multiply",
|
| "description": "Multiply two numbers and return the result.",
|
| "parameters": {
|
| "type": "object",
|
| "properties": {
|
| "a": {"type": "number", "description": "First number"},
|
| "b": {"type": "number", "description": "Second number"},
|
| },
|
| "required": ["a", "b"],
|
| },
|
| },
|
| },
|
| {
|
| "type": "function",
|
| "function": {
|
| "name": "get_weather",
|
| "description": "Get the current weather for a given city.",
|
| "parameters": {
|
| "type": "object",
|
| "properties": {
|
| "city": {"type": "string", "description": "City name"},
|
| },
|
| "required": ["city"],
|
| },
|
| },
|
| },
|
| {
|
| "type": "function",
|
| "function": {
|
| "name": "search_ml_examples",
|
| "description": "Search the built-in ML paper sentence catalog. Returns sentences matching the query along with their paper title, year, and label.",
|
| "parameters": {
|
| "type": "object",
|
| "properties": {
|
| "query": {"type": "string", "description": "Keyword or phrase to search for"},
|
| },
|
| "required": ["query"],
|
| },
|
| },
|
| },
|
| {
|
| "type": "function",
|
| "function": {
|
| "name": "ml_paper_info",
|
| "description": "Look up metadata (title, year, sentence count) for a specific ML paper by its id like 'vaswani-2017-attention'.",
|
| "parameters": {
|
| "type": "object",
|
| "properties": {
|
| "paper_id": {"type": "string", "description": "Paper id slug"},
|
| },
|
| "required": ["paper_id"],
|
| },
|
| },
|
| },
|
| {
|
| "type": "function",
|
| "function": {
|
| "name": "list_ml_papers",
|
| "description": "List every ML paper in the built-in catalog with its id, title, year, and sentence count.",
|
| "parameters": {
|
| "type": "object",
|
| "properties": {},
|
| },
|
| },
|
| },
|
| ]
|
|
|
