95336528f6
Co-authored-by: Clément Sirieix <clement.sirieix@mistral.ai> Co-authored-by: Kim-Adeline Miguel <51720070+kimadeline@users.noreply.github.com> Co-authored-by: Mathias Gesbert <mathias.gesbert@mistral.ai> Co-authored-by: Maxime Dolores <maxime.dolores@ext.mistral.ai> Co-authored-by: Michel Thomazo <51709227+michelTho@users.noreply.github.com> Co-authored-by: Paul Cacheux <paul.cacheux@mistral.ai> Co-authored-by: Quentin <quentin.torroba@mistral.ai> Co-authored-by: Simon <80467011+sorgfresser@users.noreply.github.com> Co-authored-by: angelapopopo <angele.lenglemetz@mistral.ai> Co-authored-by: Mistral Vibe <vibe@mistral.ai>
98 lines
2.9 KiB
Python
98 lines
2.9 KiB
Python
from __future__ import annotations
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from pathlib import Path
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from typing import Any
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from pydantic import BaseModel, Field, field_validator
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class SkillMetadata(BaseModel):
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model_config = {"populate_by_name": True}
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name: str = Field(
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...,
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min_length=1,
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max_length=64,
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pattern=r"^[a-z0-9]+(-[a-z0-9]+)*$",
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description="Skill identifier. Lowercase letters, numbers, and hyphens only.",
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)
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description: str = Field(
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...,
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min_length=1,
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max_length=1024,
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description="What this skill does and when to use it.",
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)
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license: str | None = Field(
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default=None, description="License name or reference to a bundled license file."
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)
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compatibility: str | None = Field(
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default=None,
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max_length=500,
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description="Environment requirements (intended product, system packages, etc.).",
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)
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metadata: dict[str, str] = Field(
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default_factory=dict,
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description="Arbitrary key-value mapping for additional metadata.",
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)
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allowed_tools: list[str] = Field(
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default_factory=list,
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validation_alias="allowed-tools",
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description="Space-delimited list of pre-approved tools (experimental).",
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)
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user_invocable: bool = Field(
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default=True,
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validation_alias="user-invocable",
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description="Controls whether the skill appears in the slash command menu.",
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)
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@field_validator("allowed_tools", mode="before")
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@classmethod
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def parse_allowed_tools(cls, v: str | list[str] | None) -> list[str]:
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if v is None:
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return []
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if isinstance(v, str):
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return v.split()
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return list(v)
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@field_validator("metadata", mode="before")
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@classmethod
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def normalize_metadata(cls, v: dict[str, Any] | None) -> dict[str, str]:
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if v is None:
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return {}
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return {str(k): str(val) for k, val in v.items()}
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class SkillInfo(BaseModel):
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name: str
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description: str
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license: str | None = None
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compatibility: str | None = None
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metadata: dict[str, str] = Field(default_factory=dict)
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allowed_tools: list[str] = Field(default_factory=list)
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user_invocable: bool = True
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skill_path: Path
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model_config = {"arbitrary_types_allowed": True}
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@property
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def skill_dir(self) -> Path:
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return self.skill_path.parent.resolve()
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@classmethod
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def from_metadata(cls, meta: SkillMetadata, skill_path: Path) -> SkillInfo:
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return cls(
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name=meta.name,
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description=meta.description,
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license=meta.license,
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compatibility=meta.compatibility,
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metadata=meta.metadata,
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allowed_tools=meta.allowed_tools,
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user_invocable=meta.user_invocable,
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skill_path=skill_path.resolve(),
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)
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class ParsedSkillCommand(BaseModel):
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name: str
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content: str
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extra_instructions: str | None = None
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