86 lines
2.8 KiB
Python
86 lines
2.8 KiB
Python
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 ------------------------------------------------------------
|
|
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_price(query: str) -> str:
|
|
"""Return a fake price table for a product in a city."""
|
|
# In a real task this would call an API or database
|
|
if "молоко" in query:
|
|
return "| Продукт | Цена (руб.) | Магазин |\n| Молоко | 89 | Магнит |"
|
|
if "хлеб" in query:
|
|
return "| Продукт | Цена (руб.) | Магазин |\n| Хлеб | 35 | Перекресток |"
|
|
return "No data found."
|
|
|
|
# --- Agent ----------------------------------------------------------
|
|
agent = create_deep_agent(
|
|
model=llm,
|
|
tools=[get_price],
|
|
backend=backend,
|
|
system_prompt="You are a helpful agent that can fetch product prices.",
|
|
)
|
|
|
|
# --- Stream handling -----------------------------------------------
|
|
async def main():
|
|
# Prepare the initial message
|
|
human_msg = HumanMessage(content="Какую цену у молока в Казани?")
|
|
|
|
# Start streaming
|
|
stream = agent.stream(
|
|
{"messages": [human_msg]},
|
|
stream_mode=["messages", "updates"],
|
|
)
|
|
|
|
step = 1
|
|
|
|
def format_chunk_message(chunk):
|
|
nonlocal 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
|
|
# If the message is a tool call, format it nicely
|
|
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))
|
|
|
|
print("\n--- Stream finished ---")
|
|
|
|
if __name__ == "__main__":
|
|
asyncio.run(main())
|