Update app.py

app.py

@@ -1,43 +1,43 @@
-import streamlit as st
-
-from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
-from langchain.schema import HumanMessage, SystemMessage, AIMessage
-
-st.set_page_config(page_title="LangChain Demo", page_icon=":robot:")
-st.header("Hey, I'm your DeepSeek")
-
-if "sessionMessages" not in st.session_state:
-     st.session_state.sessionMessages = [
-        SystemMessage(content="You are a helpful assistant.")
-    ]
-
-
-def load_answer(question):
-    st.session_state.sessionMessages.append(HumanMessage
-                                            (content=question))
-    assistant_answer = chat_model.invoke(st.session_state.sessionMessages)
-    st.session_state.sessionMessages.append(AIMessage(content=assistant_answer))
-    return assistant_answer.content
-
-def get_text():
-    input_text = st.text_input("You: ")
-    return input_text
-
-llm = HuggingFaceEndpoint(
-    repo_id="deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
-    task="text-generation",
-    max_new_tokens=512,
-    do_sample=True,
-    temperature=0.7,
-    repetition_penalty=1.03,
-)
-
-chat_model = ChatHuggingFace(llm=llm)
-
-user_input = get_text()
-submit = st.button('Generate')
-
-if submit:
-    response = load_answer(user_input)
-    st.subheader("Answer: ")
+import streamlit as st
+
+from langchain_huggingface import HuggingFaceEndpoint, ChatHuggingFace
+from langchain.schema import HumanMessage, SystemMessage, AIMessage
+
+st.set_page_config(page_title="LangChain Demo", page_icon=":robot:")
+st.header("Hey, I'm your DeepSeek")
+
+if "sessionMessages" not in st.session_state:
+     st.session_state.sessionMessages = [
+        SystemMessage(content="You are a helpful assistant.")
+    ]
+
+
+def load_answer(question):
+    st.session_state.sessionMessages.append(HumanMessage
+                                            (content=question))
+    assistant_answer = chat_model.invoke(st.session_state.sessionMessages)
+    st.session_state.sessionMessages.append(AIMessage(content=assistant_answer.content if hasattr(assistant_answer, "content") else str(assistant_answer)))
+    return assistant_answer.content
+
+def get_text():
+    input_text = st.text_input("You: ")
+    return input_text
+
+llm = HuggingFaceEndpoint(
+    repo_id="deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
+    task="text-generation",
+    max_new_tokens=512,
+    do_sample=True,
+    temperature=0.7,
+    repetition_penalty=1.03,
+)
+
+chat_model = ChatHuggingFace(llm=llm)
+
+user_input = get_text()
+submit = st.button('Generate')
+
+if submit:
+    response = load_answer(user_input)
+    st.subheader("Answer: ")
     st.write(response)