updated temperature value and use of groq model for faster execution

code_agent.py

@@ -34,7 +34,7 @@ from dataclasses import dataclass, replace
 from typing import Any, Optional
 import re  # For stripping markdown fences
 
-from langchain_openai import ChatOpenAI
+from langchain_groq import ChatGroq
 from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
 from langchain_core.tools import tool
 from langgraph.graph import END, StateGraph
@@ -43,7 +43,7 @@ from langgraph.graph import END, StateGraph
 # 0. Global config
 ###############################################################################
 
-MODEL_NAME = os.getenv("LANGGRAPH_MODEL", "gpt-4o-mini")
+MODEL_NAME = os.getenv("LANGGRAPH_MODEL", "qwen-qwq-32b")
 TIMEOUT_SEC = int(os.getenv("LANGGRAPH_TIMEOUT_SEC", "30"))
 
 ###############################################################################
@@ -78,7 +78,7 @@ def python_exec(code: str) -> str:
 # 2. LLM backend
 ###############################################################################
 
-llm = ChatOpenAI(model_name=MODEL_NAME, temperature=0.0)
+llm = ChatGroq(model=MODEL_NAME, temperature= 0.6)
 
 ###############################################################################
 # 3. Dataclass‑based state & LangGraph

langraph_agent.py

@@ -215,7 +215,7 @@ def build_graph(provider: str = "groq"):
         llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash", temperature=0)
     elif provider == "groq":
         # Groq https://console.groq.com/docs/models
-        llm = ChatGroq(model="qwen-qwq-32b", temperature=0) # optional : qwen-qwq-32b gemma2-9b-it
+        llm = ChatGroq(model="qwen-qwq-32b", temperature= 0.6) # optional : qwen-qwq-32b gemma2-9b-it
     elif provider == "huggingface":
         # TODO: Add huggingface endpoint
         llm = ChatHuggingFace(