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Merge pull request #1 from xingyaoww/dev
Setup Makefile, Pre-commit, and initial Tool and Schema definition
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‎.pre-commit-config.yaml‎

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repos:
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- repo: local
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hooks:
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- id: uv-format
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name: Format with uv format
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entry: uv
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args: [format]
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language: system
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types: [python]
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pass_filenames: false
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always_run: true
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- id: uv-check
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name: Lint with ruff
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entry: uv
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args: [run, ruff, check, --fix]
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language: system
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types: [python]
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pass_filenames: false
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always_run: true

‎Makefile‎

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# OpenHands V1 Makefile
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# Minimal Makefile for OpenHands V1 using uv
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# Colors for output
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GREEN := \033[32m
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YELLOW := \033[33m
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RED := \033[31m
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CYAN := \033[36m
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RESET := \033[0m
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# Required uv version
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REQUIRED_UV_VERSION := 0.8.13
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.PHONY: build format lint clean help check-uv-version
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# Default target
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.DEFAULT_GOAL := help
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# Check uv version
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check-uv-version:
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@echo "$(YELLOW)Checking uv version...$(RESET)"
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@UV_VERSION=$$(uv --version | cut -d' ' -f2); \
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REQUIRED_VERSION=$(REQUIRED_UV_VERSION); \
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if [ "$$(printf '%s\n' "$$REQUIRED_VERSION" "$$UV_VERSION" | sort -V | head -n1)" != "$$REQUIRED_VERSION" ]; then \
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echo "$(RED)Error: uv version $$UV_VERSION is less than required $$REQUIRED_VERSION$(RESET)"; \
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echo "$(YELLOW)Please update uv with: uv self update$(RESET)"; \
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exit 1; \
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fi; \
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echo "$(GREEN)uv version $$UV_VERSION meets requirements$(RESET)"
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# Main build target - setup everything
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build: check-uv-version
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@echo "$(CYAN)Setting up OpenHands V1 development environment...$(RESET)"
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@echo "$(YELLOW)Installing dependencies with uv sync --dev...$(RESET)"
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@uv sync --dev
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@echo "$(GREEN)Dependencies installed successfully.$(RESET)"
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@echo "$(YELLOW)Setting up pre-commit hooks...$(RESET)"
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@uv run pre-commit install
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@echo "$(GREEN)Pre-commit hooks installed successfully.$(RESET)"
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@echo "$(GREEN)Build complete! Development environment is ready.$(RESET)"
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# Format code using uv format
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format:
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@echo "$(YELLOW)Formatting code with uv format...$(RESET)"
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@uv format
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@echo "$(GREEN)Code formatted successfully.$(RESET)"
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# Lint code
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lint:
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@echo "$(YELLOW)Linting code with ruff...$(RESET)"
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@uv run ruff check --fix
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@echo "$(GREEN)Linting completed.$(RESET)"
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# Clean up cache files
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clean:
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@echo "$(YELLOW)Cleaning up cache files...$(RESET)"
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@find . -type d -name "__pycache__" -exec rm -rf {} + 2>/dev/null || true
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@find . -type f -name "*.pyc" -delete 2>/dev/null || true
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@rm -rf .pytest_cache .ruff_cache .mypy_cache 2>/dev/null || true
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@echo "$(GREEN)Cache files cleaned.$(RESET)"
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# Show help
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help:
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@echo "$(CYAN)OpenHands V1 Makefile$(RESET)"
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@echo "Available targets:"
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@echo " $(GREEN)build$(RESET) - Setup development environment (install deps + hooks)"
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@echo " $(GREEN)format$(RESET) - Format code with uv format"
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@echo " $(GREEN)lint$(RESET) - Lint code with ruff"
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@echo " $(GREEN)clean$(RESET) - Clean up cache files"
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@echo " $(GREEN)help$(RESET) - Show this help message"

‎openhands/runtime/schema.py‎

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from typing import Any, TypeVar
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from pydantic import BaseModel, Field, ConfigDict, create_model
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S = TypeVar("S", bound="Schema")
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def py_type(spec: dict[str, Any]) -> Any:
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"""Map JSON schema types to Python types."""
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t = spec.get("type")
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if t == "array":
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items = spec.get("items", {})
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inner = py_type(items) if isinstance(items, dict) else Any
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return list[inner] # type: ignore[index]
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if t == "object":
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return dict[str, Any]
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_map = {
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"string": str,
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"integer": int,
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"number": float,
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"boolean": bool,
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}
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if t in _map:
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return _map[t]
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return Any
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class Schema(BaseModel):
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"""Base schema for input action / output observation."""
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model_config = ConfigDict(extra="forbid")
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@classmethod
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def to_mcp_schema(cls) -> dict[str, Any]:
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"""Convert to JSON schema format compatible with MCP."""
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js = cls.model_json_schema()
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req = [n for n, f in cls.model_fields.items() if f.is_required()]
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return {
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"type": "object",
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"properties": js.get("properties", {}) or {},
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"required": req or [],
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}
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@classmethod
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def from_mcp_schema(
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cls: type[S], model_name: str, schema: dict[str, Any]
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) -> type["S"]:
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"""Create a Schema subclass from an MCP/JSON Schema object."""
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assert isinstance(schema, dict), "Schema must be a dict"
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assert schema.get("type") == "object", "Only object schemas are supported"
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props: dict[str, Any] = schema.get("properties", {}) or {}
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required = set(schema.get("required", []) or [])
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fields: dict[str, tuple] = {}
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for fname, spec in props.items():
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tp = py_type(spec if isinstance(spec, dict) else {})
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default = ... if fname in required else None
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desc: str | None = (
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spec.get("description") if isinstance(spec, dict) else None
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)
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fields[fname] = (
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tp,
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Field(default=default, description=desc)
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if desc
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else Field(default=default),
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)
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return create_model(model_name, __base__=cls, **fields) # type: ignore[return-value]
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class ActionBase(Schema):
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"""Base schema for input action."""
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pass
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class ObservationBase(Schema):
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"""Base schema for output observation."""
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model_config = ConfigDict(extra="allow")

