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Fabro
parent
7fcc9750fc
commit
6718d3db98
6 changed files with 366 additions and 9 deletions
File diff suppressed because one or more lines are too long
177
nodes/simplify_gpt/prompt.md
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177
nodes/simplify_gpt/prompt.md
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Goal: # Fix: Workflow TOML config lost in detach mode
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## Context
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When running `fabro run -d implement-plan`, the `[pull_request]` config from `fabro.toml` / `cli.toml` / `workflow.toml` is silently dropped, so no PR is created despite `enabled = true` at all config levels.
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**Root cause chain**:
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1. `create.rs` tries to copy the workflow TOML as `run.toml`, but checks the **raw CLI arg** (`"implement-plan"` — no extension) instead of the resolved path. So `run.toml` is never saved.
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2. `RunEngine` always uses cached `graph.fabro` (a DOT file), so `prepare_workflow` returns `run_cfg = None`, losing all TOML-level config.
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3. `pull_request` and `asset_globs` in `RunConfig` only check `run_cfg` without falling back to `run_defaults`.
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## Fix 1: Serialize merged `run_cfg` to `run.toml` in create.rs
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**File**: `lib/crates/fabro-cli/src/commands/create.rs`
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Replace the raw-file-copy block (lines 53-58) with serialization of the already-merged `WorkflowRunConfig`:
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- Change `let prep = prepare_workflow(...)` to `let mut prep = ...`
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- Replace the extension check with:
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```rust
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if let Some(mut cfg) = prep.run_cfg.take() {
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cfg.graph = "graph.fabro".to_string();
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let toml_str = toml::to_string_pretty(&cfg)
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.context("Failed to serialize run config")?;
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tokio::fs::write(run_dir.join("run.toml"), toml_str).await?;
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}
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```
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- Add `use anyhow::Context;` if needed
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**Why serialize instead of copy**: The raw TOML's `graph` field (e.g. `"workflow.fabro"`) would point to a nonexistent file in the run dir. Serializing lets us rewrite `graph` to `"graph.fabro"` (the cached name). The serialized config also has all defaults merged, env vars resolved, and dockerfiles inlined — making the run dir self-contained.
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**Why `take()` not `clone()`**: `WorkflowRunConfig` doesn't derive `Clone`, and `prep.run_cfg` is unused after this point in `create.rs`.
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## Fix 2: Use `run.toml` in RunEngine path
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**File**: `lib/crates/fabro-cli/src/main.rs` (lines 727-733)
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Replace the workflow path resolution to use `run.toml`:
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```rust
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let cached_toml = run_dir.join("run.toml");
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let workflow_path = if cached_toml.exists() {
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cached_toml
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} else {
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run_dir.join("graph.fabro")
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};
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```
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When `run.toml` exists, `prepare_workflow` → `resolve_workflow` sees `.toml`, calls `load_run_config`, and `resolve_graph_path` resolves `"graph.fabro"` relative to the run dir — pointing to the cached graph that already exists there.
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## Fix 3: Add `run_defaults` fallbacks (defense-in-depth)
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**File**: `lib/crates/fabro-cli/src/commands/run.rs`
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Even with Fixes 1+2, bare `.fabro` files passed directly would still hit `run_cfg = None`. Add fallbacks matching the pattern already used elsewhere in the file:
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**3a. `pull_request`** (line 1424-1428):
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```rust
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pull_request: run_cfg
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.as_ref()
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.and_then(|c| c.pull_request.as_ref())
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.or(run_defaults.pull_request.as_ref())
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.filter(|p| p.enabled)
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.cloned(),
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```
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**3b. `asset_globs`** (line 1429-1433):
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```rust
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asset_globs: run_cfg
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.as_ref()
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.and_then(|c| c.assets.as_ref())
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.or(run_defaults.assets.as_ref())
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.map(|a| a.include.clone())
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.unwrap_or_default(),
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```
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**3c. `devcontainer`** (line 969-973):
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```rust
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let devcontainer_config = if run_cfg
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.as_ref()
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.and_then(|c| c.sandbox.as_ref())
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.or(run_defaults.sandbox.as_ref())
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.and_then(|s| s.devcontainer)
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.unwrap_or(false)
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```
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**3d. `sandbox.env`** (line 1300-1306):
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```rust
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if let Some(toml_env) = run_cfg
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.as_ref()
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.and_then(|c| c.sandbox.as_ref())
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.or(run_defaults.sandbox.as_ref())
