chore: merge origin/main into mintlify/af82bda4 and resolve conflicts
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mintlify[bot]
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---
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title: Configurations
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description: "Reference for Mem0 LLM configuration keys in Python and TypeScript, covering provider precedence, environment variables, and per-provider parameters."
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title: "LLM Configuration Reference"
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sidebarTitle: "Configurations"
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description: "Reference for LLM configuration options in Mem0 for Python and TypeScript, including value precedence rules."
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---
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## How to define configurations?
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## Supported LLMs
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For detailed information on configuring specific LLMs, please visit the [LLMs](./models) section. There you'll find information for each supported LLM with provider-specific usage examples and configuration details.
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For detailed information on configuring specific LLMs, please visit the [LLMs](./overview) section. There you'll find information for each supported LLM with provider-specific usage examples and configuration details.
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---
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title: AWS Bedrock
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description: "Run Claude and other Bedrock LLMs in Mem0 using boto3 or the AWS SDK Converse API, with IAM credentials and cross-region inference profile support."
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title: "AWS Bedrock as LLM Provider"
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sidebarTitle: "AWS Bedrock"
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description: "Configure AWS Bedrock as an LLM provider in Mem0 with IAM authentication and Claude model support."
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---
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### Setup
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The TypeScript provider calls the Bedrock [Converse API](https://docs.aws.amazon.com/bedrock/latest/userguide/conversation-inference.html), a single uniform interface across the current Bedrock model families. Streaming and `InvokeModel`-only models are not supported yet.
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</Note>
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### Application inference profiles
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Bedrock resolves the model family from the model identifier. An application inference profile ARN ends in an opaque ID, so there is nothing to resolve from. Set `provider_override` (Python) / `providerOverride` (TypeScript) when your model is one:
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<CodeGroup>
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```python Python
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config = {
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"llm": {
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"provider": "aws_bedrock",
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"config": {
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"model": "arn:aws:bedrock:us-east-1:123456789012:application-inference-profile/abc123xyz",
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"provider_override": "anthropic",
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}
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}
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}
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```
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```typescript TypeScript
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const config = {
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llm: {
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provider: 'aws_bedrock',
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config: {
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model: 'arn:aws:bedrock:us-east-1:123456789012:application-inference-profile/abc123xyz',
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providerOverride: 'anthropic',
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},
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},
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};
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```
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</CodeGroup>
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Without it, initialization raises `Unknown provider in model` (Python: `ValueError`; TypeScript: `Error`). Plain model IDs and cross-region inference profiles such as `us.anthropic.claude-sonnet-4-20250514-v1:0` still resolve automatically and need no override.
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### Config
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All available parameters for the `aws_bedrock` config are present in [Master List of All Params in Config](../config).
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---
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title: Azure OpenAI
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description: "Use Azure OpenAI deployments as a Mem0 LLM with API key or Azure Identity auth, including the azure_openai_structured provider for structured output."
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title: "Azure OpenAI as LLM Provider"
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sidebarTitle: "Azure OpenAI"
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description: "Configure Azure OpenAI as an LLM provider in Mem0 with Azure Identity authentication and deployment settings."
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---
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<Note> Mem0 Now Supports Azure OpenAI Models in TypeScript SDK </Note>
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description: "Use DeepSeek chat models such as deepseek-chat as a Mem0 LLM with the DEEPSEEK_API_KEY and an optional DEEPSEEK_API_BASE custom endpoint URL."
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---
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To use DeepSeek LLM models, you have to set the `DEEPSEEK_API_KEY` environment variable. You can also optionally set `DEEPSEEK_API_BASE` if you need to use a different API endpoint (defaults to "https://api.deepseek.com").
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To use DeepSeek LLM models, you have to set the `DEEPSEEK_API_KEY` environment variable. You can also optionally set `DEEPSEEK_API_BASE` if you need to use a different API endpoint (defaults to `https://api.deepseek.com`).
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## Usage
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---
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title: Google AI
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description: "Use Google Gemini models like gemini-2.0-flash-001 as a Mem0 LLM through the new google.genai SDK with the GOOGLE_API_KEY environment variable."
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title: "Google AI as LLM Provider"
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sidebarTitle: "Google AI"
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description: "Configure Google Gemini as an LLM provider in Mem0 using the google.genai SDK and GOOGLE_API_KEY variable."
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---
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To use the Gemini model, set the `GOOGLE_API_KEY` environment variable. You can obtain the Google/Gemini API key from [Google AI Studio](https://aistudio.google.com/app/apikey).
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---
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title: LangChain
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description: "Wire LangChain ChatOpenAI, ChatAnthropic, and other chat model classes into Mem0 as the LLM provider to reuse existing LangChain integrations."
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title: "LangChain as LLM Provider"
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sidebarTitle: "LangChain"
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description: "Use LangChain as an LLM provider in Mem0 to integrate with various chat models through a unified interface."
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---
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---
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title: LM Studio
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description: "Run local GGUF models in Mem0 via LM Studio server on localhost:1234 using its OpenAI-compatible API, with optional lmstudio_response_format schema."
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title: "LM Studio as LLM Provider"
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sidebarTitle: "LM Studio"
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description: "Configure LM Studio as an LLM provider in Mem0 for running local language models via an OpenAI-compatible API."
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---
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To use LM Studio with Mem0, you'll need to have LM Studio running locally with its server enabled. LM Studio provides a way to run local LLMs with an OpenAI-compatible API.
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To use LM Studio, you need to:
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1. Download and install [LM Studio](https://lmstudio.ai/)
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2. Start a local server from the "Server" tab
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3. Set the appropriate `lmstudio_base_url` in your configuration (default is usually http://localhost:1234/v1)
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3. Set the appropriate `lmstudio_base_url` in your configuration (default is usually `http://localhost:1234/v1`)
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</Note>
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## Config
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description: "Use MiniMax chat models like MiniMax-M2.7 as a Mem0 LLM with the MINIMAX_API_KEY and an optional MINIMAX_API_BASE custom endpoint override."
