marimo-flow/config.yaml.example at main · synapticore-io/marimo-flow · GitHub

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# marimo-flow agent config — copy to ``config.yaml`` in the repo root to
# customise per-role model picks. Rename to ``config.yaml``,
# ``marimo-flow.yaml`` or point ``$MARIMO_FLOW_CONFIG`` at any file.
#
# Model specs use pydantic-ai's provider prefix: "<provider>:<model>".
# Supported providers (pydantic-ai 1.84+):
#   openai, anthropic, google-gla, google-vertex, groq, mistral, cohere,
#   bedrock, huggingface, ollama, deepseek, openrouter, vercel, azure,
#   cerebras, xai, moonshotai, fireworks, together, heroku, github,
#   litellm, nebius, ovhcloud, alibaba, sambanova, outlines,
#   sentence-transformers, voyageai.
#
# Each provider reads its own auth from the standard env var
# (OPENAI_API_KEY, ANTHROPIC_API_KEY, GROQ_API_KEY, OLLAMA_BASE_URL, ...).
# You can also seed env vars here via the optional ``env:`` block below;
# real shell-exported values always win over anything set here.

# Optional — pin provider endpoints / non-secret env without editing shells.
# Do NOT commit API keys here; put those in .env (gitignored) or export them.
# env:
#   OLLAMA_BASE_URL: http://localhost:11434/v1

# Backend URIs — override the hardcoded defaults without touching code.
# Env vars MLFLOW_TRACKING_URI / MARIMO_MCP_URL win over these.
# mlflow:
#   tracking_uri: sqlite:///mlruns.db
# marimo:
#   mcp_url: http://127.0.0.1:2718/mcp/server

# Per-role model assignment. Missing roles fall back to DEFAULT_MODELS
# (shipped with the repo, all point at Ollama Cloud).
models:
  # Classifier that dispatches to specialist nodes. Low token budget.
  route:    ollama:gemma4:31b-cloud

  # Edits / inspects marimo notebook cells via MCP.
  notebook: ollama:qwen3-coder:480b-cloud

  # Defines the PINA Problem (PDE + domain + conditions).
  problem:  ollama:qwen3-coder:480b-cloud

  # Picks the NN architecture (FeedForward, FNO, DeepONet, ...).
  model:    ollama:qwen3.5:cloud

  # Wires the Solver (PINN-family, SupervisedSolver).
  solver:   ollama:qwen3-coder:480b-cloud

  # Runs pina.Trainer and logs metrics to MLflow.
  training: ollama:qwen3-coder:480b-cloud

  # Reads/writes the MLflow tracking backend (experiments, runs, tags).
  mlflow:   ollama:gpt-oss:20b-cloud

  # User-facing chat; orchestrates the sub-agents through the graph.
  lead:     ollama:kimi-k2.5:cloud

# ─────────────────────────────────────────────────────────────────────────
# Example: mixed providers (uncomment + export the matching API keys)
# ─────────────────────────────────────────────────────────────────────────
# models:
#   lead:     anthropic:claude-sonnet-4-6
#   route:    groq:llama-3.3-70b-versatile
#   problem:  openai:gpt-5
#   model:    openai:gpt-5
#   solver:   anthropic:claude-sonnet-4-6
#   training: anthropic:claude-sonnet-4-6
#   mlflow:   groq:llama-3.3-70b-versatile
#   notebook: openai:gpt-5
#
# ─────────────────────────────────────────────────────────────────────────
# Example: OpenAI-compatible router (OpenRouter, Together, Fireworks, ...)
# ─────────────────────────────────────────────────────────────────────────
# models:
#   lead:     openrouter:anthropic/claude-sonnet-4.6
#   problem:  together:Qwen/Qwen2.5-Coder-32B-Instruct
#   model:    fireworks:accounts/fireworks/models/llama-v3p3-70b-instruct