Unstract Adapters
Project description
Unstract Adapters
This is Unstract's python package which helps to configure to a number of different LLMs, Embeddings and VectorDBs.
LLMs
The following LLMs are supported:
LLM | Version |
---|---|
OpenAI | 1.3.9 |
Azure OpenAI | 1.3.9 |
Anthropic | 0.7.8 |
PaLM | 0.3.1 |
Replicate | 0.22.0 |
AnyScale | 0.5.165 |
Mistral | 0.0.8 |
Embeddings
The following Embeddings are supported:
Embedding | Version |
---|---|
OpenAI | 1.3.9 |
Azure OpenAI | 1.3.9 |
Qdrant FastEmbed | 0.1.3 |
HuggingFace | 0.0.1 |
PaLM | 0.3.1 |
VectorDBs
The following VectorDBs are supported:
Vector DB | Version |
---|---|
Milvus | 2.3.4 |
Pinecone | 2.2.4 |
Postgres | 0.2.4 |
Qdrant | 1.7.0 |
Supabase | 2.2.1 |
Weaviate | 3.25.3 |
Installation
Local Development
To get started with local development,
- Create and source a virtual environment if you haven't already following these steps.
- If you're using Mac, install the below library needed for PyMSSQL
brew install pkg-config freetds
- Install the required dependencies with
pdm install
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
unstract_adapters-0.6.0.tar.gz
(60.5 kB
view details)
Built Distribution
File details
Details for the file unstract_adapters-0.6.0.tar.gz
.
File metadata
- Download URL: unstract_adapters-0.6.0.tar.gz
- Upload date:
- Size: 60.5 kB
- Tags: Source
- Uploaded using Trusted Publishing? Yes
- Uploaded via: pdm/2.12.3 CPython/3.8.10
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 29ef970d5f7c06b80093fc8984adc5c8eb440606e87cc2733dc85bfa331ca7ce |
|
MD5 | 205e45a34c8567ac70531aca2510777e |
|
BLAKE2b-256 | 601566ec74fcd9c5e4a4e1ca0349193f515f7b401e3522a16c13b14e109837e4 |
Provenance
File details
Details for the file unstract_adapters-0.6.0-py3-none-any.whl
.
File metadata
- Download URL: unstract_adapters-0.6.0-py3-none-any.whl
- Upload date:
- Size: 116.3 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? Yes
- Uploaded via: pdm/2.12.3 CPython/3.8.10
File hashes
Algorithm | Hash digest | |
---|---|---|
SHA256 | 6b16655c27115ced06d2ab36a1779d357a00e986a8c8a47f997011271c4e5436 |
|
MD5 | fab6c65c742d58cacb4e6e6bc9651194 |
|
BLAKE2b-256 | 2341b2d87f2516b2d4fa632afa95debc532cd760ee725631d718a2c1ff46c66b |