[chethanuk]

What

Custom-mode llm_classifier routes can now set response_format_type = "json_object". On main the runner rejects that combination at config load. Capability and escalation routes already support it.

It works the same way as for the packaged classifiers. Switchyard appends the configured response_schema to the judge prompt, sends {"type": "json_object"}, and checks the verdict against the schema locally. A verdict that fails the check falls back to default_target. JSON Schema stays the default, so existing routes don't change.

• ClassifierContract::from_inner_schema takes the response format. from_config and the custom path share one helper, schema_in_prompt.
• In JSON Object mode, a response_schema whose root type doesn't allow object (a string other than "object", or an array without it) is rejected at load. The provider only returns objects, so such a schema would send every turn to default_target. A schema with no type at all is not checked.
• CustomClassifierConfig gets a response_format_type field (default JsonSchema). The runner passes it for the top-level route in build_algorithm and for the nested subagents classifier in build_subagent_router_config.
• The Python CustomClassifierConfig takes response_format_type="json_schema", parsed the same way as the other classifier configs. The switchyard_rust/libsy.py stub is updated.
• Docs: the response_format_type row in toml_schema.md and the custom section of llm_classifier_routing.md.

Why

For NVIDIA-NeMo#429. Some providers support JSON Object mode but not JSON Schema, and custom classifiers couldn't use them. The contract follows the issue's conservative option: response_schema is still required in both modes and is the source of truth, so a prompt never needs its own copy. Provider wrappers such as {"json_schema": {...}} are still rejected as an inner schema.

Before / After

Same config and request against a stub OpenAI upstream. The config (custom-json-object.toml) and stub (mock.py) are in pr-evidence/6. Both binaries were built with cargo build --locked -p switchyard-server --bin switchyard-server, the stub was started with python3 mock.py 18431, and every output line below is copied verbatim from that run.

$ grep -E '^(mode|response_format_type) ' custom-json-object.toml
mode = "custom"
response_format_type = "json_object"

Before, base a601a9a3f9db149a1ad430fa43b1463a170c8a82 (fork main, before it was synced to upstream). The server exits with status 1:

$ switchyard-server --config custom-json-object.toml --host 127.0.0.1 --port 18432
invalid server config custom-json-object.toml: llm_classifier route custom mode custom cannot use capability or escalation fields and response_format_type must be 'json_schema': llm_classifier route custom mode custom cannot use capability or escalation fields and response_format_type must be 'json_schema': llm_classifier route custom mode custom cannot use capability or escalation fields and response_format_type must be 'json_schema'

After, PR head d9c819f599322108d8debd0df16608a7e7cb3547 (re-run at this head):

$ switchyard-server --config custom-json-object.toml --host 127.0.0.1 --port 18432 &
$ curl -s http://127.0.0.1:18432/v1/chat/completions -H 'Content-Type: application/json' -d '{"model":"switchyard/custom","messages":[{"role":"user","content":"Refactor the scheduler."}]}' | jq -r '.model, .choices[0].message.content'
strong/model
hello from strong/model
$ cat mock.log   # what the stub upstream received
[mock] judge response_format = {"type": "json_object"}
[mock] schema in judge prompt: True
[mock] completion served by strong/model

Notes for reviewers

Start with crates/libsy/src/algorithms/util/classifier_contract.rs. Both constructors run validate_prompt on the template, never on the prompt with the schema appended. The appended text is never empty, and a schema may itself contain the literal {{RESPONSE_SCHEMA}}.

This adds a public field to CustomClassifierConfig, so Rust callers that build it with a struct literal instead of new() must add response_format_type. It follows how other public config fields were added before 1.0.

build_subagent_router_config is easy to miss. Without the field there, a nested custom classifier would quietly stay on JSON Schema; subagent_custom_classifier_can_request_json_object_output covers it.

The server test mock used to recognize custom judge calls only by response_format.json_schema. It now also recognizes a json_object request whose prompt contains the custom schema.

Verification, at the head of this PR rebased on fbabf51c (upstream main):

cargo fmt --all --check                                                                      # clean
cargo clippy -p switchyard-libsy -p switchyard-runner -p switchyard-server -p switchyard-py \
  --all-targets -- -D warnings                                                               # clean
cargo test -p switchyard-libsy -p switchyard-runner -p switchyard-server                     # all pass (330 libsy unit tests, 64 runner, 58 server)

The new runner and server tests fail on main with the old config error. The Python tests (tests/test_libsy_minimal_bindings.py) pass locally against an extension built with maturin develop (22 passed, including the two new custom-classifier tests). They have not run on the fork's CI.

