chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
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import os
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import gc
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import tempfile
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import uuid
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import pandas as pd
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from typing import Optional, Dict, Any
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import logging
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from gitingest import ingest
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from llama_index.core import Settings, PromptTemplate, VectorStoreIndex, SimpleDirectoryReader
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from llama_index.core.node_parser import MarkdownNodeParser
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import streamlit as st
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from dotenv import load_dotenv
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# Configure logging
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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load_dotenv()
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# Constants
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MAX_REPO_SIZE = 100 * 1024 * 1024 # 100MB
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SUPPORTED_REPO_TYPES = ['.py', '.md', '.ipynb', '.js', '.ts', '.json']
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class GitHubRAGError(Exception):
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"""Custom exception for GitHub RAG application errors"""
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pass
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def validate_github_url(url: str) -> bool:
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"""Validate GitHub repository URL"""
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return url.startswith(('https://github.com/', 'http://github.com/'))
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def get_repo_name(url: str) -> str:
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"""Extract repository name from URL"""
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try:
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return url.split('/')[-1].replace('.git', '')
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except Exception as e:
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raise GitHubRAGError(f"Invalid repository URL: {str(e)}")
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def reset_chat():
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"""Reset chat session and clean up resources"""
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try:
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st.session_state.messages = []
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st.session_state.context = None
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gc.collect()
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logger.info("Chat session reset successfully")
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except Exception as e:
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logger.error(f"Error resetting chat: {str(e)}")
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raise GitHubRAGError("Failed to reset chat session")
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def process_with_gitingets(github_url: str) -> tuple:
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"""Process GitHub repository using gitingest"""
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try:
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summary, tree, content = ingest(github_url)
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if not all([summary, tree, content]):
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raise GitHubRAGError("Failed to process repository: Missing data")
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return summary, tree, content
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except Exception as e:
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logger.error(f"Error processing repository: {str(e)}")
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raise GitHubRAGError(f"Failed to process repository: {str(e)}")
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def create_query_engine(content_path: str, repo_name: str) -> Any:
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"""Create and configure query engine"""
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try:
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loader = SimpleDirectoryReader(input_dir=content_path)
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docs = loader.load_data()
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node_parser = MarkdownNodeParser()
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index = VectorStoreIndex.from_documents(
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documents=docs,
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transformations=[node_parser],
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show_progress=True
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)
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qa_prompt_tmpl_str = """
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You are an AI assistant specialized in analyzing GitHub repositories.
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Repository structure:
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{tree}
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---------------------
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Context information from the repository:
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{context_str}
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---------------------
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Given the repository structure and context above, provide a clear and precise answer to the query.
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Focus on the repository's content, code structure, and implementation details.
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If the information is not available in the context, respond with 'I don't have enough information about that aspect of the repository.'
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Query: {query_str}
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Answer: """
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qa_prompt_tmpl = PromptTemplate(qa_prompt_tmpl_str)
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query_engine = index.as_query_engine(streaming=True)
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query_engine.update_prompts(
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{"response_synthesizer:text_qa_template": qa_prompt_tmpl}
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)
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return query_engine
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except Exception as e:
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logger.error(f"Error creating query engine: {str(e)}")
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raise GitHubRAGError(f"Failed to create query engine: {str(e)}")
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# Initialize session state
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if "id" not in st.session_state:
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st.session_state.id = uuid.uuid4()
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st.session_state.file_cache = {}
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st.session_state.messages = []
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session_id = st.session_state.id
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# Sidebar
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with st.sidebar:
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st.header("Add your GitHub repository!")
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github_url = st.text_input(
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"Enter GitHub repository URL",
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placeholder="https://github.com/username/repo",
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help="Enter a valid GitHub repository URL"
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)
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load_repo = st.button("Load Repository", type="primary")
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if github_url and load_repo:
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try:
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# Validate URL
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if not validate_github_url(github_url):
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st.error("Please enter a valid GitHub repository URL")
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st.stop()
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repo_name = get_repo_name(github_url)
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file_key = f"{session_id}-{repo_name}"
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if file_key not in st.session_state.file_cache:
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with st.spinner("Processing your repository..."):
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with tempfile.TemporaryDirectory() as temp_dir:
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try:
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summary, tree, content = process_with_gitingets(github_url)
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# Write content to temporary file
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content_path = os.path.join(temp_dir, f"{repo_name}_content.md")
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with open(content_path, "w", encoding="utf-8") as f:
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f.write(content)
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# Create and cache query engine
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query_engine = create_query_engine(temp_dir, repo_name)
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st.session_state.file_cache[file_key] = query_engine
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st.success("Repository loaded successfully! Ready to chat.")
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logger.info(f"Successfully processed repository: {repo_name}")
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except GitHubRAGError as e:
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st.error(str(e))
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logger.error(f"Error processing repository {repo_name}: {str(e)}")
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st.stop()
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except Exception as e:
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st.error("An unexpected error occurred while processing the repository")
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logger.error(f"Unexpected error: {str(e)}")
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st.stop()
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else:
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st.info("Repository already loaded. Ready to chat!")
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except Exception as e:
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st.error(f"An error occurred: {str(e)}")
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logger.error(f"Error in repository loading process: {str(e)}")
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st.stop()
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# Main content
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col1, col2 = st.columns([6, 1])
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with col1:
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st.header("Chat with GitHub using RAG </>")
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with col2:
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st.button("Clear Chat ↺", on_click=reset_chat, help="Clear chat history and reset session")
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# Display chat history
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for message in st.session_state.messages:
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with st.chat_message(message["role"]):
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st.markdown(message["content"])
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# Chat input
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if prompt := st.chat_input("What's up?"):
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try:
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# Add user message to chat history
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st.session_state.messages.append({"role": "user", "content": prompt})
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# Display user message
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with st.chat_message("user"):
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st.markdown(prompt)
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# Process and display assistant response
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with st.chat_message("assistant"):
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message_placeholder = st.empty()
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full_response = ""
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try:
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repo_name = get_repo_name(github_url)
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file_key = f"{session_id}-{repo_name}"
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query_engine = st.session_state.file_cache.get(file_key)
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if query_engine is None:
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raise GitHubRAGError("Please load a repository first!")
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response = query_engine.query(prompt)
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if hasattr(response, 'response_gen'):
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for chunk in response.response_gen:
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if isinstance(chunk, str):
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full_response += chunk
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message_placeholder.markdown(full_response + "▌")
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else:
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full_response = str(response)
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message_placeholder.markdown(full_response)
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message_placeholder.markdown(full_response)
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st.session_state.messages.append({"role": "assistant", "content": full_response})
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except GitHubRAGError as e:
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st.error(str(e))
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logger.error(f"Error in chat processing: {str(e)}")
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except Exception as e:
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st.error("An unexpected error occurred while processing your query")
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logger.error(f"Unexpected error in chat: {str(e)}")
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except Exception as e:
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st.error("An error occurred in the chat system")
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logger.error(f"Chat system error: {str(e)}")
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