support dify tool

docs/index.md

@@ -1,13 +1,17 @@
 # template-langgraph
 
-## Operations
-
-see [test_all.sh](../scripts/test_all.sh) for all operations
+## Overview
 
 ```shell
-# Start Docker containers
+# Set up environment
 docker compose up -d
+```
+
+## Testing
 
+see [test_all.sh](../scripts/test_all.sh) for all operations
+
+```shell
 # Test all scripts
 bash scripts/test_all.sh
 ```

scripts/dify_operator.py

@@ -54,7 +54,7 @@ def run_workflow(
             ensure_ascii=False,
         )
     )
-    logger.info(f"Input: {response['data']['outputs']['requirements']}, Output: {response['data']['outputs']['text']}")
+    logger.info(f"Output: {response['data']['outputs']['text']}")
 
 
 if __name__ == "__main__":

scripts/qdrant_operator.py

@@ -6,7 +6,7 @@
 
 from template_langgraph.llms.azure_openais import AzureOpenAiWrapper
 from template_langgraph.loggers import get_logger
-from template_langgraph.tools.qdrants import QdrantClientWrapper
+from template_langgraph.tools.qdrant_tool import QdrantClientWrapper
 from template_langgraph.utilities.csv_loaders import CsvLoaderWrapper
 
 # Initialize the Typer application

scripts/test_all.sh

@@ -1,5 +1,11 @@
 #!/bin/bash
 
+# Stop on errors, undefined variables, and pipe failures
+set -euo pipefail
+
+# Run Docker Compose to set up the environment
+docker compose up -d --wait
+
 # Qdrant
 uv run python scripts/qdrant_operator.py --help
 uv run python scripts/qdrant_operator.py delete-collection --collection-name qa_kabuto --verbose
@@ -24,7 +30,7 @@ AGENT_NAMES=(
     "task_decomposer_agent"
 )
 for AGENT_NAME in "${AGENT_NAMES[@]}"; do
-    uv run python scripts/agent_runner.py png --name "$AGENT_NAME" --verbose --output "generated/${AGENT_NAME}.png"
+    uv run python scripts/agent_operator.py png --name "$AGENT_NAME" --verbose --output "generated/${AGENT_NAME}.png"
 done
 
 ## Run agents
@@ -38,5 +44,8 @@ NAME_QUESTION_ARRAY=(
 for NAME_QUESTION in "${NAME_QUESTION_ARRAY[@]}"; do
     IFS=':' read -r AGENT_NAME QUESTION <<< "$NAME_QUESTION"
     echo "Running agent: $AGENT_NAME with question: $QUESTION"
-    uv run python scripts/agent_runner.py run --name "$AGENT_NAME" --verbose --question "$QUESTION"
+    uv run python scripts/agent_operator.py run --name "$AGENT_NAME" --verbose --question "$QUESTION"
 done
+
+# Clean up Docker Compose environment
+docker compose down --remove-orphans

template_langgraph/agents/chat_with_tools_agent/agent.py

@@ -6,8 +6,9 @@
 from template_langgraph.agents.chat_with_tools_agent.models import AgentState
 from template_langgraph.llms.azure_openais import AzureOpenAiWrapper
 from template_langgraph.loggers import get_logger
+from template_langgraph.tools.dify_tool import run_dify_workflow
 from template_langgraph.tools.elasticsearch_tool import search_elasticsearch
-from template_langgraph.tools.qdrants import search_qdrant
+from template_langgraph.tools.qdrant_tool import search_qdrant
 
 logger = get_logger(__name__)
 
@@ -39,6 +40,11 @@ def __call__(self, inputs: dict):
 class ChatWithToolsAgent:
     def __init__(self):
         self.llm = AzureOpenAiWrapper().chat_model
+        self.tools = [
+            run_dify_workflow,
+            search_qdrant,
+            search_elasticsearch,
+        ]
 
     def create_graph(self):
         """Create the main graph for the agent."""
@@ -50,10 +56,7 @@ def create_graph(self):
         workflow.add_node(
             "tools",
             BasicToolNode(
-                tools=[
-                    search_qdrant,
-                    search_elasticsearch,
-                ]
+                tools=self.tools,
             ),
         )
 
@@ -78,10 +81,7 @@ def chat_with_tools(self, state: AgentState) -> AgentState:
         """Chat with tools using the state."""
         logger.info(f"Chatting with tools using state: {state}")
         llm_with_tools = self.llm.bind_tools(
-            tools=[
-                search_qdrant,
-                search_elasticsearch,
-            ],
+            tools=self.tools,
         )
         return {
             "messages": [

template_langgraph/agents/kabuto_helpdesk_agent/agent.py

@@ -2,8 +2,9 @@
 
 from template_langgraph.llms.azure_openais import AzureOpenAiWrapper
 from template_langgraph.loggers import get_logger
+from template_langgraph.tools.dify_tool import run_dify_workflow
 from template_langgraph.tools.elasticsearch_tool import search_elasticsearch
-from template_langgraph.tools.qdrants import search_qdrant
+from template_langgraph.tools.qdrant_tool import search_qdrant
 
 logger = get_logger(__name__)
 
@@ -13,6 +14,7 @@ def __init__(self, tools=None):
         if tools is None:
             # Default tool for searching Qdrant
             tools = [
+                run_dify_workflow,
                 search_qdrant,
                 search_elasticsearch,
                 # Add other tools as needed

template_langgraph/tools/dify_tool.py

@@ -1,6 +1,8 @@
 from functools import lru_cache
 
 import httpx
+from langchain.tools import tool
+from pydantic import BaseModel, Field
 from pydantic_settings import BaseSettings, SettingsConfigDict
 
 
@@ -48,3 +50,36 @@ def run_workflow(
             )
             response.raise_for_status()
             return response.json()
+
+
+class DifyWorkflowInput(BaseModel):
+    requirements: str = Field(
+        default="生成 AI のサービス概要を教えてください。日本語でお願いします",
+        description="Requirements for running the Dify workflow",
+    )
+
+
+class DifyWorkflowOutput(BaseModel):
+    response: dict = Field(description="Output data from the Dify workflow")
+
+
+@tool(args_schema=DifyWorkflowInput)
+def run_dify_workflow(
+    requirements: str = "生成 AI のサービス概要を教えてください。日本語でお願いします",
+) -> DifyWorkflowOutput:
+    """
+    Difyワークフローを実行します。
+    指定された入力パラメータでワークフローを実行し、結果を返します。
+    """
+    wrapper = DifyClientWrapper()
+    response = wrapper.run_workflow(
+        inputs={
+            "inputs": {
+                "requirements": requirements,
+            },
+            "response_mode": "blocking",
+            "user": "abc-123",
+        }
+    )
+
+    return DifyWorkflowOutput(response=response)