We're a healthcare company with strict HIPAA requirements. We've been running traditional ML models in production for years, deployed via Seldon Core on-prem. The audit trail is solid: we know who deployed what model, what data was used, and what predictions were made.

Now we're exploring agentic AI for clinical decision support. The problem is auditability. An agent doesn't just make a single prediction. It reasons, calls multiple tools, iterates, and produces a final output. Compliance wants to know every step: which agent made which decision, what tools were called, what LLM was used, and what data was accessed.

Most agentic platforms are SaaS-first and don't support on-prem deployment. Even the ones that do have weak auditing compared to what we're used to with Seldon. We need a solution that can run in our air-gapped environment, meets HIPAA requirements, and gives us a complete audit trail across the entire agentic workflow. Is anyone else navigating this? What's working?

hi,
i'm shan from India. I'm learning Langchain. Since I'm a total noob in python and langchain i'm not able to test my tools in jupyter notebook one by one.

Actually, i'm trying a simple get_weather agent. but i couldn't run the tool before running the llm for testing. Kindly, help me.

Here is my coe:

get_weather.invoke({"location":"beijing"})

get_weather.invoke({"location":"beijing"})

get_weather.invoke({"location":"beijing"})

get_weather.invoke({"location":"beijing"})

get_weather.invoke({"location":"beijing"})

get_weather.invoke({"location":"beijing"})

get_weather.invoke({"location":"beijing"})

get_weather.invoke({"location":"beijing"})

import os
import json
from dotenv import load_dotenv, find_dotenv
from langchain_deepseek import ChatDeepSeek


from urllib.parse import quote
from httpx import request

def get_weather(location:str)->str:
    """
    this is used to get the weather of a city anywhere in the world. 


    Args:
        location (str): specify the location to get its weather. eg) 'New York', 'Beijing', 'New Delhi' e.tc 


    Returns:
        return a string that explains that city's weather in celsius, fareheight and how the weather is.
    """
    key=os.environ.get("WEATHER_API_KEY")
    url="https://api.weatherapi.com/v1/current.json?q={location}&key={key}"
    encoded_url=quote(url)
    response=request.get(encoded_url).json()
    if response:
        return f"weather data for **{location}**: celsius: {response["current"].temp_c} farenheight: {response["current"].temp_f}, day is: {response["current"]["condition"].text}"
    #    data=response.json()
    #    return data
    else:
        return f"Weather API failed retry after some time"



  get_weather.invoke("beijing")

for this i get the error:

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
Cell In[28], line 1
----> 1 get_weather.invoke("beijing")

File ~/Documents/Agentic-experiments/tools-experiments/.venv/lib/python3.12/site-packages/langchain_core/tools/base.py:738, in BaseTool.invoke(self, input, config, **kwargs)
    730 
    731 def invoke(
    732     self,
   (...)    735     **kwargs: Any,
    736 ) -> Any:
    737     tool_input, kwargs = _prep_run_args(input, config, **kwargs)
--> 738     return self.run(tool_input, **kwargs)

File ~/Documents/Agentic-experiments/tools-experiments/.venv/lib/python3.12/site-packages/langchain_core/tools/base.py:1100, in BaseTool.run(self, tool_input, verbose, start_color, color, callbacks, tags, metadata, run_name, run_id, config, tool_call_id, **kwargs)
   1098 if error_to_raise:
   1099     run_manager.on_tool_error(error_to_raise, tool_call_id=tool_call_id)
-> 1100     raise error_to_raise
   1101 output = _format_output(content, artifact, tool_call_id, self.name, status)
   1102 run_manager.on_tool_end(output, color=color, name=self.name, **kwargs)

File ~/Documents/Agentic-experiments/tools-experiments/.venv/lib/python3.12/site-packages/langchain_core/tools/base.py:1066, in BaseTool.run(self, tool_input, verbose, start_color, color, callbacks, tags, metadata, run_name, run_id, config, tool_call_id, **kwargs)
   1064     if config_param := _get_runnable_config_param(self._run):
   1065         tool_kwargs |= {config_param: config}
-> 1066     response = context.run(self._run, *tool_args, **tool_kwargs)
   1067 if self.response_format == "content_and_artifact":
   1068     msg = (
   1069         "Since response_format='content_and_artifact' "
   1070         "a two-tuple of the message content and raw tool output is "
   1071         f"expected. Instead, generated response is of type: "
   1072         f"{type(response)}."
   1073     )

File ~/Documents/Agentic-experiments/tools-experiments/.venv/lib/python3.12/site-packages/langchain_core/tools/structured.py:97, in StructuredTool._run(self, config, run_manager, *args, **kwargs)
     95     if config_param := _get_runnable_config_param(self.func):
     96         kwargs[config_param] = config
---> 97     return self.func(*args, **kwargs)
     98 msg = "StructuredTool does not support sync invocation."
     99 raise NotImplementedError(msg)

Cell In[25], line 41, in get_weather(location)
     37     """
     38     key=os.environ.get("WEATHER_API_KEY")
     39     url="https://api.weatherapi.com/v1/current.json?q={location}&key={key}"
     40     encoded_url=quote(url)
---> 41     response=request.get(encoded_url)
     42     if response:
     43         # return f"weather data for **{location}**: celsius: {response["current"].temp_c} farenheight: {response["current"].temp_f}, day is: {response["current"]["condition"].text}"
     44        data=response.json()

AttributeError: 'function' object has no attribute 'get'

how to resolve this and get results in testing what the tool prints.