update

app/docker-compose.yml

@@ -3,6 +3,7 @@ version: "3.9"
 services:
   streamlit:
     build: ./streamlit
+    platform: linux/amd64
     ports:
       - "8501:8501"
     volumes:

app/streamlit/Dockerfile

@@ -2,12 +2,6 @@ FROM python:3.11-slim
 
 WORKDIR /app/streamlit
 
-RUN apt-get update && apt-get install -y \
-    build-essential \
-    curl \
-    software-properties-common \
-    && rm -rf /var/lib/apt/lists/*
-
 COPY requirements.txt ./
 
 RUN pip install --no-cache-dir -r requirements.txt
@@ -15,8 +9,10 @@ RUN pip install --no-cache-dir -r requirements.txt
 COPY Chatbot.py .
 COPY .env .
 
+# Run python to initialize download of SentenceTransformer model
+COPY initialize_sentence_transformer.py .
+RUN python initialize_sentence_transformer.py
+
 EXPOSE 8501
 
-HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
+ENTRYPOINT ["streamlit", "run", "Chatbot.py"]
-
-ENTRYPOINT ["streamlit", "run", "Chatbot.py", "--server.port=8501", "--server.address=0.0.0.0"]

app/streamlit/app_test.py

@@ -1,52 +1,7 @@
-import datetime
 from unittest.mock import patch
 from streamlit.testing.v1 import AppTest
-from openai.types.chat import ChatCompletionMessage
-from openai.types.chat.chat_completion import ChatCompletion, Choice
 
 
-# See https://github.com/openai/openai-python/issues/715#issuecomment-1809203346
-def create_chat_completion(response: str, role: str = "assistant") -> ChatCompletion:
-    return ChatCompletion(
-        id="foo",
-        model="gpt-3.5-turbo",
-        object="chat.completion",
-        choices=[
-            Choice(
-                finish_reason="stop",
-                index=0,
-                message=ChatCompletionMessage(
-                    content=response,
-                    role=role,
-                ),
-            )
-        ],
-        created=int(datetime.datetime.now().timestamp()),
-    )
-
-
-@patch("langchain_deepseek.ChatDeepSeek.invoke")
-@patch("langchain_google_genai.ChatGoogleGenerativeAI.invoke")
-@patch("langchain_community.llms.moonshot.Moonshot.invoke")
-def test_Chatbot(moonshot_llm, gemini_llm, deepseek_llm):
-    at = AppTest.from_file("Chatbot.py").run()
-    assert not at.exception
-    
-    QUERY = "What is the best treatment for hypertension?"
-    RESPONSE = "The best treatment for hypertension is..."
-    
-    deepseek_llm.return_value.content = RESPONSE
-    gemini_llm.return_value.content = RESPONSE
-    moonshot_llm.return_value = RESPONSE
-    
-    at.chat_input[0].set_value(QUERY).run()
-    
-    assert any(mock.called for mock in [deepseek_llm, gemini_llm, moonshot_llm])
-    assert at.chat_message[1].markdown[0].value == QUERY
-    assert at.chat_message[2].markdown[0].value == RESPONSE
-    assert at.chat_message[2].avatar == "assistant"
-    assert not at.exception
-
 
 @patch("langchain.llms.OpenAI.__call__")
 def test_Langchain_Quickstart(langchain_llm):

app/streamlit/initialize_sentence_transformer.py

@@ -0,0 +1,7 @@
+from decouple import config
+from sentence_transformers import SentenceTransformer
+
+EMBEDDING_MODEL = config("EMBEDDING_MODEL", cast=str, default="paraphrase-multilingual-mpnet-base-v2")
+
+# Initialize embedding model
+model = SentenceTransformer(EMBEDDING_MODEL)