{"id":50913,"date":"2024-09-10T00:00:00","date_gmt":"2024-09-10T07:00:00","guid":{"rendered":"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/%e6%9c%aa%e5%88%86%e9%a1%9e\/interact-with-griddb-data-using-a-langchain-chatbot\/"},"modified":"2025-11-14T07:56:52","modified_gmt":"2025-11-14T15:56:52","slug":"interact-with-griddb-data-using-a-langchain-chatbot","status":"publish","type":"post","link":"https:\/\/griddb-linux-hte8hndjf8cka8ht.westus-01.azurewebsites.net\/ja\/%e6%9c%aa%e5%88%86%e9%a1%9e\/interact-with-griddb-data-using-a-langchain-chatbot\/","title":{"rendered":"LangChain\u30c1\u30e3\u30c3\u30c8\u30dc\u30c3\u30c8\u3092\u4f7f\u7528\u3057\u3066GridDB\u30c7\u30fc\u30bf\u3068\u3084\u308a\u3068\u308a\u3059\u308b"},"content":{"rendered":"

\u3053\u306e\u8a18\u4e8b\u3067\u306f\u3001GridDB\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u304b\u3089\u81ea\u7136\u8a00\u8a9e\u30af\u30a8\u30ea\u3092\u4f7f\u7528\u3057\u3066\u60c5\u5831\u3092\u53d6\u5f97\u3059\u308bLangChain\u30c1\u30e3\u30c3\u30c8\u30dc\u30c3\u30c8\u306e\u4f5c\u6210\u65b9\u6cd5\u3092\u8aac\u660e\u3057\u307e\u3059\u3002Python\u306eLangChain\u30e9\u30a4\u30d6\u30e9\u30ea<\/a>\u3068OpenAI GPT-4o<\/a> LLM(\u5927\u898f\u6a21\u8a00\u8a9e\u30e2\u30c7\u30eb)\u3092\u4f7f\u7528\u3057\u3066\u3001\u81ea\u7136\u8a00\u8a9e\u30af\u30a8\u30ea\u3092GridDB\u30af\u30a8\u30ea\u306b\u5909\u63db\u3057\u3001\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u3068\u30b7\u30fc\u30e0\u30ec\u30b9\u306b\u3084\u308a\u3068\u308a\u3057\u307e\u3059\u3002<\/p>\n

\u30bd\u30fc\u30b9\u30b3\u30fc\u30c9\u304a\u3088\u3073Jupyter Notebook<\/h2>\n

\u30bd\u30fc\u30b9\u30b3\u30fc\u30c9(Jupyter Notebook)\u306f\u3001GitHub\u306e\u30ea\u30dd\u30b8\u30c8\u30ea\u304b\u3089\u5165\u624b\u3067\u304d\u307e\u3059\u3002<\/p>\n

\n
$ git clone https:\/\/github.com\/griddbnet\/Blogs.git --branch chatbot<\/code><\/pre>\n<\/div>\n
\u524d\u63d0\u6761\u4ef6<\/h2>\n
\u3053\u306e\u8a18\u4e8b\u306e\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3059\u308b\u306b\u306f\u3001\u4ee5\u4e0b\u306e\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002 1. GridDB C Client 2. GridDB Python client<\/p>\n
GridDB Python Package Index (Pypi)<\/a> \u30da\u30fc\u30b8\u306e\u624b\u9806\u306b\u5f93\u3063\u3066\u3001\u3053\u308c\u3089\u306e\u30af\u30e9\u30a4\u30a2\u30f3\u30c8\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u307e\u3059\u3002<\/p>\n
\u307e\u305f\u3001LangChain\u3001Numpy\u3001Pandas\u3001Seaborn \u30e9\u30a4\u30d6\u30e9\u30ea\u3082\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n
\u4ee5\u4e0b\u306e\u30b9\u30af\u30ea\u30d7\u30c8\u306f\u3001\u3053\u306e\u30d6\u30ed\u30b0\u306e\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u3059\u308b\u305f\u3081\u306b\u5fc5\u8981\u306a\u30e9\u30a4\u30d6\u30e9\u30ea\u3092\u30a4\u30f3\u30b9\u30c8\u30fc\u30eb\u3057\u3001\u30a4\u30f3\u30dd\u30fc\u30c8\u3057\u307e\u3059\u3002<\/p>\n
\n
!pip install langchain\n!pip install langchain-core\n!pip install langchain-openai\n!pip install langchain-experimental\n!pip install tabulate<\/code><\/pre>\n<\/div>\n
\n
