update

agent.py

@@ -4,6 +4,7 @@ import time
 from typing import Optional
 
 from langchain.chat_models import init_chat_model
+
 from langchain_community.document_loaders import WikipediaLoader, ArxivLoader
 from langchain_community.tools import TavilySearchResults
 from langchain_core.messages import HumanMessage, SystemMessage, AIMessage, AnyMessage
@@ -11,7 +12,7 @@ from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
 from langgraph.graph import add_messages, START, END, StateGraph
 from langchain_core.tools import tool
 from langgraph.prebuilt import ToolNode
-
+from pydantic import SecretStr
 
 from typing_extensions import TypedDict, Annotated
 
@@ -30,6 +31,13 @@ def get_llm():
     #return init_chat_model("llama-3.3-70b-versatile", model_provider="groq")
 
     return init_chat_model("gemini-2.0-flash", model_provider="google_genai")
+    #return AzureChatOpenAI(
+       # api_key=SecretStr(os.environ["AZURE_OPENAI_API_KEY"]),
+       # azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
+        #azure_deployment="gpt-4o-mini",
+        #api_version=os.environ["AZURE_OPENAI_API_VERSION"],
+    #)
+
 
 def get_graph(llm):
     with open('prompts/system_prompt.md', 'r', encoding='utf-8') as markdown_file:
@@ -207,6 +215,8 @@ def get_graph(llm):
 
     def call_model(state: State):
         print("\n-------------------- Agent has been called -----------------------------------\n")
+        print("Waiting for 5 seconds...")
+        time.sleep(5)
         # get all messages from the state
         messages = state["messages"]
         # append instruction message
@@ -216,12 +226,14 @@ def get_graph(llm):
         # invoke LLM
         response = llm_with_tools.invoke(prompt_answer)
         print("Agent has made a decision:\n", response.content, response.tool_calls)
-        print("Waiting for 4 seconds...")
-        time.sleep(4)
+
 
         return {"messages": [response], "aggregate": ["Agent"]}
 
     def get_answer(state: State):
+        print("\n-------------------- Generating Answer -----------------------------------\n")
+        print("Waiting for 5 seconds...")
+        time.sleep(5)
         # get all messages from the state
         messages = state["messages"]
         # add prompt message

app.py

@@ -126,8 +126,8 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     answers_payload = []
     print(f"Running agent on {len(questions_data)} questions...")
     for item in questions_data:
-        print("Waiting for 20 seconds...")
-        time.sleep(20)
+        print("Waiting for 5 seconds...")
+        time.sleep(5)
         task_id = item.get("task_id")
         question_text = item.get("question")
         content_type = None