RAG

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# Definition of used LLM

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def graphPrompt(input: str, metadata={}, model="mixtral:latest"):

if model == None:

model = "mixtral:latest"

chunk_id = metadata.get('chunk_id', None)

# model_info =... See more

Continuously Monitor and Experiment¶

Continuously monitor your system's performance and run experiments to test improvements.

• Set up monitoring and logging to track system performance over time


• Regularly review the data to identify trends and issues


• Design and run experiments to test potential improvements


• Measure the impact of changes on precision,

... See more

Introducing Wren Engine

The advent of Trend AI agents has revolutionized the landscape of business intelligence and data management. In the near future, multiple AI agents will be deployed to harness and interpret vast amounts of internal knowledge stored within databases and data warehouses. To facilitate this, a semantic engine is crucial. This... See more

Elasticsearch at Twitter

Elasticsearch is a search engine based on the Lucene library. It is a popular open source tool widely used in industry and is known for its distributed nature, speed, scalability, and simple REST APIs.

The Search Infrastructure team builds infrastructure to host search as a service. Since we are such a central... See more

Balance Latency and Performance¶

Finally, make informed decisions about trade-offs between system latency and search performance based on your specific use case and user requirements.

• Understand the latency and performance requirements for your application


• Measure the impact of different configurations on latency and performance


• Make trade-offs based

... See more

Welcome to RAGatouille

Easily use and train state of the art retrieval methods in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.

The main motivation of RAGatouille is simple: bridging the gap between state-of-the-art research and alchemical RAG pipeline practices. RAG is complex, and there are many moving parts. To... See more

Unlike some other popular algorithms, DiskANN is designed to keep memory usage to a minimum. This makes it a great match for use cases where Turso already excels at.

#Multitenancy

Turso allows for an easy implementation of a database-per-tenant pattern, where databases can be cheaply created on-demand. Keeping memory consumption at bay is critical... See more

FuzzTypes

FuzzTypes is a set of "autocorrecting" annotation types that expands upon Pydantic's included data conversions. Designed for simplicity, it provides powerful normalization capabilities (e.g. named entity linking) to ensure structured data is composed of "smart things" not "dumb strings".

Ensuring relevant metadata (e.g., date ranges, file names, ownership) is extracted and searchable is crucial for improving search results.

• Extract relevant metadata from your documents


• Include metadata in your search indexes


• Use query understanding to extract metadata from user queries


• Expand search queries with relevant metadata to improve results

For... See more