import griddb_python as griddb\nimport pandas as pd\nfrom langchain_openai import OpenAI\nfrom langchain_openai import ChatOpenAI\nfrom langchain_core.prompts import ChatPromptTemplate\nfrom langchain_core.pydantic_v1 import BaseModel, Field\nfrom langchain.agents.agent_types import AgentType\nfrom langchain_experimental.agents.agent_toolkits import create_pandas_dataframe_agent\nfrom langchain.memory import ConversationBufferMemory\nfrom langchain.chains import ConversationChain\nfrom typing import List, Dict<\/code><\/pre>\n<\/div>\n
GridDB\u3068\u306e\u63a5\u7d9a\u306e\u4f5c\u6210<\/h2>\n
LangChain\u30c1\u30e3\u30c3\u30c8\u30dc\u30c3\u30c8\u3067GridDB\u3068\u3084\u308a\u53d6\u308a\u3059\u308b\u306b\u306f\u3001GridDB\u30a4\u30f3\u30b9\u30bf\u30f3\u30b9\u3068\u306e\u63a5\u7d9a\u3092\u4f5c\u6210\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u305d\u306e\u305f\u3081\u306b\u306f\u3001get_instance()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u4f7f\u7528\u3057\u3066\u3001StoreFactory<\/code>\u30af\u30e9\u30b9\u306e\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u4f5c\u6210\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002\u6b21\u306b\u3001\u30d5\u30a1\u30af\u30bf\u30fc\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u306eget_store()<\/code>\u30e1\u30bd\u30c3\u30c9\u3092\u547c\u3073\u51fa\u3057\u3001\u30c7\u30fc\u30bf\u30d9\u30fc\u30b9\u306e\u30db\u30b9\u30c8\u540d\u3001\u30af\u30e9\u30b9\u30bf\u540d\u3001\u30e6\u30fc\u30b6\u30fc\u3001\u30d1\u30b9\u30ef\u30fc\u30c9\u306e\u30d1\u30e9\u30e1\u30fc\u30bf\u3092\u6e21\u3057\u307e\u3059\u3002<\/p>\n
\u6b21\u306e\u30b9\u30af\u30ea\u30d7\u30c8\u3067\u306f\u3001GridDB\u30a4\u30f3\u30b9\u30bf\u30f3\u30b9\u3068\u306e\u63a5\u7d9a\u3092\u884c\u3044\u3001\u30b3\u30f3\u30c6\u30ca\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u4f5c\u6210\u3059\u308b\u3053\u3068\u3067\u63a5\u7d9a\u304c\u6210\u529f\u3057\u305f\u304b\u3069\u3046\u304b\u3092\u30c6\u30b9\u30c8\u3057\u307e\u3059\u3002<\/p>\n
\n
factory = griddb.StoreFactory.get_instance()\n\nDB_HOST = \"127.0.0.1:10001\"\nDB_CLUSTER = \"myCluster\"\nDB_USER = \"admin\"\nDB_PASS = \"admin\"\n\ntry:\n    gridstore = factory.get_store(\n        notification_member = DB_HOST,\n        cluster_name = DB_CLUSTER,\n        username = DB_USER,\n        password = DB_PASS\n    )\n\n    container1 = gridstore.get_container(\"container1\")\n    if container1 == None:\n        print(\"Container does not exist\")\n    print(\"Successfully connected to GridDB\")\n\nexcept griddb.GSException as e:\n    for i in range(e.get_error_stack_size()):\n        print(\"[\", i, \"]\")\n        print(e.get_error_code(i))\n        print(e.get_location(i))\n        print(e.get_message(i))\n<\/code><\/pre>\n<\/div>\n
\u51fa\u529b:<\/strong><\/p>\n
\u30b3\u30f3\u30c6\u30ca\u304c\u5b58\u5728\u3057\u307e\u305b\u3093 GridDB\u306b\u6b63\u5e38\u306b\u63a5\u7d9a\u3057\u307e\u3057\u305f<\/p>\n
\u63a5\u7d9a\u306b\u6210\u529f\u3059\u308b\u3068\u3001\u4e0a\u8a18\u306e\u30e1\u30c3\u30bb\u30fc\u30b8\u304c\u8868\u793a\u3055\u308c\u307e\u3059\u3002\u63a5\u7d9a\u306b\u5931\u6557\u3057\u305f\u5834\u5408\u306f\u3001\u8a8d\u8a3c\u60c5\u5831\u3092\u78ba\u8a8d\u3057\u3066\u518d\u5ea6\u63a5\u7d9a\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n
