add header image

app.py

@@ -6,6 +6,7 @@ import pandas as pd
 import faiss
 import hdbscan
 from sklearn.feature_extraction.text import CountVectorizer
+from PIL import image
 
 from src.modelling.topics.topic_extractor import (
     TopicExtractionConfig, TopicExtractor
@@ -28,6 +29,8 @@ def get_prompt_without_reviews(title):
     return f"""We are doing a marketing research analysis, in particular we are trying to understand what users thing about a particular market in order to generate tips for future sellers.
 In particular, we are interesting to analyze the market for "{title}"
 
+Take into account what customers are saying in the internet about these products. How are their reviews? How is the distribution of the product? What characteristics do they value the most?
+
 Can you write some recomendations about how can we disrupt this market? Try to propose the necesary methodology to create a breaking product."""
 
 
@@ -64,19 +67,15 @@ This doesn't mean you make a mistake, I search amazon products and try to extrac
 
 TEST_MODE = False
 
-
 def setup_palm():
     palm.configure(api_key=os.environ.get('PALM_TOKEN'))
 
-
 @st.cache_data
 def load_data():
     reviews = pd.read_csv("data/filtered_reviews.csv").set_index("reviewID")
     products = pd.read_csv("data/products.csv")
-
     return reviews, products
 
-
 def load_uncached_models():
     topic_extraction_config = TopicExtractionConfig(
         vectorizer_model=CountVectorizer(
@@ -166,6 +165,8 @@ def render_search():
     Render the search form in the sidebar.
     """
     with st.sidebar:
+        image = Image.open('electronic.png')
+        st.image(image)
         query = st.text_input(
             label="What kind of product are you trying to sell?",
             placeholder="Your magic idea goes here ✨",
@@ -197,7 +198,6 @@ def render_search():
 
 
 def render_palm_results():
-    # TODO: temporal
     st.write("# ALMond recommendations")
     st.write(st.session_state.palm_output)