add comet

requirements.txt

@@ -5,4 +5,7 @@ torch
 transformers
 sentence-transformers
 datasets
-openai
+openai
+opik
+comet-llm==2.1.0
+comet_ml==3.33.8

src/streamlit_app.py

@@ -27,10 +27,14 @@ from transformers import CLIPProcessor, CLIPModel
 from datasets import load_dataset, get_dataset_split_names
 from PIL import Image
 import openai
+import comet_llm
+
+
 
 # ========== 🔑 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 ==========
 @st.cache_resource(show_spinner=False)
 def load_models():
@@ -89,6 +93,16 @@ st.title("🩺 Multimodal Medical Chatbot")
 
 query = st.text_input("Enter your medical question or symptom description:")
 
+@track
+def get_chat_completion_openai(prompt: str):
+    return client.chat.completions.create(
+        model="gpt-4o",  # or "gpt-4" if you need the older GPT-4
+        messages=[{"role": "user", "content": prompt}],
+        temperature=0.5,
+        max_tokens=150
+    )
+
+
 if query:
     with st.spinner("Searching medical cases..."):
         text_embeddings = embed_texts(data[TEXT_COLUMN])
@@ -112,13 +126,8 @@ if query:
             from openai import OpenAI
             client = OpenAI(api_key=openai.api_key)
 
-            response = client.chat.completions.create(
-            model="gpt-4o",  # or "gpt-4" if you need the older GPT-4
-            messages=[{"role": "user", "content": prompt}],
-            temperature=0.5,
-            max_tokens=150
-            )
-            explanation = response.choices[0].message.content
+            explanation = get_chat_completion_openai()
+            explanation = explanation.choices[0].message.content
 
             st.markdown(f"### 🤖 Explanation by GPT:\n{explanation}")
         else: