├── node_postprocessors ├── __init__.py └── duplicate_postprocessing.py ├── static └── banner.gif ├── Pipfile ├── download_docs.py ├── ingestion.py ├── README.MD ├── main.py ├── .gitignore └── LICENSE /node_postprocessors/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /static/banner.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/emarco177/llamaindex-documentation-helper/main/static/banner.gif -------------------------------------------------------------------------------- /Pipfile: -------------------------------------------------------------------------------- 1 | [[source]] 2 | url = "https://pypi.org/simple" 3 | verify_ssl = true 4 | name = "pypi" 5 | 6 | [packages] 7 | requests = "*" 8 | beautifulsoup4 = "*" 9 | llama-index = "*" 10 | openai = "*" 11 | python-dotenv = "*" 12 | black = "*" 13 | llama-cpp-python = "*" 14 | transformers = "*" 15 | streamlit = "*" 16 | llama-index-llms-openai = "*" 17 | 18 | [dev-packages] 19 | 20 | [requires] 21 | python_version = "3.10" 22 | -------------------------------------------------------------------------------- /node_postprocessors/duplicate_postprocessing.py: -------------------------------------------------------------------------------- 1 | from abc import abstractmethod 2 | from typing import List, Optional 3 | 4 | from llama_index.core import QueryBundle 5 | from llama_index.core.schema import NodeWithScore 6 | 7 | 8 | class DuplicateRemoverNodePostprocessor: 9 | """Node postprocessor.""" 10 | 11 | @abstractmethod 12 | def postprocess_nodes( 13 | self, nodes: List[NodeWithScore], query_bundle: Optional[QueryBundle] 14 | ) -> List[NodeWithScore]: 15 | """Postprocess nodes.""" 16 | print("_postprocess_nodes enter") 17 | 18 | unique_hashes = set() 19 | unique_nodes = [] 20 | 21 | for node in nodes: 22 | node_hash = node.node.hash 23 | 24 | if node_hash not in unique_hashes: 25 | unique_hashes.add(node_hash) 26 | unique_nodes.append(node) 27 | 28 | return unique_nodes 29 | -------------------------------------------------------------------------------- /download_docs.py: -------------------------------------------------------------------------------- 1 | import requests 2 | from bs4 import BeautifulSoup 3 | import os 4 | import urllib 5 | 6 | # The URL to scrape 7 | ur0 = "https://gpt-index.readthedocs.io/en/stable/" 8 | url = "https://docs.llamaindex.ai/en/stable/" 9 | 10 | # The directory to store files in 11 | output_dir = "./llamindex-docs/" 12 | 13 | # Create the output directory if it doesn't exist 14 | os.makedirs(output_dir, exist_ok=True) 15 | 16 | # Fetch the page 17 | response = requests.get(url) 18 | soup = BeautifulSoup(response.text, "html.parser") 19 | 20 | # Find all links to .html files 21 | links = soup.find_all("a", href=True) 22 | 23 | for link in links: 24 | href = link["href"] 25 | 26 | # If it's a .html file 27 | if href.endswith(".html"): 28 | # Make a full URL if necessary 29 | if not href.startswith("http"): 30 | href = urllib.parse.urljoin(url, href) 31 | 32 | # Fetch the .html file 33 | print(f"downloading {href}") 34 | file_response = requests.get(href) 35 | 36 | # Write it to a file 37 | file_name = os.path.join(output_dir, os.path.basename(href)) 38 | with open(file_name, "w", encoding="utf-8") as file: 39 | file.write(file_response.text) 40 | -------------------------------------------------------------------------------- /ingestion.py: -------------------------------------------------------------------------------- 1 | from dotenv import load_dotenv 2 | import os 3 | from llama_index.core import SimpleDirectoryReader, Settings 4 | from llama_index.core.node_parser import SimpleNodeParser 5 | from llama_index.llms.openai import OpenAI 6 | from llama_index.embeddings.openai import OpenAIEmbedding 7 | from llama_index.core import VectorStoreIndex, StorageContext 8 | from llama_index.vector_stores.pinecone import PineconeVectorStore 9 | from pinecone import Pinecone 10 | 11 | load_dotenv() 12 | 13 | if __name__ == "__main__": 14 | print("Going to ingest pinecone documentation...") 