67e371934c
Two related findings from round 12 reviewers: 1. The local GGUF tool loop in `generate_chat_completion_with_tools` iterates every entry of `tool_calls` returned by llama-server, even when the caller explicitly opted out of parallel tool calls. The `parallel_tool_calls` flag is forwarded to llama-server, but llama .cpp does not enforce it on every jinja template (https://github.com/ggml-org/llama.cpp/issues/22043), so a model that ignores the flag still ran multiple tools per turn. Cap `tool_calls` to the first entry when the flag is False so the client-side contract holds regardless of upstream behavior. 2. llama-server documents `parallel_tool_calls` as defaulting to FALSE (https://github.com/ggml-org/llama.cpp/blob/master/tools/server/README.md), so the previous chat-adapter shape (forward only on explicit false) meant the UI's default-on state could never enable parallel tool calls there. Always forward the user's preference on the local path so the toggle actually does what it says. External providers default to true everywhere, so the external branch is unchanged. Test pins the GGUF tool-loop cap by source-level assertion (the loop itself is integration-only). |
||
|---|---|---|
| .. | ||
| __init__.py | ||
| _html_to_md.py | ||
| anthropic_compat.py | ||
| audio_codecs.py | ||
| chat_template_helpers.py | ||
| defaults.py | ||
| external_provider.py | ||
| inference.py | ||
| key_exchange.py | ||
| llama_cpp.py | ||
| llama_server_args.py | ||
| mlx_inference.py | ||
| orchestrator.py | ||
| pricing.py | ||
| providers.py | ||
| safetensors_agentic.py | ||
| tool_call_parser.py | ||
| tools.py | ||
| worker.py | ||