import streamlit as st from src.main import ConversationalResponse import os # Constants ROLE_USER = "user" ROLE_ASSISTANT = "assistant" # MAX_MESSAGES = 5 # Commented out but can be reactivated later st.set_page_config(page_title="Chat with Git LLAMA2", page_icon="🦙") st.title("Chat with Git LLAMA2 🦙📚") st.markdown("by [Rohan Kataria](https://www.linkedin.com/in/imrohan/) view more at [VEW.AI](https://vew.ai/)") st.markdown("This app allows you to chat with Git code files. You can paste link to the Git repository and ask questions about it. In the background uses the Git Loader and ConversationalRetrieval chain from langchain, Ollama, Streamlit for UI.") @st.cache_resource(ttl="1h") def load_agent(url, branch, file_filter): with st.spinner('Loading Git documents...'): agent = ConversationalResponse(url, branch, file_filter) st.success("Git Loaded Successfully") return agent def main(): git_link = st.sidebar.text_input("Enter your Git Link") branch = st.sidebar.text_input("Enter your Git Branch") file_filter = st.sidebar.text_input("Enter the Extension of Files to Load eg. py,sql,r (no spaces)") if "agent" not in st.session_state: st.session_state["agent"] = None st.session_state["user_message_count"] = 0 if st.sidebar.button("Load Agent"): if git_link and branch and file_filter: try: st.session_state["agent"] = load_agent(git_link, branch, file_filter) st.session_state["messages"] = [{"role": ROLE_ASSISTANT, "content": "How can I help you?"}] st.session_state["user_message_count"] = 0 except Exception as e: st.sidebar.error(f"Error loading Git repository: {str(e)}") return if st.session_state["agent"]: # Chat will only appear if the agent is loaded for msg in st.session_state.messages: st.chat_message(msg["role"]).write(msg["content"]) # if st.session_state["user_message_count"] < MAX_MESSAGES: # Commented out to remove message limit check user_query = st.chat_input(placeholder="Ask me anything!") if user_query: st.session_state.messages.append({"role": ROLE_USER, "content": user_query}) st.chat_message(ROLE_USER).write(user_query) st.session_state["user_message_count"] += 1 # Generate the response with st.spinner("Generating response"): response = st.session_state["agent"](user_query) # Display the response immediately st.chat_message(ROLE_ASSISTANT).write(response) # Add the response to the message history st.session_state.messages.append({"role": ROLE_ASSISTANT, "content": response}) # else: # st.warning("Your message limit is over. Contact [Rohan Kataria](https://www.linkedin.com/in/imrohan/) to increase the limit.") # Commented out the warning message about message limit if __name__ == "__main__": main()