GridDB\u3078\u306e\u30b5\u30f3\u30d7\u30eb\u30c7\u30fc\u30bf\u306e\u633f\u5165<\/h2>\n
GridDB\u30b3\u30f3\u30c6\u30ca\u304b\u3089\u60c5\u5831\u3092\u53d6\u5f97\u3059\u308b\u30c1\u30e3\u30c3\u30c8\u30dc\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002<\/p>\n
\u3053\u3053\u3067\u306f\u30011970\u5e74\u304b\u30892022\u5e74\u307e\u3067\u306e\u5404\u56fd\u306e\u4eba\u53e3\u7d71\u8a08\u60c5\u5831\u3092\u683c\u7d0d\u3057\u305fGridDB\u30b3\u30f3\u30c6\u30ca\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002\u3053\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u8a73\u7d30\u306b\u3064\u3044\u3066\u306f\u3001\u4ee5\u524d\u306e\u8a18\u4e8bworld population data analysis using GridDB<\/a>\u3092\u53c2\u7167\u3057\u3066\u304f\u3060\u3055\u3044\u3002<\/p>\n
\u307e\u305f\u3001Kaggle\u304b\u3089\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9<\/a>\u3059\u308b\u3053\u3068\u3082\u3067\u304d\u307e\u3059\u3002\u4ee5\u4e0b\u306e\u30b9\u30af\u30ea\u30d7\u30c8\u3067\u306f\u3001\u30c0\u30a6\u30f3\u30ed\u30fc\u30c9\u3057\u305f\u300cworld_population.csv\u300d\u3092Pandas DataFrame\u306b\u8aad\u307f\u8fbc\u3093\u3067\u3044\u307e\u3059\u3002<\/p>\n
\n
## Dataset link: https:\/\/www.kaggle.com\/datasets\/iamsouravbanerjee\/world-population-dataset\n\ndataset = pd.read_csv(r\"\/home\/mani\/GridDB Projects\/world_population.csv\")\nprint(dataset.shape)\ndataset.head()<\/code><\/pre>\n<\/div>\n
\u51fa\u529b:<\/strong><\/p>\n
\"\"<\/a><\/p>\n
\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u306f\u3001\u56fd\u5225\u4eba\u53e3\u3001\u9996\u90fd\u3001\u5927\u9678\u306a\u3069\u306e\u60c5\u5831\u304c\u542b\u307e\u308c\u3066\u3044\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/p>\n
\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u5217\u306b\u306f\u7279\u6b8a\u6587\u5b57\u304c\u542b\u307e\u308c\u3066\u3044\u307e\u3059\u304c\u3001GridDB\u3067\u306f\u5217\u540d\u306b\u7279\u6b8a\u6587\u5b57\u3092\u4f7f\u7528\u3067\u304d\u306a\u3044\u305f\u3081\u3001\u524a\u9664\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n
\n
dataset.columns = dataset.columns.str.replace('[^a-zA-Z0-9]', '_', regex=True)\ndataset.dtypes<\/code><\/pre>\n<\/div>\n
\u51fa\u529b:<\/strong><\/p>\n
\"\"<\/a><\/p>\n
\u6b21\u306b\u3001GridDB\u5bfe\u5fdc\u306e\u30ab\u30e9\u30e0\u30bf\u30a4\u30d7\u306bDataFrame\u306e\u30ab\u30e9\u30e0\u3092\u30de\u30c3\u30d4\u30f3\u30b0\u3057\u3066\u304b\u3089\u3001GridDB\u30b3\u30f3\u30c6\u30ca\u306b\u30c7\u30fc\u30bf\u3092\u633f\u5165\u3057\u307e\u3059\u3002<\/p>\n
\u6b21\u306e\u30b9\u30af\u30ea\u30d7\u30c8\u306f\u3001dataset<\/code> DataFrame\u306e\u30c7\u30fc\u30bf\u3092PopulationStats<\/code> GridDB\u30b3\u30f3\u30c6\u30ca\u306b\u633f\u5165\u3057\u307e\u3059\u3002<\/p>\n
\n
# see all GridDB data types: https:\/\/docs.griddb.net\/architecture\/data-model\/#data-type\n\ndef map_pandas_dtype_to_griddb(dtype):\n    if dtype == 'int64':\n        return griddb.Type.LONG\n    elif dtype == 'float64':\n        return griddb.Type.FLOAT\n    elif dtype == 'object':\n        return griddb.Type.STRING\n    # Add more column types if you want\n    else:\n        raise ValueError(f'Unsupported pandas type: {dtype}')\n\ncontainer_columns = []\nfor column_name, dtype in