Squashed 'packages/tools/' content from commit 78317b9c

git-subtree-dir: packages/tools
git-subtree-split: 78317b9c127f18bd040c1d77e3c0840cdc9a5b38

crewai_tools/tools/rag/rag_tool.py

@@ -0,0 +1,70 @@
+import portalocker
+
+from abc import ABC, abstractmethod
+from typing import Any
+from pydantic import BaseModel, ConfigDict, Field, model_validator
+
+from crewai.tools import BaseTool
+
+
+class Adapter(BaseModel, ABC):
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+    @abstractmethod
+    def query(self, question: str) -> str:
+        """Query the knowledge base with a question and return the answer."""
+
+    @abstractmethod
+    def add(
+        self,
+        *args: Any,
+        **kwargs: Any,
+    ) -> None:
+        """Add content to the knowledge base."""
+
+
+class RagTool(BaseTool):
+    class _AdapterPlaceholder(Adapter):
+        def query(self, question: str) -> str:
+            raise NotImplementedError
+
+        def add(self, *args: Any, **kwargs: Any) -> None:
+            raise NotImplementedError
+
+    name: str = "Knowledge base"
+    description: str = "A knowledge base that can be used to answer questions."
+    summarize: bool = False
+    adapter: Adapter = Field(default_factory=_AdapterPlaceholder)
+    config: dict[str, Any] | None = None
+
+    @model_validator(mode="after")
+    def _set_default_adapter(self):
+        if isinstance(self.adapter, RagTool._AdapterPlaceholder):
+            try:
+                from embedchain import App
+            except ImportError:
+                raise ImportError("embedchain is not installed. Please install it with `pip install crewai-tools[embedchain]`")
+
+            from crewai_tools.adapters.embedchain_adapter import EmbedchainAdapter
+
+            with portalocker.Lock("crewai-rag-tool.lock", timeout=10):
+                app = App.from_config(config=self.config) if self.config else App()
+
+            self.adapter = EmbedchainAdapter(
+                embedchain_app=app, summarize=self.summarize
+            )
+
+        return self
+
+    def add(
+        self,
+        *args: Any,
+        **kwargs: Any,
+    ) -> None:
+        self.adapter.add(*args, **kwargs)
+
+    def _run(
+        self,
+        query: str,
+    ) -> str:
+        return f"Relevant Content:\n{self.adapter.query(query)}"