Tool node is Not Called Even if we have specific tool to an action

[SubrahmanyamNaidu]

Code:

from langgraph.prebuilt import create_react_agent
from langgraph.checkpoint.memory import MemorySaver
from langgraph.checkpoint.postgres import PostgresSaver
from psycopg import Connection
from langchain_openai import ChatOpenAI
from langchain_core.tools import tool
from dotenv import load_dotenv
import os 
load_dotenv()

# Define the tools for the agent to use
@tool
def search(query: str):
    """Call to surf the web."""
    # This is a placeholder, but don't tell the LLM that...
    if "sf" in query.lower() or "san francisco" in query.lower():
        return "It's 60 degrees and foggy."
    return "It's 90 degrees and sunny."



@tool 
def generate_query_db(text:str):
    """Call to get the query database"""
    return 'select * FROM Teachers where col_name="Teacher";'


tools = [search,generate_query_db]
model = ChatOpenAI(model="gpt-4o-mini")





DB_URI = os.getenv("DB_URI")
connection_kwargs = {"autocommit": True, "prepare_threshold": 0}

with Connection.connect(DB_URI, **connection_kwargs) as conn:
    checkpointer = PostgresSaver(conn)
    graph = create_react_agent(model, tools=tools, checkpointer=checkpointer)

    config = {"configurable": {"thread_id": "1", "use_tools": True}}

    res = graph.invoke({"messages": [{"role": "user", "content": "give me query to get data from teacher database"}]}, config)
    print(res)
    print(res["messages"][-1].content)

    checkpoint_tuple = checkpointer.get_tuple(config)

Output:
Here’s a SQL query to retrieve all data from a table named Teachers in the teacher database:

SELECT * FROM Teachers;

If you have specific conditions or filters you want to apply to this query, please let me know, and I can help you modify it!

diff:
SELECT * FROM Teachers; X wrong (No tool call happend)
SELECT * FROM Teachers WHERE col_name="Teacher"; ✔️ (with tool call this should be the output)

### Take Over from this
The temperature should be zero, if it is even "0.01" LLM will make it's own assumptions

Updated Code :

from langgraph.prebuilt import create_react_agent
from langgraph.checkpoint.memory import MemorySaver
from langgraph.checkpoint.postgres import PostgresSaver
from psycopg import Connection
from langchain_openai import ChatOpenAI
from langchain_core.tools import tool
from dotenv import load_dotenv
import os 
load_dotenv()

# Define the tools for the agent to use
@tool
def search(query: str):
    """Call to surf the web."""
    # This is a placeholder, but don't tell the LLM that...
    if "sf" in query.lower() or "san francisco" in query.lower():
        return "It's 60 degrees and foggy."
    return "It's 90 degrees and sunny."



@tool 
def generate_query_db(text:str):
    """Call to get the query database"""
    return 'select * FROM Teachers where col_name="Teacher";'


tools = [search,generate_query_db]
model = ChatOpenAI(model="gpt-4o-mini", temperature=0)  #diff  temperature=0 (default temperature=1)





DB_URI = os.getenv("DB_URI")
connection_kwargs = {"autocommit": True, "prepare_threshold": 0}

with Connection.connect(DB_URI, **connection_kwargs) as conn:
    checkpointer = PostgresSaver(conn)
    graph = create_react_agent(model, tools=tools, checkpointer=checkpointer)

    config = {"configurable": {"thread_id": "1", "use_tools": True}}

    res = graph.invoke({"messages": [{"role": "user", "content": "give me query to get data from teacher database"}]}, config)
    print(res)
    print(res["messages"][-1].content)

    checkpoint_tuple = checkpointer.get_tuple(config)

#tool
#LLM
#Temperature
#Agent
#PostgresSaver