Move modules around

haystack_experimental/dataclasses/tool.py

@@ -12,6 +12,8 @@
 from haystack.utils import deserialize_callable, serialize_callable
 from pydantic import TypeAdapter, create_model
 
+from haystack_experimental.tools import extract_component_parameters
+
 with LazyImport(message="Run 'pip install jsonschema'") as jsonschema_import:
     from jsonschema import Draft202012Validator
     from jsonschema.exceptions import SchemaError
@@ -216,18 +218,11 @@ def from_component(cls, component: Component, name: str, description: str) -> "T
         """
 
         if not isinstance(component, Component):
-            raise ValueError(
-                f"{component} is not a Haystack component!" "Can only create a Tool from a Haystack component instance."
-            )
-
-        if getattr(component, "__haystack_added_to_pipeline__", None):
-            msg = (
-                "Component has been added in a Pipeline and can't be used to create a Tool. "
-                "Create Tool from a non-pipeline component instead."
+            message = (
+                f"Object {component!r} is not a Haystack component. "
+                "Use this method to create a Tool only with Haystack component instances."
             )
-            raise ValueError(msg)
-
-        from haystack_experimental.components.tools.openai.component_caller import extract_component_parameters
+            raise ValueError(message)
 
         # Extract the parameters schema from the component
         parameters = extract_component_parameters(component)

haystack_experimental/tools/__init__.py

@@ -0,0 +1,7 @@
+# SPDX-FileCopyrightText: 2022-present deepset GmbH <info@deepset.ai>
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from .tool_component_descriptor import extract_component_parameters
+
+__all__ = ["extract_component_parameters"]

haystack_experimental/components/tools/openai/component_caller.py → haystack_experimental/tools/tool_component_descriptor.py

@@ -2,14 +2,13 @@
 #
 # SPDX-License-Identifier: Apache-2.0
 
-from dataclasses import MISSING, fields, is_dataclass
+from dataclasses import fields, is_dataclass
 from inspect import getdoc
 from typing import Any, Callable, Dict, Union, get_args, get_origin
 
 from docstring_parser import parse
 from haystack import logging
 from haystack.core.component import Component
-from pydantic.fields import FieldInfo
 
 from haystack_experimental.util.utils import is_pydantic_v2_model
 
@@ -77,6 +76,25 @@ def get_param_descriptions(method: Callable) -> Dict[str, str]:
     return param_descriptions
 
 
+class UnsupportedTypeError(Exception):
+    """Raised when a type is not supported for schema generation."""
+
+    pass
+
+
+def is_nullable_type(python_type: Any) -> bool:
+    """
+    Checks if the type is a Union with NoneType (i.e., Optional).
+
+    :param python_type: The Python type to check.
+    :returns: True if the type is a Union with NoneType, False otherwise.
+    """
+    origin = get_origin(python_type)
+    if origin is Union:
+        return type(None) in get_args(python_type)
+    return False
+
+
 # ruff: noqa: PLR0912
 def create_property_schema(python_type: Any, description: str, default: Any = None) -> Dict[str, Any]:
     """
@@ -130,16 +148,3 @@ def create_property_schema(python_type: Any, description: str, default: Any = No
         schema["default"] = default
 
     return schema
-
-
-def is_nullable_type(python_type: Any) -> bool:
-    """
-    Checks if the type is a Union with NoneType (i.e., Optional).
-
-    :param python_type: The Python type to check.
-    :returns: True if the type is a Union with NoneType, False otherwise.
-    """
-    origin = get_origin(python_type)
-    if origin is Union:
-        return type(None) in get_args(python_type)
-    return False

test/components/tools/test_tool_component.py

@@ -30,7 +30,7 @@ def run(self, text: str) -> Dict[str, str]:
         """
         A simple component that generates text.
 
-        :param text: user's introductory message
+        :param text: user's name
         :return: A dictionary with the generated text.
         """
         return {"reply": f"Hello, {text}!"}
@@ -160,7 +160,7 @@ def test_from_component_basic(self):
             "properties": {
                 "text": {
                     "type": "string",
-                    "description": "user's introductory message"
+                    "description": "user's name"
                 }
             },
             "required": ["text"]
@@ -436,18 +436,6 @@ def foo(self, text: str):
                 description="This should fail"
             )
 
-    def test_from_component_for_pipeline_component(self):
-        pipeline = Pipeline()
-        component = SimpleComponent()
-        pipeline.add_component("component", component)
-
-        with pytest.raises(ValueError):
-            Tool.from_component(
-                component=component,
-                name="invalid_tool",
-                description="This should fail"
-            )
-
 
 ## Integration tests
 class TestToolComponentInPipelineWithOpenAI:
@@ -605,7 +593,7 @@ def test_document_processor_in_pipeline(self):
         pipeline.connect("llm.replies", "tool_invoker.messages")
 
         message = ChatMessage.from_user(
-            text="I have two documents. First one says 'Hello world' and second one says 'Goodbye world'. Can you concatenate them?"
+            text="Concatenate these documents: First one says 'Hello world' and second one says 'Goodbye world'. Set only content field of the document only. Do not set id, meta, score, embedding, sparse_embedding, dataframe, blob fields."
         )
 
         result = pipeline.run({"llm": {"messages": [message]}})