dataset.dtypes.items():\n    griddb_dtype = map_pandas_dtype_to_griddb(str(dtype))\n    container_columns.append([column_name, griddb_dtype])\n\ncontainer_info = griddb.ContainerInfo(\"PopulationStats\",\n                                      container_columns,\n                                      griddb.ContainerType.COLLECTION, True)\n\n\ntry:\n    cont = gridstore.put_container(container_info)\n    for index, row in dataset.iterrows():\n        cont.put(row.tolist())\n    print(\"All rows have been successfully stored in the GridDB container.\")\n\nexcept griddb.GSException as e:\n    for i in range(e.get_error_stack_size()):\n        print(\"[\", i, \"]\")\n        print(e.get_error_code(i))\n        print(e.get_location(i))\n        print(e.get_message(i))<\/code><\/pre>\n<\/div>\n
\u51fa\u529b:<\/strong><\/p>\n
\u3059\u3079\u3066\u306e\u884c\u304cGridDB\u30b3\u30f3\u30c6\u30ca\u306b\u6b63\u5e38\u306b\u683c\u7d0d\u3055\u308c\u307e\u3057\u305f\u3002<\/p>\n
\u30b5\u30f3\u30d7\u30eb\u30ec\u30b3\u30fc\u30c9\u3092\u542b\u3080GridDB\u30b3\u30f3\u30c6\u30ca\u3092\u4f5c\u6210\u3057\u305f\u306e\u3067\u3001\u30b5\u30f3\u30d7\u30eb\u30c7\u30fc\u30bf\u30b3\u30f3\u30c6\u30ca\u304b\u3089\u60c5\u5831\u3092\u53d6\u5f97\u3067\u304d\u308bLangChain\u30c1\u30e3\u30c3\u30c8\u30dc\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002<\/p>\n
GridDB\u30c7\u30fc\u30bf\u3068\u3084\u308a\u3068\u308a\u3059\u308bLangChain\u30c1\u30e3\u30c3\u30c8\u30dc\u30c3\u30c8\u306e\u4f5c\u6210<\/h2>\n
LangChain\u3067\u306f\u3001\u5e45\u5e83\u3044\u5927\u898f\u6a21\u8a00\u8a9e\u30e2\u30c7\u30eb(LLM)\u3092\u4f7f\u7528\u3057\u3066\u30c1\u30e3\u30c3\u30c8\u30dc\u30c3\u30c8\u3092\u4f5c\u6210\u3067\u304d\u307e\u3059\u3002\u4eca\u56de\u306f\u3001OpenAI\u306e\u6700\u65b0LLM\u3067\u3042\u308bGPT-4o<\/a>\u3092\u4f7f\u7528\u3057\u3066LangChain\u30c1\u30e3\u30c3\u30c8\u30dc\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u307e\u3059\u3002<\/p>\n
LangChain\u3067GPT-4o\u3092\u4f7f\u7528\u3059\u308b\u306b\u306f\u3001ChatOpenAI<\/code>\u30af\u30e9\u30b9\u306e\u30aa\u30d6\u30b8\u30a7\u30af\u30c8\u3092\u4f5c\u6210\u3057\u3001OpenAI API\u30ad\u30fc<\/a>\u3092\u6e21\u3059\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n
\n
OPENAI_API_KEY = \"YOUR_OPENAI_API_KEY\"\nllm = ChatOpenAI(api_key = OPENAI_API_KEY ,\n                 temperature = 0,\n                model_name = \"gpt-4o\")<\/code><\/pre>\n<\/div>\n
\u8868\u5f62\u5f0f\u30c7\u30fc\u30bf\u7528\u306e\u30c1\u30e3\u30c3\u30c8\u30dc\u30c3\u30c8\u3092\u4f5c\u6210\u3059\u308b\u969b\u306e\u30c7\u30d5\u30a9\u30eb\u30c8LangChain\u30c1\u30a7\u30fc\u30f3\u306e\u554f\u984c<\/h3>\n
\u524d\u56de\u306e\u8a18\u4e8b\u3067\u306f\u3001LangChain\u3092\u4f7f\u7528\u3057\u305fGridDB\u306eCRUD\u64cd\u4f5c<\/a>\u306e\u5b9f\u884c\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3057\u305f\u3002<\/p>\n
\u305d\u306e\u8a18\u4e8b\u3067\u4f7f\u7528\u3057\u305f\u30a2\u30d7\u30ed\u30fc\u30c1\u306f\u3001GridDB\u306e\u30b3\u30f3\u30c6\u30ca\u3068\u30ab\u30e9\u30e0\u306e\u6b63\u78ba\u306a\u540d\u524d\u304c\u65e2\u77e5\u306e\u5834\u5408\u306b\u3001\u81ea\u7136\u8a00\u8a9e\u3092\u4f7f\u7528\u3057\u3066GridDB\u3068\u3084\u308a\u53d6\u308a\u3059\u308b\u306e\u306b\u9069\u3057\u3066\u3044\u307e\u3059\u3002\u305d\u3046\u3067\u306a\u3044\u5834\u5408\u3001LLM\u306f\u4f5c\u6210\u3057\u305f\u30ab\u30e9\u30e0\u540d\u3092\u4f7f\u7528\u3057\u3066\u60c5\u5831\u3092\u53d6\u5f97\u3057\u3088\u3046\u3068\u3057\u307e\u3059\u3002<\/p>\n
