fix image similarity detection

src/streamlit_app.py

@@ -2,7 +2,7 @@
 #   ✅ Cache-Safe Multimodal App
 # ================================
 
-import os
+import shutil, os
 
 # ====== Force all cache dirs to /tmp (writable in most environments) ======
 CACHE_BASE = "/tmp/cache"
@@ -13,6 +13,11 @@ os.environ["HF_DATASETS_CACHE"] = f"{CACHE_BASE}/hf_datasets"
 os.environ["TORCH_HOME"] = f"{CACHE_BASE}/torch"
 os.environ["STREAMLIT_CACHE_DIR"] = f"{CACHE_BASE}/streamlit_cache"
 os.environ["STREAMLIT_STATIC_DIR"] = f"{CACHE_BASE}/streamlit_static"
+os.environ["STREAMLIT_CONFIG_DIR"] = "/tmp/.streamlit"
+
+# Create the directories before imports
+os.makedirs(os.environ["STREAMLIT_CONFIG_DIR"], exist_ok=True)
+shutil.copyfile(".streamlit/config.toml", "/tmp/.streamlit/config.toml")
 
 # Create the directories before imports
 for path in os.environ.values():
@@ -30,13 +35,6 @@ import openai
 import comet_llm
 from opik import track
 
-os.environ["STREAMLIT_CONFIG_DIR"] = "/tmp/.streamlit"
-os.environ["STREAMLIT_CACHE_DIR"] = f"{CACHE_BASE}/streamlit_cache"
-os.environ["STREAMLIT_STATIC_DIR"] = f"{CACHE_BASE}/streamlit_static"
-
-os.makedirs("/tmp/.streamlit", exist_ok=True)
-
-
 # ========== 🔑 API Key ==========
 openai.api_key = os.getenv("OPENAI_API_KEY")
 os.environ["OPIK_API_KEY"] = os.getenv("OPIK_API_KEY")
@@ -126,8 +124,8 @@ 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_file = st.file_uploader("Upload an image to find similar medical cases:", type=["png", "jpg", "jpeg"], accept_multiple_files=False)
+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)
 
 @track
 def get_chat_completion_openai(client, prompt: str):
@@ -150,33 +148,34 @@ def get_similar_prompt(query):
 
 
 
-# if query:
-#     with st.spinner("Searching medical cases..."):
-#
-#
-#         # Compute similarity
-#         selected = get_similar_prompt(query)
-#
-#         # Show Image
-#         st.image(selected['image'], caption="Most relevant medical image", use_container_width=True)
-#
-#         # Show Text
-#         st.markdown(f"**Case Description:** {selected[TEXT_COLUMN]}")
-#
-#         # GPT Explanation
-#         if openai.api_key:
-#             prompt = f"Explain this case in plain English: {selected[TEXT_COLUMN]}"
-#
-#             explanation = get_chat_completion_openai(client, prompt)
-#             explanation = explanation.choices[0].message.content
-#
-#             st.markdown(f"### 🤖 Explanation by GPT:\n{explanation}")
-#         else:
-#             st.warning("OpenAI API key not found. Please set OPENAI_API_KEY as a secret environment variable.")
-
-if uploaded_file:
+if query:
+    with st.spinner("Searching medical cases..."):
+
+
+        # Compute similarity
+        selected = get_similar_prompt(query)
+
+        # Show Image
+        st.image(selected['image'], caption="Most relevant medical image", use_container_width=True)
+
+        # Show Text
+        st.markdown(f"**Case Description:** {selected[TEXT_COLUMN]}")
+
+        # GPT Explanation
+        if openai.api_key:
+            prompt = f"Explain this case in plain English: {selected[TEXT_COLUMN]}"
+
+            explanation = get_chat_completion_openai(client, prompt)
+            explanation = explanation.choices[0].message.content
+
+            st.markdown(f"### 🤖 Explanation by GPT:\n{explanation}")
+        else:
+            st.warning("OpenAI API key not found. Please set OPENAI_API_KEY as a secret environment variable.")
+
+if uploaded_files:
     with st.spinner("Searching medical cases..."):
-        print(uploaded_file)
+        print(uploaded_files)
+        uploaded_file = uploaded_files[0]
         st.write(f'uploading file {uploaded_file.name}')
         query_image = Image.open(uploaded_file).convert("RGB")
         st.image(query_image, caption="Your uploaded image", use_container_width=True)