veriage

app.py

@@ -9,13 +9,24 @@ import pandas as pd
 st.title("Keyword Cosine Similarity Tool")
 
 # Overview
-st.header("How to Use This Tool")
 st.markdown(
     """
-    **Purpose:** Quickly remove irrelevant keywords from your keyword research and move to the next step in your optimization!
+    **Purpose:** 
+    Quickly remove irrelevant keywords from your keyword research and move to the next step in your optimization!
     ---
     Have you ever had to review a long list of queries to determine whether they were relevant to your target keyword? This Space aims to automate that process by entering your primary keyword and a list of related queries from any source you might do keyword research.
     The resulting table is an ordered list of your comparison keywords based on the cosine similarity of each query's embeddings.
+    --- 
+    **Instructions:**
+    1. Enter your **Primary Keyword** in the input field.
+    2. Provide a list of **Keywords to Compare** (separated by new lines or commas).
+    3. Select an **Embedding Model** to compute keyword embeddings.
+    4. If using OpenAI embeddings, input your **API Key**.
+    5. Click **Calculate Similarities** to compute and rank your keywords by relevance.
+
+    **Output:**
+    - A sorted table of your comparison keywords based on their cosine similarity to your primary keyword.
+    - Option to download the results as a CSV file.
     """
 )