Add userguide

about/userguide.md

@@ -0,0 +1,8 @@
+## **User Guide:**
+
+Each startup in the state selected are represented by dots and colored based on state. Hovering over each dot will give the company name along with its categories. The startup input by the user is representated by a hexagon and is placed among similar ones based on the model's computational findings. 
+
+
+1.   Particularly dense clusters are indication of a more competitive market segment.
+2.   Dots in isolation either indicates a untapped market or non viable market. The user needs to conduct additional market research for inferring what that segment means.
+3.  Stratified or linear groupings may result from firms uniquely applying a common core technology, such as data analytics.

app.py

@@ -21,6 +21,10 @@ from bertopic import BERTopic
 import pickle
 import os
 
+def read_markdown(path,parent='about/'):
+    with open(os.path.join(parent,path)) as f:
+        return f.read()
+
 def visualizer(prob_req, embed, df, index, company_name):
     
     with st.spinner("Visualizing the results !!!"):
@@ -66,7 +70,7 @@ def preprocess(name, group, state, states_used, desc):
     text = ' '.join(lemmatizer.lemmatize(w) for w in text.split(' '))
     return text
     
-@st.cache(persist=True,suppress_st_warning=True)
+@st.cache(persist=True,suppress_st_warning=True,show_spinner=False)
 def load_topic_model(model_path, name, group, state, states_used, desc):
 
     with st.spinner("Creating Topic Models ....."):
@@ -100,7 +104,8 @@ def app():
     st.title("Competitive Analysis of Companies ")
     
     check_examples = st.sidebar.checkbox("Try Examples!")
-
+    
+    st.markdown(read_markdown('userguide.md'))
     #companyname = st.text_input('Input company name here:', value="")
     #companygrp = st.text_input('Input industry group here:', value="")
     #companydesc = st.text_input("Input company description: (can be found in the company's linkedin page)", value="")