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.and_then(|s| s.env.clone())
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```
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## Verification
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1. `cargo build --workspace`
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2. `cargo test --workspace`
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3. `cargo clippy --workspace -- -D warnings`
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4. Manual: `fabro run -d implement-plan` with `[pull_request] enabled = true` in `fabro.toml` → verify `run.toml` in run dir has `graph = "graph.fabro"` and `[pull_request]` → verify PR created
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## Completed stages
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- **toolchain**: success
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- Script: `command -v cargo >/dev/null || { curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y && sudo ln -sf $HOME/.cargo/bin/* /usr/local/bin/; }; cargo --version 2>&1`
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- Stdout:
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```
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cargo 1.94.0 (85eff7c80 2026-01-15)
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```
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- Stderr: (empty)
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- **preflight_compile**: success
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- Script: `cargo check -q --workspace 2>&1`
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- Stdout: (empty)
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- Stderr: (empty)
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- **preflight_lint**: success
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- Script: `cargo clippy -q --workspace -- -D warnings 2>&1`
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- Stdout: (empty)
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- Stderr: (empty)
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- **implement**: success
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- Model: claude-opus-4-6, 20.7k tokens in / 5.3k out
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- Files: /home/daytona/workspace/lib/crates/fabro-cli/src/commands/create.rs, /home/daytona/workspace/lib/crates/fabro-cli/src/commands/run.rs, /home/daytona/workspace/lib/crates/fabro-cli/src/main.rs
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- **simplify_opus**: success
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- Model: claude-opus-4-6, 50.7k tokens in / 13.4k out
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- Files: /home/daytona/workspace/lib/crates/fabro-cli/src/commands/run.rs
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# Simplify: Code Review and Cleanup
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Review all changed files for reuse, quality, and efficiency. Fix any issues found.
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## Phase 1: Identify Changes
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Run git diff (or git diff HEAD if there are staged changes) to see what changed. If there are no git changes, review the most recently modified files that the user mentioned or that you edited earlier in this conversation.
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## Phase 2: Launch Three Review Agents in Parallel
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Use the Agent tool to launch all three agents concurrently in a single message. Pass each agent the full diff so it has the complete context.
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### Agent 1: Code Reuse Review
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For each change:
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1. Search for existing utilities and helpers that could replace newly written code. Use Grep to find similar patterns elsewhere in the codebase — common locations are utility directories, shared modules, and files adjacent to the changed ones.
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2. Flag any new function that duplicates existing functionality. Suggest the existing function to use instead.
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3. Flag any inline logic that could use an existing utility — hand-rolled string manipulation, manual path handling, custom environment checks, ad-hoc type guards, and similar patterns are common candidates.
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Note: This is a greenfield app, so focus on maximizing simplicity and don't worry about changing things to achieve it.
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### Agent 2: Code Quality Review
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Review the same changes for hacky patterns:
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1. Redundant state: state that duplicates existing state, cached values that could be derived, observers/effects that could be direct calls
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2. Parameter sprawl: adding new parameters to a function instead of generalizing or restructuring existing ones
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3. Copy-paste with slight variation: near-duplicate code blocks that should be unified with a shared abstraction
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4. Leaky abstractions: exposing internal details that should be encapsulated, or breaking existing abstraction boundaries
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5. Stringly-typed code: using raw strings where constants, enums (string unions), or branded types already exist in the codebase
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Note: This is a greenfield app, so be aggressive in optimizing quality.
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### Agent 3: Efficiency Review
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Review the same changes for efficiency:
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1. Unnecessary work: redundant computations, repeated file reads, duplicate network/API calls, N+1 patterns
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2. Missed concurrency: independent operations run sequentially when they could run in parallel
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3. Hot-path bloat: new blocking work added to startup or per-request/per-render hot paths
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4. Unnecessary existence checks: pre-checking file/resource existence before operating (TOCTOU anti-pattern) — operate directly and handle the error
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5. Memory: unbounded data structures, missing cleanup, event listener leaks
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6. Overly broad operations: reading entire files when only a portion is needed, loading all items when filtering for one
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## Phase 3: Fix Issues
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Wait for all three agents to complete. Aggregate their findings and fix each issue directly. If a finding is a false positive or not worth addressing, note it and move on — do not argue with the finding, just skip it.
