From e9c930c430e840ef74a3170e64d378af3b417ecb Mon Sep 17 00:00:00 2001 From: Kartik Date: Sat, 27 Jun 2026 18:42:02 +0530 Subject: [PATCH] docs(components): fix LLM & embedder model IDs and TS support lists (#5838) --- docs/components/embedders/models/aws_bedrock.mdx | 4 ++++ docs/components/embedders/models/google_AI.mdx | 5 +++-- docs/components/embedders/models/lmstudio.mdx | 4 ++-- docs/components/embedders/overview.mdx | 3 ++- docs/components/llms/config.mdx | 4 ++-- docs/components/llms/models/anthropic.mdx | 4 ++-- docs/components/llms/models/aws_bedrock.mdx | 2 +- docs/components/llms/models/groq.mdx | 4 ++-- docs/components/llms/models/xAI.mdx | 2 +- docs/components/llms/overview.mdx | 2 +- 10 files changed, 20 insertions(+), 14 deletions(-) diff --git a/docs/components/embedders/models/aws_bedrock.mdx b/docs/components/embedders/models/aws_bedrock.mdx index e5430e03d..d474f9655 100644 --- a/docs/components/embedders/models/aws_bedrock.mdx +++ b/docs/components/embedders/models/aws_bedrock.mdx @@ -59,5 +59,9 @@ Here are the parameters available for configuring AWS Bedrock embedder: | Parameter | Description | Default Value | | --- | --- | --- | | `model` | The name of the embedding model to use | `amazon.titan-embed-text-v1` | +| `aws_region` | AWS region for the Bedrock client | `us-west-2` | +| `aws_access_key_id` | AWS access key ID for authentication | `None` | +| `aws_secret_access_key` | AWS secret access key for authentication | `None` | +| `aws_session_token` | AWS session token for temporary credentials | `None` | diff --git a/docs/components/embedders/models/google_AI.mdx b/docs/components/embedders/models/google_AI.mdx index 7c9db18c1..8dccf45e5 100644 --- a/docs/components/embedders/models/google_AI.mdx +++ b/docs/components/embedders/models/google_AI.mdx @@ -67,14 +67,15 @@ Here are the parameters available for configuring Gemini embedder: | Parameter | Description | Default Value | | ---------------- | ------------------------------------ | ----------------------- | | `model` | The name of the embedding model to use| `models/gemini-embedding-001` | -| `embedding_dims` | Dimensions of the embedding model | `1536` | +| `embedding_dims` | Dimensions of the embedding model | `768` | | `api_key` | The Google API key | `None` | +| `output_dimensionality` | Output dimensionality for the embedding model (Gemini-specific; used when `embedding_dims` is not set) | `None` | | Parameter | Description | Default Value | | ----------------- | --------------------------------------------- | -------------------------- | | `model` | The name of the embedding model to use | `gemini-embedding-001` | -| `embeddingDims` | Dimensions of the embedding model | `1536` | +| `embeddingDims` | Dimensions of the embedding model. When not set, uses the model's native output dimensionality (3072 for `gemini-embedding-001`; MRL truncation to 768, 1536, or 3072 is supported) | `None` | | `apiKey` | Google API key | `None` | diff --git a/docs/components/embedders/models/lmstudio.mdx b/docs/components/embedders/models/lmstudio.mdx index 4b8d2212c..66234d8cc 100644 --- a/docs/components/embedders/models/lmstudio.mdx +++ b/docs/components/embedders/models/lmstudio.mdx @@ -16,7 +16,7 @@ config = { "embedder": { "provider": "lmstudio", "config": { - "model": "nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.f16.gguf" + "model": "nomic-ai/nomic-embed-text-v1.5-GGUF" } } } @@ -37,6 +37,6 @@ Here are the parameters available for configuring LM Studio embedder: | Parameter | Description | Default Value | | --- | --- | --- | -| `model` | The name of the LM Studio model to use | `nomic-embed-text-v1.5-GGUF/nomic-embed-text-v1.5.f16.gguf` | +| `model` | The name of the LM Studio model to use | `nomic-ai/nomic-embed-text-v1.5-GGUF` | | `embedding_dims` | Dimensions of the embedding model | `1536` | | `lmstudio_base_url` | Base URL for LM Studio connection | `http://localhost:1234/v1` | \ No newline at end of file diff --git a/docs/components/embedders/overview.mdx b/docs/components/embedders/overview.mdx index 45f23d8a5..08921e2b2 100644 --- a/docs/components/embedders/overview.mdx +++ b/docs/components/embedders/overview.mdx @@ -10,7 +10,7 @@ Mem0 offers support for various embedding models, allowing users to choose the o See the list of supported embedders below. - The following embedders are supported in the Python implementation. The TypeScript implementation currently only supports OpenAI. + All embedders listed below are supported in the Python implementation. The TypeScript implementation supports: **OpenAI**, **Azure OpenAI**, **Google