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Improve titles and order of Features (#449)
* Clarify Arrow engine usage * Tweak title and order of Features in sidebar
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spiceaidocs/docs/features/configurable-llms/default_overrides.md renamed to spiceaidocs/docs/features/ai-gateway/default_overrides.md

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---
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title: 'AI Gateway - Configuring LLMs'
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sidebar_label: 'AI Gateway'
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description: 'Learn how to configure language models and use Spice as an AI Gateway.'
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---
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Spice provides a high-performance, OpenAI API-compatible AI Gateway optimized for managing and scaling large language models (LLMs).
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Additionally, Spice offers tools for Enterprise Retrieval-Augmented Generation (RAG), such as SQL query across federated datasets and an advanced search feature (see [Search](/features/search)).
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Spice also supports **full OpenTelemetry observability**, enabling detailed tracking of data flows and requests for full transparency and easier debugging.
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## Configuring Language Models
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Spice supports a variety of LLMs (see [Model Components](/components/models/index.md)).
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### Core Features
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- **Custom Tools**: Equip models with tools to interact with the Spice runtime.
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- **System Prompts**: Customize system prompts and override defaults for [`v1/chat/completion`](/api/http/chat-completions.md).
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For detailed configuration and API usage, refer to the [API Documentation](/api).

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spiceaidocs/docs/features/caching/index.md

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title: 'Results Caching'
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sidebar_label: 'Results Caching'
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description: 'Learn how to use Spice in-memory caching of query results'
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title: 'Change Data Capture (CDC)'
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sidebar_label: 'Change Data Capture'
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description: 'Learn how to use Change Data Capture (CDC) in Spice.'
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---
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Change Data Capture (CDC) is a technique to capture changed rows from a database's transaction log and deliver to consumers with low latency. Leveraging this technique allows Spice to keep [locally accelerated](../local-acceleration/index.md) datasets up-to-date in real-time with the source data, and is highly efficient by only transferring the changed rows instead of re-fetching the entire dataset on refresh.
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Change Data Capture (CDC) is a technique to capture changed rows from a database's transaction log and deliver to consumers with low latency. Leveraging this technique allows Spice to keep [locally accelerated](../data-acceleration/index.md) datasets up-to-date in real-time with the source data, and is highly efficient by only transferring the changed rows instead of re-fetching the entire dataset on refresh.
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## Benefits
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spiceaidocs/docs/features/configurable-llms/index.md

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title: 'Local Acceleration'
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sidebar_label: 'Local Acceleration'
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description: 'Learn how to use local acceleration in Spice.'
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title: 'Data Acceleration'
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sidebar_label: 'Data Acceleration'
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description: 'Learn how to use local data acceleration in Spice.'
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sidebar_position: 2
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spiceaidocs/docs/features/data-ingestion/index.md

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title: 'Data Ingestion'
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sidebar_label: 'Data Ingestion'
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description: 'Learn how to ingest data in Spice.'
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Data can be ingested by the Spice runtime for replication to a Data Connector, like PostgreSQL or the Spice.ai Cloud platform.
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By default, the runtime exposes an [OpenTelemety](https://opentelemetry.io) (OTEL) endpoint at grpc://127.0.0.1:50052 for data ingestion.
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- Only Spice.ai replication is supported for now.
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