diff --git a/api/routes/tools.py b/api/routes/tools.py index d4e07cd..85ba2b9 100644 --- a/api/routes/tools.py +++ b/api/routes/tools.py @@ -1,7 +1,6 @@ """Utility and Tool API endpoints.""" import logging -from typing import Optional from fastapi import APIRouter, HTTPException, Query diff --git a/casts/blog_writer/modules/agents.py b/casts/blog_writer/modules/agents.py index 6c93e59..6c98b06 100644 --- a/casts/blog_writer/modules/agents.py +++ b/casts/blog_writer/modules/agents.py @@ -13,7 +13,6 @@ from typing import Optional from langchain.agents import create_agent -from langchain_core.language_models import BaseChatModel from .models import get_llm from .state import LLMProvider diff --git a/casts/blog_writer/modules/nodes.py b/casts/blog_writer/modules/nodes.py index f6ef5ac..9139ff3 100644 --- a/casts/blog_writer/modules/nodes.py +++ b/casts/blog_writer/modules/nodes.py @@ -13,6 +13,7 @@ import json import re +from typing import Any, Optional import markdown @@ -33,6 +34,50 @@ from casts.blog_writer.modules.tools import fetch_content, generate_image +def _extract_json(text: str) -> Optional[Any]: + """Extract JSON from LLM response text. + + Handles multiple formats: + 1. ```json ... ``` code blocks + 2. ``` ... ``` code blocks without language tag + 3. Raw JSON object {...} + 4. Raw JSON array [...] + """ + # Try code block with json tag + json_match = re.search(r"```json\s*([\s\S]*?)```", text) + if json_match: + try: + return json.loads(json_match.group(1).strip()) + except json.JSONDecodeError: + pass + + # Try code block without tag + json_match = re.search(r"```\s*([\s\S]*?)```", text) + if json_match: + try: + return json.loads(json_match.group(1).strip()) + except json.JSONDecodeError: + pass + + # Try to find raw JSON object + json_match = re.search(r"\{[\s\S]*\}", text) + if json_match: + try: + return json.loads(json_match.group(0)) + except json.JSONDecodeError: + pass + + # Try to find raw JSON array + json_match = re.search(r"\[[\s\S]*\]", text) + if json_match: + try: + return json.loads(json_match.group(0)) + except json.JSONDecodeError: + pass + + return None + + class FetchContent(AsyncBaseNode): """URL에서 웹 콘텐츠 수집 (BS4/Playwright).""" @@ -79,15 +124,8 @@ async def execute(self, state, config=None): self.log("컨텐츠 분석 중...") response = await llm.ainvoke(prompt) - try: - # Parse JSON from response - content = response.content - # Extract JSON from markdown code block if present - json_match = re.search(r"```(?:json)?\s*([\s\S]*?)```", content) - if json_match: - content = json_match.group(1) - analyzed_content = json.loads(content) - except json.JSONDecodeError: + analyzed_content = _extract_json(response.content) + if not analyzed_content: # Fallback structure analyzed_content = { "title": "Untitled", @@ -134,14 +172,13 @@ async def execute(self, state, config=None): self.log("키워드 추천 중...") response = await llm.ainvoke(prompt) - try: - content = response.content - json_match = re.search(r"```(?:json)?\s*([\s\S]*?)```", content) - if json_match: - content = json_match.group(1) - data = json.loads(content) + data = _extract_json(response.content) + if data and isinstance(data, dict) and "keywords" in data: suggested_keywords = data.get("keywords", [])[:30] - except json.JSONDecodeError: + elif data and isinstance(data, list): + # Handle case where LLM returns just an array + suggested_keywords = data[:30] + else: # Fallback: extract any quoted words suggested_keywords = re.findall(r'"([^"]+)"', response.content)[:30] @@ -226,13 +263,8 @@ async def execute(self, state, config=None): self.log("SEO 최적화 중...") response = await llm.ainvoke(prompt) - try: - content = response.content - json_match = re.search(r"```(?:json)?\s*([\s\S]*?)