Update code so it can run with or without posters

Author: sfc-gh-lacosta

recipes/weaviate/demo_app.py

@@ -8,7 +8,7 @@
 
 # Constants
 ENV_VARS = ["WEAVIATE_URL", "WEAVIATE_API_KEY", "COHERE_API_KEY"]
-NUM_IMAGES_PER_ROW = 5
+NUM_RECOMMENDATIONS_PER_ROW = 5
 SEARCH_LIMIT = 10
 
 # Search Mode descriptions
@@ -34,11 +34,18 @@ def display_chat_messages():
         with st.chat_message(message["role"]):
             st.markdown(message["content"])
             if "images" in message:
-                for i in range(0, len(message["images"]), NUM_IMAGES_PER_ROW):
-                    cols = st.columns(NUM_IMAGES_PER_ROW)
+                for i in range(0, len(message["images"]), NUM_RECOMMENDATIONS_PER_ROW):
+                    cols = st.columns(NUM_RECOMMENDATIONS_PER_ROW)
                     for j, col in enumerate(cols):
                         if i + j < len(message["images"]):
                             col.image(message["images"][i + j], width=200)
+            if "titles" in message:
+                for i in range(0, len(message["titles"]), NUM_RECOMMENDATIONS_PER_ROW):
+                    cols = st.columns(NUM_RECOMMENDATIONS_PER_ROW)
+                    for j, col in enumerate(cols):
+                        if i + j < len(message["titles"]):
+                            col.write(message["titles"][i + j])
+
 
 def base64_to_image(base64_str):
     """Convert base64 string to image"""
@@ -112,7 +119,10 @@ def perform_search(conn, movie_type, rag_prompt, year_range, mode):
     df = conn.query(
         "MovieDemo",
         query=movie_type,
-        return_properties=["title", "tagline", "poster"],
+        # Uncomment the line below  if you want to use this with poster images
+        # return_properties=["title", "tagline", "poster"],
+        # Comment out the line below  if you want to use this with poster images
+        return_properties=["title", "tagline"],
         filters=(
             WeaviateFilter.by_property("release_year").greater_or_equal(year_range[0]) &
             WeaviateFilter.by_property("release_year").less_or_equal(year_range[1])
@@ -122,6 +132,8 @@ def perform_search(conn, movie_type, rag_prompt, year_range, mode):
     )
 
     images = []
+    titles = []
+    
     if df is None or df.empty:
         with st.chat_message("assistant"):
             st.write(f"No movies found matching {movie_type} and using {mode}. Please try again.")
@@ -130,16 +142,21 @@ def perform_search(conn, movie_type, rag_prompt, year_range, mode):
     else:
         with st.chat_message("assistant"):
             st.write("Raw search results.")
-            cols = st.columns(NUM_IMAGES_PER_ROW)
+            cols = st.columns(NUM_RECOMMENDATIONS_PER_ROW)
             for index, row in df.iterrows():
-                col = cols[index % NUM_IMAGES_PER_ROW]
-                col.write(row['title'])
+                col = cols[index % NUM_RECOMMENDATIONS_PER_ROW]
+                if "poster" in row and row["poster"]:
+                    col.image(base64_to_image(row["poster"]), width=200)
+                    images.append(base64_to_image(row["poster"]))
+                else:
+                    col.write(f"{row['title']}")
+                    titles.append(row["title"])
+            
             st.write("Now generating recommendation from these: ...")
 
         st.session_state.messages.append(
-            {"role": "assistant", "content": "Raw search results. Generating recommendation from these: ...", "images": images}
-        )
-
+            {"role": "assistant", "content": "Raw search results. Generating recommendation from these: ...", "images": images, "titles": titles})
+        
         with conn.client() as client:
             collection = client.collections.get("MovieDemo")
             response = collection.generate.hybrid(

recipes/weaviate/helpers/add_data.py

@@ -83,10 +83,11 @@
             name="budget",
             data_type=DataType.INT,
         ),
-        Property(
-            name="poster",
-            data_type=DataType.BLOB
-        ),
+        # Uncomment the lines below if you want to use this with poster images
+        # Property(
+        #     name="poster",
+        #     data_type=DataType.BLOB
+        # ),
     ],
     vectorizer_config=Configure.Vectorizer.text2vec_cohere(),
     vector_index_config=Configure.VectorIndex.hnsw(
@@ -109,9 +110,10 @@
             date_object = datetime.strptime(movie_row["release_date"], "%Y-%m-%d").replace(
                 tzinfo=timezone.utc
             )
-            img_path = (img_dir / f"{movie_row['id']}_poster.jpg")
-            with open(img_path, "rb") as file:
-                poster_b64 = base64.b64encode(file.read()).decode("utf-8")
+            # Uncomment the lines below if you want to use this with poster images
+            # img_path = (img_dir / f"{movie_row['id']}_poster.jpg")
+            # with open(img_path, "rb") as file:
+            #     poster_b64 = base64.b64encode(file.read()).decode("utf-8")
 
             props = {
                 k: movie_row[k]
@@ -128,7 +130,8 @@
             props["movie_id"] = movie_row["id"]
             props["release_year"] = date_object.year
             props["genres"] = [genre["name"] for genre in movie_row["genres"]]
-            props["poster"] = poster_b64
+            # Uncomment the line below if you want to use this with poster images
+            # props["poster"] = poster_b64
 
             batch.add_object(properties=props, uuid=generate_uuid5(movie_row["id"]))
         except Exception as e:

recipes/weaviate/helpers/verify_data.py

@@ -5,38 +5,38 @@
 import os
 
 
-config = toml.load("/Users/lacosta/Desktop/PROJECTS/cookbook/recipes/weaviate/.streamlit/secrets.toml")
+# Construct the path to the toml file
+current_dir = os.path.dirname(__file__)
+parent_dir = os.path.dirname(current_dir)
+toml_file_path = os.path.join(parent_dir, ".streamlit/secrets.toml")
+
+config = toml.load(toml_file_path)
 
 # Access values from the TOML file
 weaviate_api_key = config["WEAVIATE_API_KEY"]
 weaviate_url = config["WEAVIATE_URL"]
 cohere_api_key = config["COHERE_API_KEY"]
 
-weaviate_url = config["WEAVIATE_URL"]
-weaviate_apikey = config["WEAVIATE_API_KEY"]  # WCS_DEMO_ADMIN_KEY or WCS_DEMO_RO_KEY
-cohere_apikey = config["COHERE_API_KEY"]
-
-
 client = weaviate.connect_to_weaviate_cloud(
     cluster_url=weaviate_url,
-    auth_credentials=Auth.api_key(weaviate_apikey),
+    auth_credentials=Auth.api_key(weaviate_api_key),
     headers={
-        "X-Cohere-Api-Key": cohere_apikey
+        "X-Cohere-Api-Key": cohere_api_key
     }
 )
 
 # # If you are using a local instance of Weaviate, you can use the following code
 # client = weaviate.connect_to_local(
 #     headers={
-#         "X-Cohere-Api-Key": cohere_apikey
+#         "X-Cohere-Api-Key": cohere_api_key
 #     }
 # )
 
 movies = client.collections.get("MovieDemo")
 
 print(movies.aggregate.over_all(total_count=True))
 
-r = movies.query.fetch_objects(limit=1, return_properties=["poster"])
-print(r.objects[0].properties["poster"])
+r = movies.query.fetch_objects(limit=1, return_properties=["title"])
+print(r.objects[0].properties["title"])
 
 client.close()