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| import streamlit as st | |
| from src.main import ConversationalResponse | |
| import os | |
| # Constants | |
| ROLE_USER = "user" | |
| ROLE_ASSISTANT = "assistant" | |
| st.set_page_config(page_title="Chat with Git Codes", page_icon="🦜") | |
| st.title("Chat with Git Codes 🤖📄") | |
| 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. You can paste link to the Git repository and ask questions about it. In the backround uses the Git Loader and ConversationalRetrival chain from langchain, Streamlit for UI.") | |
| 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(): | |
| api_key = st.sidebar.text_input("Enter your OpenAI API Key", type="password") | |
| if api_key: | |
| os.environ["OPENAI_API_KEY"] = api_key | |
| else: | |
| st.sidebar.error("Please enter your OpenAI API Key.") | |
| return | |
| 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 | |
| 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?"}] | |
| 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"]) | |
| 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) | |
| # 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}) | |
| if __name__ == "__main__": | |
| main() |