updates

README.md

@@ -47,15 +47,13 @@ There are several ways to create an environment in Python. Follow these steps to
 Once you have your environment set up and activated, you need to install the necessary libraries. Run the following command to install the required packages:
 
 ```bash
-pip install streamlit python-dotenv  ibm_watson_machine_learning requests chromadb
+pip install streamlit python-dotenv  ibm_watson_machine_learning requests chromadb sentence_transformers
 ```
 
 IMPORTANT: Be aware of the disk space that will be taken up by documents when they're loaded into
 chromadb on your laptop. The size in chroma will likely be the same as .txt file size
 
 
-
-
 ## Step 3: Getting API from IBM Cloud
 
 ### Obtaining an API Key

run.py

@@ -0,0 +1,56 @@
+# For reading credentials from the .env file
+import os
+from dotenv import load_dotenv
+import streamlit as st
+import webchat
+
+# URL of the hosted LLMs is hardcoded because at this time all LLMs share the same endpoint
+url = "https://us-south.ml.cloud.ibm.com"
+
+# These global variables will be updated in get_credentials() function
+watsonx_project_id = ""
+api_key = ""
+
+def get_credentials():
+    load_dotenv()
+    # Update the global variables that will be used for authentication in another function
+    globals()["api_key"] = os.getenv("API_KEY", "")
+    globals()["watsonx_project_id"] = os.getenv("PROJECT_ID", "")
+
+def main():
+    # Get the API key and project id and update global variables
+    get_credentials()
+
+    # Use the full page instead of a narrow central column
+    st.set_page_config(layout="wide")
+
+    # Streamlit app title
+    st.title("🌠Demo of RAG with a Web page")
+
+    # Sidebar for settings
+    st.sidebar.header("Settings")
+    api_key_input = st.sidebar.text_input("API Key", api_key)
+    project_id_input = st.sidebar.text_input("Project ID", watsonx_project_id)
+    
+    # Update credentials if provided by the user
+    if api_key_input:
+        globals()["api_key"] = api_key_input
+    if project_id_input:
+        globals()["watsonx_project_id"] = project_id_input
+
+    user_url = st.text_input('Provide a URL')
+    collection_name = st.text_input('Provide a unique name for this website (lower case). Use the same name for the same URL to avoid loading data multiple times.')
+
+    # UI component to enter the question
+    question = st.text_area('Question', height=100)
+    button_clicked = st.button("Answer the question")
+
+    st.subheader("Response")
+
+    # Invoke the LLM when the button is clicked
+    if button_clicked:
+        response = webchat.answer_questions_from_web(api_key, watsonx_project_id, user_url, question, collection_name)
+        st.write(response)
+
+if __name__ == "__main__":
+    main()