\u4f8b\u3048\u3070\u3001\u6b21\u306e\u30bb\u30af\u30b7\u30e7\u30f3\u3067\u306f\u30012020\u5e74\u306e\u4eba\u53e3\u304c\u6700\u3082\u591a\u3044\u4e0a\u4f4d3\u30ab\u56fd\u306e\u540d\u524d\u3092\u53d6\u5f97\u3057\u3088\u3046\u3068\u3057\u307e\u3059\u3002<\/p>\n
\n
class SelectData(BaseModel):\n    container_name: str = Field(description=\"the container name from the user query\")\n    query:str = Field(description=\"natural language converted to SELECT query\")\n\nsystem_command = \"\"\"\nConvert user commands into SQL queries for Griddb.\n\"\"\"\n\nuser_prompt = ChatPromptTemplate.from_messages([\n    (\"system\", system_command),\n    (\"user\", \"{input}\")\n])\n\nselect_chain = user_prompt | llm.with_structured_output(SelectData)\n\ndef select_records(query):\n\n    select_data = select_chain.invoke(query)\n    container_name = select_data.container_name\n    select_query = select_data.query\n\n    print(select_query)\n\n    result_container = gridstore.get_container(container_name)\n    query = result_container.query(select_query)\n    rs = query.fetch()\n    result_data = rs.fetch_rows()\n    return result_data\n\n\nselect_records(\"From the PopulationStats container, return the top 3 countries with the highest population in 2020\")<\/code><\/pre>\n<\/div>\n
\u51fa\u529b:<\/strong><\/p>\n
\"\"<\/a><\/p>\n
\u4e0a\u8a18\u306e\u51fa\u529b\u304b\u3089\u3001LLM\u304c country<\/code>\u3001population<\/code>\u3001\u304a\u3088\u3073 year<\/code> \u5217\u304b\u3089\u60c5\u5831\u3092\u8fd4\u3059\u30af\u30a8\u30ea\u3092\u751f\u6210\u3057\u3066\u3044\u308b\u3053\u3068\u304c\u5206\u304b\u308a\u307e\u3059\u3002\u3057\u304b\u3057\u3001\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u3092\u898b\u308b\u3068\u3001year<\/code> \u5217\u306f\u5b58\u5728\u3057\u307e\u305b\u3093\u3002\u4ee3\u308f\u308a\u306b\u30012020\u5e74\u306e\u4eba\u53e3\u60c5\u5831\u306f 2020 Population<\/code> \u5217\u306b\u683c\u7d0d\u3055\u308c\u3066\u3044\u307e\u3059\u3002<\/p>\n
\u3053\u306e\u554f\u984c\u3092\u89e3\u6c7a\u3059\u308b\u306b\u306f\u3001LangChain\u30a8\u30fc\u30b8\u30a7\u30f3\u30c8\u3092\u4f7f\u7528\u3057\u307e\u3059\u3002<\/p>\n
\u8868\u5f62\u5f0f\u30c7\u30fc\u30bf\u3068\u3084\u308a\u3068\u308a\u3059\u308b\u305f\u3081\u306eLangChain\u30a8\u30fc\u30b8\u30a7\u30f3\u30c8<\/h3>\n
LangChain\u30a8\u30fc\u30b8\u30a7\u30f3\u30c8\u3092\u4f7f\u7528\u3059\u308b\u306b\u306f\u3001BaseModel<\/code>\u30af\u30e9\u30b9\u3068\u3001\u30e6\u30fc\u30b6\u30fc\u306e\u30af\u30a8\u30ea\u304b\u3089\u30b3\u30f3\u30c6\u30ca\u540d\u3068\u8ffd\u52a0\u306e\u30af\u30a8\u30ea\u60c5\u5831\u3092\u62bd\u51fa\u3059\u308bselect_chain<\/code>\u3092\u5b9a\u7fa9\u3057\u307e\u3059\u3002<\/p>\n
\n
