parser2.py

import os
from llama_parse import LlamaParse
NEO4J_URI = ""
NEO4J_USERNAME = "neo4j"
NEO4J_PASSWORD = ""
NEO4J_DATABASE = "neo4j"

import os

os.environ["OPENAI_API_KEY"] = ""
os.environ['GROQ_API_KEY'] = ""

from llama_index.core import KnowledgeGraphIndex
from llama_index.core import StorageContext
from llama_index.graph_stores.neo4j import Neo4jGraphStore


from llama_index.llms.openai import OpenAI
from llama_index.tools.neo4j import Neo4jQueryToolSpec
from llama_index.llms.openai import OpenAI
from llama_index.agent.openai import OpenAIAgent
import nest_asyncio
from groq import Groq
import os

upload_folder = "./uploads"

def parse_docs ():
    parser = LlamaParse(
        api_key="LLAMA_PARSER_API_KEY",
        result_type="markdown",
        num_workers=4,
        verbose=True,
        language="en",
    )

    graph_store = Neo4jGraphStore(
        username=NEO4J_USERNAME,
        password=NEO4J_PASSWORD,
        url=NEO4J_URI,
        database=NEO4J_DATABASE,
    )

    file_list = os.listdir(upload_folder)
    if len(file_list) == 1:
        document_path = os.path.join(upload_folder, file_list[0])
        
        documents = parser.load_data(document_path)

    storage_context = StorageContext.from_defaults(graph_store=graph_store)
    index = KnowledgeGraphIndex.from_documents(
        documents,
        storage_context=storage_context,
        max_triplets_per_chunk=2,
    )

    print("Graph data uploaded successfully.")

    return documents
    
file_content = parse_docs()
with open("parsed_content.txt", 'w') as file:
    for docs in file_content:
        file.write(docs.text + "\n")