Best Retrieval-Augmented Generation (RAG) Software for Python
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Compare the Top Retrieval-Augmented Generation (RAG) Software that integrates with Python as of July 2025
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This a list of Retrieval-Augmented Generation (RAG) software that integrates with Python. Use the filters on the left to add additional filters for products that have integrations with Python. View the products that work with Python in the table below.
What is Retrieval-Augmented Generation (RAG) Software for Python?
Retrieval-Augmented Generation (RAG) tools are advanced AI systems that combine information retrieval with text generation to produce more accurate and contextually relevant outputs. These tools first retrieve relevant data from a vast corpus or database, and then use that information to generate responses or content, enhancing the accuracy and detail of the generated text. RAG tools are particularly useful in applications requiring up-to-date information or specialized knowledge, such as customer support, content creation, and research. By leveraging both retrieval and generation capabilities, RAG tools improve the quality of responses in tasks like question-answering and summarization. This approach bridges the gap between static knowledge bases and dynamic content generation, providing more reliable and context-aware results. Compare and read user reviews of the best Retrieval-Augmented Generation (RAG) software for Python currently available using the table below. This list is updated regularly.
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1
Vertex AI
Google
Vertex AI Search is a powerful, scalable enterprise search solution from Google Cloud, designed to deliver Google-quality search experiences across websites, intranets, and custom applications. The platform leverages advanced crawling, document understanding, and generative AI capabilities to provide highly relevant search results. It integrates seamlessly with existing business systems and supports features like real-time updates, vector search, and RAG (Retrieval Augmented Generation) for enhancing generative AI applications. Vertex AI Search is tailored for industries such as retail, healthcare, and media, offering specialized solutions that improve both search performance and customer engagement.Starting Price: Free ($300 in free credits) -
2
Mistral AI
Mistral AI
Mistral AI is a pioneering artificial intelligence startup specializing in open-source generative AI. The company offers a range of customizable, enterprise-grade AI solutions deployable across various platforms, including on-premises, cloud, edge, and devices. Flagship products include "Le Chat," a multilingual AI assistant designed to enhance productivity in both personal and professional contexts, and "La Plateforme," a developer platform that enables the creation and deployment of AI-powered applications. Committed to transparency and innovation, Mistral AI positions itself as a leading independent AI lab, contributing significantly to open-source AI and policy development.Starting Price: Free -
3
Cohere
Cohere AI
Cohere is an enterprise AI platform that enables developers and businesses to build powerful language-based applications. Specializing in large language models (LLMs), Cohere provides solutions for text generation, summarization, and semantic search. Their model offerings include the Command family for high-performance language tasks and Aya Expanse for multilingual applications across 23 languages. Focused on security and customization, Cohere allows flexible deployment across major cloud providers, private cloud environments, or on-premises setups to meet diverse enterprise needs. The company collaborates with industry leaders like Oracle and Salesforce to integrate generative AI into business applications, improving automation and customer engagement. Additionally, Cohere For AI, their research lab, advances machine learning through open-source projects and a global research community.Starting Price: Free -
4
HyperCrawl
HyperCrawl
HyperCrawl is the first web crawler designed specifically for LLM and RAG applications and develops powerful retrieval engines. Our focus was to boost the retrieval process by eliminating the crawl time of domains. We introduced multiple advanced methods to create a novel approach to building an ML-first web crawler. Instead of waiting for each webpage to load one by one (like standing in line at the grocery store), it asks for multiple web pages at the same time (like placing multiple online orders simultaneously). This way, it doesn’t waste time waiting and can move on to other tasks. By setting a high concurrency, the crawler can handle multiple tasks simultaneously. This speeds up the process compared to handling only a few tasks at a time. HyperLLM reduces the time and resources needed to open new connections by reusing existing ones. Think of it like reusing a shopping bag instead of getting a new one every time.Starting Price: Free -
5
Llama 3.2
Meta
The open-source AI model you can fine-tune, distill and deploy anywhere is now available in more versions. Choose from 1B, 3B, 11B or 90B, or continue building with Llama 3.1. Llama 3.2 is a collection of large language models (LLMs) pretrained and fine-tuned in 1B and 3B sizes that are multilingual text only, and 11B and 90B sizes that take both text and image inputs and output text. Develop highly performative and efficient applications from our latest release. Use our 1B or 3B models for on device applications such as summarizing a discussion from your phone or calling on-device tools like calendar. Use our 11B or 90B models for image use cases such as transforming an existing image into something new or getting more information from an image of your surroundings.Starting Price: Free -
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Llama 3.3
Meta
Llama 3.3 is the latest iteration in the Llama series of language models, developed to push the boundaries of AI-powered understanding and communication. With enhanced contextual reasoning, improved language generation, and advanced fine-tuning capabilities, Llama 3.3 is designed to deliver highly accurate, human-like responses across diverse applications. This version features a larger training dataset, refined algorithms for nuanced comprehension, and reduced biases compared to its predecessors. Llama 3.3 excels in tasks such as natural language understanding, creative writing, technical explanation, and multilingual communication, making it an indispensable tool for businesses, developers, and researchers. Its modular architecture allows for customizable deployment in specialized domains, ensuring versatility and performance at scale.Starting Price: Free -