15 | from llama_index.readers.file import UnstructuredReader 16 | 17 | dir_reader = SimpleDirectoryReader( 18 | input_dir="./llamaindex-docs", 19 | file_extractor={".html": UnstructuredReader()}, 20 | ) 21 | documents = dir_reader.load_data() 22 | node_parser = SimpleNodeParser.from_defaults(chunk_size=500, chunk_overlap=20) 23 | 24 | llm = OpenAI(model="gpt-3.5-turbo", temperature=0) 25 | embed_model = OpenAIEmbedding(model="text-embedding-3-small", embed_batch_size=100) 26 | 27 | Settings.llm = OpenAI() 28 | Settings.embed_model = OpenAIEmbedding() 29 | 30 | index_name = "llamaindex-documentation-helper" 31 | pc = Pinecone(api_key=os.environ["PINECONE_API_KEY"]) 32 | pinecone_index = pc.Index(name=index_name) 33 | vector_store = PineconeVectorStore(pinecone_index=pinecone_index) 34 | storage_context = StorageContext.from_defaults(vector_store=vector_store) 35 | 36 | index = VectorStoreIndex.from_documents( 37 | documents=documents, 38 | storage_context=storage_context, 39 | show_progress=True, 40 | ) 41 | print("finished ingesting...") 42 | -------------------------------------------------------------------------------- /README.MD: -------------------------------------------------------------------------------- 1 | 2 | # LlamaIndex Documentation Helper 3 | 4 | A repository for learning LlamaIndex by building a generative ai RAG application. 5 | 6 | This is a web application is using a Pinecone as a vectorstore and answers questions about LlamaIndex 7 | (sources from LlamaIndex official documentation). 8 | 9 | 10 | ![Logo](https://github.com/emarco177/llamaindex-documentation-helper/blob/main/static/banner.gif) 11 | 12 | [![udemy](https://img.shields.io/badge/LangChain%20Udemy%20Course-%2412.99-green)](https://www.udemy.com/course/langchain/?couponCode=LANGCHAINCD8C0B4060) 13 | 14 | ## Environment Variables 15 | 16 | To run this project, you will need to add the following environment variables to your .env file 17 | 18 | `PINECONE_API_KEY` 19 | `PINECONE_ENVIRONMENT_REGION` 20 | `OPENAI_API_KEY` 21 | 22 | ## Run Locally 23 | 24 | Clone the project 25 | 26 | ```bash 27 | git clone https://github.com/emarco177/llamaindex-documentation-helper.git 28 | ``` 29 | 30 | Go to the project directory 31 | 32 | ```bash 33 | cd llamaindex-documentation-helper 34 | ``` 35 | 36 | Download LlamaIndex Documentation 37 | ```bash 38 | python download_docs.py 39 | ``` 40 | 41 | Install dependencies 42 | 43 | ```bash 44 | pipenv install 45 | ``` 46 | 47 | Start streamlit 48 | 49 | ```bash 50 | streamlit run main.py 51 | ``` 52 | 53 | 54 | ## Running Tests 55 | 56 | To run tests, run the following command 57 | 58 | ```bash 59 | pipenv run pytest . 60 | ``` 61 | 62 | 63 | ## 🔗 Links 64 | [![portfolio](https://img.shields.io/badge/my_portfolio-000?style=for-the-badge&logo=ko-fi&logoColor=white)](https://www.udemy.com/course/langchain/?referralCode=D981B8213164A3EA91AC) 65 | [![linkedin](https://img.shields.io/badge/linkedin-0A66C2?style=for-the-badge&logo=linkedin&logoColor=white)](https://www.linkedin.com/in/eden-marco/) 66 | [![twitter](https://img.shields.io/badge/twitter-1DA1F2?style=for-the-badge&logo=twitter&logoColor=white)](https://www.udemy.com/user/eden-marco/) -------------------------------------------------------------------------------- /main.py: -------------------------------------------------------------------------------- 1 | from dotenv import load_dotenv 2 | from llama_index.core.chat_engine.types import ChatMode 3 | from llama_index.core.postprocessor import SentenceEmbeddingOptimizer 4 | 5 | from node_postprocessors.duplicate_postprocessing import ( 6 | DuplicateRemoverNodePostprocessor, 7 | ) 8 | 9 | load_dotenv() 10 | import os 11 | 12 | from llama_index.core.callbacks import LlamaDebugHandler, CallbackManager 13 | 14 | 15 | import streamlit as st 16 | from pinecone import