Nolan Tremelling
e7db62e6bd
* Add scheduler and vacuum * Lint * Refactor test workflow, add mock scheduler to tests * 0 3 * * * * Missing quote in toml * Add maintenance service mock
129 lines
4.0 KiB
TOML
129 lines
4.0 KiB
TOML
[app]
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# app settings are global available like `r2r_config.agent.app`
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# project_name = "r2r_default" # optional, can also set with `R2R_PROJECT_NAME` env var
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default_max_documents_per_user = 10_000
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default_max_chunks_per_user = 10_000_000
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default_max_collections_per_user = 5_000
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# Set the default max upload size to 200 GB for local testing
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default_max_upload_size = 214748364800
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# LLM used for internal operations, like deriving conversation names
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fast_llm = "openai/gpt-4o-mini"
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# LLM used for user-facing output, like RAG replies
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quality_llm = "openai/gpt-4o"
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# LLM used for ingesting visual inputs
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vlm = "openai/gpt-4o"
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# LLM used for transcription
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audio_lm = "openai/whisper-1"
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# Reasoning model, used for `research` agent
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reasoning_llm = "openai/o3-mini"
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# Planning model, used for `research` agent
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planning_llm = "anthropic/claude-3-7-sonnet-20250219"
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[agent]
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rag_agent_static_prompt = "static_rag_agent"
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rag_agent_dynamic_prompt = "dynamic_rag_agent"
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# The following tools are available to the `rag` agent
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rag_tools = ["search_file_descriptions", "search_file_knowledge", "get_file_content"] # can add "web_search" | "web_scrape"
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# The following tools are available to the `research` agent
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research_tools = ["rag", "reasoning", "critique", "python_executor"]
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[auth]
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provider = "r2r"
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access_token_lifetime_in_minutes = 60000
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refresh_token_lifetime_in_days = 7
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require_authentication = false
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require_email_verification = false
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default_admin_email = "admin@example.com"
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default_admin_password = "change_me_immediately"
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[completion]
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provider = "r2r"
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concurrent_request_limit = 64
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[completion.generation_config]
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temperature = 0.1
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top_p = 1
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max_tokens_to_sample = 4_096
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stream = false
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add_generation_kwargs = { }
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[crypto]
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provider = "bcrypt"
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[database]
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default_collection_name = "Default"
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default_collection_description = "Your default collection."
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collection_summary_prompt = "collection_summary"
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[database.graph_creation_settings]
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graph_entity_description_prompt = "graph_entity_description"
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graph_extraction_prompt = "graph_extraction"
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entity_types = [] # if empty, all entities are extracted
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relation_types = [] # if empty, all relations are extracted
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automatic_deduplication = true # enable automatic deduplication of entities
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[database.graph_enrichment_settings]
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graph_communities_prompt = "graph_communities"
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[database.maintenance]
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vacuum_schedule = "0 3 * * *" # Run at 3:00 AM daily
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[embedding]
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provider = "litellm"
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# For basic applications, use `openai/text-embedding-3-small` with `base_dimension = 512`
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# For advanced applications, use `openai/text-embedding-3-large` with `base_dimension = 3072` and binary quantization
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base_model = "openai/text-embedding-3-small"
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base_dimension = 512
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# rerank_model = "huggingface/mixedbread-ai/mxbai-rerank-large-v1" # reranking model
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batch_size = 128
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add_title_as_prefix = false
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concurrent_request_limit = 256
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initial_backoff = 1.0
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quantization_settings = { quantization_type = "FP32" }
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[completion_embedding]
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# Generally this should be the same as the embedding config, but advanced users may want to run with a different provider to reduce latency
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provider = "litellm"
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base_model = "openai/text-embedding-3-small"
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base_dimension = 512
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batch_size = 128
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add_title_as_prefix = false
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concurrent_request_limit = 256
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[ingestion]
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provider = "r2r"
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chunking_strategy = "recursive"
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chunk_size = 1_024
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chunk_overlap = 512
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excluded_parsers = ["mp4"]
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automatic_extraction = true # enable automatic extraction of entities and relations
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[ingestion.chunk_enrichment_settings]
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chunk_enrichment_prompt = "chunk_enrichment"
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enable_chunk_enrichment = false # disabled by default
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n_chunks = 2 # the number of chunks (both preceding and succeeding) to use in enrichment
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[ingestion.extra_parsers]
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pdf = "zerox"
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[logging]
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provider = "r2r"
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log_table = "logs"
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log_info_table = "log_info"
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[orchestration]
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provider = "simple"
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[email]
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provider = "console_mock" # `smtp` | `sendgrid` supported
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[scheduler]
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provider = "apscheduler"
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