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

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

crewai_tools/tools/contextualai_rerank_tool/contextual_rerank_tool.py

@@ -0,0 +1,68 @@
+from typing import Any, Optional, Type, List
+from crewai.tools import BaseTool
+from pydantic import BaseModel, Field
+
+
+class ContextualAIRerankSchema(BaseModel):
+    """Schema for contextual rerank tool."""
+    query: str = Field(..., description="The search query to rerank documents against")
+    documents: List[str] = Field(..., description="List of document texts to rerank")
+    instruction: Optional[str] = Field(default=None, description="Optional instruction for reranking behavior")
+    metadata: Optional[List[str]] = Field(default=None, description="Optional metadata for each document")
+    model: str = Field(default="ctxl-rerank-en-v1-instruct", description="Reranker model to use")
+
+
+class ContextualAIRerankTool(BaseTool):
+    """Tool to rerank documents using Contextual AI's instruction-following reranker."""
+    
+    name: str = "Contextual AI Document Reranker"
+    description: str = "Rerank documents using Contextual AI's instruction-following reranker"
+    args_schema: Type[BaseModel] = ContextualAIRerankSchema
+    
+    api_key: str
+    package_dependencies: List[str] = ["contextual-client"]
+
+    def _run(
+        self,
+        query: str,
+        documents: List[str],
+        instruction: Optional[str] = None,
+        metadata: Optional[List[str]] = None,
+        model: str = "ctxl-rerank-en-v1-instruct"
+    ) -> str:
+        """Rerank documents using Contextual AI's instruction-following reranker."""
+        try:
+            import requests
+            import json
+
+            base_url = "https://api.contextual.ai/v1"
+            headers = {
+                "accept": "application/json",
+                "content-type": "application/json",
+                "authorization": f"Bearer {self.api_key}"
+            }
+
+            payload = {
+                "query": query,
+                "documents": documents,
+                "model": model
+            }
+
+            if instruction:
+                payload["instruction"] = instruction
+
+            if metadata:
+                if len(metadata) != len(documents):
+                    raise ValueError("Metadata list must have the same length as documents list")
+                payload["metadata"] = metadata
+
+            rerank_url = f"{base_url}/rerank"
+            result = requests.post(rerank_url, json=payload, headers=headers)
+
+            if result.status_code != 200:
+                raise RuntimeError(f"Reranker API returned status {result.status_code}: {result.text}")
+
+            return json.dumps(result.json(), indent=2)
+
+        except Exception as e:
+            return f"Failed to rerank documents: {str(e)}"