- remove disconnect_task
- move disconnect logic to a per-request handler that wraps cleanup operation and directly polls the request state with throttling
- exclusively signal disconnect with CancelledError
- rework completions endpoint to follow same approach as chat completions, share some code
- refactor OAI endpoints a bit
- correct behavior for batched completion requests
- make sure logprobs work for completion and streaming completion requests
- more tests
- remove ToolConfig, reduce to a single `tool_format` argument and hard-code extra args like start/end tokens
- dispatch to short, self-contained (and probably easily vibe coded) parser for each model type
- remove autodetection (seems infeasible since parsing effectively starts during streaming, and there is overlap between tool formats for different models)
- streamline xml parser and dedicate to qwen3_coder models
- add parsers for glm4.x, minimax-m2.x and mistral (seems shaky, probably because mistralai don't validate against hf)
- update docs
- move tool config from template_vars to separate yml config
- new per-gen stream collector used for both streaming and non-streaming requests to ensure logic is consistent for both
- move responsibility for switching between phases to stream collector
- collect tool calls during streaming and parse at the end of each gen
- prevent streaming empty content spans (be nice to clients)
- correctly aggregate usage stats for n>1 requests, always emit with last chunk in last gen to finish
- collect logprobs in model wrapper and correctly handle logprobs for multi-token chars etc.
- respect top_logprobs argument in request
- handle a number of edge cases like <think> tag being part of held string, etc.
- retain tool parsing and inference-abort fixes from #413, apply similar fix to non-stream request as well
Still TODO:
- testing and validation with more models and tool schemas (tested on Qwen so far)
- enable JSON constraint for JSON tool models
- possibly some pydantification
- documentation
Since cache_size is a more important parameter now for multi-user
setups, mark it as such by placing it below max_seq_len.
Signed-off-by: kingbri <8082010+kingbri1@users.noreply.github.com>
- Cache size is now given only by the cache_size config option. Default is 4096 (user should always override to max out VRAM)
- max_seq_len, if not overridden in the config, will default to the model's config.json
- max_seq_len is reduced to be no larger than the cache
This allows for users to use nccl or native depending on the GPU setup.
NCCL is only available with Linux built wheels.
Signed-off-by: kingbri <8082010+kingbri1@users.noreply.github.com>
Adding these to each generation chunk helps remove redundancy and
unecessary request ID operations.
Signed-off-by: kingbri <8082010+kingbri1@users.noreply.github.com>
Doing this helps reduce the model's burden of generating the tool
call ID and type (which is always "function"). Follow mistral's spec
for tool call IDs by using a 9 character alphanumeric string.
Signed-off-by: kingbri <8082010+kingbri1@users.noreply.github.com>