Pinecone 17 | from llama_index.core import VectorStoreIndex 18 | from llama_index.vector_stores.pinecone import PineconeVectorStore 19 | 20 | from llama_index.core.settings import Settings 21 | from llama_index.llms.openai import OpenAI 22 | from llama_index.embeddings.openai import OpenAIEmbedding 23 | 24 | print("***Streamlit LlamaIndex Documentation Helper***") 25 | 26 | llama_debug = LlamaDebugHandler(print_trace_on_end=True) 27 | callback_manager = CallbackManager(handlers=[llama_debug]) 28 | 29 | Settings.llm = OpenAI() 30 | Settings.embed_model = OpenAIEmbedding(model="text-embedding-3-small") 31 | Settings.callback_manager = callback_manager 32 | 33 | 34 | @st.cache_resource(show_spinner=False) 35 | def get_index() -> VectorStoreIndex: 36 | pc = Pinecone(api_key=os.environ["PINECONE_API_KEY"]) 37 | pinecone_index = pc.Index(name="llamaindex-documentation-helper") 38 | vector_store = PineconeVectorStore(pinecone_index=pinecone_index) 39 | 40 | return VectorStoreIndex.from_vector_store(vector_store=vector_store) 41 | 42 | 43 | index = get_index() 44 | if "chat_engine" not in st.session_state.keys(): 45 | postprocessor = SentenceEmbeddingOptimizer( 46 | embed_model=OpenAIEmbedding(), 47 | percentile_cutoff=0.5, 48 | threshold_cutoff=0.7, 49 | ) 50 | 51 | st.session_state.chat_engine = index.as_chat_engine( 52 | chat_mode=ChatMode.CONTEXT, 53 | verbose=True, 54 | node_postprocessors=[postprocessor, DuplicateRemoverNodePostprocessor()], 55 | ) 56 | 57 | 58 | st.set_page_config( 59 | page_title="Chat with LlamaIndex docs, powered by LlamaIndex", 60 | page_icon="🦙", 61 | layout="centered", 62 | initial_sidebar_state="auto", 63 | menu_items=None, 64 | ) 65 | 66 | st.title("Chat with LlamaIndex docs 💬🦙") 67 | 68 | if "messages" not in st.session_state.keys(): 69 | st.session_state.messages = [ 70 | { 71 | "role": "assistant", 72 | "content": "Ask me a question about LlamaIndex's open source python library?", 73 | } 74 | ] 75 | 76 | 77 | if prompt := st.chat_input("Your question"): 78 | st.session_state.messages.append({"role": "user", "content": prompt}) 79 | 80 | for message in st.session_state.messages: 81 | with st.chat_message(message["role"]): 82 | st.write(message["content"]) 83 | 84 | if st.session_state.messages[-1]["role"] != "assistant": 85 | with st.chat_message("assistant"): 86 | with st.spinner("Thinking..."): 87 | response = st.session_state.chat_engine.chat(message=prompt) 88 | st.write(response.response) 89 | nodes = [node for node in response.source_nodes] 90 | for col, node, i in zip(st.columns(len(nodes)), nodes, range(len(nodes))): 91 | with col: 92 | st.header(f"Source Node {i+1}: score= {node.score}") 93 | st.write(node.text) 94 | message = {"role": "assistant", "content": response.response} 95 | st.session_state.messages.append(message) 96 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | share/python-wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | MANIFEST 28 | 29 | # PyInstaller 30 | # Usually these files are written by a python script from a template 31 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 32 | *.manifest 33 | *.spec 34 | 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .nox/ 43 | .coverage 44 | .coverage.* 45 | .cache 46 | nosetests.xml 47 | coverage.xml 48 | *.cover 49 | *.py,cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | cover/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | .pybuilder/ 76 | target/ 77 | 78 | # Jupyter Notebook 79 | .ipynb_checkpoints 80 | 81 | # IPython 82 | profile_default/ 83 | ipython_config.py 84 | 85 | # pyenv 86 | # For a library or package, you might want to ignore these files since the code is 87 | # intended to run in multiple environments; otherwise, check them in: 88 | # .python-version 89 | 90 | # pipenv 91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 92 | # However, in case of collaboration, if having 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