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When done, briefly summarize what was fixed (or confirm the code was already clean).
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5
nodes/simplify_gpt/provider_used.json
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5
nodes/simplify_gpt/provider_used.json
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{
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"mode": "agent",
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"provider": "openai",
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"model": "gpt-5.4"
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}
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43
nodes/simplify_gpt/response.md
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43
nodes/simplify_gpt/response.md
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Reviewed and cleaned up the detach-mode fix.
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What I changed
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- `lib/crates/fabro-cli/src/commands/run.rs`
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- Added shared helpers/constants for cached run files:
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- `RUN_GRAPH_FILE`
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- `RUN_CONFIG_FILE`
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- `cached_graph_path()`
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- `cached_run_config_path()`
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- `write_run_config_snapshot()`
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- Removed duplicated `run.toml` serialization logic from both create/run paths.
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- Stopped mutating live `run_cfg` just to rewrite `graph`; snapshot serialization now rewrites the TOML via a serialized value instead.
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- Centralized detached-workflow resolution in `resolve_workflow_source()`, with fallback from missing cached `run.toml` to sibling `graph.fabro` for backward compatibility.
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- Reused the shared graph-path helper in the run-branch resume path too.
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- Added focused tests for:
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- snapshot serialization rewriting `graph`
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- fallback from missing cached `run.toml` to `graph.fabro`
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- `lib/crates/fabro-cli/src/commands/create.rs`
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- Reused the shared cached-file helpers.
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- Removed now-unneeded mutability and `Context` import.
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- `lib/crates/fabro-cli/src/main.rs`
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- Removed the `exists()` check.
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- Detached engine now always points at cached `run.toml`; `prepare_workflow()` handles legacy fallback cleanly.
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Why this cleanup
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- Fixes the code-quality issue of mutating runtime config for persistence.
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- Removes copy-pasted snapshot-writing logic.
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- Removes the TOCTOU-style `exists()` check in detached startup.
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- Centralizes the cached run-dir file contract.
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Validation
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- `cargo fmt --all`
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- `cargo test -p fabro-cli`
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- `cargo clippy -p fabro-cli -- -D warnings`
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- `cargo build --workspace`
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- `cargo clippy --workspace -- -D warnings`
