| # PaperChat | |
| This repo is an implementation of a chatbot specifically focused on question answering over the [LangChain documentation](https://langchain.readthedocs.io/en/latest/). | |
| ## 🚀 Important Links | |
| Website: [chat.langchain.dev](https://chat.langchain.dev) | |
| Hugging Face Spage: [huggingface.co/spaces/hwchase17/chat-langchain](https://huggingface.co/spaces/hwchase17/chat-langchain) | |
| Blog Post: [blog.langchain.dev/langchain-chat/](https://blog.langchain.dev/langchain-chat/) | |
| ## 📚 Technical description | |
| There are two components: ingestion and question-answering. | |
| Ingestion has the following steps: | |
| 1. Pull html from documentation site | |
| 2. Parse html with BeautifulSoup | |
| 3. Split documents with LangChain's [TextSplitter](https://langchain.readthedocs.io/en/latest/modules/utils/combine_docs_examples/textsplitter.html) | |
| 4. Create a vectorstore of embeddings, using LangChain's [vectorstore wrapper](https://langchain.readthedocs.io/en/latest/modules/utils/combine_docs_examples/vectorstores.html) (with OpenAI's embeddings and Weaviate's vectorstore) | |
| Question-Answering has the following steps: | |
| 1. Given the chat history and new user input, determine what a standalone question would be (using GPT-3) | |
| 2. Given that standalone question, look up relevant documents from the vectorstore | |
| 3. Pass the standalone question and relevant documents to GPT-3 to generate a final answer | |
| ## 🧠 How to Extend to your documentation | |
| Coming soon. | |