fireworks add completion logprobs adapter (#778)

# What does this PR do?

- add completion log probs for fireworks

## Test Plan

<img width="849" alt="image"
src="https://github.com/user-attachments/assets/5aa1f27f-02a6-422c-8478-94dd1e345342"
/>


## Sources

Please link relevant resources if necessary.


## Before submitting

- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Ran pre-commit to handle lint / formatting issues.
- [ ] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
      Pull Request section?
- [ ] Updated relevant documentation.
- [ ] Wrote necessary unit or integration tests.
This commit is contained in:
Xi Yan 2025-01-16 10:37:07 -08:00 committed by GitHub
parent 05f6b44da7
commit e239280932
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
2 changed files with 37 additions and 3 deletions

View file

@ -168,7 +168,10 @@ class FireworksInferenceAdapter(
yield chunk
def _build_options(
self, sampling_params: Optional[SamplingParams], fmt: ResponseFormat
self,
sampling_params: Optional[SamplingParams],
fmt: ResponseFormat,
logprobs: Optional[LogProbConfig],
) -> dict:
options = get_sampling_options(sampling_params)
options.setdefault("max_tokens", 512)
@ -187,6 +190,11 @@ class FireworksInferenceAdapter(
else:
raise ValueError(f"Unknown response format {fmt.type}")
if logprobs and logprobs.top_k:
options["logprobs"] = logprobs.top_k
if options["logprobs"] <= 0 or options["logprobs"] >= 5:
raise ValueError("Required range: 0 < top_k < 5")
return options
async def chat_completion(
@ -280,7 +288,9 @@ class FireworksInferenceAdapter(
"model": request.model,
**input_dict,
"stream": request.stream,
**self._build_options(request.sampling_params, request.response_format),
**self._build_options(
request.sampling_params, request.response_format, request.logprobs
),
}
async def embeddings(

View file

@ -4,7 +4,7 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from typing import AsyncGenerator, List, Optional
from typing import AsyncGenerator, Dict, List, Optional
from llama_models.llama3.api.chat_format import ChatFormat
@ -34,6 +34,7 @@ from llama_stack.apis.inference import (
CompletionResponse,
CompletionResponseStreamChunk,
Message,
TokenLogProbs,
)
from llama_stack.providers.utils.inference.prompt_adapter import (
@ -45,10 +46,21 @@ class OpenAICompatCompletionChoiceDelta(BaseModel):
content: str
class OpenAICompatLogprobs(BaseModel):
text_offset: Optional[List[int]] = None
token_logprobs: Optional[List[float]] = None
tokens: Optional[List[str]] = None
top_logprobs: Optional[List[Dict[str, float]]] = None
class OpenAICompatCompletionChoice(BaseModel):
finish_reason: Optional[str] = None
text: Optional[str] = None
delta: Optional[OpenAICompatCompletionChoiceDelta] = None
logprobs: Optional[OpenAICompatLogprobs] = None
class OpenAICompatCompletionResponse(BaseModel):
@ -104,6 +116,14 @@ def get_stop_reason(finish_reason: str) -> StopReason:
return StopReason.out_of_tokens
def convert_openai_completion_logprobs(
logprobs: Optional[OpenAICompatLogprobs],
) -> Optional[List[TokenLogProbs]]:
if not logprobs:
return None
return [TokenLogProbs(logprobs_by_token=x) for x in logprobs.top_logprobs]
def process_completion_response(
response: OpenAICompatCompletionResponse, formatter: ChatFormat
) -> CompletionResponse:
@ -113,16 +133,19 @@ def process_completion_response(
return CompletionResponse(
stop_reason=StopReason.end_of_turn,
content=choice.text[: -len("<|eot_id|>")],
logprobs=convert_openai_completion_logprobs(choice.logprobs),
)
# drop suffix <eom_id> if present and return stop reason as end of message
if choice.text.endswith("<|eom_id|>"):
return CompletionResponse(
stop_reason=StopReason.end_of_message,
content=choice.text[: -len("<|eom_id|>")],
logprobs=convert_openai_completion_logprobs(choice.logprobs),
)
return CompletionResponse(
stop_reason=get_stop_reason(choice.finish_reason),
content=choice.text,
logprobs=convert_openai_completion_logprobs(choice.logprobs),
)
@ -165,6 +188,7 @@ async def process_completion_stream_response(
yield CompletionResponseStreamChunk(
delta=text,
stop_reason=stop_reason,
logprobs=convert_openai_completion_logprobs(choice.logprobs),
)
if finish_reason:
if finish_reason in ["stop", "eos", "eos_token"]: