Update pages/1_📊_About.py

pages/1_📊_About.py

@@ -11,21 +11,21 @@ with tab1:
     st.markdown("**Application:** Gofynd.com")
     st.markdown("**Total Products:** 14,000")
     st.markdown("**Data Used:**")
-    st.markdown("- Text fields - Name, Brand, Category, Gender")
-    st.markdown("- Images - Single Images (First image of the product)")
-    st.markdown("Embedding Model: Used CLIP model for Generating the Embeddings for Text and Image")
-    st.markdown("Weightage [Text, Image]: [0.1, 0.9]")
-    st.markdown("Vector Database: Milvus")
-    st.markdown("ML Pipeline Orchestration: Vertex AI Pipeline")
-    st.markdown("Supported Input data format:")
-    st.markdown("Similarity Metric: Inner Product")
-    st.markdown("Type of Index: FLAT_L2")
+    st.markdown("- **Text Fields-** Name, Brand, Category, Gender")
+    st.markdown("- **Images-** Single Images (First image of the product)")
+    st.markdown("**Embedding Model:** Used CLIP model for Generating the Embeddings for Text and Image")
+    st.markdown("**Weightage [Text, Image]:** [0.1, 0.9]")
+    st.markdown("**Vector Database:** Milvus")
+    st.markdown("**ML Pipeline Orchestration:** Vertex AI Pipeline")
+    st.markdown("**Supported Input Data Format:** JSON")
+    st.markdown("**Similarity Metric:** Inner Product")
+    st.markdown("**Index Type:** FLAT_L2")
     
     st.subheader("Input Sample Data:")
     st.markdown("Sample data can be displayed here.")
     
-    st.subheader("STEPS")
-    st.markdown("**TRAINING:**")
+    st.subheader("Steps")
+    st.markdown("**Training:**")
     st.markdown("1. Pull the Catalog data from Fynd Platform")
     st.markdown("2. Parse Textual and Image data from Catalog data")
     st.markdown("3. Generate Embeddings for Textual fields")
@@ -33,7 +33,7 @@ with tab1:
     st.markdown("5. Aggregate Embeddings with help of defined weightage")
     st.markdown("6. Store it to Vector DB - Milvus")
     
-    st.markdown("**SERVING:**")
+    st.markdown("**Serving:**")
     st.markdown("1. Convert the Users’s query as Input text string to Embeddings with CLIP model")
     st.markdown("2. Pass the user’s search query to LLM - OpenAI’S GPT3 to detect the search entities - Query, Brand, Category, Price, Sorting type")
     st.markdown("3. Prepare and Apply Search Query on Collection of Milvus DB on which the data is indexed")
@@ -45,23 +45,23 @@ with tab2:
     st.markdown("**Application:** Gofynd.com")
     st.markdown("**Total Documents:** FAQ, Return, Shipping, T&C")
     st.markdown("**Framework:** Langchain")
-    st.markdown("Embedding Model: Used OpenAI’s GPT3.5 model for Generating the Embeddings for Text docus")
-    st.markdown("Vector Database: Milvus")
-    st.markdown("ML Pipeline Orchestration: Vertex AI Pipeline")
-    st.markdown("Supported Input data format: Strict JSON format (Other formats to be added shortly)")
-    st.markdown("Support file type: JSON")
-    st.markdown("Similarity Metric: Inner Product")
-    st.markdown("Type of Index: FLAT_L2")
+    st.markdown("**Embedding Model:** OpenAI’s GPT3.5")
+    st.markdown("**Vector Database:** Milvus")
+    st.markdown("**ML Pipeline Orchestration:** Vertex AI Pipeline")
+    st.markdown("**Supported Input data format:** Strict JSON format (Other formats to be added shortly)")
+    st.markdown("**Support file type:** JSON")
+    st.markdown("**Similarity Metric:** Inner Product")
+    st.markdown("**Type of Index:** FLAT_L2")
     
-    st.subheader("STEPS")
-    st.markdown("**TRAINING:**")
+    st.subheader("Steps")
+    st.markdown("**Training:**")
     st.markdown("1. Pull Textual policy documents from FDK")
     st.markdown("2. Parse the file data and make all documents at flat level")
     st.markdown("3. Apply splitters to convert the documents to chunks")
     st.markdown("4. Generate the Embeddings for those chunks")
     st.markdown("5. Store Embeddings to Milvus DB and create Index")
     
-    st.markdown("**SERVING:**")
+    st.markdown("**Serving:**")
     st.markdown("1. Convert users’ question to embeddings with help of OpenAI’s GPT3.5 model")
     st.markdown("2. Apply Embedding Search Query on Collection of Milvus DB on which the data is indexed and Fetch top 10 Docs")
     st.markdown("3. Use PROMPT template to prepare PROMPT = TEMPLATE + CONTEXT and use OpenAI’s to generate the response")