class SelectData(BaseModel):\n    container_name: str = Field(description=\"the container name from the user query\")\n    natural_query:str = Field(description = \"user query string to retrieve additional information from result returned by the SELECT query\")\n\nsystem_command = \"\"\"\nConvert user commands into SQL queries for Griddb.\n\"\"\"\n\nuser_prompt = ChatPromptTemplate.from_messages([\n    (\"system\", system_command),\n    (\"user\", \"{input}\")\n])\n\nselect_chain = user_prompt | llm.with_structured_output(SelectData)\n<\/code><\/pre>\n<\/div>\n
\u6b21\u306b\u3001\u30e6\u30fc\u30b6\u30fc\u306e\u30af\u30a8\u30ea\u3092\u53d7\u3051\u53d6\u308a\u3001\u30b3\u30f3\u30c6\u30ca\u540d\u3068\u8ffd\u52a0\u306e\u30af\u30a8\u30ea\u3092\u53d6\u5f97\u3059\u308b\u305f\u3081\u306b select_chain<\/code> \u3092\u547c\u3073\u51fa\u3059 select_records()<\/code> \u95a2\u6570\u3092\u5b9a\u7fa9\u3057\u307e\u3059\u3002 select_records()<\/code> \u95a2\u6570\u306f\u3001Pandas DataFrame \u5185\u306e\u30b3\u30f3\u30c6\u30ca\u30c7\u30fc\u30bf\u3092\u53d6\u5f97\u3057\u307e\u3059\u3002<\/p>\n
\u6b21\u306e\u30b9\u30c6\u30c3\u30d7\u306f\u3001OpenAI\u306e create_pandas_dataframe_agent()<\/code> \u3092\u4f5c\u6210\u3057\u3001GridDB\u30a4\u30f3\u30b9\u30bf\u30f3\u30b9\u304b\u3089\u306e\u30b3\u30f3\u30c6\u30ca\u30c7\u30fc\u30bf\u3092\u542b\u3080DataFrame\u3092\u6e21\u3059\u3053\u3068\u3067\u3059\u3002<\/p>\n
\u8ffd\u52a0\u306e\u30af\u30a8\u30ea\u306f\u3001\u30a8\u30fc\u30b8\u30a7\u30f3\u30c8\u306e invoke()<\/code> \u30e1\u30bd\u30c3\u30c9\u306b\u6e21\u3055\u308c\u307e\u3059\u3002\u30a8\u30fc\u30b8\u30a7\u30f3\u30c8\u306f\u3001\u8ffd\u52a0\u306e\u30e6\u30fc\u30b6\u30fc\u30af\u30a8\u30ea\u306b\u57fa\u3065\u3044\u3066DataFrame\u304b\u3089\u60c5\u5831\u3092\u53d6\u5f97\u3057\u307e\u3059\u3002<\/p>\n
\n
def select_records(query):\n\n    select_data = select_chain.invoke(query)\n    container_name = select_data.container_name\n    select_query = f\"SELECT * FROM {container_name}\"\n    natural_query = select_data. natural_query\n\n    print(f\"Select query: {select_query}\")\n    print(f\"Additional query: {natural_query}\")\n\n    result_container = gridstore.get_container(container_name)\n    query = result_container.query(select_query)\n    rs = query.fetch()\n    result_data = rs.fetch_rows()\n\n    agent = create_pandas_dataframe_agent(\n            ChatOpenAI(\n                api_key = OPENAI_API_KEY,\n                temperature=0,\n                model=\"gpt-4o\"),\n                result_data,\n                verbose=True,\n                agent_type=AgentType.OPENAI_FUNCTIONS,\n                allow_dangerous_code = True\n            )\n\n    response = agent.invoke(f\"Return the following information: {natural_query}\")\n    return response\n<\/code><\/pre>\n<\/div>\n
\u6b21\u306e\u30af\u30a8\u30ea\u3092\u4f7f\u7528\u3057\u3066\u3001select_records<\/code> \u30e1\u30bd\u30c3\u30c9\u3092\u30c6\u30b9\u30c8\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002PopulationStats\u30b3\u30f3\u30c6\u30ca\u304b\u3089\u30012020\u5e74\u306e\u4eba\u53e3\u304c\u6700\u3082\u591a\u3044\u4e0a\u4f4d3\u30ab\u56fd\u3092\u8fd4\u3059<\/code>\u3002<\/p>\n
\n
select_records(\"From the PopulationStats container, return the top 3 countries with the highest population in 2020\")<\/code><\/pre>\n<\/div>\n
\u51fa\u529b:<\/strong><\/p>\n
\"\"<\/a><\/p>\n
