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gen: (GPT-5) news summarizer agent で実装されている Scraper と Summarizer の抽象クラスを作成してリファクタしてください
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‎template_langgraph/agents/image_classifier_agent/classifiers.py‎

Lines changed: 1 addition & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -60,7 +60,7 @@ def predict(self, prompt: str, image: str, llm: Any) -> Result: # noqa: D401
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class LlmClassifier(BaseClassifier):
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"""LLM-backed classifier using the provided model's structured output capability."""
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63-
def predict(self, prompt: str, image: str, llm: BaseChatModel) -> Result: # noqa: D401
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def predict(self, prompt: str, image: str, llm: BaseChatModel):
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logger.info(f"Classifying image with LLM: {prompt}")
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return llm.with_structured_output(Result).invoke(
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input=[

‎template_langgraph/agents/news_summarizer_agent/agent.py‎

Lines changed: 14 additions & 54 deletions
Original file line numberDiff line numberDiff line change
@@ -8,6 +8,16 @@
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StructuredArticle,
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SummarizeWebContentState,
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)
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from template_langgraph.agents.news_summarizer_agent.scrapers import (
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BaseScraper,
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HttpxScraper,
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MockScraper,
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)
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from template_langgraph.agents.news_summarizer_agent.summarizers import (
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BaseSummarizer,
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LlmSummarizer,
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MockSummarizer,
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)
1121
from template_langgraph.llms.azure_openais import AzureOpenAiWrapper
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from template_langgraph.loggers import get_logger
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@@ -20,68 +30,18 @@ def notify(self, id: str, body: dict) -> None:
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logger.info(f"Notification sent for request {id}: {body}")
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2232

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class MockScraper:
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def scrape(self, url: str) -> str:
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"""Simulate scraping a web page."""
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return "<html><body><h1>Mocked web content</h1></body></html>"
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class HttpxScraper:
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def scrape(self, url: str) -> str:
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"""Retrieve the HTML content of a web page."""
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with httpx.Client() as client:
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response = client.get(url)
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response.raise_for_status()
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return response.text
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37-
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class MockSummarizer:
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def summarize(
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self,
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prompt: str,
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content: str,
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) -> StructuredArticle:
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"""Simulate summarizing the input."""
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return StructuredArticle(
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title="Mocked Title",
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date="2023-01-01",
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summary=f"Mocked summary of the content: {content}, prompt: {prompt}",
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keywords=["mock", "summary"],
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score=75,
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)
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53-
54-
class LlmSummarizer:
55-
def __init__(self, llm=AzureOpenAiWrapper().chat_model):
56-
self.llm = llm
57-
58-
def summarize(
59-
self,
60-
prompt: str,
61-
content: str,
62-
) -> StructuredArticle:
63-
"""Use the LLM to summarize the input."""
64-
logger.info(f"Summarizing input with LLM: {prompt}")
65-
return self.llm.with_structured_output(StructuredArticle).invoke(
66-
input=[
67-
{"role": "system", "content": prompt},
68-
{"role": "user", "content": content},
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]
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)
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72-
7333
class NewsSummarizerAgent:
7434
def __init__(
7535
self,
7636
llm=AzureOpenAiWrapper().chat_model,
7737
notifier=MockNotifier(),
78-
scraper=MockScraper(),
79-
summarizer=MockSummarizer(),
38+
scraper: BaseScraper = MockScraper(),
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summarizer: BaseSummarizer = MockSummarizer(),
8040
):
8141
self.llm = llm
8242
self.notifier = notifier
83-
self.scraper = scraper
84-
self.summarizer = summarizer
43+
self.scraper: BaseScraper = scraper
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self.summarizer: BaseSummarizer = summarizer
8545

8646
def create_graph(self):
8747
"""Create the main graph for the agent."""

