How To Chat With A Github Repository Using Llama-index

github_openai_llamaindex.py

# Import the Github Repository Reader class
import os
from tokens import githubToken, apikey
import openai
from llama_index.readers import GithubRepositoryReader
from llama_index import VectorStoreIndex
from llama_index import StorageContext, load_index_from_storage

openai.api_key = apikey

os.environ["GITHUB_TOKEN"] = githubToken

folder_path = "./storage"

folder_exists = os.path.exists(folder_path) and os.path.isdir(folder_path)


if folder_exists:
    # rebuild storage context
    storage_context = StorageContext.from_defaults(persist_dir="./storage")
    # load index
    index = load_index_from_storage(storage_context)
else:
    # Read the llama-index repository
    reader = GithubRepositoryReader("jerryjliu",
                                    "llama_index",
                                    ignore_directories=[".github", ".vscode",
                                                        "benchmarks", "docs",
                                                        "examples", "experimental",
                                                        "scripts", "tests"])
    # Load data from the main branch
    branch_documents = reader.load_data(branch="main")
    # Building and querying an index
    index = VectorStoreIndex.from_documents(branch_documents)
    index.storage_context.persist()

query_engine = index.as_query_engine()

while True:
    conversation = {}

    question = input("\n Write your question or enter 'quit' to quit. \n\n")

    conversation[question] = ""

    if question == 'quit':
        break

    prompt = f"Respond to this question: {question} given the conversation history: {conversation} \n"

    response = query_engine.query(prompt)

    conversation[question] = response

    print(response)