From 85bdc8bcec2b2f2a5213743f2c8e0fdc6dad745c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=D0=98=D0=BB=D1=8C=D1=8F=205f1b81b8-4f5d-11e8-9c2d-fa7ae01?=
 =?UTF-8?q?bbebc?= <gurevich1104@mail.ru>
Date: Tue, 30 Jun 2026 16:06:53 +0000
Subject: [PATCH] add: main.py

---
 main.py | 96 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 96 insertions(+)
 create mode 100644 main.py

diff --git a/main.py b/main.py
new file mode 100644
index 0000000..cb20fb6
--- /dev/null
+++ b/main.py
@@ -0,0 +1,96 @@
+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
+
+# --- LLM и backend -----------------------------------------------------------
+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 = CompositeBackend([
+    LocalShellBackend(workspace_dir="./workspace"),
+    FilesystemBackend(),
+])
+
+# --- Tool with sub‑agent -----------------------------------------------------
+@tool
+def get_price(query: str) -> str:
+    """Return a fake price table for a product in a city.
+    Internally a sub‑agent is used to generate the answer.
+    """
+    # Создаём суб‑агента, который просто отвечает на запрос
+    sub_agent = create_deep_agent(
+        model=llm,
+        tools=[],
+        backend=backend,
+        system_prompt="You are a price lookup assistant.",
+    )
+    # Запускаем суб‑агента в отдельном цикле событий
+    loop = asyncio.new_event_loop()
+    asyncio.set_event_loop(loop)
+    try:
+        result = loop.run_until_complete(
+            sub_agent.ainvoke(
+                {"messages": [HumanMessage(content=f"Provide price for {query}")]},
+                {"configurable": {"thread_id": f"price-{query}"}},
+            )
+        )
+    finally:
+        loop.close()
+    return result["messages"][-1].content
+
+# --- Главный агент ----------------------------------------------------------
+agent = create_deep_agent(
+    model=llm,
+    tools=[get_price],
+    backend=backend,
+    system_prompt="You are a helpful agent. Use tools when necessary.",
+)
+
+# --- Stream ----------------------------------------------
+stream = agent.stream(
+    {
+        "messages": [HumanMessage(content="What is the price of milk in Kazan?")],
+    },
+    stream_mode=["messages", "updates"],
+)
+
+# --- Handlers ------------------------------------------
+step = 1
+
+def format_chunk_message(chunk):
+    global step
+    message, meta = chunk
+    if meta.get("langgraph_step") != step:
+        step = meta.get("langgraph_step")
+        print("\n--- --- ---\n")
+    if message.content:
+        print(message.content, end="", flush=True)
+
+
+def format_message(message):
+    if message.content:
+        return message.content
+    # tool call representation
+    if message.tool_calls:
+        call = message.tool_calls[0]
+        return f"{call['name']}({call['args']})"
+    return ""
+
+for chunk in stream:
+    chunk_type, chunk_data = chunk
+    if chunk_type == "messages":
+        format_chunk_message(chunk_data)
+    elif chunk_type == "updates":
+        if chunk_data.get("model"):
+            last_msg = chunk_data["model"]["messages"][-1]
+            print(format_message(last_msg), end="", flush=True)
+
+# --- End of script ----------------------------------------------------------