d2ca1926f8
'погода Балашиха сейчас' returns Russian weather sites (gismeteo, meteotrend) that report in °C, vs English queries which return Fahrenheit snippets that the model misreads as Celsius. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
123 lines
4.2 KiB
Python
123 lines
4.2 KiB
Python
"""
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Fast Tools — pre-flight tools invoked by a classifier before the main LLM call.
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Each FastTool has:
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- matches(message) → bool : regex classifier that determines if this tool applies
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- run(message) → str : async fetch that returns enrichment context
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FastToolRunner holds a list of FastTools. The Router uses any_matches() to force
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the tier to medium before LLM classification. run_agent_task() calls run_matching()
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to build extra context that is injected into the system prompt.
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To add a new fast tool:
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1. Subclass FastTool, implement name/matches/run
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2. Add an instance to the list passed to FastToolRunner in agent.py
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"""
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import asyncio
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import re
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from abc import ABC, abstractmethod
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import httpx
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class FastTool(ABC):
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"""Base class for all pre-flight fast tools."""
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@property
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@abstractmethod
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def name(self) -> str: ...
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@abstractmethod
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def matches(self, message: str) -> bool: ...
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@abstractmethod
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async def run(self, message: str) -> str: ...
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class WeatherTool(FastTool):
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"""
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Fetches current weather for the user's location (Balashikha, Moscow region)
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by querying SearXNG, which has external internet access.
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Triggered by any weather-related query. The Router also forces medium tier
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when this tool matches so the richer model handles the injected data.
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"""
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_PATTERN = re.compile(
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r"\b(weather|forecast|temperature|rain(ing)?|snow(ing)?|humidity|wind\s*speed"
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r"|холодно|тепло|погода|прогноз погоды"
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r"|how (hot|cold|warm) is it|what.?s the (weather|temp)|dress for the weather)\b",
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re.IGNORECASE,
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)
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# Fixed query — always fetch home location weather
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_SEARCH_QUERY = "погода Балашиха сейчас" # Russian query → Celsius sources
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def __init__(self, searxng_url: str):
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self._searxng_url = searxng_url
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@property
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def name(self) -> str:
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return "weather"
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def matches(self, message: str) -> bool:
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return bool(self._PATTERN.search(message))
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async def run(self, message: str) -> str:
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"""Query SearXNG for Balashikha weather and return current conditions snippet."""
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try:
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async with httpx.AsyncClient(timeout=15) as client:
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r = await client.get(
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f"{self._searxng_url}/search",
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params={"q": self._SEARCH_QUERY, "format": "json"},
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)
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r.raise_for_status()
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items = r.json().get("results", [])[:5]
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except Exception as e:
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return f"[weather error: {e}]"
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if not items:
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return ""
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# Prefer results whose snippets contain actual current conditions
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lines = ["Current weather data for Balashikha, Moscow region (temperatures in °C):\n"]
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for item in items:
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snippet = item.get("content", "")
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title = item.get("title", "")
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url = item.get("url", "")
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if snippet:
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lines.append(f"[{title}]\n{snippet}\nSource: {url}\n")
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return "\n".join(lines) if len(lines) > 1 else ""
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class FastToolRunner:
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"""
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Classifier + executor for fast tools.
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Used in two places:
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- Router.route(): any_matches() forces medium tier before LLM classification
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- run_agent_task(): run_matching() builds enrichment context in the pre-flight gather
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"""
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def __init__(self, tools: list[FastTool]):
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self._tools = tools
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def any_matches(self, message: str) -> bool:
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"""True if any fast tool applies to this message."""
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return any(t.matches(message) for t in self._tools)
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def matching_names(self, message: str) -> list[str]:
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"""Names of tools that match this message (for logging)."""
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return [t.name for t in self._tools if t.matches(message)]
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async def run_matching(self, message: str) -> str:
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"""Run all matching tools concurrently and return combined context."""
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matching = [t for t in self._tools if t.matches(message)]
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if not matching:
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return ""
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results = await asyncio.gather(*[t.run(message) for t in matching])
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parts = [r for r in results if r and not r.startswith("[")]
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return "\n\n".join(parts)
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