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- `cargo test --workspace`
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All passed.
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I did not run the manual PR-creation flow, so that part remains unverified in this environment.
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6
nodes/simplify_gpt/status.json
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6
nodes/simplify_gpt/status.json
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{
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"status": "success",
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"notes": "Stage completed: simplify_gpt",
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"failure_reason": null,
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"timestamp": "2026-03-21T16:14:07.129648+00:00"
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}
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102
nodes/simplify_opus/diff.patch
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102
nodes/simplify_opus/diff.patch
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@ -0,0 +1,102 @@
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diff --git a/lib/crates/fabro-cli/src/commands/run.rs b/lib/crates/fabro-cli/src/commands/run.rs
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index c5336799..264fbc48 100644
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--- a/lib/crates/fabro-cli/src/commands/run.rs
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+++ b/lib/crates/fabro-cli/src/commands/run.rs
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@@ -610,7 +610,7 @@ pub async fn run_command(
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let PreparedWorkflow {
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source,
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graph,
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- run_cfg,
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+ mut run_cfg,
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sandbox_provider,
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model,
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provider,
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@@ -698,10 +698,11 @@ pub async fn run_command(
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);
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});
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- if workflow_path.extension().is_some_and(|ext| ext == "toml") {
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- if let Ok(toml_contents) = tokio::fs::read(workflow_path).await {
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- tokio::fs::write(run_dir.join("run.toml"), toml_contents).await?;
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- }
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+ // Serialize the merged run config so the run dir is self-contained
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+ if let Some(ref mut cfg) = run_cfg {
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+ cfg.graph = "graph.fabro".to_string();
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+ let toml_str = toml::to_string_pretty(&*cfg).context("Failed to serialize run config")?;
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+ tokio::fs::write(run_dir.join("run.toml"), toml_str).await?;
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}
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// Create progress UI (used for both normal and verbose modes)
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diff --git a/lib/crates/fabro-model/src/.catalog.rs.pending-snap b/lib/crates/fabro-model/src/.catalog.rs.pending-snap
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deleted file mode 100644
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index c30cbf5d..00000000
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--- a/lib/crates/fabro-model/src/.catalog.rs.pending-snap
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+++ /dev/null
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@@ -1,7 +0,0 @@
