CodeCow/Scrapegraph-ai
1
0
Fork 0
mirror of https://github.com/VinciGit00/Scrapegraph-ai.git synced 2026-06-25 21:11:11 +08:00
Code Issues Actions Packages Projects Releases Wiki Activity

ci(release): 0.7.0-beta.2 [skip ci]

Browse Source 
## [0.7.0-beta.2](https://github.com/VinciGit00/Scrapegraph-ai/compare/v0.7.0-beta.1...v0.7.0-beta.2) (2024-05-03)

### Features

* Azure implementation + embeddings refactoring ([aa9271e](aa9271e7bc))

### Refactor

* Changed the way embedding model is created in AbstractGraph class and removed handling of embedding model creation from RAGNode. Now AbstractGraph will call a dedicated method for embedding models instead of _create_llm. This makes it easy to use any LLM with any supported embedding model. ([819cbcd](819cbcd3be))
This commit is contained in:
semantic-release-bot 2024-05-03 19:41:30 +00:00
parent aa9271e7bc
commit 42fa02e65a
2 changed files with 13 additions and 1 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

12
CHANGELOG.md
View File

@ -1,3 +1,15 @@
## [0.7.0-beta.2](https://github.com/VinciGit00/Scrapegraph-ai/compare/v0.7.0-beta.1...v0.7.0-beta.2) (2024-05-03)
### Features
* Azure implementation + embeddings refactoring ([aa9271e](https://github.com/VinciGit00/Scrapegraph-ai/commit/aa9271e7bc4daa54860499d0615580b17550ff58))
### Refactor
* Changed the way embedding model is created in AbstractGraph class and removed handling of embedding model creation from RAGNode. Now AbstractGraph will call a dedicated method for embedding models instead of _create_llm. This makes it easy to use any LLM with any supported embedding model. ([819cbcd](https://github.com/VinciGit00/Scrapegraph-ai/commit/819cbcd3be1a8cb195de0b44c6b6d4d824e2a42a))
## [0.7.0-beta.1](https://github.com/VinciGit00/Scrapegraph-ai/compare/v0.6.2...v0.7.0-beta.1) (2024-05-03)

2
pyproject.toml
View File

@ -1,7 +1,7 @@
[tool.poetry]
name = "scrapegraphai"
version = "0.7.0b1"
version = "0.7.0b2"
description = "A web scraping library based on LangChain which uses LLM and direct graph logic to create scraping pipelines."
authors = [