LangChain Web Interface with Streamlit

This code is designed to create a web interface for the LangChain Library using Streamlit. LangChain is a library for natural language processing and machine learning tasks. The web interface allows users to interact with LangChain and perform various language-related tasks.

Code Overview

The code performs the following steps:

1. Import necessary libraries:

   • langchain.vectorstores.Pinecone: Import Pinecone for vector indexing.
   • langchain.embeddings.openai.OpenAIEmbeddings: Import OpenAI embeddings for natural language understanding.
   • langchain.chat_models.ChatOpenAI: Import the ChatOpenAI model for chat-based language tasks.
   • langchain.chains.RetrievalQA: Import RetrievalQA for question-answering tasks.
   • pinecone: Import Pinecone Python SDK for working with Pinecone.
   • streamlit: Import Streamlit for building the web interface.
   • os: Import the operating system module for handling environment variables.
   • mojafunkcja: Import custom functions (st_style, positive_login, init_cond_llm) from a module named mojafunkcja.

2. Configure Streamlit settings:

   • Set the page title, icon, and layout for the Streamlit web app.

3. Define the main function:

   • Initialize various environment variables, such as OPENAI_API_KEY, PINECONE_API_KEY, and PINECONE_API_ENV.
   • Initialize OpenAI embeddings and Pinecone indexing.
   • Create a Pinecone index for storing embeddings.
   • Set up the Streamlit sidebar with an image.
   • Define the main user interface components and interaction logic.
   • Allow users to input text queries.
   • Use LangChain to process user queries and generate responses.
   • Enable users to download the generated responses as a text file.

4. Execute the main function:

   • Authenticate users using the positive_login function.
   • Launch the Streamlit app with the specified configurations.

Usage Instructions

Users can interact with the web interface by entering text queries in the provided input field and clicking the "Submit" button. LangChain processes the queries and generates responses, which are displayed on the interface. Users can also download the generated responses as a text file.

Environmental Variables

To run this code, you may need to set the following environment variables:

• OPENAI_API_KEY: An API key for OpenAI services.
• PINECONE_API_KEY: An API key for Pinecone services.
• PINECONE_API_ENV: The environment for Pinecone (e.g., "production" or "development").

Additional Information

This code provides a user-friendly interface for leveraging LangChain's natural language processing capabilities and can be useful for various language-related tasks.

For more details and usage examples, please refer to the code and accompanying documentation on GitHub.

Script Details

• Author: Positive
• Date: 07.09.2023
• License: MIT