Update article_generator.py

article_generator.py

@@ -1,18 +1,62 @@
+import gradio as gr
+import requests
+from bs4 import BeautifulSoup
 from langchain.llms import OpenAI
+from langchain.chat_models import ChatOpenAI
 from langchain_experimental.plan_and_execute import PlanAndExecute, load_agent_executor, load_chat_planner
-import openai
-import os
-
-def generate_article(headline, api_key):
-    """見出しを基にしてLangchainのPlanAndExecuteモデルにより記事本文を生成する"""
-    openai.api_key = api_key
-    openai_llm = OpenAI(api_key=api_key)
-
-    # PlanAndExecuteの設定
-    agent_executor = load_agent_executor("simple", llm=openai_llm)
-    chat_planner = load_chat_planner("headline_to_article", llm=openai_llm)
-    plan_and_execute = PlanAndExecute(planner=chat_planner, executor=agent_executor)
-
-    # 記事生成
-    output = plan_and_execute.execute({"headline": headline})
-    return output["text"]
+from langchain.agents.tools import Tool
+
+# 環境変数からAPIキーを設定
+openai.api_key = os.getenv("OPENAI_API_KEY")
+tavily_api_key = os.getenv('TAVILY_API_KEY')
+
+class EnhancedTavilySearchTool:
+    def search(self, query):
+        params = {
+            'api_key': tavily_api_key,
+            'query': query,
+            'max_results': 10,
+            'detail_level': 'high'
+        }
+        response = requests.post('https://api.tavily.com/search', json=params)
+        if response.status_code == 200:
+            return response.json()['results']
+        else:
+            raise Exception("Failed to fetch data from Tavily API")
+
+def main(editable_output2, keyword_id):
+    tavily_search_tool = Tool(
+        name="TavilySearch",
+        func=EnhancedTavilySearchTool().search,
+        description="Enhanced search tool using Tavily API"
+    )
+
+    tools = [tavily_search_tool]
+
+    llm = ChatOpenAI(model_name="gpt-3.5-turbo-1106", temperature=0, max_tokens=1000)
+    planner = load_chat_planner(llm)
+    executor = load_agent_executor(llm, tools, verbose=True)
+    agent = PlanAndExecute(planner=planner, executor=executor, verbose=True)
+
+    soup = BeautifulSoup(editable_output2, 'html.parser')
+    h1_text = soup.find('h1').get_text()
+
+    # 実行と結果の取得
+    result = agent.run(f"Research about {h1_text}")
+    return result
+
+# Gradioインターフェースの設定
+with gr.Blocks() as app:
+    with gr.Column():
+        input_html = gr.Textbox(label="Editable HTML Output", placeholder="HTML content here...", lines=10)
+        keyword_id_input = gr.Textbox(label="Keyword ID", placeholder="Enter Keyword ID...")
+        generate_button = gr.Button("Generate")
+        output_article = gr.Textbox(label="Generated Article", lines=20, readonly=True)
+
+    generate_button.click(
+        fn=main,
+        inputs=[input_html, keyword_id_input],
+        outputs=output_article
+    )
+
+app.launch()