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-{"run_id":"1774108419-651283619","line":604,"new":{"module_name":"fabro_model__catalog__tests","snapshot_name":"gpt_5_3_codex_spark_in_catalog","metadata":{"source":"lib/crates/fabro-model/src/catalog.rs","assertion_line":604,"expression":"m"},"snapshot":"ModelInfo {\n id: \"gpt-5.3-codex-spark\",\n provider: \"openai\",\n family: \"gpt-5\",\n display_name: \"GPT-5.3 Codex Spark\",\n limits: ModelLimits {\n context_window: 131072,\n max_output: Some(\n 128000,\n ),\n },\n training: Some(\n \"2025-08-31\",\n ),\n features: ModelFeatures {\n tools: true,\n vision: false,\n reasoning: true,\n effort: true,\n },\n costs: ModelCosts {\n input_cost_per_mtok: None,\n output_cost_per_mtok: None,\n cache_input_cost_per_mtok: None,\n },\n estimated_output_tps: Some(\n 1000.0,\n ),\n aliases: [\n \"codex-spark\",\n ],\n default: false,\n}"},"old":{"module_name":"fabro_model__catalog__tests","metadata":{},"snapshot":"ModelInfo {\n id: \"gpt-5.3-codex-spark\",\n provider: \"openai\",\n family: \"gpt-5\",\n display_name: \"GPT-5.3 Codex Spark\",\n limits: ModelLimits {\n context_window: 131072,\n max_output: Some(\n 128000,\n ),\n },\n training: Some(\n \"2025-08-31\",\n ),\n features: ModelFeatures {\n tools: true,\n vision: false,\n reasoning: true,\n },\n costs: ModelCosts {\n input_cost_per_mtok: None,\n output_cost_per_mtok: None,\n cache_input_cost_per_mtok: None,\n },\n estimated_output_tps: Some(\n 1000.0,\n ),\n aliases: [\n \"codex-spark\",\n ],\n default: false,\n}"}}
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-{"run_id":"1774108419-651283619","line":333,"new":{"module_name":"fabro_model__catalog__tests","snapshot_name":"gemini_3_1_flash_lite_in_catalog","metadata":{"source":"lib/crates/fabro-model/src/catalog.rs","assertion_line":333,"expression":"m"},"snapshot":"ModelInfo {\n id: \"gemini-3.1-flash-lite-preview\",\n provider: \"gemini\",\n family: \"gemini-3\",\n display_name: \"Gemini 3.1 Flash Lite (Preview)\",\n limits: ModelLimits {\n context_window: 1048576,\n max_output: Some(\n 65536,\n ),\n },\n training: Some(\n \"2025-01-01\",\n ),\n features: ModelFeatures {\n tools: true,\n vision: true,\n reasoning: true,\n effort: true,\n },\n costs: ModelCosts {\n input_cost_per_mtok: Some(\n 0.25,\n ),\n output_cost_per_mtok: Some(\n 1.5,\n ),\n cache_input_cost_per_mtok: Some(\n 0.0625,\n ),\n },\n estimated_output_tps: Some(\n 200.0,\n ),\n aliases: [\n \"gemini-flash-lite\",\n ],\n default: false,\n}"},"old":{"module_name":"fabro_model__catalog__tests","metadata":{},"snapshot":"ModelInfo {\n id: \"gemini-3.1-flash-lite-preview\",\n provider: \"gemini\",\n family: \"gemini-3\",\n display_name: \"Gemini 3.1 Flash Lite (Preview)\",\n limits: ModelLimits {\n context_window: 1048576,\n max_output: Some(\n 65536,\n ),\n },\n training: Some(\n \"2025-01-01\",\n ),\n features: ModelFeatures {\n tools: true,\n vision: true,\n reasoning: true,\n },\n costs: ModelCosts {\n input_cost_per_mtok: Some(\n 0.25,\n ),\n output_cost_per_mtok: Some(\n 1.5,\n ),\n cache_input_cost_per_mtok: Some(\n 0.0625,\n ),\n },\n estimated_output_tps: Some(\n 200.0,\n ),\n aliases: [\n \"gemini-flash-lite\",\n ],\n default: false,\n}"}}
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-{"run_id":"1774108419-651283619","line":254,"new":{"module_name":"fabro_model__catalog__tests","snapshot_name":"get_model_info_by_id","metadata":{"source":"lib/crates/fabro-model/src/catalog.rs","assertion_line":254,"expression":"info"},"snapshot":"ModelInfo {\n id: \"claude-opus-4-6\",\n provider: \"anthropic\",\n family: \"claude-4\",\n display_name: \"Claude Opus 4.6\",\n limits: ModelLimits {\n context_window: 1000000,\n max_output: Some(\n 128000,\n ),\n },\n training: Some(\n \"2025-08-01\",\n ),\n features: ModelFeatures {\n tools: true,\n vision: true,\n reasoning: true,\n effort: true,\n },\n costs: ModelCosts {\n input_cost_per_mtok: Some(\n 15.0,\n ),\n output_cost_per_mtok: Some(\n 75.0,\n ),\n cache_input_cost_per_mtok: Some(\n 1.5,\n ),\n },\n estimated_output_tps: Some(\n 25.0,\n ),\n aliases: [\n \"opus\",\n \"claude-opus\",\n ],\n default: