Can someone share their experience on building a use case where you need the agent to be deployed on langGraph or on any server but you need the agent to access user’s local file system … is interupt the only option to achieve this ? is there a better to design such solution ?
I think what you are describing is similar to a user uploading a file from their machine (like a upload PDF or image file).
If your agent is deployed remotely, it cannot directly reach into the user’s local filesystem same security model as the web.
So the safest pattern is:
agent requests the file
interrupt triggers the UI / frontent
user selects or uploads the file
then continue the graph
In that context, yes, interrupts is the right tool.
You can also read the local file if you give a file name in a prompt
I have done it without a prompt..i.e I hardcoded the file path
here is the outline
Steps to enable a LangGraph agent to read local files:
- Define a File Reading Tool: Create a Python function that takes a file path as input and returns the content of the file. This function will serve as a tool for your LangGraph agent.
from pathlib import Path
def read_local_file(file_path: str) -> str:
"""Reads the content of a local file and returns it as a string."""
try:
with open(Path(file_path), 'r') as f:
content = f.read()
return content
except FileNotFoundError:
return f"Error: File not found at {file_path}"
except Exception as e:
return f"Error reading file: {e}"
When defining your LangGraph agent, include this read_local_file function as one of its available tools.
from langchain_core.tools import Tool
from langgraph.prebuilt import create_react_agent
# ... (define your LLM and other components)
file_reader_tool = Tool(
name="read_file",
func=read_local_file,
description="Reads the content of a local file given its path."
)
tools = [file_reader_tool, ...] # Include other tools as needed
agent_executor = create_react_agent(llm, tools=tools)