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  CodeAnt Review Status

✅  Review completed

Status	Commit	Started (UTC)	Finished (UTC)
✅  Incremental review completed	11b8af7	Oct 30, 2026 · 07:19	07:20
✅  Incremental review completed	1ffbd00	Oct 02, 2026 · 09:03	09:03
✅  Incremental review completed	d9e7eb7	Oct 01, 2026 · 20:32	20:33
✅  Incremental review completed	723f761	Sep 30, 2026 · 14:21	14:22
✅  Incremental review completed	0739a18	Sep 30, 2026 · 12:40	12:41

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• Route changes are validated and backed up before the server restarts. Harness settings show a preview before installation and preserve the original files for restoration.
• Custom classifiers can request JSON Object output. Switchyard includes the configured schema in the judge prompt, checks verdicts against it, and uses the default target for invalid verdicts.
• Python hosts can build configured routes from deployment TOML without Switchyard creating upstream provider clients.
• VGR can run without its decision deadline and efficient-turn budget when configured. Served-answer reporting keeps turn handling accurate after incomplete replies and recovery messages.
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Walkthrough

Custom classifier routes now support json_object and json_schema response formats. The selected format propagates through Rust and Python configuration, changes contract construction, validates JSON Object verdicts locally, and is covered by deployment and integration tests.

Changes

Custom classifier response formats

Layer / File(s)	Summary
Classifier contract format handling crates/libsy/src/algorithms/llm_class.rs, crates/libsy/src/algorithms/util/classifier_contract.rs	Custom classifier contracts accept the selected response format. JSON Object mode appends the configured schema to the prompt and validates verdicts locally.
Configuration and runtime propagation crates/switchyard-py/src/libsy_bindings.rs, switchyard_rust/libsy.py, crates/switchyard-runner/src/algorithm.rs	Rust routes and Python bindings accept response_format_type, default it to json_schema, reject unknown values, and pass the setting to runtime custom classifiers.
Deployment and integration validation crates/switchyard-runner/src/config.rs, crates/switchyard-server/tests/server.rs, tests/test_libsy_minimal_bindings.py	Tests cover top-level and subagent JSON Object routes, schema prompts, local verdict validation, fallback routing, and invalid format values.
Configuration documentation CHANGELOG.md, docs/reference/toml_schema.md, docs/routing_algorithms/llm_classifier_routing.md	Documentation describes JSON Object configuration, schema placement, local validation, defaults, and fallback behavior.

Priority: ⬇️ Low

Estimated code review effort: 3 (Moderate) | ~25 minutes

Merge Risk: 🔵 Low · up to ebdbf

The configuration reference can mislead custom-classifier users about automatic schema insertion. Correct the wording before merge or ensure owners explicitly accept this narrow documentation risk.

🚥 Pre-merge checks | ✅ 4 | ❌ 1

❌ Failed checks (1 warning)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 51.61% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 31 functions across 8 files. (3 skipped: …	Write docstrings for the functions missing them to satisfy the coverage threshold.

✅ Passed checks (4 passed)

Check name	Status	Explanation
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title clearly and concisely describes the main change: adding JSON Object output support for custom classifiers.

Full details: Docstring Coverage

Explanation

Docstring coverage is 51.61% which is insufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 31 functions across 8 files. (3 skipped: 3 unsupported.)

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Actionable comments posted: 1

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• 🪄 Fix CodeRabbit comments on this PR

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Inline comments:
In `@docs/reference/toml_schema.md`:
- Line 219: Update the response_format_type documentation to clarify that in
custom JSON Object mode, the configured response_schema is the source of truth,
Switchyard inserts it into the judge prompt automatically, and users must not
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📒 Files selected for processing (11)

