Metadata-Version: 2.1
Name: lense
Version: 0.0.71
Summary: For QandA
Home-page: https://github.com/tandan-kumar-covalenseglobal/Lense
Author: Covalense
Author-email: Admin@covalenseglobal.com
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.11
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: required
Requires-Dist: pandas ==2.2.2
Requires-Dist: PyPDF2 ==3.0.1
Requires-Dist: python-docx ==1.1.0
Requires-Dist: python-pptx ==0.6.23
Requires-Dist: llama-index ==0.10.29
Requires-Dist: llama-index.llms.azure-openai ==0.1.5
Requires-Dist: llama-index.embeddings.azure-openai ==0.1.6
Requires-Dist: langchain ==0.1.16
Requires-Dist: huggingface-hub ==0.22.2
Requires-Dist: PyMuPDF ==1.24.1
Requires-Dist: sentence-transformers ==2.6.1
Requires-Dist: llama-index-embeddings-langchain ==0.1.2
Requires-Dist: llama-index-llms-langchain ==0.1.3
Requires-Dist: llama-index.experimental ==0.1.3
Requires-Dist: langchain-google-genai ==1.0.2
Requires-Dist: langchain-experimental ==0.0.57
Requires-Dist: langchain-openai ==0.1.3
Requires-Dist: psycopg2 ==2.9.9
Requires-Dist: fastapi ==0.110.2
Requires-Dist: python-multipart ==0.0.9
Requires-Dist: uvicorn ==0.29.0
Requires-Dist: langchain-community ==0.0.34
Requires-Dist: nest-asyncio

lensegt

LenseGt is a toolkit for QandA using RAG approach. It offers the users to extract answers to users from the doc. 

# Table of Contents

# Motivation
# Features
# Installation
# usage


# Motivation:
In market, we have many models and it's a challenge for developer or end user to connect to model and every time they need to write the code. SO, we come up with lensegt which helps the user to connect to any model with least amount of time on code.

# Features

This module can be used based on gui as well as cli 

#  Installation 
 pip install lense

# Usage
   # Cli-mode
        from lensegt import lense
        filename = "abc.pdf"
        lense.load_file(filename) 

            for openai connections 
            lense.engine(engine_type="OpenAI",api_key="sk-I4***J1TbO1")

            for azureopen ai
            lense.engine(engine_type="Azure OpenAI",api_key= "17b15**6f",api_version="2017-*-preview" ,azure_endpoint="https://covalenseopenaieastus2.openai.azure.com/")

        lense.chat_query("summary of the file")

   # for GUI
       from lensegt import lense
       lense.start()


          
 