‎template_langgraph/agents/news_summarizer_agent/scrapers.py‎

Lines changed: 62 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,62 @@
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"""Scraper interfaces and implementations for NewsSummarizerAgent.
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This module defines an abstract base scraper so different scraping strategies
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(mock, httpx-based, future headless browser, etc.) can be plugged into the agent
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without changing orchestration logic.
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"""
7+
8+
from __future__ import annotations
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10+
from abc import ABC, abstractmethod
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12+
import httpx
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from template_langgraph.loggers import get_logger
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logger = get_logger(__name__)
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18+
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class BaseScraper(ABC):
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"""Abstract base scraper.
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Implementations should raise exceptions outward only when they are truly
23+
unrecoverable; transient network issues should surface as httpx.RequestError
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so the caller can decide how to handle them.
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"""
26+
27+
@abstractmethod
28+
def scrape(self, url: str) -> str: # pragma: no cover - interface
29+
"""Retrieve raw textual/HTML content for the given URL.
30+
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Args:
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url: Target URL.
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Returns:
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str: Raw content (HTML / text).
35+
"""
36+
raise NotImplementedError
37+
38+
39+
class MockScraper(BaseScraper):
40+
"""Deterministic scraper for tests / offline development."""
41+
42+
def scrape(self, url: str) -> str: # noqa: D401
43+
logger.info(f"Mock scrape for URL: {url}")
44+
return "<html><body><h1>Mocked web content</h1></body></html>"
45+
46+
47+
class HttpxScraper(BaseScraper):
48+
"""Simple httpx based scraper."""
49+
50+
def scrape(self, url: str) -> str: # noqa: D401
51+
logger.info(f"Fetching URL via httpx: {url}")
52+
with httpx.Client() as client:
53+
response = client.get(url)
54+
response.raise_for_status()
55+
return response.text
56+
57+
58+
__all__ = [
59+
"BaseScraper",
60+
"MockScraper",
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"HttpxScraper",
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]

‎template_langgraph/agents/news_summarizer_agent/summarizers.py‎

Lines changed: 59 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -0,0 +1,59 @@
1+
"""Summarizer interfaces and implementations for NewsSummarizerAgent."""
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3+
from __future__ import annotations
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5+
from abc import ABC, abstractmethod
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from typing import Any
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8+
from langchain_core.language_models.chat_models import BaseChatModel
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10+
from template_langgraph.agents.news_summarizer_agent.models import StructuredArticle
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from template_langgraph.llms.azure_openais import AzureOpenAiWrapper
12+
from template_langgraph.loggers import get_logger
13+
14+
logger = get_logger(__name__)
15+
16+
17+
class BaseSummarizer(ABC):
18+
"""Abstract base summarizer returning a StructuredArticle."""
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20+
@abstractmethod
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def summarize(self, prompt: str, content: str) -> StructuredArticle: # pragma: no cover - interface
22+
"""Summarize raw content using a given prompt."""
23+
raise NotImplementedError
24+
25+
26+
class MockSummarizer(BaseSummarizer):
27+
"""Deterministic summarizer for tests / offline development."""
28+
29+
def summarize(self, prompt: str, content: str) -> StructuredArticle: # noqa: D401
30+
return StructuredArticle(
31+
title="Mocked Title",
32+
date="2023-01-01",
33+
summary=f"Mocked summary of the content: {content}, prompt: {prompt}",
34+
keywords=["mock", "summary"],
35+
score=75,
36+
)
37+
38+
39+
class LlmSummarizer(BaseSummarizer):
40+
"""LLM backed summarizer leveraging structured output."""
41+
42+
def __init__(self, llm: BaseChatModel | Any = AzureOpenAiWrapper().chat_model):
43+
self.llm = llm
44+
45+
def summarize(self, prompt: str, content: str) -> StructuredArticle: # noqa: D401
46+
logger.info(f"Summarizing input with LLM: {prompt}")
47+
return self.llm.with_structured_output(StructuredArticle).invoke(
48+
input=[
49+
{"role": "system", "content": prompt},
50+
{"role": "user", "content": content},
51+
]
52+
)
53+
54+
55+
__all__ = [
56+
"BaseSummarizer",
57+
"MockSummarizer",
58+
"LlmSummarizer",
59+
]

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