7
Pathway
Pathway
Pathway is a Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG. Pathway comes with an easy-to-use Python API, allowing you to seamlessly integrate your favorite Python ML libraries. Pathway code is versatile and robust: you can use it in both development and production environments, handling both batch and streaming data effectively. The same code can be used for local development, CI/CD tests, running batch jobs, handling stream replays, and processing data streams. Pathway is powered by a scalable Rust engine based on Differential Dataflow and performs incremental computation. Your Pathway code, despite being written in Python, is run by the Rust engine, enabling multithreading, multiprocessing, and distributed computations. All the pipeline is kept in memory and can be easily deployed with Docker and Kubernetes. -
8
Linkup
Linkup
Linkup is an AI tool designed to enhance language models by enabling them to access and interact with real-time web content. By integrating directly with AI pipelines, Linkup provides a way to retrieve relevant, up-to-date data from trusted sources 15 times faster than traditional web scraping methods. This allows AI models to answer queries with accurate, real-time information, enriching responses and reducing hallucinations. Linkup supports content retrieval across multiple media formats including text, images, PDFs, and videos, making it versatile for a wide range of applications, from fact-checking and sales call preparation to trip planning. The platform also simplifies AI interaction with web content, eliminating the need for complex scraping setups and cleaning data. Linkup is designed to integrate seamlessly with popular LLMs like Claude and offers no-code options for ease of use.Starting Price: €5 per 1,000 queries -
9
Orq.ai
Orq.ai
Orq.ai is the #1 platform for software teams to operate agentic AI systems at scale. Optimize prompts, deploy use cases, and monitor performance, no blind spots, no vibe checks. Experiment with prompts and LLM configurations before moving to production. Evaluate agentic AI systems in offline environments. Roll out GenAI features to specific user groups with guardrails, data privacy safeguards, and advanced RAG pipelines. Visualize all events triggered by agents for fast debugging. Get granular control on cost, latency, and performance. Connect to your favorite AI models, or bring your own. Speed up your workflow with out-of-the-box components built for agentic AI systems. Manage core stages of the LLM app lifecycle in one central platform. Self-hosted or hybrid deployment with SOC 2 and GDPR compliance for enterprise security. -
10
Databricks Data Intelligence Platform
Databricks
The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker. -
11
Dify
Dify
Dify is an open-source platform designed to streamline the development and operation of generative AI applications. It offers a comprehensive suite of tools, including an intuitive orchestration studio for visual workflow design, a Prompt IDE for prompt testing and refinement, and enterprise-level LLMOps capabilities for monitoring and optimizing large language models. Dify supports integration with various LLMs, such as OpenAI's GPT series and open-source models like Llama, providing flexibility for developers to select models that best fit their needs. Additionally, its Backend-as-a-Service (BaaS) features enable seamless incorporation of AI functionalities into existing enterprise systems, facilitating the creation of AI-powered chatbots, document summarization tools, and virtual assistants. -
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Second State
Second State
Fast, lightweight, portable, rust-powered, and OpenAI compatible. We work with cloud providers, especially edge cloud/CDN compute providers, to support microservices for web apps. Use cases include AI inference, database access, CRM, ecommerce, workflow management, and server-side rendering. We work with streaming frameworks and databases to support embedded serverless functions for data filtering and analytics. The serverless functions could be database UDFs. They could also be embedded in data ingest or query result streams. Take full advantage of the GPUs, write once, and run anywhere. Get started with the Llama 2 series of models on your own device in 5 minutes. Retrieval-argumented generation (RAG) is a very popular approach to building AI agents with external knowledge bases. Create an HTTP microservice for image classification. It runs YOLO and Mediapipe models at native GPU speed. -
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Superlinked
Superlinked
Combine semantic relevance and user feedback to reliably retrieve the optimal document chunks in your retrieval augmented generation system. Combine semantic relevance and document freshness in your search system, because more recent results tend to be more accurate. Build a real-time personalized ecommerce product feed with user vectors constructed from SKU embeddings the user interacted with. Discover behavioral clusters of your customers using a vector index in your data warehouse. Describe and load your data, use spaces to construct your indices and run queries - all in-memory within a Python notebook. -
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TopK
TopK
TopK is a serverless, cloud-native, document database built for powering search applications. It features native support for both vector search (vectors are simply another data type) and keyword search (BM25-style) in a single, unified system. With its powerful query expression language, TopK enables you to build reliable search applications (semantic search, RAG, multi-modal, you name it) without juggling multiple databases or services. Our unified retrieval engine will evolve to support document transformation (automatically generate embeddings), query understanding (parse metadata filters from user query), and adaptive ranking (provide more relevant results by sending “relevance feedback” back to TopK) under one unified roof.
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