\u51fa\u529b\u7d50\u679c\u304b\u3089\u3001SELECT \u30af\u30a8\u30ea\u304c PopulationStats<\/code> \u30b3\u30f3\u30c6\u30ca\u304b\u3089\u3059\u3079\u3066\u306e\u30ec\u30b3\u30fc\u30c9\u3092\u9078\u629e\u3057\u3001\u8ffd\u52a0\u306e\u30af\u30a8\u30ea\u304c 2020 \u5e74\u306e\u4eba\u53e3\u4e0a\u4f4d 3 \u30ab\u56fd<\/code> \u3092\u53d6\u5f97\u3059\u308b\u3053\u3068\u304c\u308f\u304b\u308a\u307e\u3059\u3002<\/p>\n
\u4e0a\u8a18\u306e\u51fa\u529b\u7d50\u679c\u304b\u3089\u308f\u304b\u308b\u3088\u3046\u306b\u3001\u30a8\u30fc\u30b8\u30a7\u30f3\u30c8\u306f\u5bfe\u5fdc\u3059\u308b result_data<\/code> DataFrame \u306b\u30a2\u30af\u30bb\u30b9\u3067\u304d\u3001\u5fc5\u8981\u306a\u60c5\u5831\u3092\u8fd4\u3059\u3053\u3068\u304c\u3067\u304d\u308b\u305f\u3081\u3001PopulationStats<\/code> \u30b3\u30f3\u30c6\u30ca\u306e\u30ab\u30e9\u30e0\u540d\u3092\u77e5\u308b\u3053\u3068\u304c\u3067\u304d\u307e\u3059\u3002<\/p>\n
GridDB\u30c7\u30fc\u30bf\u3092\u4f7f\u7528\u3057\u305fLangChain\u30c1\u30e3\u30c3\u30c8\u30dc\u30c3\u30c8\u306e\u5bfe\u8a71\u3092\u69cb\u7bc9<\/h3>\n
\u6b21\u306b\u3001\u524d\u56de\u306e\u5bfe\u8a71\u3092\u8a18\u61b6\u3067\u304d\u308b\u30c1\u30e3\u30c3\u30c8\u30dc\u30c3\u30c8\u3092\u4f5c\u6210\u3057\u3066\u307f\u307e\u3057\u3087\u3046\u3002<\/p>\n
\u524d\u56de\u306e\u30b9\u30af\u30ea\u30d7\u30c8\u306e\u3088\u3046\u306bselect_records<\/code>\u95a2\u6570\u3067\u30a8\u30fc\u30b8\u30a7\u30f3\u30c8\u3092\u7e70\u308a\u8fd4\u3057\u5b9a\u7fa9\u3059\u308b\u306e\u3067\u306f\u306a\u304f\u3001DataFrame\u3067\u30b3\u30f3\u30c6\u30ca\u60c5\u5831\u3092\u53d6\u5f97\u3057\u3001\u305d\u306eDataFrame\u3092\u30a8\u30fc\u30b8\u30a7\u30f3\u30c8\u30671\u56de\u3060\u3051\u4f7f\u7528\u3059\u308b\u3053\u3068\u3092\u304a\u52e7\u3081\u3057\u307e\u3059\u3002<\/p>\n
\u6b21\u306e\u30b9\u30af\u30ea\u30d7\u30c8\u3067\u306f\u3001SelectData<\/code> \u30d9\u30fc\u30b9\u30af\u30e9\u30b9\u3068\u3001\u30e6\u30fc\u30b6\u30fc\u30af\u30a8\u30ea\u304b\u3089\u30b3\u30f3\u30c6\u30ca\u540d\u3092\u53d6\u5f97\u3059\u308b select_records()<\/code> \u95a2\u6570\u3092\u5b9a\u7fa9\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n
\n
class SelectData(BaseModel):\n    container_name: str = Field(description=\"the container name from the user query\")\n    query:str = Field(description=\"natural language converted to SELECT query\")\n\n\n\nsystem_command = \"\"\"\nConvert user commands into SQL queries for Griddb.\n\"\"\"\n\nuser_prompt = ChatPromptTemplate.from_messages([\n    (\"system\", system_command),\n    (\"user\", \"{input}\")\n])\n\nselect_chain = user_prompt | llm.with_structured_output(SelectData)\n\ndef select_records(query):\n\n    select_data = select_chain.invoke(query)\n    container_name = select_data.container_name\n    select_query = select_data.query\n\n    result_container = gridstore.get_container(container_name)\n    query = result_container.query(select_query)\n    rs = query.fetch()\n    result_data = rs.fetch_rows()\n    return result_data\n\n\nresult_data = select_records(\"SELECT all records from PopulationStats container\")<\/code><\/pre>\n<\/div>\n