‎openhands/runtime/tool.py‎

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from typing import Any, Callable
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from pydantic import BaseModel
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from .schema import ActionBase, ObservationBase, Schema
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class ToolAnnotations(BaseModel):
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title: str | None = None
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readOnlyHint: bool | None = None
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destructiveHint: bool | None = None
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idempotentHint: bool | None = None
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openWorldHint: bool | None = None
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class Tool:
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"""Tool that wraps an executor function with input/output validation and schema.
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- Normalize input/output schemas (class or dict) into both model+schema.
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- Validate inputs before execute.
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- Coerce outputs only if an output model is defined; else return vanilla JSON.
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- Export MCP tool description.
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"""
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def __init__(
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self,
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*,
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name: str,
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input_schema: type[ActionBase] | dict[str, Any],
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output_schema: type[ObservationBase] | dict[str, Any] | None = None,
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description: str | None = None,
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annotations: ToolAnnotations | None = None,
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_meta: dict[str, Any] | None = None,
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execute_fn: Callable[[ActionBase], ObservationBase] | None = None,
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):
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self.name = name
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self.description = description
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self.annotations = annotations
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self._meta = _meta
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self._set_input_schema(input_schema)
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self._set_output_schema(output_schema)
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self.execute_fn = execute_fn
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def _set_input_schema(
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self, input_schema: dict[str, Any] | type[ActionBase]
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) -> None:
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# ---- INPUT: class or dict -> model + schema
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self.action_type: type[ActionBase]
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self.input_schema: dict[str, Any]
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if isinstance(input_schema, type) and issubclass(input_schema, Schema):
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self.action_type = input_schema
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self.input_schema = input_schema.to_mcp_schema()
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elif isinstance(input_schema, dict):
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self.input_schema = input_schema
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self.action_type = ActionBase.from_mcp_schema(
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f"{self.name}Action", input_schema
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)
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else:
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raise TypeError(
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"input_schema must be ActionBase subclass or dict JSON schema"
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)
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def _set_output_schema(
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self, output_schema: dict[str, Any] | type[ObservationBase] | None
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) -> None:
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# ---- OUTPUT: optional class or dict -> model + schema
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self.observation_type: type[ObservationBase] | None
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self.output_schema: dict[str, Any] | None
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if output_schema is None:
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self.observation_type = None
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self.output_schema = None
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elif isinstance(output_schema, type) and issubclass(output_schema, Schema):
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self.observation_type = output_schema
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self.output_schema = output_schema.to_mcp_schema()
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elif isinstance(output_schema, dict):
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self.output_schema = output_schema
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self.observation_type = ObservationBase.from_mcp_schema(
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f"{self.name}Observation", output_schema
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)
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else:
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raise TypeError(
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"output_schema must be ObservationBase subclass, dict, or None"
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)
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def call(self, action: ActionBase) -> ObservationBase:
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if self.execute_fn is None:
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raise NotImplementedError(f"Tool '{self.name}' has no executor")
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# Execute
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result = self.execute_fn(action)
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# Coerce output only if we declared a model; else wrap in base ObservationBase
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if self.observation_type:
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if isinstance(result, self.observation_type):
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return result
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return self.observation_type.model_validate(result)
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else:
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# When no output schema is defined, wrap the result in ObservationBase
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if isinstance(result, ObservationBase):
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return result
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elif isinstance(result, BaseModel):
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return ObservationBase.model_validate(result.model_dump())
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elif isinstance(result, dict):
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return ObservationBase.model_validate(result)
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raise TypeError(
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"Output must be dict or BaseModel when no output schema is defined"
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)
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def to_mcp_tool(self) -> dict[str, Any]:
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out = {
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"name": self.name,
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"description": self.description,
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"inputSchema": self.input_schema,
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}
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if self.annotations:
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out["annotations"] = self.annotations
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if self._meta is not None:
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out["_meta"] = self._meta
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if self.output_schema:
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out["outputSchema"] = self.output_schema
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return out

‎pyproject.toml‎

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"litellm>=1.75.9",
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"pydantic>=2.11.7",
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]
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[dependency-groups]
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dev = [
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"pre-commit>=4.3.0",
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"ruff>=0.12.10",
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]

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