add: main.py

main.py

@@ -0,0 +1,101 @@
+import os
+import json
+import asyncio
+from rich.console import Console
+from langchain_openai import ChatOpenAI
+from langchain.tools import tool
+from deepagents import create_deep_agent
+from deepagents.backends import FilesystemBackend, LocalShellBackend, CompositeBackend
+from langgraph.checkpoint.memory import MemorySaver
+
+# --- LLM -------------------------------------------------------------------
+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 --------------------------------------------------------------
+backend = CompositeBackend([
+    LocalShellBackend(workspace_dir="./workspace"),
+    FilesystemBackend(),
+])
+
+# --- Tool ------------------------------------------------------------------
+@tool
+def get_weather(query: str) -> str:
+    """Return a fake weather report for a given city and date.
+    The argument is a JSON string with keys "city" and "date".
+    """
+    try:
+        data = json.loads(query)
+        city = data.get("city", "unknown")
+        date = data.get("date", "unknown")
+        return f"Weather in {city} on {date}: sunny, 25°C."
+    except Exception as e:
+        return f"Error parsing query: {e}"
+
+# --- Agent -----------------------------------------------------------------
+memory = MemorySaver()
+
+agent = create_deep_agent(
+    model=llm,
+    tools=[get_weather],
+    backend=backend,
+    system_prompt="You are a helpful weather assistant. Use the get_weather tool when asked about weather.",
+    checkpointer=memory,
+    interrupt_before=["tools"],  # pause before each tool call
+)
+
+console = Console()
+
+# ---------------------------------------------------------------------------
+async def ask_and_run(user_input, config):
+    """Run the agent with optional user input.
+    If user_input is None, the agent resumes from the paused state.
+    """
+    # Stream the agent's response
+    async for chunk in agent.stream(user_input, config=config, stream_mode=["messages", "updates"]):
+        state = agent.get_state(config)
+        chunk_type, chunk_data = chunk
+
+        if chunk_type == "messages":
+            # chunk_data can be a dict with 'content'
+            if isinstance(chunk_data, dict) and "content" in chunk_data:
+                console.print(chunk_data["content"], end="")
+            else:
+                console.print(chunk_data)
+        elif chunk_type == "updates":
+            console.print("\n[bold]Tool call:[/bold]", chunk_data)
+
+        # Detect pause before tool call
+        if "__interrupt__" in chunk_data and state.next == ("tools",):
+            # Retrieve the pending tool call
+            last_msg = state.values["messages"][-1]
+            tool_call = None
+            if hasattr(last_msg, "tool_calls") and last_msg.tool_calls:
+                tool_call = last_msg.tool_calls[0]
+            if tool_call:
+                tool_name = tool_call["name"]
+                tool_args = tool_call["args"]
+                console.print(f"\n[bold]Agent wants to call {tool_name}({tool_args})[/bold]")
+                answer = input("Разрешить? (Y/n): ")
+                if answer.lower().strip() == "y":
+                    await ask_and_run(None, config)  # resume
+                else:
+                    console.print("[red]Отменено[/red]")
+                    break
+
+# ---------------------------------------------------------------------------
+async def main():
+    console.print("\n[bold green]Weather Agent ready! Type 'exit' to quit.[/bold green]")
+    config = {"configurable": {"thread_id": "session-1"}}
+    while True:
+        user_input = input("\nВы: ")
+        if user_input.lower() == "exit":
+            break
+        await ask_and_run({"messages": [{"role": "human", "content": user_input}]}, config)
+
+if __name__ == "__main__":
+    asyncio.run(main())