\u6b21\u306b\u3001\u30e6\u30fc\u30b6\u30fc\u306e\u30af\u30a8\u30ea\u3092\u53d7\u3051\u53d6\u308a\u3001create_pandas_dataframe_agent<\/code> \u30a8\u30fc\u30b8\u30a7\u30f3\u30c8\u3092\u4f7f\u7528\u3057\u3066 Pandas DataFrame \u306b\u95a2\u3059\u308b\u60c5\u5831\u3092\u8fd4\u3059 create_pandas_dataframe_agent<\/code> \u304a\u3088\u3073 get_response()<\/code> \u95a2\u6570\u3092\u5b9a\u7fa9\u3057\u307e\u3059\u3002<\/p>\n
\u30c1\u30e3\u30c3\u30c8\u30dc\u30c3\u30c8\u306e\u6a5f\u80fd\u3092\u5b9f\u88c5\u3059\u308b\u306b\u306f\u3001get_response()<\/code> \u95a2\u6570\u3092\u547c\u3073\u51fa\u3057\u7d9a\u3051\u3001\u30a8\u30fc\u30b8\u30a7\u30f3\u30c8\u306e\u5fdc\u7b54\u3092\u30b3\u30f3\u30bd\u30fc\u30eb\u306b\u8868\u793a\u3059\u308b while<\/code> \u30eb\u30fc\u30d7\u3092\u5b9f\u884c\u3059\u308b chat_with_agent()<\/code> \u95a2\u6570\u3092\u5b9a\u7fa9\u3057\u307e\u3059\u3002\u3053\u306e\u30eb\u30fc\u30d7\u306f\u3001\u30e6\u30fc\u30b6\u30fc\u304c\u300cbye, quit\u300d\u307e\u305f\u306f\u300cexit\u300d\u3068\u5165\u529b\u3059\u308b\u3068\u7d42\u4e86\u3057\u307e\u3059\u3002<\/p>\n
\n
agent = create_pandas_dataframe_agent(\n    ChatOpenAI(\n        api_key=OPENAI_API_KEY,\n        temperature=0,\n        model=\"gpt-4\"\n    ),\n    result_data,\n    agent_type=AgentType.OPENAI_FUNCTIONS,\n    allow_dangerous_code=True,\n)\n\n\n\ndef get_response(natural_query):\n    # Create a conversation chain\n\n\n    # Get the response from the agent\n    response = agent.invoke(f\"Return the following information: {natural_query}\")\n\n    # Add the interaction to the conversation memory\n    return response\n\n\n# Function to chat with the agent\ndef chat_with_agent():\n    while True:\n        user_input = input(\"You: \")\n        if user_input.lower() in ['exit', 'quit', 'bye']:\n            print(\"AI: Goodbye!\")\n            break\n\n        response = get_response(user_input)\n        print(f\"AI: {response['output']}\")\n\nchat_with_agent()<\/code><\/pre>\n<\/div>\n
\u51fa\u529b:<\/strong><\/p>\n
\"\"<\/a><\/p>\n
\u4e0a\u8a18\u306e\u51fa\u529b\u304b\u3089\u3001GridDB\u30b3\u30f3\u30c6\u30ca\u304b\u3089\u4e16\u754c\u4eba\u53e3\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306b\u95a2\u3059\u308b\u56de\u7b54\u3092\u53d6\u5f97\u3059\u308b\u30c1\u30e3\u30c3\u30c8\u30dc\u30c3\u30c8\u306e\u3088\u3046\u306a\u6a5f\u80fd\u3092\u78ba\u8a8d\u3067\u304d\u307e\u3059\u3002<\/p>\n
\u307e\u3068\u3081<\/p>\n
\u672c\u8a18\u4e8b\u3067\u306f\u3001\u81ea\u7136\u8a00\u8a9e\u30af\u30a8\u30ea\u3092\u4f7f\u7528\u3057\u3066GridDB\u30c7\u30fc\u30bf\u3068\u5bfe\u8a71\u3059\u308bLangChain\u30c1\u30e3\u30c3\u30c8\u30dc\u30c3\u30c8\u306e\u4f5c\u6210\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3057\u305f\u3002Python\u3068GridDB\u306e\u63a5\u7d9a\u65b9\u6cd5\u3001GridDB\u30b3\u30f3\u30c6\u30ca\u3078\u306e\u30b5\u30f3\u30d7\u30eb\u30c7\u30fc\u30bf\u306e\u633f\u5165\u65b9\u6cd5\u3001LangChain\u30a8\u30fc\u30b8\u30a7\u30f3\u30c8\u3092\u4f7f\u7528\u3057\u305f\u60c5\u5831\u53d6\u5f97\u65b9\u6cd5\u306b\u3064\u3044\u3066\u8aac\u660e\u3057\u307e\u3057\u305f\u3002\u307e\u305f\u3001LangChain\u30a8\u30fc\u30b8\u30a7\u30f3\u30c8\u3092\u4f7f\u7528\u3057\u305f\u30c1\u30e3\u30c3\u30c8\u30dc\u30c3\u30c8\u306e\u4f5c\u6210\u65b9\u6cd5\u306b\u3064\u3044\u3066\u3082\u8aac\u660e\u3057\u307e\u3057\u305f\u3002<\/p>\n
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