AI**, **Langchain**, **LM Studio**, and **Ollama**. @@ -24,6 +24,7 @@ See the list of supported embedders below. + ## Usage diff --git a/docs/components/llms/config.mdx b/docs/components/llms/config.mdx index 1be19b78a..f493d9fc7 100644 --- a/docs/components/llms/config.mdx +++ b/docs/components/llms/config.mdx @@ -98,7 +98,7 @@ Here's a comprehensive list of all parameters that can be used across different | `max_tokens` | Tokens to generate | All | | `top_p` | Probability threshold for nucleus sampling | All | | `top_k` | Number of highest probability tokens to keep | All | - | `http_client_proxies`| Allow proxy server settings | AzureOpenAI | + | `http_client_proxies`| Allow proxy server settings | All | | `models` | List of models | Openrouter | | `route` | Routing strategy | Openrouter | | `openrouter_base_url`| Base URL for Openrouter API | Openrouter | @@ -110,7 +110,7 @@ Here's a comprehensive list of all parameters that can be used across different | `deepseek_base_url` | Base URL for DeepSeek API | DeepSeek | | `xai_base_url` | Base URL for XAI API | XAI | | `sarvam_base_url` | Base URL for Sarvam API | Sarvam | - | `reasoning_effort` | Reasoning level (low, medium, high) | Sarvam | + | `reasoning_effort` | Reasoning level (low, medium, high) | All | | `frequency_penalty` | Penalize frequent tokens (-2.0 to 2.0) | Sarvam | | `presence_penalty` | Penalize existing tokens (-2.0 to 2.0) | Sarvam | | `seed` | Seed for deterministic sampling | Sarvam | diff --git a/docs/components/llms/models/anthropic.mdx b/docs/components/llms/models/anthropic.mdx index 488a06e4a..8305609aa 100644 --- a/docs/components/llms/models/anthropic.mdx +++ b/docs/components/llms/models/anthropic.mdx @@ -20,7 +20,7 @@ config = { "llm": { "provider": "anthropic", "config": { - "model": "claude-sonnet-4-20250514", + "model": "claude-sonnet-4-6", "temperature": 0.1, "max_tokens": 2000, } @@ -45,7 +45,7 @@ const config = { provider: 'anthropic', config: { apiKey: process.env.ANTHROPIC_API_KEY || '', - model: 'claude-sonnet-4-20250514', + model: 'claude-sonnet-4-6', temperature: 0.1, maxTokens: 2000, }, diff --git a/docs/components/llms/models/aws_bedrock.mdx b/docs/components/llms/models/aws_bedrock.mdx index 76b0efedd..3d3de2d29 100644 --- a/docs/components/llms/models/aws_bedrock.mdx +++ b/docs/components/llms/models/aws_bedrock.mdx @@ -6,7 +6,7 @@ description: "Configure AWS Bedrock as an LLM provider in Mem0 with IAM authenti ### 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). - You will also need to authenticate the `boto3` client by using a method in the [AWS documentation](https://boto3.amazonaws.com/v1/documentation/api/latest/guide/credentials.html#configuring-credentials) -- You will have to export `AWS_REGION`, `AWS_ACCESS_KEY`, and `AWS_SECRET_ACCESS_KEY` to set environment variables. +- You will have to export `AWS_REGION`, `AWS_ACCESS_KEY_ID`, and `AWS_SECRET_ACCESS_KEY` to set environment variables. ### Usage diff --git a/docs/components/llms/models/groq.mdx b/docs/components/llms/models/groq.mdx index d6a82743e..e3c802729 100644 --- a/docs/components/llms/models/groq.mdx +++ b/docs/components/llms/models/groq.mdx @@ -21,7 +21,7 @@ config = { "llm": { "provider": "groq", "config": { - "model": "mixtral-8x7b-32768", + "model": "llama-3.3-70b-versatile", "temperature": 0.1, "max_tokens": 2000, } @@ -46,7 +46,7 @@ const config = { provider: 'groq', config: { apiKey: process.env.GROQ_API_KEY || '', - model: 'mixtral-8x7b-32768', + model: 'llama3-70b-8192', temperature: 0.1, maxTokens: 1000, }, diff --git a/docs/components/llms/models/xAI.mdx b/docs/components/llms/models/xAI.mdx index fb6d930fa..b75b4530c 100644 --- a/docs/components/llms/models/xAI.mdx +++ b/docs/components/llms/models/xAI.mdx @@ -20,7 +20,7 @@ config = { "llm": { "provider": "xai", "config": { - "model": "grok-3-beta", + "model": "grok-4.3", "temperature": 0.1, "max_tokens": 2000, } diff --git a/docs/components/llms/overview.mdx b/docs/components/llms/overview.mdx index 94a5cc160..c207e5e06 100644 --- a/docs/components/llms/overview.mdx +++ b/docs/components/llms/overview.mdx @@ -16,7 +16,7 @@ For a comprehensive list of available parameters for llm configuration, please r See the list of supported LLMs below. - All LLMs are supported in Python. The following LLMs are also supported in TypeScript: **OpenAI**, **Anthropic**, and **Groq**. + All LLMs are supported in Python. The following LLMs are also supported in TypeScript: **OpenAI**, **Anthropic**, **Groq**, **Azure OpenAI**, **DeepSeek**, **Google AI**, **Langchain**, **LM Studio**, **Mistral AI**, and **Ollama**.