I am trying to get Langchain Bedrock and Anthropic to use a tool/function I have defined in my python file. It does kick off the right tool use and seems to be returning output_tokens count but no output.

My first query does kick off the right tool called get_weather. But returns no output.

My second query does not kick off any tool usage correctly, as expected, and returns answer.

Code:

import os                                                   # Access to env varibales
from dotenv import find_dotenv, load_dotenv                 # Set up to read API keys from .env #install python-dotenv
dotenv_path = find_dotenv()                                 # find_dotenv wil find teh .env up te parent path 
load_dotenv(dotenv_path)                                    # now you have access to os.environ[HUGGINGFACEHUB_API_TOKEN]

import json

import boto3
from langchain_community.llms import Bedrock

aws_region = "us-east-1"
model_id = "anthropic.claude-v2:1"
model_id = "anthropic.claude-3-sonnet-20240229-v1:0"
model_id = "anthropic.claude-3-sonnet-20240229-v1:0"


model = boto3.client(service_name="bedrock-runtime",  region_name="us-east-1")

# Define a custom tool
def get_weather(input: str) -> str:
    # Replace this with your actual tool implementation
    return f"The weather in {input} is sunny and sujata."

# Define the tool schema
tool_schema = {
    "type": "object",
    "properties": {
        "location": {"type": "string", "description": "The city and state, e.g. San Francisco, CA"}
    },
    "required": ["location"]
}

# Define the tool
tool = [{
    "name": "get_weather",
    "description": "Get the current weather in a given location",
    "input_schema": tool_schema
},]



# Define the tools to use
tools = [
    {"name": "get_weather", "description": "Get the current weather in a given location"},
#    {"name": "get_temperature", "description": "Get the current temperature in a given location"}
]

# Create the request body

def query(prompt):
    body = json.dumps({
        "max_tokens": 256,
        "messages": [{"role": "user", "content": prompt}],
        "anthropic_version": "bedrock-2023-05-31",
        "tools": tool
    })


    # Define the prompt
    response = model.invoke_model(body=body, modelId=model_id)
    
    
    print("------------------------------------")
    print("q: " + prompt)

    # Print the response
    #print(response["body"])
    streaming_body=response["body"]
    # Print the contents of the StreamingBody object
    s= streaming_body.read().decode('utf-8')
    sJson= json.loads(s)
    
    
    #print("a: "+ json.dumps(sJson["content"],indent=4))
    print(json.dumps(sJson,indent=4))#["content"])
    
query("What is the weather like in San Francisco?")
query("What is teh capital of India?")

output:

------------------------------------
q: What is the weather like in San Francisco?
{
    "id": "msg_bdrk_01KCn2u3P2f2WCiQ4yuvkpNL",
    "type": "message",
    "role": "assistant",
    "model": "claude-3-sonnet-20240229",
    "content": [
        {
            "type": "text",
            "text": "Okay, let's get the current weather for San Francisco:"
        },
        {
            "type": "tool_use",
            "id": "toolu_bdrk_01J6xY1kfNA1dVMbkqCpAp3K",
            "name": "get_weather",
            "input": {
                "location": "San Francisco, CA"
            }
        }
    ],
    "stop_reason": "tool_use",
    "stop_sequence": null,
    "usage": {
        "input_tokens": 249,
        "output_tokens": 70
    }
}
------------------------------------
q: What is teh capital of India?
{
    "id": "msg_bdrk_011qdVBM8cAq69Z7w7TnVsMs",
    "type": "message",
    "role": "assistant",
    "model": "claude-3-sonnet-20240229",
    "content": [
        {
            "type": "text",
            "text": "The capital of India is New Delhi."
        }
    ],
    "stop_reason": "end_turn",
    "stop_sequence": null,
    "usage": {
        "input_tokens": 248,
        "output_tokens": 11
    }
}