false,\n}"},"old":{"module_name":"fabro_model__catalog__tests","metadata":{},"snapshot":"ModelInfo {\n id: \"claude-opus-4-6\",\n provider: \"anthropic\",\n family: \"claude-4\",\n display_name: \"Claude Opus 4.6\",\n limits: ModelLimits {\n context_window: 1000000,\n max_output: Some(\n 128000,\n ),\n },\n training: Some(\n \"2025-08-01\",\n ),\n features: ModelFeatures {\n tools: true,\n vision: true,\n reasoning: true,\n },\n costs: ModelCosts {\n input_cost_per_mtok: Some(\n 15.0,\n ),\n output_cost_per_mtok: Some(\n 75.0,\n ),\n cache_input_cost_per_mtok: Some(\n 1.5,\n ),\n },\n estimated_output_tps: Some(\n 25.0,\n ),\n aliases: [\n \"opus\",\n \"claude-opus\",\n ],\n default: false,\n}"}}
|
||||
-{"run_id":"1774108419-651283619","line":492,"new":{"module_name":"fabro_model__catalog__tests","snapshot_name":"gpt_5_4_in_catalog","metadata":{"source":"lib/crates/fabro-model/src/catalog.rs","assertion_line":492,"expression":"m"},"snapshot":"ModelInfo {\n id: \"gpt-5.4\",\n provider: \"openai\",\n family: \"gpt-5\",\n display_name: \"GPT-5.4\",\n limits: ModelLimits {\n context_window: 1047576,\n max_output: Some(\n 128000,\n ),\n },\n training: Some(\n \"2025-08-31\",\n ),\n features: ModelFeatures {\n tools: true,\n vision: true,\n reasoning: true,\n effort: true,\n },\n costs: ModelCosts {\n input_cost_per_mtok: Some(\n 2.5,\n ),\n output_cost_per_mtok: Some(\n 15.0,\n ),\n cache_input_cost_per_mtok: Some(\n 0.25,\n ),\n },\n estimated_output_tps: Some(\n 70.0,\n ),\n aliases: [\n \"gpt54\",\n \"gpt-54\",\n ],\n default: true,\n}"},"old":{"module_name":"fabro_model__catalog__tests","metadata":{},"snapshot":"ModelInfo {\n id: \"gpt-5.4\",\n provider: \"openai\",\n family: \"gpt-5\",\n display_name: \"GPT-5.4\",\n limits: ModelLimits {\n context_window: 1047576,\n max_output: Some(\n 128000,\n ),\n },\n training: Some(\n \"2025-08-31\",\n ),\n features: ModelFeatures {\n tools: true,\n vision: true,\n reasoning: true,\n },\n costs: ModelCosts {\n input_cost_per_mtok: Some(\n 2.5,\n ),\n output_cost_per_mtok: Some(\n 15.0,\n ),\n cache_input_cost_per_mtok: Some(\n 0.25,\n ),\n },\n estimated_output_tps: Some(\n 70.0,\n ),\n aliases: [\n \"gpt54\",\n \"gpt-54\",\n ],\n default: true,\n}"}}
|
||||
-{"run_id":"1774108419-651283619","line":538,"new":{"module_name":"fabro_model__catalog__tests","snapshot_name":"gpt_5_4_pro_in_catalog","metadata":{"source":"lib/crates/fabro-model/src/catalog.rs","assertion_line":538,"expression":"m"},"snapshot":"ModelInfo {\n id: \"gpt-5.4-pro\",\n provider: \"openai\",\n family: \"gpt-5\",\n display_name: \"GPT-5.4 Pro\",\n limits: ModelLimits {\n context_window: 1047576,\n max_output: Some(\n 128000,\n ),\n },\n training: Some(\n \"2025-08-31\",\n ),\n features: ModelFeatures {\n tools: true,\n vision: true,\n reasoning: true,\n effort: true,\n },\n costs: ModelCosts {\n input_cost_per_mtok: Some(\n 30.0,\n ),\n output_cost_per_mtok: Some(\n 180.0,\n ),\n cache_input_cost_per_mtok: Some(\n 3.0,\n ),\n },\n estimated_output_tps: Some(\n 20.0,\n ),\n aliases: [\n \"gpt54-pro\",\n \"gpt-54-pro\",\n ],\n default: false,\n}"},"old":{"module_name":"fabro_model__catalog__tests","metadata":{},"snapshot":"ModelInfo {\n id: \"gpt-5.4-pro\",\n provider: \"openai\",\n family: \"gpt-5\",\n display_name: \"GPT-5.4 Pro\",\n limits: ModelLimits {\n context_window: 1047576,\n max_output: Some(\n 128000,\n ),\n },\n training: Some(\n \"2025-08-31\",\n ),\n features: ModelFeatures {\n tools: true,\n vision: true,\n reasoning: true,\n },\n costs: ModelCosts {\n input_cost_per_mtok: Some(\n 30.0,\n ),\n output_cost_per_mtok: Some(\n 180.0,\n ),\n cache_input_cost_per_mtok: Some(\n 3.0,\n ),\n },\n estimated_output_tps: Some(\n 20.0,\n ),\n aliases: [\n \"gpt54-pro\",\n \"gpt-54-pro\",\n ],\n default: false,\n}"}}
|
||||
