src/readme.md

# OpenAI Embedding and Query Processing

This Python script is designed to interact with OpenAI's GPT-3.5 Turbo model and the OpenAI Embedding API. It provides functionality for creating and loading embeddings, calculating vector similarity, ordering document sections by query similarity, and constructing prompts for the GPT-3.5 Turbo model.

## Key Features

1. **Embedding Creation and Loading**: The script includes functions for creating embeddings for each row in a dataframe using the OpenAI Embedding API (`compute_doc_embeddings`) and for loading embeddings from a CSV file (`load_embeddings`).

2. **Vector Similarity**: The `vector_similarity` function calculates the similarity between two vectors. This is used to compare the embedding of a user's query with the embeddings of document sections.

3. **Document Section Ordering**: The `order_document_sections_by_query_similarity` function compares the embedding of a user's query with the embeddings of document sections and returns a list of document sections sorted by relevance in descending order.

4. **Prompt Construction**: The `construct_prompt` function constructs a prompt for the GPT-3.5 Turbo model based on a user's query and the most relevant document sections.

5. **Query Answering**: The `answer_query_with_context` function uses the GPT-3.5 Turbo model to generate a response to a user's query. It constructs a prompt based on the user's query and the most relevant document sections, sends this prompt to the GPT-3.5 Turbo model, and returns the model's response.

## Usage

To use this script, you will need to import it into your Python project and call the functions as needed. For example, you might use the `compute_doc_embeddings` function to create embeddings for your document sections, the `order_document_sections_by_query_similarity` function to order the sections by relevance to a user's query, and the `answer_query_with_context` function to generate a response to the query.

## Dependencies

This script requires the following Python packages:

- OpenAI
- Tiktoken
- Numpy
- Pandas
- Configparser
- Warnings

These can be installed using pip:

```bash
pip install openai tiktoken numpy pandas configparser warnings