```", content) - if json_match: - content = json_match.group(1) - seo_meta = json.loads(content) - except json.JSONDecodeError: + seo_meta = _extract_json(response.content) + if not seo_meta: seo_meta = { "title": "Blog Post", "description": blog_markdown[:160], diff --git a/casts/blog_writer/modules/prompts.py b/casts/blog_writer/modules/prompts.py index 791cff7..93eb6e7 100644 --- a/casts/blog_writer/modules/prompts.py +++ b/casts/blog_writer/modules/prompts.py @@ -38,6 +38,7 @@ - SEO에 효과적인 키워드 - 검색량이 높을 것으로 예상되는 키워드 - 콘텐츠 주제와 밀접하게 관련된 키워드 +- 반드시 한글 키워드로 제안 (영문 브랜드명/기술명은 그대로 사용 가능) JSON 형식으로 키워드를 리스트로 반환하세요 (최대 30개): {{"keywords": ["키워드1", "키워드2", ...]}}""" diff --git a/casts/blog_writer/modules/tools.py b/casts/blog_writer/modules/tools.py index d5a8265..9127eba 100644 --- a/casts/blog_writer/modules/tools.py +++ b/casts/blog_writer/modules/tools.py @@ -60,8 +60,12 @@ async def fetch_with_playwright(url: str) -> str: await page.goto(url, wait_until="networkidle") - # Get main content - content = await page.content() + # Handle Naver blog iframe + if "blog.naver.com" in url: + content = await _extract_naver_blog_content(page) + else: + content = await page.content() + await browser.close() soup = BeautifulSoup(content, "html.parser") @@ -74,10 +78,36 @@ async def fetch_with_playwright(url: str) -> str: return "\n".join(lines) +async def _extract_naver_blog_content(page) -> str: + """Extract content from Naver blog iframe. + + Naver blogs load actual content inside an iframe. + """ + try: + # Wait for iframe to load + iframe_element = await page.wait_for_selector( + "iframe#mainFrame", timeout=10000 + ) + if iframe_element: + frame = await iframe_element.content_frame() + if frame: + # Wait for content to render inside iframe + await frame.wait_for_selector( + ".se-main-container, .post-view, #postViewArea", + timeout=10000, + ) + return await frame.content() + except Exception: + pass + + # Fallback to main page content + return await page.content() + + async def fetch_content( url: str, scraper_type: ScraperType = ScraperType.BEAUTIFULSOUP ) -> str: - """Fetch web content using configured scraper. + """Fetch web content using configured scraper with fallback support. Args: url: URL to fetch @@ -86,9 +116,35 @@ async def fetch_content( Returns: Extracted text content """ + # If explicitly requested Playwright, use it directly if scraper_type == ScraperType.PLAYWRIGHT: return await fetch_with_playwright(url) - return await fetch_with_beautifulsoup(url) + + # Try BeautifulSoup first + content = await fetch_with_beautifulsoup(url) + + # Fallback to Playwright if content seems insufficient + # (JS-rendered sites like Naver blog return minimal content with BS4) + if len(content) < 200 or _is_js_rendered_site(url): + try: + playwright_content = await fetch_with_playwright(url) + if len(playwright_content) > len(content): + return playwright_content + except Exception: + pass # Stick with BS4 content if Playwright fails + + return content + + +def _is_js_rendered_site(url: str) -> bool: + """Check if URL is known to require JavaScript rendering.""" + js_sites = [ + "blog.naver.com", + "m.blog.naver.com", + "post.naver.com", + "brunch.co.kr", + ] + return any(site in url for site in js_sites) # ============================================================================= diff --git a/casts/chat/modules/models.py b/casts/chat/modules/models.py index f040a5b..f73e7ef 100644 --- a/casts/chat/modules/models.py +++ b/casts/chat/modules/models.py @@ -12,7 +12,6 @@ - Embedding Models: https://docs.langchain.com/oss/python/integrations/text_embedding """ -from typing import Optional from langchain.chat_models import init_chat_model from langchain_core.language_models import BaseChatModel diff --git a/pyproject.toml b/pyproject.toml index a8be788..7d90ebe 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -14,6 +14,7 @@ dependencies = [ "langchain-openai>=1.1.6", "langgraph>=1.0.0", "markdown>=3.10", + "playwright>=1.58.0", "pydantic-settings>=2.1.0", "python-dotenv>=1.0.1", "uvicorn[standard]>=0.34.0", diff --git a/uv.lock b/uv.lock index 5158cd5..5455135 100644 --- a/uv.lock +++ b/uv.lock @@ -66,6 +66,7 @@ dependencies = [ { name = 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