-{"run_id":"1774108419-651283619","line":446,"new":{"module_name":"fabro_model__catalog__tests","snapshot_name":"mercury_2_in_catalog","metadata":{"source":"lib/crates/fabro-model/src/catalog.rs","assertion_line":446,"expression":"m"},"snapshot":"ModelInfo {\n id: \"mercury-2\",\n provider: \"inception\",\n family: \"mercury\",\n display_name: \"Mercury 2\",\n limits: ModelLimits {\n context_window: 131072,\n max_output: Some(\n 50000,\n ),\n },\n training: None,\n features: ModelFeatures {\n tools: true,\n vision: false,\n reasoning: true,\n effort: true,\n },\n costs: ModelCosts {\n input_cost_per_mtok: Some(\n 0.25,\n ),\n output_cost_per_mtok: Some(\n 0.75,\n ),\n cache_input_cost_per_mtok: None,\n },\n estimated_output_tps: Some(\n 1000.0,\n ),\n aliases: [\n \"mercury\",\n ],\n default: true,\n}"},"old":{"module_name":"fabro_model__catalog__tests","metadata":{},"snapshot":"ModelInfo {\n id: \"mercury-2\",\n provider: \"inception\",\n family: \"mercury\",\n display_name: \"Mercury 2\",\n limits: ModelLimits {\n context_window: 131072,\n max_output: Some(\n 50000,\n ),\n },\n training: None,\n features: ModelFeatures {\n tools: true,\n vision: false,\n reasoning: true,\n },\n costs: ModelCosts {\n input_cost_per_mtok: Some(\n 0.25,\n ),\n output_cost_per_mtok: Some(\n 0.75,\n ),\n cache_input_cost_per_mtok: None,\n },\n estimated_output_tps: Some(\n 1000.0,\n ),\n aliases: [\n \"mercury\",\n ],\n default: true,\n}"}}
|
||||
-{"run_id":"1774108419-651283619","line":386,"new":{"module_name":"fabro_model__catalog__tests","snapshot_name":"kimi_k2_5_in_catalog","metadata":{"source":"lib/crates/fabro-model/src/catalog.rs","assertion_line":386,"expression":"m"},"snapshot":"ModelInfo {\n id: \"kimi-k2.5\",\n provider: \"kimi\",\n family: \"kimi-k2\",\n display_name: \"Kimi K2.5\",\n limits: ModelLimits {\n context_window: 262144,\n max_output: Some(\n 16000,\n ),\n },\n training: Some(\n \"2025-10-01\",\n ),\n features: ModelFeatures {\n tools: true,\n vision: true,\n reasoning: false,\n effort: false,\n },\n costs: ModelCosts {\n input_cost_per_mtok: Some(\n 0.6,\n ),\n output_cost_per_mtok: Some(\n 3.0,\n ),\n cache_input_cost_per_mtok: None,\n },\n estimated_output_tps: Some(\n 50.0,\n ),\n aliases: [\n \"kimi\",\n ],\n default: true,\n}"},"old":{"module_name":"fabro_model__catalog__tests","metadata":{},"snapshot":"ModelInfo {\n id: \"kimi-k2.5\",\n provider: \"kimi\",\n family: \"kimi-k2\",\n display_name: \"Kimi K2.5\",\n limits: ModelLimits {\n context_window: 262144,\n max_output: Some(\n 16000,\n ),\n },\n training: Some(\n \"2025-10-01\",\n ),\n features: ModelFeatures {\n tools: true,\n vision: true,\n reasoning: false,\n },\n costs: ModelCosts {\n input_cost_per_mtok: Some(\n 0.6,\n ),\n output_cost_per_mtok: Some(\n 3.0,\n ),\n cache_input_cost_per_mtok: None,\n },\n estimated_output_tps: Some(\n 50.0,\n ),\n aliases: [\n \"kimi\",\n ],\n default: true,\n}"}}
|
||||
diff --git a/lib/crates/fabro-model/src/catalog.rs b/lib/crates/fabro-model/src/catalog.rs
|
||||
index ae90f442..525a0e6a 100644
|
||||
--- a/lib/crates/fabro-model/src/catalog.rs
|
||||
+++ b/lib/crates/fabro-model/src/catalog.rs
|
||||
@@ -270,6 +270,7 @@ mod tests {
|
||||
tools: true,
|
||||
vision: true,
|
||||
reasoning: true,
|
||||
+ effort: true,
|
||||
},
|
||||
costs: ModelCosts {
|
||||
input_cost_per_mtok: Some(
|
||||
@@ -349,6 +350,7 @@ mod tests {
|
||||
tools: true,
|
||||
vision: true,
|
||||
reasoning: true,
|
||||
+ effort: true,
|
||||
},
|
||||
costs: ModelCosts {
|
||||
input_cost_per_mtok: Some(
|
||||
@@ -402,6 +404,7 @@ mod tests {
|
||||
tools: true,
|
||||
vision: true,
|
||||
reasoning: false,
|
||||
+ effort: false,
|
||||
},
|
||||
costs: ModelCosts {
|
||||
input_cost_per_mtok: Some(
|
||||
@@ -460,6 +463,7 @@ mod tests {
|
||||
tools: true,
|
||||
vision: false,
|
||||
reasoning: true,
|
||||
+ effort: true,
|
||||
},
|
||||
costs: ModelCosts {
|
||||
input_cost_per_mtok: Some(
|
||||
@@ -508,6 +512,7 @@ mod tests {
|
||||
tools: true,
|
||||
vision: true,
|
||||
reasoning: true,
|
||||
+ effort: true,
|
||||
},
|
||||
costs: ModelCosts {
|
||||
input_cost_per_mtok: Some(
|
||||
@@ -554,6 +559,7 @@ mod tests {
|
||||
tools: true,
|
||||
vision: true,
|
||||
reasoning: true,
|
||||
+ effort: true,
|
||||
},
|
||||
costs: ModelCosts {
|
||||
input_cost_per_mtok: Some(
|
||||
@@ -620,6 +626,7 @@ mod tests {
|
||||
tools: true,
|
||||
vision: false,
|
||||
reasoning: true,
|
||||
+ effort: true,
|
||||
},
|
||||
costs: ModelCosts {
|
||||
input_cost_per_mtok: None,
|
||||
Loading…
Add table
Reference in a new issue