• CHANGELOG.md
• crates/libsy/src/algorithms/llm_class.rs
• crates/libsy/src/algorithms/util/classifier_contract.rs
• crates/switchyard-py/src/libsy_bindings.rs
• crates/switchyard-runner/src/algorithm.rs
• crates/switchyard-runner/src/config.rs
• crates/switchyard-server/tests/server.rs
• docs/reference/toml_schema.md
• docs/routing_algorithms/llm_classifier_routing.md
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• Route changes are validated and backed up before the server restarts. Harness settings show a preview before installation and preserve the original files for restoration.
• Custom classifiers can request JSON Object output. Switchyard includes the configured schema in the judge prompt, checks verdicts against it, and uses the default target for invalid verdicts.
• Python hosts can build configured routes from deployment TOML without Switchyard creating upstream provider clients.
• VGR can run without its decision deadline and efficient-turn budget when configured. Served-answer reporting keeps turn handling accurate after incomplete replies and recovery messages.
• OpenAI Chat requests retry once without an explicitly rejected thinking option; Codex Responses requests with string input are sent in the format that endpoint expects.

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• Added Routes and Harnesses pages to inspect and filter routes, review route changes, and preview, install, or restore routing settings for Codex CLI, Codex app, Claude Code, and Pi. You can also choose saved Codex or Claude accounts or a custom settings file.
• Route changes are validated and backed up before the server restarts. Harness settings show a preview before installation and preserve the original files for restoration.
• Custom classifiers can request JSON Object output. Switchyard includes the configured schema in the judge prompt, checks verdicts against it, and uses the default target for invalid verdicts.
• Python hosts can build configured routes from deployment TOML without Switchyard creating upstream provider clients.
• VGR can run without its decision deadline and efficient-turn budget when configured. Served-answer reporting keeps turn handling accurate after incomplete replies and recovery messages.
• OpenAI Chat requests retry once without an explicitly rejected thinking option; Codex Responses requests with string input are sent in the format that endpoint expects.

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• Added Routes and Harnesses pages to inspect and filter routes, review route changes, and preview, install, or restore routing settings for Codex CLI, Codex app, Claude Code, and Pi. You can also choose saved Codex or Claude accounts or a custom settings file.
• Route changes are validated and backed up before the server restarts. Harness settings show a preview before installation and preserve the original files for restoration.
• Custom classifiers can request JSON Object output. Switchyard includes the configured schema in the judge prompt, checks verdicts against it, and uses the default target for invalid verdicts.
• Python hosts can build configured routes from deployment TOML without Switchyard creating upstream provider clients.
• VGR can run without its decision deadline and efficient-turn budget when configured. Served-answer reporting keeps turn handling accurate after incomplete replies and recovery messages.
• OpenAI Chat requests retry once without an explicitly rejected thinking option; Codex Responses requests with string input are sent in the format that endpoint expects.

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[chethanuk]

Thanks for the review. Changes are in 10ac672.

• Unrelated translation diff: fixed. I rebased the branch onto fork main (a601a9a), so the PR now shows only the 10 feature files. The two upstream commits (fix(translation): keep the provider reasoning id when a summary streams before it NVIDIA-NeMo/Switchyard#861, fix(responses): preserve streamed response IDs for conversation continuation NVIDIA-NeMo/Switchyard#869) don't touch any of them. The body now says the "before" screenshot came from upstream c7fee3e.
• type union rejected in json_object mode: real bug, fixed. The guard now rejects only a string type other than "object" or an array that doesn't contain it. I added ["string", "null"] to the rejection test and a new test that ["object"] and ["object", "null"] are accepted. I left out schemas like {"const": "x"} on purpose: the check is there to catch the obvious mistake at load, and local validation still sends anything else to default_target.
• Stale docs: fixed. The line-126 table row now matches toml_schema.md. The custom-section paragraph and the CustomClassifierConfig::response_schema doc comment now describe both modes.
• No positive Python test: added test_custom_classifier_config_accepts_json_object_output. It checks that the judge request has {"type": "json_object"} and that the schema appears in the prompt.
• from __future__ removal, skill_distillation snapshot, configure flags, STATS_TEST_LOCK, switchyard-skill-distillation validation, negative-flag test: these don't apply here. None of those files are in this PR. They're from the skill-distillation branch (the review worktree at 4759b61).

Verification: cargo test -p switchyard-libsy classifier_contract passed 10/10, and cargo fmt --check and cargo clippy -p switchyard-libsy --all-targets -D warnings are clean. ruff check on the test file passes. I couldn't run the new Python test because the disk filled while maturin develop was building. CI will run it.

