If you develop Memobase locally, you can use a config.yaml file to configure Memobase Backend.

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Full Explanation of config.yaml

We use a single config.yaml file as the source to configure Memobase Backend. An example is like this: 
# Storage and Performance
persistent_chat_blobs: false
buffer_flush_interval: 3600
max_chat_blob_buffer_token_size: 1024
max_profile_subtopics: 15
max_pre_profile_token_size: 128
cache_user_profiles_ttl: 1200

# Timezone
use_timezone: "UTC"

# LLM Configuration
language: "en"
llm_style: "openai"
llm_base_url: "https://api.openai.com/v1/"
llm_api_key: "YOUR-KEY"
best_llm_model: "gpt-4o-mini"
summary_llm_model: null

# Embedding Configuration
enable_event_embedding: true
embedding_provider: "openai"
embedding_api_key: null
embedding_base_url: null
embedding_dim: 1536
embedding_model: "text-embedding-3-small"
embedding_max_token_size: 8192

# Profile Configuration
additional_user_profiles:
  - topic: "gaming"
    sub_topics:
      - "Soul-Like"
      - "RPG"
profile_strict_mode: false
profile_validate_mode: true

# Summary Configuration
minimum_chats_token_size_for_event_summary: 256

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Configuration Categories

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Storage and Performance

  • persistent_chat_blobs: boolean, default to false. If set to true, the chat blobs will be persisted in the database.
  • buffer_flush_interval: int, default to 3600 (1 hour). Controls how frequently the chat buffer is flushed to persistent storage.
  • max_chat_blob_buffer_token_size: int, default to 1024. This is the parameter to control the buffer size of Memobase. Larger numbers lower your LLM cost but increase profile update lag.
  • max_profile_subtopics: int, default to 15. The maximum subtopics one topic can have. When a topic has more than this, it will trigger a re-organization.
  • max_pre_profile_token_size: int, default to 128. The maximum token size of one profile slot. When a profile slot is larger, it will trigger a re-summary.
  • cache_user_profiles_ttl: int, default to 1200 (20 minutes). Time-to-live for cached user profiles in seconds.
  • llm_tab_separator: string, default to "::". The separator used for tabs in LLM communications.

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Timezone Configuration

  • use_timezone: string, default to null. Options include "UTC", "America/New_York", "Europe/London", "Asia/Tokyo", and "Asia/Shanghai". If not set, the system’s local timezone is used.

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LLM Configuration

  • language: string, default to "en", available options {"en", "zh"}. The prompt language of Memobase.
  • llm_style: string, default to "openai", available options {"openai", "doubao_cache"}. The LLM provider style.
  • llm_base_url: string, default to null. The base URL of any OpenAI-Compatible API.
  • llm_api_key: string, required. Your LLM API key.
  • llm_openai_default_query: dictionary, default to null. Default query parameters for OpenAI API calls.
  • llm_openai_default_header: dictionary, default to null. Default headers for OpenAI API calls.
  • best_llm_model: string, default to "gpt-4o-mini". The AI model to use for primary functions.
  • summary_llm_model: string, default to null. The AI model to use for summarization. If not specified, falls back to best_llm_model.
  • system_prompt: string, default to null. Custom system prompt for the LLM.

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Embedding Configuration

  • enable_event_embedding: boolean, default to true. Whether to enable event embedding.
  • embedding_provider: string, default to "openai", available options {"openai", "jina"}. The embedding provider to use.
  • embedding_api_key: string, default to null. If not specified and provider is OpenAI, falls back to llm_api_key.
  • embedding_base_url: string, default to null. For Jina, defaults to "https://api.jina.ai/v1" if not specified.
  • embedding_dim: int, default to 1536. The dimension size of the embeddings.
  • embedding_model: string, default to "text-embedding-3-small". For Jina, must be "jina-embeddings-v3".
  • embedding_max_token_size: int, default to 8192. Maximum token size for text to be embedded.

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Profile Configuration

Check what a profile is in Memobase here.
  • additional_user_profiles: list, default to []. Add additional user profiles. Each profile should have a topic and a list of sub_topics.
    • For topic, it must have a topic field and optionally a description field:
    additional_user_profiles:
  - topic: "gaming"
    # description: "User's gaming interests"
    sub_topics:
      ...
    • For each sub_topic, it must have a name field (or just be a string) and optionally a description field:
    sub_topics:
  - "SP1"
  - name: "SP2"
    description: "Sub-Profile 2"
  • overwrite_user_profiles: list, default to null. Format is the same as additional_user_profiles. Memobase has built-in profile slots like work_title, name, etc. For full control of the slots, use this parameter. The final profile slots will be only those defined here.
  • profile_strict_mode: boolean, default to false. Enforces strict validation of profile structure.
  • profile_validate_mode: boolean, default to true. Enables validation of profile data.

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Summary Configuration

  • minimum_chats_token_size_for_event_summary: int, default to 256. Minimum token size required to trigger an event summary.
  • event_tags: list, default to []. Custom event tags for classification.

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Telemetry Configuration

  • telemetry_deployment_environment: string, default to "local". The deployment environment identifier for telemetry.

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Environment Variable Overrides

All configuration values can be overridden using environment variables. The naming convention is to prefix the configuration field name with MEMOBASE_ and convert it to uppercase. For example, to override the llm_api_key configuration: 
export MEMOBASE_LLM_API_KEY="your-api-key-here"
This is particularly useful for:
  • Keeping sensitive information like API keys out of configuration files
  • Deploying to different environments (development, staging, production)
  • Containerized deployments where environment variables are the preferred configuration method
For complex data types (lists, dictionaries, etc.), you can use JSON-formatted strings: 
# Override additional_user_profiles with a JSON array
export MEMOBASE_ADDITIONAL_USER_PROFILES='[{"topic": "gaming", "sub_topics": ["RPG", "Strategy"]}]'
The server will automatically parse JSON-formatted environment variables when appropriate.