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fix(router): normalize model names for usage tracking across endpoints

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Alpha Nerd 2026-02-17 11:35:53 +01:00
parent 372fe9fb72
commit 836c5f41ea
2 changed files with 27 additions and 17 deletions
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42
router.py
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@ -2684,7 +2684,16 @@ async def openai_chat_completions_proxy(request: Request):
# 2. Endpoint logic
endpoint = await choose_endpoint(model)
await increment_usage(endpoint, model)
# Normalize model name for tracking so it matches the PS table key:
# - Ollama: PS reports "model:latest" → append ":latest" when missing
# - llama-server: PS reports _normalize_llama_model_name(id) → strip HF prefix/quant
# - External OpenAI: not shown in PS, keep as-is
tracking_model = model
if endpoint in config.llama_server_endpoints:
tracking_model = _normalize_llama_model_name(model)
elif not is_ext_openai_endpoint(endpoint) and ":" not in model:
tracking_model = model + ":latest"
await increment_usage(endpoint, tracking_model)
base_url = ep2base(endpoint)
oclient = openai.AsyncOpenAI(base_url=base_url, default_headers=default_headers, api_key=config.api_keys.get(endpoint, "no-key"))
# 3. Async generator that streams completions data and decrements the counter
@ -2731,11 +2740,7 @@ async def openai_chat_completions_proxy(request: Request):
if llama_usage:
prompt_tok, comp_tok = llama_usage
if prompt_tok != 0 or comp_tok != 0:
local_model = model
if not is_ext_openai_endpoint(endpoint):
if not ":" in model:
local_model = model if ":" in model else model + ":latest"
await token_queue.put((endpoint, local_model, prompt_tok, comp_tok))
await token_queue.put((endpoint, tracking_model, prompt_tok, comp_tok))
yield b"data: [DONE]\n\n"
else:
prompt_tok = 0
@ -2748,7 +2753,7 @@ async def openai_chat_completions_proxy(request: Request):
if llama_usage:
prompt_tok, comp_tok = llama_usage
if prompt_tok != 0 or comp_tok != 0:
await token_queue.put((endpoint, model, prompt_tok, comp_tok))
await token_queue.put((endpoint, tracking_model, prompt_tok, comp_tok))
json_line = (
async_gen.model_dump_json()
if hasattr(async_gen, "model_dump_json")
@ -2758,7 +2763,7 @@ async def openai_chat_completions_proxy(request: Request):
finally:
# Ensure counter is decremented even if an exception occurs
await decrement_usage(endpoint, model)
await decrement_usage(endpoint, tracking_model)
# 4. Return a StreamingResponse backed by the generator
return StreamingResponse(
@ -2832,7 +2837,16 @@ async def openai_completions_proxy(request: Request):
# 2. Endpoint logic
endpoint = await choose_endpoint(model)
await increment_usage(endpoint, model)
# Normalize model name for tracking so it matches the PS table key:
# - Ollama: PS reports "model:latest" → append ":latest" when missing
# - llama-server: PS reports _normalize_llama_model_name(id) → strip HF prefix/quant
# - External OpenAI: not shown in PS, keep as-is
tracking_model = model
if endpoint in config.llama_server_endpoints:
tracking_model = _normalize_llama_model_name(model)
elif not is_ext_openai_endpoint(endpoint) and ":" not in model:
tracking_model = model + ":latest"
await increment_usage(endpoint, tracking_model)
base_url = ep2base(endpoint)
oclient = openai.AsyncOpenAI(base_url=base_url, default_headers=default_headers, api_key=config.api_keys.get(endpoint, "no-key"))
@ -2870,11 +2884,7 @@ async def openai_completions_proxy(request: Request):
if llama_usage:
prompt_tok, comp_tok = llama_usage
if prompt_tok != 0 or comp_tok != 0:
local_model = model
if not is_ext_openai_endpoint(endpoint):
if not ":" in model:
local_model = model if ":" in model else model + ":latest"
await token_queue.put((endpoint, local_model, prompt_tok, comp_tok))
await token_queue.put((endpoint, tracking_model, prompt_tok, comp_tok))
# Final DONE event
yield b"data: [DONE]\n\n"
else:
@ -2888,7 +2898,7 @@ async def openai_completions_proxy(request: Request):
if llama_usage:
prompt_tok, comp_tok = llama_usage
if prompt_tok != 0 or comp_tok != 0:
await token_queue.put((endpoint, model, prompt_tok, comp_tok))
await token_queue.put((endpoint, tracking_model, prompt_tok, comp_tok))
json_line = (
async_gen.model_dump_json()
if hasattr(async_gen, "model_dump_json")
@ -2898,7 +2908,7 @@ async def openai_completions_proxy(request: Request):
finally:
# Ensure counter is decremented even if an exception occurs
await decrement_usage(endpoint, model)
await decrement_usage(endpoint, tracking_model)
# 4. Return a StreamingResponse backed by the generator
return StreamingResponse(