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• Added Routes and Harnesses pages to inspect and filter routes, review route changes, and preview, install, or restore routing settings for Codex CLI, Codex app, Claude Code, and Pi. You can also choose saved Codex or Claude accounts or a custom settings file.
• Route changes are validated and backed up before the server restarts. Harness settings show a preview before installation and preserve the original files for restoration.
• Custom classifiers can request JSON Object output. Switchyard includes the configured schema in the judge prompt, checks verdicts against it, and uses the default target for invalid verdicts.
• Python hosts can build configured routes from deployment TOML without Switchyard creating upstream provider clients.
• VGR can run without its decision deadline and efficient-turn budget when configured. Served-answer reporting keeps turn handling accurate after incomplete replies and recovery messages.
• OpenAI Chat requests retry once without an explicitly rejected thinking option; Codex Responses requests with string input are sent in the format that endpoint expects.

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✅ Route edits reviewed and backed up before restart
✅ Harness settings previewed before installation and recoverable afterward
✅ Custom classifiers usable with JSON-object-only providers

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• Added Routes and Harnesses pages to inspect and filter routes, review route changes, and preview, install, or restore routing settings for Codex CLI, Codex app, Claude Code, and Pi. You can also choose saved Codex or Claude accounts or a custom settings file.
• Route changes are validated and backed up before the server restarts. Harness settings show a preview before installation and preserve the original files for restoration.
• Custom classifiers can request JSON Object output. Switchyard includes the configured schema in the judge prompt, checks verdicts against it, and uses the default target for invalid verdicts.
• Python hosts can build configured routes from deployment TOML without Switchyard creating upstream provider clients.
• VGR can run without its decision deadline and efficient-turn budget when configured. Served-answer reporting keeps turn handling accurate after incomplete replies and recovery messages.
• OpenAI Chat requests retry once without an explicitly rejected thinking option; Codex Responses requests with string input are sent in the format that endpoint expects.

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✅ Route edits reviewed and backed up before restart
✅ Harness settings previewed before installation and recoverable afterward
✅ Custom classifiers usable with JSON-object-only providers

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What Changed

• Added Routes and Harnesses pages to inspect and filter routes, review route changes, and preview, install, or restore routing settings for Codex CLI, Codex app, Claude Code, and Pi. You can also choose saved Codex or Claude accounts or a custom settings file.
• Route changes are validated and backed up before the server restarts. Harness settings show a preview before installation and preserve the original files for restoration.
• Custom classifiers can request JSON Object output. Switchyard includes the configured schema in the judge prompt, checks verdicts against it, and uses the default target for invalid verdicts.
• Python hosts can build configured routes from deployment TOML without Switchyard creating upstream provider clients.
• VGR can run without its decision deadline and efficient-turn budget when configured. Served-answer reporting keeps turn handling accurate after incomplete replies and recovery messages.
• OpenAI Chat requests retry once without an explicitly rejected thinking option; Codex Responses requests with string input are sent in the format that endpoint expects.

Impact

✅ Route edits reviewed and backed up before restart
✅ Harness settings previewed before installation and recoverable afterward
✅ Custom classifiers usable with JSON-object-only providers

💡 Usage Guide

Checking Your Pull Request

Every time you make a pull request, our system automatically looks through it. We check for security issues, mistakes in how you're setting up your infrastructure, and common code problems. We do this to make sure your changes are solid and won't cause any trouble later.

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[codeant-ai]

CodeAnt-AI Description

Manage routes and harness settings from the terminal app

What Changed

• Added Routes and Harnesses pages to inspect and filter routes, review route changes, and preview, install, or restore routing settings for Codex CLI, Codex app, Claude Code, and Pi. You can also choose saved Codex or Claude accounts or a custom settings file.
• Route changes are validated and backed up before the server restarts. Harness settings show a preview before installation and preserve the original files for restoration.
• Custom classifiers can request JSON Object output. Switchyard includes the configured schema in the judge prompt, checks verdicts against it, and uses the default target for invalid verdicts.
• Python hosts can build configured routes from deployment TOML without Switchyard creating upstream provider clients.
• VGR can run without its decision deadline and efficient-turn budget when configured. Served-answer reporting keeps turn handling accurate after incomplete replies and recovery messages.
• OpenAI Chat requests retry once without an explicitly rejected thinking option; Codex Responses requests with string input are sent in the format that endpoint expects.

