Merge pull request #79 from ks6088ts-labs/feature/issue-78_internals

add internals library and slack notifier

Author: ks6088ts

.env.template

@@ -51,7 +51,7 @@ AI_SEARCH_KEY="xxx"
 AI_SEARCH_INDEX_NAME="kabuto"
 
 # ---------
-# Utilities
+# Internals
 # ---------
 
 ## CSV Loader Settings
@@ -63,3 +63,13 @@ PDF_LOADER_DATA_DIR_PATH="./data"
 ## OpenTelemetry Settings
 OTEL_SERVICE_NAME="template-langgraph"
 OTEL_COLLECTOR_ENDPOINT="http://localhost:4317"
+
+## Scraper Settings
+SCRAPER_TYPE="mock" # Options: "mock", "httpx", "youtube_transcript"
+
+## Summarizer Settings
+SUMMARIZER_TYPE="mock" # Options: "mock", "llm"
+
+## Notifier Settings
+NOTIFIER_TYPE="mock" # Options: "mock", "slack"
+NOTIFIER_SLACK_WEBHOOK_URL="https://hooks.slack.com/services/xxx"

docs/index.ja.md

@@ -130,7 +130,7 @@ Pydantic モデルを使用して AI 応答から構造化データを取得す
 
 - **`template_langgraph/llms/`** - LLM API ラッパー（Azure OpenAI など）
 - **`template_langgraph/tools/`** - 検索、データ取得用ツール実装
-- **`template_langgraph/utilities/`** - ドキュメント読み込みと処理用ヘルパー関数
+- **`template_langgraph/internals/`** - 内部ユーティリティとヘルパー関数（CSV/PDF ローダー、Otel ラッパーなど）
 
 ## サンプルコードの実行
 

docs/index.md

@@ -130,7 +130,7 @@ Implements the supervisor pattern where one agent coordinates multiple specializ
 
 - **`template_langgraph/llms/`** - LLM API wrappers (Azure OpenAI, etc.)
 - **`template_langgraph/tools/`** - Tool implementations for search, data retrieval
-- **`template_langgraph/utilities/`** - Helper functions for document loading and processing
+- **`template_langgraph/internals/`** - Internal utilities and helper functions (CSV/PDF loaders, Otel wrappers, etc.)
 
 ## Running the Examples
 

scripts/agent_operator.py

@@ -9,23 +9,12 @@
 from template_langgraph.agents.image_classifier_agent.models import Results
 from template_langgraph.agents.issue_formatter_agent.agent import graph as issue_formatter_agent_graph
 from template_langgraph.agents.kabuto_helpdesk_agent.agent import graph as kabuto_helpdesk_agent_graph
-from template_langgraph.agents.news_summarizer_agent.agent import MockNotifier, NewsSummarizerAgent
-from template_langgraph.agents.news_summarizer_agent.agent import (
-    graph as news_summarizer_agent_graph,
-)
+from template_langgraph.agents.news_summarizer_agent.agent import graph as news_summarizer_agent_graph
 from template_langgraph.agents.news_summarizer_agent.models import (
     AgentInputState,
     AgentState,
     Article,
 )
-from template_langgraph.agents.news_summarizer_agent.scrapers import (
-    BaseScraper,
-    HttpxScraper,
-    YouTubeTranscriptScraper,
-)
-from template_langgraph.agents.news_summarizer_agent.summarizers import (
-    LlmSummarizer,
-)
 from template_langgraph.agents.task_decomposer_agent.agent import graph as task_decomposer_agent_graph
 from template_langgraph.loggers import get_logger
 
@@ -56,18 +45,6 @@ def get_agent_graph(name: str):
         raise ValueError(f"Unknown agent name: {name}")
 
 
-def get_scraper(scraper_type: str) -> BaseScraper:
-    scraper = None
-    if scraper_type == "Httpx":
-        scraper = HttpxScraper()
-    elif scraper_type == "YouTubeTranscript":
-        scraper = YouTubeTranscriptScraper()
-
-    if not scraper:
-        raise ValueError(f"Unknown scraper type: {scraper_type}")
-    return scraper
-
-
 @app.command()
 def png(
     name: str = typer.Option(
@@ -159,12 +136,6 @@ def news_summarizer_agent(
         "-u",
         help="Comma-separated list of URLs to summarize",
     ),
-    scraper: str = typer.Option(
-        "Httpx",  # YouTubeTranscript
-        "--scraper",
-        "-s",
-        help="Scraper to use for fetching content",
-    ),
     verbose: bool = typer.Option(
         False,
         "--verbose",
@@ -176,11 +147,7 @@ def news_summarizer_agent(
     if verbose:
         logger.setLevel(logging.DEBUG)
 
-    graph = NewsSummarizerAgent(
-        notifier=MockNotifier(),
-        scraper=get_scraper(scraper),
-        summarizer=LlmSummarizer(),
-    ).create_graph()
+    graph = news_summarizer_agent_graph
     for event in graph.stream(
         input=AgentState(
             input=AgentInputState(

scripts/ai_search_operator.py

@@ -3,10 +3,10 @@
 import typer
 from dotenv import load_dotenv
 
+from template_langgraph.internals.csv_loaders import CsvLoaderWrapper
+from template_langgraph.internals.pdf_loaders import PdfLoaderWrapper
 from template_langgraph.loggers import get_logger
 from template_langgraph.tools.ai_search_tool import AiSearchClientWrapper
-from template_langgraph.utilities.csv_loaders import CsvLoaderWrapper
-from template_langgraph.utilities.pdf_loaders import PdfLoaderWrapper
 
