WIP: add Fabric Data Agent tool

.env.template

@@ -34,6 +34,11 @@ OLLAMA_MODEL_CHAT="gemma3:latest"
 ## Foundry Local Settings
 FOUNDRY_LOCAL_MODEL_CHAT="phi-3-mini-4k"
 
+# Fabric Data Agent Settings
+FABRIC_DATA_AGENT_NAME="your_data_agent_name"
+FABRIC_DATA_AGENT_USER_INSTRUCTIONS="your_user_instructions"
+# FIXME: add more necessary settings. proper impl ref. https://learn.microsoft.com/en-us/fabric/data-science/fabric-data-agent-sdk
+
 # ---------
 # Tools
 # ---------

template_langgraph/tools/common.py

@@ -4,6 +4,7 @@
 from template_langgraph.tools.cosmosdb_tool import search_cosmosdb
 from template_langgraph.tools.dify_tool import run_dify_workflow
 from template_langgraph.tools.elasticsearch_tool import search_elasticsearch
+from template_langgraph.tools.fabric_data_agent_tool import search_fabric_data_agent
 from template_langgraph.tools.mcp_tool import McpClientWrapper
 from template_langgraph.tools.qdrant_tool import search_qdrant
 from template_langgraph.tools.sql_database_tool import SqlDatabaseClientWrapper
@@ -20,6 +21,7 @@ def get_default_tools():
             run_dify_workflow,
             search_qdrant,
             search_elasticsearch,
+            search_fabric_data_agent,
         ]
         + SqlDatabaseClientWrapper().get_tools(
             llm=AzureOpenAiWrapper().chat_model,

template_langgraph/tools/fabric_data_agent_tool.py

@@ -0,0 +1,94 @@
+from functools import lru_cache
+from uuid import uuid4
+
+from langchain_core.tools import tool
+from pydantic import BaseModel, Field
+from pydantic_settings import BaseSettings, SettingsConfigDict
+
+from template_langgraph.loggers import get_logger
+
+logger = get_logger(__name__)
+logger.setLevel("DEBUG")
+
+
+class Settings(BaseSettings):
+    fabric_data_agent_name: str = "your_fabric_data_agent_name"
+    fabric_data_agent_user_instructions: str = "your_fabric_data_agent_user_instructions"
+
+    model_config = SettingsConfigDict(
+        env_file=".env",
+        env_ignore_empty=True,
+        extra="ignore",
+    )
+
+
+@lru_cache
+def get_fabric_data_agent_settings() -> Settings:
+    """Get Fabric Data Agent settings."""
+    return Settings()
+
+
+# FIXME: properly implement Fabric Data Agent client
+class FabricDataAgentWrapper:
+    def __init__(
+        self,
+        settings: Settings = None,
+    ):
+        if settings is None:
+            settings = get_fabric_data_agent_settings()
+        self.settings = settings
+
+    def search(self, query: str, k: int = 5) -> list[dict]:
+        """Search for similar documents in Fabric Data Agent."""
+        logger.info(f"Just returning mock results for query: {query}, k: {k}")
+        return [
+            {
+                "content": f"mock result #1 for {query}",
+                "id": str(uuid4()),
+            },
+            {
+                "content": f"mock result #2 for {query}",
+                "id": str(uuid4()),
+            },
+        ]
+
+
+class FabricDataAgentInput(BaseModel):
+    query: str = Field(
+        default="禅モード",
+        description="Query to search in the Fabric Data Agent",
+    )
+    k: int = Field(
+        default=5,
+        description="Number of results to return from the similarity search",
+    )
+
+
+class FabricDataAgentOutput(BaseModel):
+    content: str = Field(description="Content of the document")
+    id: str = Field(description="ID of the document")
+
+
+@tool(args_schema=FabricDataAgentInput)
+def search_fabric_data_agent(query: str, k: int = 5) -> list[FabricDataAgentOutput]:
+    """Search for similar documents in Fabric Data Agent.
+
+    Args:
+        query: The search query string
+        k: Number of results to return (default: 5)
+
+    Returns:
+        FabricDataAgentOutput: A Pydantic model containing the search results
+    """
+    # FIXME: do not create every time
+    wrapper = FabricDataAgentWrapper()
+    results = wrapper.search(query=query, k=k)
+    outputs = []
+    for result in results:
+        outputs.append(
+            FabricDataAgentOutput(
+                content=result["content"],
+                id=result["id"],
+            ),
+        )
+    return outputs