Impact

✅ Route edits reviewed and backed up before restart
✅ Harness settings previewed before installation and recoverable afterward
✅ Custom classifiers usable with JSON-object-only providers

💡 Usage Guide

Checking Your Pull Request

Every time you make a pull request, our system automatically looks through it. We check for security issues, mistakes in how you're setting up your infrastructure, and common code problems. We do this to make sure your changes are solid and won't cause any trouble later.

Talking to CodeAnt AI

Got a question or need a hand with something in your pull request? You can easily get in touch with CodeAnt AI right here. Just type the following in a comment on your pull request, and replace "Your question here" with whatever you want to ask:

@codeant-ai ask: Your question here

This lets you have a chat with CodeAnt AI about your pull request, making it easier to understand and improve your code.

Example

@codeant-ai ask: Can you suggest a safer alternative to storing this secret?

Preserve Org Learnings with CodeAnt

You can record team preferences so CodeAnt AI applies them in future reviews. Reply directly to the specific CodeAnt AI suggestion (in the same thread) and replace "Your feedback here" with your input:

@codeant-ai: Your feedback here

This helps CodeAnt AI learn and adapt to your team's coding style and standards.

Example

@codeant-ai: Do not flag unused imports.

Retrigger review

Ask CodeAnt AI to review the PR again, by typing:

@codeant-ai: review

Check Your Repository Health

To analyze the health of your code repository, visit our dashboard at https://app.codeant.ai. This tool helps you identify potential issues and areas for improvement in your codebase, ensuring your repository maintains high standards of code health.

[codeant-ai]

CodeAnt-AI Description

Manage routes and harness settings from the terminal app

What Changed

• Added Routes and Harnesses pages to inspect and filter routes, review route changes, and preview, install, or restore routing settings for Codex CLI, Codex app, Claude Code, and Pi. You can also choose saved Codex or Claude accounts or a custom settings file.
• Route changes are validated and backed up before the server restarts. Harness settings show a preview before installation and preserve the original files for restoration.
• Custom classifiers can request JSON Object output. Switchyard includes the configured schema in the judge prompt, checks verdicts against it, and uses the default target for invalid verdicts.
• Python hosts can build configured routes from deployment TOML without Switchyard creating upstream provider clients.
• VGR can run without its decision deadline and efficient-turn budget when configured. Served-answer reporting keeps turn handling accurate after incomplete replies and recovery messages.
• OpenAI Chat requests retry once without an explicitly rejected thinking option; Codex Responses requests with string input are sent in the format that endpoint expects.

Impact

✅ Route edits reviewed and backed up before restart
✅ Harness settings previewed before installation and recoverable afterward
✅ Custom classifiers usable with JSON-object-only providers

💡 Usage Guide

Checking Your Pull Request

Every time you make a pull request, our system automatically looks through it. We check for security issues, mistakes in how you're setting up your infrastructure, and common code problems. We do this to make sure your changes are solid and won't cause any trouble later.

Talking to CodeAnt AI

Got a question or need a hand with something in your pull request? You can easily get in touch with CodeAnt AI right here. Just type the following in a comment on your pull request, and replace "Your question here" with whatever you want to ask:

@codeant-ai ask: Your question here

This lets you have a chat with CodeAnt AI about your pull request, making it easier to understand and improve your code.

Example

@codeant-ai ask: Can you suggest a safer alternative to storing this secret?

Preserve Org Learnings with CodeAnt

You can record team preferences so CodeAnt AI applies them in future reviews. Reply directly to the specific CodeAnt AI suggestion (in the same thread) and replace "Your feedback here" with your input:

@codeant-ai: Your feedback here

This helps CodeAnt AI learn and adapt to your team's coding style and standards.

Example

@codeant-ai: Do not flag unused imports.

Retrigger review

Ask CodeAnt AI to review the PR again, by typing:

@codeant-ai: review

Check Your Repository Health

To analyze the health of your code repository, visit our dashboard at https://app.codeant.ai. This tool helps you identify potential issues and areas for improvement in your codebase, ensuring your repository maintains high standards of code health.

[github-actions]

PR Preview Action v1.8.2
🚀 View preview at https://chethanuk.github.io/Switchyard/pr-preview/pr-6/
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