https://github.com/jackeygao/thoughtsgpt

🍔 thoughtsGPT
https://github.com/jackeygao/thoughtsgpt

gpt rag

Last synced: about 1 month ago
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🍔 thoughtsGPT

• Host: GitHub
• URL: https://github.com/jackeygao/thoughtsgpt
• Owner: jackeyGao
• Created: 2023-10-18T07:35:10.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2023-10-23T14:07:59.000Z (about 1 year ago)
• Last Synced: 2024-10-14T19:42:39.461Z (3 months ago)
• Topics: gpt, rag
• Language: Python
• Homepage: https://feishu.streamlit.app/
• Size: 63 MB
• Stars: 0
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
## 🍔 thoughtsGPT

Knowledge document AI assistant, GPT 有所思。

[🍨 demo](https://feishu.streamlit.app/)

## used langchain module

- core/parsing.py:from langchain.docstore.document import Document

- core/parsing.py:from langchain.document_loaders.url import UnstructuredURLLoader

- core/prompts.py:from langchain.prompts import PromptTemplate

- core/prompts.py:from langchain.chains.qa_with_sources.stuff_prompt import template # this template

- core/chunking.py:from langchain.text_splitter import RecursiveCharacterTextSplitter

- core/utils.py:from langchain.chains.combine_documents.stuff import StuffDocumentsChain

- core/utils.py:from langchain.chat_models import ChatOpenAI

- core/utils.py:from langchain.chat_models.base import BaseChatModel

- core/debug.py:from langchain.vectorstores import VectorStore

- core/debug.py:from langchain.embeddings.base import Embeddings

- core/debug.py:from langchain.embeddings.fake import FakeEmbeddings as FakeEmbeddingsBase

- core/debug.py:from langchain.chat_models.fake import FakeListChatModel

- core/qa.py:from langchain.chains.qa_with_sources import load_qa_with_sources_chain

- core/qa.py:from langchain.prompts import PromptTemplate

- core/qa.py:from langchain.chat_models.base import BaseChatModel

- core/embedding.py:from langchain.vectorstores import VectorStore

- core/embedding.py:from langchain.vectorstores.faiss import FAISS

- core/embedding.py:from langchain.vectorstores.chroma import Chroma

- core/embedding.py:from langchain.embeddings import OpenAIEmbeddings

- core/embedding.py:from langchain.embeddings.base import Embeddings

- core/embedding.py:from langchain.docstore.document import Document