fix image similarity detection

requirements.txt

@@ -1,6 +1,6 @@
 altair
 pandas
-streamlit
+streamlit~=1.48.0
 torch
 transformers
 sentence-transformers
@@ -8,4 +8,5 @@ datasets
 openai
 opik
 comet-llm==2.1.0
-comet_ml==3.33.8
+comet_ml==3.33.8
+pillow~=11.3.0

src/streamlit_app.py

@@ -30,12 +30,12 @@ from sentence_transformers import SentenceTransformer, util
 from transformers import CLIPProcessor, CLIPModel
 from datasets import load_dataset, get_dataset_split_names
 from PIL import Image
-import openai
+from openai import OpenAI
 import comet_llm
 from opik import track
 
 # ========== 🔑 API Key ==========
-openai.api_key = os.getenv("OPENAI_API_KEY")
+OpenAI.api_key = os.getenv("OPENAI_API_KEY")
 os.environ["OPIK_API_KEY"] = os.getenv("OPIK_API_KEY")
 os.environ["OPIK_WORKSPACE"] = os.getenv("OPIK_WORKSPACE")
 # ========== 📥 Load Models ==========
@@ -86,8 +86,7 @@ def embed_dataset_images(_dataset):
 data = load_medical_data()
 dataset_image_features = embed_dataset_images(data)
 
-from openai import OpenAI
-client = OpenAI(api_key=openai.api_key)
+client = OpenAI(api_key=OpenAI.api_key)
 # Temporary debug display
 #st.write("Dataset columns:", data.features.keys())
 
@@ -117,19 +116,6 @@ def embed_dataset_texts(_texts):
 def embed_query_text(query):
     return text_model.encode([query], convert_to_tensor=True)[0]
 
-# Pick which text column to use
-TEXT_COLUMN = "complaints"  # or "general_complaint", depending on your needs
-
-# ========== 🧑‍⚕️ App UI ==========
-st.title("🩺 Multimodal Medical Chatbot")
-
-query = st.text_input("Enter your medical question or symptom description:")
-uploaded_files = st.file_uploader("Upload an image to find similar medical cases:", type=["png", "jpg", "jpeg"], accept_multiple_files=True)
-
-st.write(f"Number of files: {len(uploaded_files)}")
-for uploaded_file in uploaded_files:
-    st.write(f"File name: {uploaded_file.name}")
-
 @track
 def get_chat_completion_openai(client, prompt: str):
     return client.chat.completions.create(
@@ -150,6 +136,19 @@ def get_similar_prompt(query):
     return data[idx]
 
 
+# Pick which text column to use
+TEXT_COLUMN = "complaints"  # or "general_complaint", depending on your needs
+
+# ========== 🧑‍⚕️ App UI ==========
+st.title("🩺 Multimodal Medical Chatbot")
+
+query = st.text_input("Enter your medical question or symptom description:")
+uploaded_files = st.file_uploader("Upload an image to find similar medical cases:", type=["png", "jpg", "jpeg"], accept_multiple_files=True)
+
+st.write(f"Number of files: {len(uploaded_files)}")
+for uploaded_file in uploaded_files:
+    st.write(f"File name: {uploaded_file.name}")
+
 
 if query:
     with st.spinner("Searching medical cases..."):
@@ -165,7 +164,7 @@ if query:
         st.markdown(f"**Case Description:** {selected[TEXT_COLUMN]}")
 
         # GPT Explanation
-        if openai.api_key:
+        if OpenAI.api_key:
             prompt = f"Explain this case in plain English: {selected[TEXT_COLUMN]}"
 
             explanation = get_chat_completion_openai(client, prompt)