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llm-app
LLM App templates for RAG, knowledge mining, and stream analytics. Ready to run with Docker,⚡in sync with your data sources.
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chatgpt-api-python-sales
Find real-time sales with AI-powered Python API using ChatGPT and LLM (Large Language Model) App.
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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pathway
Pathway is a high-throughput, low-latency data processing framework that handles live data & streaming for you. Made with ❤️ for Python & ML/AI developers.
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
In this case, you need to build a custom LLM (Language Learning Model) app efficiently to give context to the answer process. A promising approach you find on the internet is utilizing LLMs with vector databases that come with costs like increased prep work, infrastructure, and complexity. Keeping source and vectors in sync is painful. Instead, you can use an open-source LLM App library in Python to implement real-time in-memory data indexing directly reading data from any compatible storage and showing this data on Streamlit UI.
You can follow the steps below to understand how to build a discount finder app. The project source code can be found on GitHub. If you want to quickly start using the app, you can skip this part clone the repository, and run the code sample by following the instructions in the README.md file there. The tutorial consists of two parts:
Inspired by this article around enterprise search, our sample app should expose an HTTP REST API endpoint in Python to answer user queries about current sales by retrieving the latest deals from various sources (CSV, Jsonlines, API, message brokers, or databases), filters and presents deals based on user queries or chosen data sources, leverages OpenAI API Embeddings and Chat Completion endpoints to generate AI assistant responses and offers user-friendly UI with Streamlit.
Maintain a data snapshot to observe variations in sales prices over time, as Pathway provides a built-in feature to compute differences between two alterations.
For example, when you ask ChatGPT “Can you find me discounts this week for Adidas men’s shoes?”, a standard response you can get from the ChatGPT UI interface without having custom knowledge is:
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