mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-07-29 15:23:51 +00:00
update inference adapters
This commit is contained in:
parent
29d1ef3fdc
commit
7d6ebf4b72
5 changed files with 75 additions and 5 deletions
|
@ -76,7 +76,28 @@ class FireworksInferenceAdapter(Inference):
|
|||
|
||||
return options
|
||||
|
||||
async def chat_completion(self, request: ChatCompletionRequest) -> AsyncGenerator:
|
||||
async def chat_completion(
|
||||
self,
|
||||
model: str,
|
||||
messages: List[Message],
|
||||
sampling_params: Optional[SamplingParams] = SamplingParams(),
|
||||
tools: Optional[List[ToolDefinition]] = list(),
|
||||
tool_choice: Optional[ToolChoice] = ToolChoice.auto,
|
||||
tool_prompt_format: Optional[ToolPromptFormat] = ToolPromptFormat.json,
|
||||
stream: Optional[bool] = False,
|
||||
logprobs: Optional[LogProbConfig] = None,
|
||||
) -> AsyncGenerator:
|
||||
request = ChatCompletionRequest(
|
||||
model=model,
|
||||
messages=messages,
|
||||
sampling_params=sampling_params,
|
||||
tools=tools,
|
||||
tool_choice=tool_choice,
|
||||
tool_prompt_format=tool_prompt_format,
|
||||
stream=stream,
|
||||
logprobs=logprobs,
|
||||
)
|
||||
|
||||
messages = prepare_messages(request)
|
||||
|
||||
# accumulate sampling params and other options to pass to fireworks
|
||||
|
|
|
@ -84,7 +84,28 @@ class OllamaInferenceAdapter(Inference):
|
|||
|
||||
return options
|
||||
|
||||
async def chat_completion(self, request: ChatCompletionRequest) -> AsyncGenerator:
|
||||
async def chat_completion(
|
||||
self,
|
||||
model: str,
|
||||
messages: List[Message],
|
||||
sampling_params: Optional[SamplingParams] = SamplingParams(),
|
||||
tools: Optional[List[ToolDefinition]] = list(),
|
||||
tool_choice: Optional[ToolChoice] = ToolChoice.auto,
|
||||
tool_prompt_format: Optional[ToolPromptFormat] = ToolPromptFormat.json,
|
||||
stream: Optional[bool] = False,
|
||||
logprobs: Optional[LogProbConfig] = None,
|
||||
) -> AsyncGenerator:
|
||||
request = ChatCompletionRequest(
|
||||
model=model,
|
||||
messages=messages,
|
||||
sampling_params=sampling_params,
|
||||
tools=tools,
|
||||
tool_choice=tool_choice,
|
||||
tool_prompt_format=tool_prompt_format,
|
||||
stream=stream,
|
||||
logprobs=logprobs,
|
||||
)
|
||||
|
||||
messages = prepare_messages(request)
|
||||
# accumulate sampling params and other options to pass to ollama
|
||||
options = self.get_ollama_chat_options(request)
|
||||
|
|
|
@ -87,7 +87,28 @@ class TGIInferenceAdapter(Inference):
|
|||
|
||||
return options
|
||||
|
||||
async def chat_completion(self, request: ChatCompletionRequest) -> AsyncGenerator:
|
||||
async def chat_completion(
|
||||
self,
|
||||
model: str,
|
||||
messages: List[Message],
|
||||
sampling_params: Optional[SamplingParams] = SamplingParams(),
|
||||
tools: Optional[List[ToolDefinition]] = list(),
|
||||
tool_choice: Optional[ToolChoice] = ToolChoice.auto,
|
||||
tool_prompt_format: Optional[ToolPromptFormat] = ToolPromptFormat.json,
|
||||
stream: Optional[bool] = False,
|
||||
logprobs: Optional[LogProbConfig] = None,
|
||||
) -> AsyncGenerator:
|
||||
request = ChatCompletionRequest(
|
||||
model=model,
|
||||
messages=messages,
|
||||
sampling_params=sampling_params,
|
||||
tools=tools,
|
||||
tool_choice=tool_choice,
|
||||
tool_prompt_format=tool_prompt_format,
|
||||
stream=stream,
|
||||
logprobs=logprobs,
|
||||
)
|
||||
|
||||
messages = prepare_messages(request)
|
||||
|
||||
model_input = self.formatter.encode_dialog_prompt(messages)
|
||||
|
|
|
@ -249,7 +249,12 @@ class InferenceTests(unittest.IsolatedAsyncioTestCase):
|
|||
stream=True,
|
||||
tools=[ToolDefinition(tool_name=BuiltinTool.brave_search)],
|
||||
)
|
||||
iterator = self.api.chat_completion(request)
|
||||
iterator = self.api.chat_completion(
|
||||
request.model,
|
||||
request.messages,
|
||||
stream=request.stream,
|
||||
tools=request.tools,
|
||||
)
|
||||
|
||||
events = []
|
||||
async for chunk in iterator:
|
||||
|
|
|
@ -61,7 +61,9 @@ class OllamaInferenceTests(unittest.IsolatedAsyncioTestCase):
|
|||
],
|
||||
stream=False,
|
||||
)
|
||||
iterator = self.api.chat_completion(request)
|
||||
iterator = self.api.chat_completion(
|
||||
request.model, request.messages, stream=request.stream
|
||||
)
|
||||
async for r in iterator:
|
||||
response = r
|
||||
print(response.completion_message.content)
|
||||
|
|
Loading…
Add table
Add a link
Reference in a new issue