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Autoresearch: dynamic-chat-templates

Objective

Implement a dynamic chat-template system that selects prompt rendering by model family for local OpenAI-compatible POST /v1/chat/completions requests. The server should ship useful built-in templates for common open-source families such as Qwen, Gemma, Llama, and Kimi, while preserving a safe generic fallback for unknown models.

Metrics

  • Primary: template_score (percent, higher is better)
  • Secondary: passed_cases, failed_cases, total_cases

How to Run

./autoresearch.sh - runs targeted ignored tests for dynamic chat-template behavior and outputs METRIC name=number lines.

Files in Scope

  • crates/inference-server/src/compat.rs - prompt preparation, model catalog, template selection, family detection, and template-focused tests
  • crates/inference-server/src/routes.rs - route-level integration if template selection needs model-aware wiring
  • crates/inference-server/src/main.rs - server boot wiring if template config/env support is needed
  • crates/api-contracts/src/chat.rs - request/response roles and content handling that templates consume
  • experiments/bench_chat_templates.py - benchmark harness for the autoresearch loop
  • autoresearch.sh - loop benchmark entrypoint and fast preflight

Off Limits

  • models/ model binaries
  • vendor/ third-party sources and prebuilt llama binaries
  • registry/ Python registry service
  • ui/ frontend files
  • unrelated latency tuning or runtime/engine experiments unless they are required to support template selection correctly

Constraints

  • No new external dependencies.
  • Preserve OpenAI-compatible behavior already implemented.
  • Regular test suite must stay green for keeps.
  • Prefer explicit, maintainable template definitions over opaque heuristics.
  • Unknown models must continue to work through a generic fallback template.
  • The benchmark is test-driven: keep/discard follows the dynamic-template suite score first.

What's Been Tried

  • Segment 1 switches the autoresearch target from latency to dynamic chat-template selection by model family.
  • The current server still renders every prompt through one generic System:/User:/Assistant: formatter in crates/inference-server/src/compat.rs.
  • prepare_prompt() is the cleanest insertion point for dynamic templates because both blocking and streaming paths already consume its rendered string.
  • ModelCatalog currently resolves aliases only; it has no model-family metadata or template registry yet.
  • The benchmark for this segment is a targeted ignored test suite that scores family detection/template rendering coverage for Qwen, Gemma, Llama, Kimi, and the generic fallback.