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chatbot_app_Containerfile

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+FROM registry.access.redhat.com/ubi9/python-311:1-77.1726664316
+WORKDIR /chat
+COPY requirements.txt .
+RUN pip install --upgrade pip
+RUN pip install --no-cache-dir --upgrade -r /chat/requirements.txt
+COPY chatbot_ui.py .
+EXPOSE 8501
+ENTRYPOINT [ "streamlit", "run", "chatbot_ui.py" ]

chatbot_app_chatbot_ui.py

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+from langchain_openai import ChatOpenAI
+from langchain.chains import LLMChain
+from langchain_community.callbacks import StreamlitCallbackHandler
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain.memory import ConversationBufferWindowMemory
+import streamlit as st
+import requests
+import time
+import json
+import os 
+
+model_service = os.getenv("MODEL_ENDPOINT",
+                          "http://localhost:8001")
+model_service = f"{model_service}/v1"
+model_service_bearer = os.getenv("MODEL_ENDPOINT_BEARER")
+request_kwargs = {}
+if model_service_bearer is not None:
+    request_kwargs = {"headers": {"Authorization": f"Bearer {model_service_bearer}"}}
+
+@st.cache_resource(show_spinner=False)
+def checking_model_service():
+    start = time.time()
+    print("Checking Model Service Availability...")
+    ready = False
+    while not ready:
+        try:
+            request_cpp = requests.get(f'{model_service}/models', **request_kwargs)
+            request_ollama = requests.get(f'{model_service[:-2]}api/tags', **request_kwargs)
+            if request_cpp.status_code == 200:
+                server = "Llamacpp_Python"
+                ready = True
+            elif request_ollama.status_code == 200:
+                server = "Ollama"
+                ready = True        
+        except:
+            pass
+        time.sleep(1)
+    print(f"{server} Model Service Available")
+    print(f"{time.time()-start} seconds")
+    return server 
+
+def get_models():
+    try:
+        response = requests.get(f"{model_service[:-2]}api/tags", **request_kwargs)
+        return [i["name"].split(":")[0] for i in  
+            json.loads(response.content)["models"]]
+    except:
+        return None
+
+with st.spinner("Checking Model Service Availability..."):
+    server = checking_model_service()
+
+def enableInput():
+    st.session_state["input_disabled"] = False
+
+def disableInput():
+    st.session_state["input_disabled"] = True
+
+st.title("💬 Chatbot")  
+if "messages" not in st.session_state:
+    st.session_state["messages"] = [{"role": "assistant", 
+                                     "content": "How can I help you?"}]
+if "input_disabled" not in st.session_state:
+    enableInput()
+
+for msg in st.session_state.messages:
+    st.chat_message(msg["role"]).write(msg["content"])
+
+@st.cache_resource()
+def memory():
+    memory = ConversationBufferWindowMemory(return_messages=True,k=3)
+    return memory
+
+model_name = os.getenv("MODEL_NAME", "") 
+
+if server == "Ollama":
+    models = get_models()
+    with st.sidebar:
+        model_name = st.radio(label="Select Model",
+            options=models)
+
+llm = ChatOpenAI(base_url=model_service, 
+        api_key="sk-no-key-required" if model_service_bearer is None else model_service_bearer,
+        model=model_name,
+        streaming=True,
+        callbacks=[StreamlitCallbackHandler(st.empty(),
+                                            expand_new_thoughts=True,
+                                            collapse_completed_thoughts=True)])
+
+prompt = ChatPromptTemplate.from_messages([
+    ("system", "You are world class technical advisor."),
+    MessagesPlaceholder(variable_name="history"),
+    ("user", "{input}")
+])
+
+chain = LLMChain(llm=llm, 
+                prompt=prompt,
+                verbose=False,
+                memory=memory())
+
+if prompt := st.chat_input(disabled=st.session_state["input_disabled"],on_submit=disableInput):
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    st.chat_message("user").markdown(prompt)
+    response = chain.invoke(prompt)
+    st.chat_message("assistant").markdown(response["text"])    
+    st.session_state.messages.append({"role": "assistant", "content": response["text"]})
+    enableInput()
+    st.rerun()

chatbot_app_requirements.txt

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+langchain==0.2.3
+langchain-openai==0.1.7
+langchain-community==0.2.4
+streamlit==1.34.0