ollama/llama/runner
Jesse Gross 3478b2cf14 runner.go: Fix deadlock with many concurrent requests
If there are no avilable slots for new sequences then a request
will not be added to the processing queue but will continue on
to wait for a response that never comes. Besides never giving a
response to the request, this prevents the model from being
unloaded due to the outstanding request.

To prevent this, there are semaphores that prevent more requests
from being processed than there are slots - one in the Ollama
server and one in the runner.
 - The Ollama server one works but it is not designed to protect
the runner's data internal structures and the runner can return a
final response before clearing its data structures.
 - The internal runner semaphore has similar behavior where it
 can release the semaphore when it issues a response. This is
 wrong - it should only release the semaphore after it has
 cleared the data structure.

In addition, we should return an error if a slot is not found
rather than deadlocking in the event we ever get to this spot.

Fixes #7779
2024-11-22 16:14:51 -08:00
..
cache.go runner.go: Don't add inputs to cache view until actually processed 2024-11-20 12:49:24 -08:00
cache_test.go runner.go: Better abstract vision model integration 2024-10-30 14:53:43 -07:00
image.go runner.go: Check for zero length images 2024-11-08 09:39:32 -08:00
image_test.go runner.go: Better abstract vision model integration 2024-10-30 14:53:43 -07:00
README.md Re-introduce the llama package (#5034) 2024-10-08 08:53:54 -07:00
requirements.go Re-introduce the llama package (#5034) 2024-10-08 08:53:54 -07:00
runner.go runner.go: Fix deadlock with many concurrent requests 2024-11-22 16:14:51 -08:00
stop.go runner.go: Handle truncation of tokens for stop sequences 2024-10-09 20:39:04 -07:00
stop_test.go runner.go: Handle truncation of tokens for stop sequences 2024-10-09 20:39:04 -07:00

runner

Note: this is a work in progress

A minimial runner for loading a model and running inference via a http web server.

./runner -model <model binary>

Completion

curl -X POST -H "Content-Type: application/json" -d '{"prompt": "hi"}' http://localhost:8080/completion

Embeddings

curl -X POST -H "Content-Type: application/json" -d '{"prompt": "turn me into an embedding"}' http://localhost:8080/embeddings