add: main.py

main.py

@@ -0,0 +1,81 @@
+import os
+import asyncio
+from langchain_openai import ChatOpenAI
+from langchain_core.messages import HumanMessage
+from langchain.tools import tool
+from deepagents import create_deep_agent
+from deepagents.backends import FilesystemBackend, LocalShellBackend, CompositeBackend
+import requests
+from bs4 import BeautifulSoup
+
+# LLM configuration – OpenRouter
+llm = ChatOpenAI(
+    model="openai/gpt-oss-20b:free",
+    base_url="https://openrouter.ai/api/v1",
+    api_key=os.getenv("OPENAI_API_KEY"),
+    temperature=0.0,
+)
+
+# Backend: virtual workspace + ability to export to real FS
+backend = CompositeBackend([
+    LocalShellBackend(workspace_dir="./workspace"),
+    FilesystemBackend(),
+])
+
+# ---------- Tools ----------
+@tool
+def search_web(query: str) -> str:
+    """Search the web using DuckDuckGo and return the first paragraph of the first result."""
+    try:
+        resp = requests.get(
+            "https://duckduckgo.com/html/",
+            params={"q": query},
+            timeout=10,
+        )
+        resp.raise_for_status()
+        soup = BeautifulSoup(resp.text, "html.parser")
+        results = soup.select("a.result__a")
+        if not results:
+            return "No results found."
+        first_link = results[0].get("href")
+        # fetch the linked page
+        page_resp = requests.get(first_link, timeout=10)
+        page_resp.raise_for_status()
+        page_soup = BeautifulSoup(page_resp.text, "html.parser")
+        # grab first paragraph
+        para = page_soup.find("p")
+        return para.get_text(strip=True) if para else "No paragraph found."
+    except Exception as e:
+        return f"Error during search: {e}"
+
+@tool
+def write_file(filename: str, content: str) -> str:
+    """Write content to a virtual file in the workspace."""
+    try:
+        backend.write_file(filename, content)
+        return f"File '{filename}' written successfully."
+    except Exception as e:
+        return f"Failed to write file: {e}"
+
+# ---------- Agent ----------
+agent = create_deep_agent(
+    model=llm,
+    tools=[search_web, write_file],
+    backend=backend,
+    system_prompt="You are a research assistant. Search the web, create virtual files, and finally export them to the real filesystem.",
+)
+
+async def main():
+    # Example task: gather information about "Python asyncio" and store in a file
+    user_prompt = "Collect a concise summary about Python asyncio and save it to summary.txt"
+    result = await agent.ainvoke(
+        {"messages": [HumanMessage(content=user_prompt)]},
+        {"configurable": {"thread_id": "session-1"}},
+    )
+    print("Agent finished.")
+    # Export virtual workspace to real filesystem
+    backend.export("./exported_workspace")
+    print("Exported virtual files to ./exported_workspace")
+
+if __name__ == "__main__":
+    asyncio.run(main())