without asr

app.py

@@ -0,0 +1,35 @@
+import streamlit as st
+from langchain_openai import ChatOpenAI
+from langchain_core.messages import AIMessage
+from langchain_community.tools.tavily_search import TavilySearchResults
+from langchain_core.messages import HumanMessage
+from langgraph.checkpoint.memory import MemorySaver
+from langgraph.prebuilt import create_react_agent
+from dotenv import load_dotenv
+
+load_dotenv()
+@st.cache_resource
+def get_model():
+    model = ChatOpenAI(model="gpt-4o", temperature=0, base_url="https://models.inference.ai.azure.com")
+    return model
+
+memory = MemorySaver()
+search = TavilySearchResults(max_results=2)
+tools = [search]
+model = get_model()
+app = create_react_agent(model, tools, checkpointer=memory)
+
+config = {"configurable": {"thread_id": "111"}}
+
+if query:=st.chat_input("Ask anything"):
+    msg= [HumanMessage(query)]
+    def gen():
+        for chunk, metadata in app.stream({"messages": msg}, config=config, stream_mode="messages"):
+            if isinstance(chunk, AIMessage):
+                yield chunk.content
+    st.write_stream(gen)
+
+
+
+
+    

requirements.txt

@@ -0,0 +1,9 @@
+langchain_community 
+langchain-openai 
+langchain 
+langgraph 
+langchainhub 
+streamlit
+
+
+