diff --git a/chat_with_github/chat_github_llama3.py b/chat_with_github/chat_github_llama3.py
new file mode 100644
index 0000000..3d279db
--- /dev/null
+++ b/chat_with_github/chat_github_llama3.py
@@ -0,0 +1,40 @@
+# Import the required libraries
+import tempfile
+from embedchain import App
+from embedchain.loaders.github import GithubLoader
+import streamlit as st
+
+loader = GithubLoader(
+    config={
+        "token":"Your_GitHub_PAT",
+        }
+    )
+
+# Define the embedchain_bot function
+def embedchain_bot(db_path):
+    return App.from_config(
+        config={
+            "llm": {"provider": "ollama", "config": {"model": "llama3:instruct", "max_tokens": 250, "temperature": 0.5, "stream": True, "base_url": 'http://localhost:11434'}},
+            "vectordb": {"provider": "chroma", "config": {"dir": db_path}},
+            "embedder": {"provider": "ollama", "config": {"model": "llama3:instruct", "base_url": 'http://localhost:11434'}},
+        }
+    )
+
+# Create Streamlit app
+st.title("Chat with GitHub Repository 💬")
+st.caption("This app allows you to chat with a GitHub Repo using OpenAI API")
+
+db_path = tempfile.mkdtemp()
+app = embedchain_bot(db_path)
+# Get the GitHub repo from the user
+git_repo = st.text_input("Enter the GitHub Repo", type="default")
+if git_repo:
+    # Add the repo to the knowledge base
+    app.add("repo:" + git_repo + " " + "type:repo", data_type="github", loader=loader)
+    st.success(f"Added {git_repo} to knowledge base!")
+    # Ask a question about the Github Repo
+    prompt = st.text_input("Ask any question about the GitHub Repo")
+    # Chat with the GitHub Repo
+    if prompt:
+        answer = app.chat(prompt)
+        st.write(answer)
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