Docs SOC2 and HIPAA update (#3075)

2025-07-01 13:51:53 +05:30
parent 6c69599db9
commit 75482fdb29
115 changed files with 126 additions and 111 deletions
--- a/docs/components/embedders/config.mdx
+++ b/docs/components/embedders/config.mdx
@@ -4,7 +4,7 @@ icon: "gear"
 iconType: "solid"
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 Config in mem0 is a dictionary that specifies the settings for your embedding models. It allows you to customize the behavior and connection details of your chosen embedder.

--- a/docs/components/embedders/overview.mdx
+++ b/docs/components/embedders/overview.mdx
@@ -4,7 +4,7 @@ icon: "info"
 iconType: "solid"
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 Mem0 offers support for various embedding models, allowing users to choose the one that best suits their needs.

--- a/docs/components/llms/config.mdx
+++ b/docs/components/llms/config.mdx
@@ -4,7 +4,7 @@ icon: "gear"
 iconType: "solid"
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 ## How to define configurations?

--- a/docs/components/llms/models/anthropic.mdx
+++ b/docs/components/llms/models/anthropic.mdx
@@ -2,9 +2,9 @@
 title: Anthropic
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

-To use anthropic's models, please set the `ANTHROPIC_API_KEY` which you find on their [Account Settings Page](https://console.anthropic.com/account/keys).
+To use Anthropic's models, please set the `ANTHROPIC_API_KEY` which you find on their [Account Settings Page](https://console.anthropic.com/account/keys).

 ## Usage

--- a/docs/components/llms/models/aws_bedrock.mdx
+++ b/docs/components/llms/models/aws_bedrock.mdx
@@ -2,7 +2,7 @@
 title: AWS Bedrock
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 ### Setup
 - Before using the AWS Bedrock LLM, make sure you have the appropriate model access from [Bedrock Console](https://us-east-1.console.aws.amazon.com/bedrock/home?region=us-east-1#/modelaccess).
--- a/docs/components/llms/models/azure_openai.mdx
+++ b/docs/components/llms/models/azure_openai.mdx
@@ -2,7 +2,7 @@
 title: Azure OpenAI
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 <Note> Mem0 Now Supports Azure OpenAI Models in TypeScript SDK </Note>

--- a/docs/components/llms/models/deepseek.mdx
+++ b/docs/components/llms/models/deepseek.mdx
@@ -2,7 +2,7 @@
 title: DeepSeek
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 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").

--- a/docs/components/llms/models/gemini.mdx
+++ b/docs/components/llms/models/gemini.mdx
@@ -2,7 +2,7 @@
 title: Gemini
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 To use the Gemini model, set the `GEMINI_API_KEY` environment variable. You can obtain the Gemini API key from [Google AI Studio](https://aistudio.google.com/app/apikey).

--- a/docs/components/llms/models/google_AI.mdx
+++ b/docs/components/llms/models/google_AI.mdx
@@ -2,7 +2,7 @@
 title: Google AI
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 To use Google AI model, you have to set the `GOOGLE_API_KEY` environment variable. You can obtain the Google API key from the [Google Maker Suite](https://makersuite.google.com/app/apikey)

--- a/docs/components/llms/models/groq.mdx
+++ b/docs/components/llms/models/groq.mdx
@@ -2,7 +2,7 @@
 title: Groq
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 [Groq](https://groq.com/) is the creator of the world's first Language Processing Unit (LPU), providing exceptional speed performance for AI workloads running on their LPU Inference Engine.

--- a/docs/components/llms/models/langchain.mdx
+++ b/docs/components/llms/models/langchain.mdx
@@ -2,7 +2,7 @@
 title: LangChain
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 Mem0 supports LangChain as a provider to access a wide range of LLM models. LangChain is a framework for developing applications powered by language models, making it easy to integrate various LLM providers through a consistent interface.

--- a/docs/components/llms/models/litellm.mdx
+++ b/docs/components/llms/models/litellm.mdx
@@ -1,4 +1,4 @@
-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 [Litellm](https://litellm.vercel.app/docs/) is compatible with over 100 large language models (LLMs), all using a standardized input/output format. You can explore the [available models](https://litellm.vercel.app/docs/providers) to use with Litellm. Ensure you set the `API_KEY` for the model you choose to use.

--- a/docs/components/llms/models/lmstudio.mdx
+++ b/docs/components/llms/models/lmstudio.mdx
@@ -2,7 +2,7 @@
 title: LM Studio
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 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.

--- a/docs/components/llms/models/mistral_AI.mdx
+++ b/docs/components/llms/models/mistral_AI.mdx
@@ -2,7 +2,7 @@
 title: Mistral AI
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 To use mistral's models, please obtain the Mistral AI api key from their [console](https://console.mistral.ai/). Set the `MISTRAL_API_KEY` environment variable to use the model as given below in the example.

--- a/docs/components/llms/models/ollama.mdx
+++ b/docs/components/llms/models/ollama.mdx
@@ -1,4 +1,4 @@
-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 You can use LLMs from Ollama to run Mem0 locally. These [models](https://ollama.com/search?c=tools) support tool support.

--- a/docs/components/llms/models/openai.mdx
+++ b/docs/components/llms/models/openai.mdx
@@ -2,7 +2,7 @@
 title: OpenAI
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 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).

--- a/docs/components/llms/models/sarvam.mdx
+++ b/docs/components/llms/models/sarvam.mdx
@@ -2,7 +2,7 @@
 title: Sarvam AI
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 **Sarvam AI** is an Indian AI company developing language models with a focus on Indian languages and cultural context. Their latest model **Sarvam-M** is designed to understand and generate content in multiple Indian languages while maintaining high performance in English.

--- a/docs/components/llms/models/together.mdx
+++ b/docs/components/llms/models/together.mdx
@@ -1,4 +1,4 @@
-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 To use TogetherAI LLM models, you have to set the `TOGETHER_API_KEY` environment variable. You can obtain the TogetherAI API key from their [Account settings page](https://api.together.xyz/settings/api-keys).

--- a/docs/components/llms/models/vllm.mdx
+++ b/docs/components/llms/models/vllm.mdx
@@ -2,7 +2,7 @@
 title: vLLM
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 [vLLM](https://docs.vllm.ai/) is a high-performance inference engine for large language models that provides significant performance improvements for local inference. It's designed to maximize throughput and memory efficiency for serving LLMs.

--- a/docs/components/llms/models/xAI.mdx
+++ b/docs/components/llms/models/xAI.mdx
@@ -2,7 +2,7 @@
 title: xAI
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 [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.

--- a/docs/components/llms/overview.mdx
+++ b/docs/components/llms/overview.mdx
@@ -4,7 +4,7 @@ icon: "info"
 iconType: "solid"
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 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.

--- a/docs/components/vectordbs/config.mdx
+++ b/docs/components/vectordbs/config.mdx
@@ -4,7 +4,7 @@ icon: "gear"
 iconType: "solid"
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 ## How to define configurations?

--- a/docs/components/vectordbs/overview.mdx
+++ b/docs/components/vectordbs/overview.mdx
@@ -4,7 +4,7 @@ icon: "info"
 iconType: "solid"
 ---

-<Snippet file="paper-release.mdx" />
+<Snippet file="security-compliance.mdx" />

 Mem0 includes built-in support for various popular databases. Memory can utilize the database provided by the user, ensuring efficient use for specific needs.