Added new demo

README.md

@@ -24,6 +24,9 @@ Streamlit app that allows you to chat with any webpage using local Llama-3 and R
 ### 📨 Chat with Gmail
 Interact with your Gmail inbox using natural language. Get accurate answers to your questions based on the content of your emails with Retrieval Augmented Generation (RAG).
 
+### 📝 Chat with Substack Newsletter
+Streamlit app that allows you to chat with a Substack newsletter using OpenAI's API and the Embedchain library. This app leverages GPT-4 to provide accurate answers to questions based on the content of the specified Substack newsletter.
+
 ### 📄 Chat with PDF
 Engage in intelligent conversation and question-answering based on the content of your PDF documents. Simply upload a PDF document and start asking questions. Chat with PDF will analyze the document, extract relevant information, and generate accurate responses to your queries.
 

chat_with_substack/README.md

@@ -0,0 +1,28 @@
+## 📝 Chat with Substack Newsletter
+Streamlit app that allows you to chat with a Substack newsletter using OpenAI's API and the Embedchain library. This app leverages GPT-4 to provide accurate answers to questions based on the content of the specified Substack newsletter.
+
+## Features
+- Input a Substack blog URL
+- Ask questions about the content of the Substack newsletter
+- Get accurate answers using OpenAI's API and Embedchain
+
+### How to get Started?
+
+1. Clone the GitHub repository
+
+```bash
+git clone https://github.com/Shubhamsaboo/awesome-llm-apps.git
+```
+2. Install the required dependencies:
+
+```bash
+pip install -r requirements.txt
+```
+3. Get your OpenAI API Key
+
+- Sign up for an [OpenAI account](https://platform.openai.com/) (or the LLM provider of your choice) and obtain your API key.
+
+4. Run the Streamlit App
+```bash
+streamlit run chat_substack.py
+```

chat_with_substack/chat_substack.py

@@ -0,0 +1,41 @@
+import streamlit as st
+from embedchain import App
+import tempfile
+
+# Define the embedchain_bot function
+def embedchain_bot(db_path, api_key):
+    return App.from_config(
+        config={
+            "llm": {"provider": "openai", "config": {"model": "gpt-4-turbo", "temperature": 0.5, "api_key": api_key}},
+            "vectordb": {"provider": "chroma", "config": {"dir": db_path}},
+            "embedder": {"provider": "openai", "config": {"api_key": api_key}},
+        }
+    )
+
+st.title("Chat with Substack Newsletter 📝")
+st.caption("This app allows you to chat with Substack newsletter using OpenAI API")
+
+# Get OpenAI API key from user
+openai_access_token = st.text_input("OpenAI API Key", type="password")
+
+if openai_access_token:
+    # Create a temporary directory to store the database
+    db_path = tempfile.mkdtemp()
+    # Create an instance of Embedchain App
+    app = embedchain_bot(db_path, openai_access_token)
+
+    # Get the Substack blog URL from the user
+    substack_url = st.text_input("Enter Substack Newsletter URL", type="default")
+
+    if substack_url:
+        # Add the Substack blog to the knowledge base
+        app.add(substack_url, data_type='substack')
+        st.success(f"Added {substack_url} to knowledge base!")
+
+        # Ask a question about the Substack blog
+        query = st.text_input("Ask any question about the substack newsletter!")
+
+        # Query the Substack blog
+        if query:
+            result = app.query(query)
+            st.write(result)

chat_with_substack/requirements.txt

@@ -0,0 +1,2 @@
+streamlit
+embedchain