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---
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To use MiniMax LLM models, you have to set the `MINIMAX_API_KEY` environment variable. You can also optionally set `MINIMAX_API_BASE` if you need to use a different API endpoint (defaults to "https://api.minimax.io/v1").
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To use MiniMax LLM models, you have to set the `MINIMAX_API_KEY` environment variable. You can also optionally set `MINIMAX_API_BASE` if you need to use a different API endpoint (defaults to `https://api.minimax.io/v1`).
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## Usage
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---
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title: Ollama
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description: "Run local Ollama LLMs such as mixtral:8x7b or llama3.1:8b as a Mem0 provider with tool calling support and a configurable Ollama server URL."
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title: "Ollama as LLM Provider"
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sidebarTitle: "Ollama"
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description: "Configure Ollama as an LLM provider in Mem0 for running local language models with tool-calling support."
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---
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You can use LLMs from Ollama to run Mem0 locally. These [models](https://ollama.com/search?c=tools) support tool calling.
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---
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title: OpenAI
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description: "Use OpenAI GPT models like gpt-5-mini as a Mem0 LLM with OPENAI_API_KEY, plus optional Openrouter routing and the openai_structured output mode."
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title: "OpenAI as LLM Provider"
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sidebarTitle: "OpenAI"
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description: "Configure OpenAI as an LLM provider in Mem0 with support for GPT models and Openrouter compatibility."
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---
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To use OpenAI LLM models, you have to set the `OPENAI_API_KEY` environment variable. You can obtain the OpenAI API key from the [OpenAI Platform](https://platform.openai.com/account/api-keys).
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---
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title: Together
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description: "Use Together AI hosted models such as MiniMaxAI/MiniMax-M3 as a Mem0 LLM with the TOGETHER_API_KEY and an optional TOGETHER_API_BASE endpoint."
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title: "Together AI as LLM Provider"
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sidebarTitle: "Together"
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description: "Configure Together AI as an LLM provider in Mem0 with API key setup and optional custom endpoint configuration."
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---
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To use Together LLM models, you have to set the `TOGETHER_API_KEY` environment variable. You can obtain the Together API key from their [Account settings page](https://api.together.ai/settings/projects/~current/api-keys).
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---
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title: xAI
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description: "Use xAI Grok models such as grok-4.3 as a Mem0 LLM with the XAI_API_KEY, plus an optional XAI_API_BASE for custom endpoint routing."
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title: "xAI Grok as LLM Provider"
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sidebarTitle: "xAI"
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description: "Configure xAI Grok models as an LLM provider in Mem0 with API key setup and usage examples."
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---
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[xAI](https://x.ai/) is a new AI company founded by Elon Musk that develops large language models, including Grok. Grok is trained on real-time data from X (formerly Twitter) and aims to provide accurate, up-to-date responses with a touch of wit and humor.
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---
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title: Overview
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description: "Compare Mem0 LLM providers including OpenAI, Anthropic, Groq, Ollama, Together, Mistral, Gemini, Bedrock, DeepSeek, xAI, Sarvam, and LangChain."
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title: "LLM Providers Overview"
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sidebarTitle: Overview
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description: "Overview of all supported LLM providers in Mem0, including OpenAI, Anthropic, Groq, Ollama, and more."
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---
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Mem0 includes built-in support for various popular large language models. Memory can utilize the LLM provided by the user, ensuring efficient use for specific needs.
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<CardGroup cols={4}>
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<Card title="OpenAI" icon="/images/provider-icons/openai.svg" href="/components/llms/models/openai" />
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<Card title="Ollama" icon="/images/provider-icons/ollama.svg" href="/components/llms/models/ollama" />
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<Card title="Azure OpenAI" icon="/images/provider-icons/azure-color.svg" href="/components/llms/models/azure_openai" />
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<Card title="Azure OpenAI" icon="/images/provider-icons/azure-color.svg" href="/components/llms/models/azure-openai" />
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<Card title="Anthropic" icon="/images/provider-icons/anthropic.svg" href="/components/llms/models/anthropic" />
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<Card title="Together" icon="/images/provider-icons/together-color.svg" href="/components/llms/models/together" />
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<Card title="Groq" icon="/images/provider-icons/groq.svg" href="/components/llms/models/groq" />
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<Card title="Litellm" icon="shuffle" href="/components/llms/models/litellm" />
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<Card title="Mistral AI" icon="/images/provider-icons/mistral-color.svg" href="/components/llms/models/mistral_AI" />
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<Card title="Google AI" icon="/images/provider-icons/google-color.svg" href="/components/llms/models/google_AI" />
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<Card title="AWS bedrock" icon="/images/provider-icons/bedrock-color.svg" href="/components/llms/models/aws_bedrock" />
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<Card title="Mistral AI" icon="/images/provider-icons/mistral-color.svg" href="/components/llms/models/mistral-ai" />
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<Card title="Google AI" icon="/images/provider-icons/google-color.svg" href="/components/llms/models/google-ai" />
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<Card title="AWS bedrock" icon="/images/provider-icons/bedrock-color.svg" href="/components/llms/models/aws-bedrock" />
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<Card title="DeepSeek" icon="/images/provider-icons/deepseek-color.svg" href="/components/llms/models/deepseek" />
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<Card title="MiniMax" icon="/images/provider-icons/minimax-color.svg" href="/components/llms/models/minimax" />
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<Card title="xAI" icon="/images/provider-icons/xai.svg" href="/components/llms/models/xAI" />
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