 # Initialize the Typer application
 app = typer.Typer(

scripts/cosmosdb_operator.py

@@ -3,10 +3,10 @@
 import typer
 from dotenv import load_dotenv
 
+from template_langgraph.internals.csv_loaders import CsvLoaderWrapper
+from template_langgraph.internals.pdf_loaders import PdfLoaderWrapper
 from template_langgraph.loggers import get_logger
 from template_langgraph.tools.cosmosdb_tool import CosmosdbClientWrapper
-from template_langgraph.utilities.csv_loaders import CsvLoaderWrapper
-from template_langgraph.utilities.pdf_loaders import PdfLoaderWrapper
 
 # Initialize the Typer application
 app = typer.Typer(

scripts/elasticsearch_operator.py

@@ -3,9 +3,9 @@
 import typer
 from dotenv import load_dotenv
 
+from template_langgraph.internals.pdf_loaders import PdfLoaderWrapper
 from template_langgraph.loggers import get_logger
 from template_langgraph.tools.elasticsearch_tool import ElasticsearchClientWrapper
-from template_langgraph.utilities.pdf_loaders import PdfLoaderWrapper
 
 # Initialize the Typer application
 app = typer.Typer(

scripts/otel_operator.py

@@ -4,8 +4,8 @@
 import typer
 from dotenv import load_dotenv
 
+from template_langgraph.internals.otel_helpers import OtelWrapper
 from template_langgraph.loggers import get_logger
-from template_langgraph.utilities.otel_helpers import OtelWrapper
 
 # Initialize the Typer application
 app = typer.Typer(

scripts/qdrant_operator.py

@@ -4,10 +4,10 @@
 from dotenv import load_dotenv
 from qdrant_client.models import PointStruct
 
+from template_langgraph.internals.csv_loaders import CsvLoaderWrapper
 from template_langgraph.llms.azure_openais import AzureOpenAiWrapper
 from template_langgraph.loggers import get_logger
 from template_langgraph.tools.qdrant_tool import QdrantClientWrapper
-from template_langgraph.utilities.csv_loaders import CsvLoaderWrapper
 
 # Initialize the Typer application
 app = typer.Typer(

template_langgraph/agents/news_summarizer_agent/agent.py

@@ -8,40 +8,27 @@
     StructuredArticle,
     SummarizeWebContentState,
 )
-from template_langgraph.agents.news_summarizer_agent.scrapers import (
-    BaseScraper,
-    HttpxScraper,
-    MockScraper,
-)
-from template_langgraph.agents.news_summarizer_agent.summarizers import (
-    BaseSummarizer,
-    LlmSummarizer,
-    MockSummarizer,
-)
+from template_langgraph.internals.notifiers import get_notifier
+from template_langgraph.internals.scrapers import get_scraper
+from template_langgraph.internals.summarizers import get_summarizer
 from template_langgraph.llms.azure_openais import AzureOpenAiWrapper
 from template_langgraph.loggers import get_logger
 
 logger = get_logger(__name__)
 
 
-class MockNotifier:
-    def notify(self, id: str, body: dict) -> None:
-        """Simulate sending a notification to the user."""
-        logger.info(f"Notification sent for request {id}: {body}")
-
-
 class NewsSummarizerAgent:
     def __init__(
         self,
         llm=AzureOpenAiWrapper().chat_model,
-        notifier=MockNotifier(),
-        scraper: BaseScraper = MockScraper(),
-        summarizer: BaseSummarizer = MockSummarizer(),
+        notifier=get_notifier(),
+        scraper=get_scraper(),
+        summarizer=get_summarizer(),
     ):
         self.llm = llm
         self.notifier = notifier
-        self.scraper: BaseScraper = scraper
-        self.summarizer: BaseSummarizer = summarizer
+        self.scraper = scraper
+        self.summarizer = summarizer
 
     def create_graph(self):
         """Create the main graph for the agent."""
@@ -127,23 +114,20 @@ def summarize_web_content(self, state: SummarizeWebContentState):
     def notify(self, state: AgentState) -> AgentState:
         """Send notifications to the user."""
         logger.info(f"Sending notifications with state: {state}")
-        # Simulate sending notifications
-        # convert list of articles to a dictionary for notification
         summary = {}
         for i, article in enumerate(state.articles):
-            summary[i] = article.model_dump()
+            summary[i] = {
+                "url": article.url,
+                "structured_article": article.structured_article.model_dump(),
+            }
         self.notifier.notify(
-            id=state.input.id,
-            body=summary,
+            text=summary.__str__(),
         )
         return state
 
 
-# For testing
-# graph = NewsSummarizerAgent().create_graph()
-
 graph = NewsSummarizerAgent(
-    notifier=MockNotifier(),
-    scraper=HttpxScraper(),
-    summarizer=LlmSummarizer(),
+    notifier=get_notifier(),
+    scraper=get_scraper(),
+    summarizer=get_summarizer(),
 ).create_graph()