Together AI basic integration (#43)

* working!

* accounting for eos

llama_toolchain/distribution/registry.py

@@ -59,6 +59,15 @@ def available_distribution_specs() -> List[DistributionSpec]:
                 Api.agentic_system: providers[Api.agentic_system]["meta-reference"],
             },
         ),
+        DistributionSpec(
+            spec_id="remote-together",
+            description="Use Together.ai for running LLM inference",
+            provider_specs={
+                Api.inference: providers[Api.inference]["together"],
+                Api.safety: providers[Api.safety]["meta-reference"],
+                Api.agentic_system: providers[Api.agentic_system]["meta-reference"],
+            },
+        ),
     ]
 
 

llama_toolchain/inference/providers.py

@@ -45,4 +45,13 @@ def available_inference_providers() -> List[ProviderSpec]:
             module="llama_toolchain.inference.fireworks",
             config_class="llama_toolchain.inference.fireworks.FireworksImplConfig",
         ),
+        InlineProviderSpec(
+            api=Api.inference,
+            provider_id="together",
+            pip_packages=[
+                "together",
+            ],
+            module="llama_toolchain.inference.together",
+            config_class="llama_toolchain.inference.together.TogetherImplConfig",
+        ),
     ]

llama_toolchain/inference/together/__init__.py

@@ -0,0 +1,8 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from .config import TogetherImplConfig  # noqa
+from .together import get_provider_impl  # noqa

llama_toolchain/inference/together/config.py

@@ -0,0 +1,20 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+from llama_models.schema_utils import json_schema_type
+from pydantic import BaseModel, Field
+
+
+@json_schema_type
+class TogetherImplConfig(BaseModel):
+    url: str = Field(
+        default="https://api.together.xyz/v1",
+        description="The URL for the Together AI server",
+    )
+    api_key: str = Field(
+        default="",
+        description="The Together AI API Key",
+    )

llama_toolchain/inference/together/together.py

@@ -0,0 +1,318 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the terms described in the LICENSE file in
+# the root directory of this source tree.
+
+import uuid
+from typing import AsyncGenerator, Dict
+
+from llama_models.llama3.api.datatypes import (
+    BuiltinTool,
+    CompletionMessage,
+    Message,
+    StopReason,
+    ToolCall,
+)
+from llama_models.llama3.api.tool_utils import ToolUtils
+from llama_models.sku_list import resolve_model
+from together import Together
+
+from llama_toolchain.distribution.datatypes import Api, ProviderSpec
+from llama_toolchain.inference.api import (
+    ChatCompletionRequest,
+    ChatCompletionResponse,
+    ChatCompletionResponseEvent,
+    ChatCompletionResponseEventType,
+    ChatCompletionResponseStreamChunk,
+    CompletionRequest,
+    Inference,
+    ToolCallDelta,
+    ToolCallParseStatus,
+)
+
+from .config import TogetherImplConfig
+
+TOGETHER_SUPPORTED_MODELS = {
+    "Meta-Llama3.1-8B-Instruct": "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo",
+    "Meta-Llama3.1-70B-Instruct": "meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo",
+    "Meta-Llama3.1-405B-Instruct": "meta-llama/Meta-Llama-3.1-405B-Instruct-Turbo",
+}
+
+
+async def get_provider_impl(
+    config: TogetherImplConfig, _deps: Dict[Api, ProviderSpec]
+) -> Inference:
+    assert isinstance(
+        config, TogetherImplConfig
+    ), f"Unexpected config type: {type(config)}"
+    impl = TogetherInference(config)
+    await impl.initialize()
+    return impl
+
+
+class TogetherInference(Inference):
+    def __init__(self, config: TogetherImplConfig) -> None:
+        self.config = config
+
+    @property
+    def client(self) -> Together:
+        return Together(api_key=self.config.api_key)
+
+    async def initialize(self) -> None:
+        return
+
+    async def shutdown(self) -> None:
+        pass
+
+    async def completion(self, request: CompletionRequest) -> AsyncGenerator:
+        raise NotImplementedError()
+
+    def _messages_to_together_messages(self, messages: list[Message]) -> list:
+        together_messages = []
+        for message in messages:
+            if message.role == "ipython":
+                role = "tool"
+            else:
+                role = message.role
+            together_messages.append({"role": role, "content": message.content})
+
+        return together_messages
+
+    def resolve_together_model(self, model_name: str) -> str:
+        model = resolve_model(model_name)
+        assert (
+            model is not None
+            and model.descriptor(shorten_default_variant=True)
+            in TOGETHER_SUPPORTED_MODELS
+        ), f"Unsupported model: {model_name}, use one of the supported models: {','.join(TOGETHER_SUPPORTED_MODELS.keys())}"
+
+        return TOGETHER_SUPPORTED_MODELS.get(
+            model.descriptor(shorten_default_variant=True)
+        )
+
+    def get_together_chat_options(self, request: ChatCompletionRequest) -> dict:
+        options = {}
+        if request.sampling_params is not None:
+            for attr in {"temperature", "top_p", "top_k", "max_tokens"}:
+                if getattr(request.sampling_params, attr):
+                    options[attr] = getattr(request.sampling_params, attr)
+
+        return options
+
+    async def chat_completion(self, request: ChatCompletionRequest) -> AsyncGenerator:
+        # accumulate sampling params and other options to pass to together
+        options = self.get_together_chat_options(request)
+        together_model = self.resolve_together_model(request.model)
+
+        if not request.stream:
+            # TODO: might need to add back an async here
+            r = self.client.chat.completions.create(
+                model=together_model,
+                messages=self._messages_to_together_messages(request.messages),
+                stream=False,
+                **options,
+            )
+            stop_reason = None
+            if r.choices[0].finish_reason:
+                if (
+                    r.choices[0].finish_reason == "stop"
+                    or r.choices[0].finish_reason == "eos"
+                ):
+                    stop_reason = StopReason.end_of_turn
+                elif r.choices[0].finish_reason == "length":
+                    stop_reason = StopReason.out_of_tokens
+
+            completion_message = decode_assistant_message_from_content(
+                r.choices[0].message.content,
+                stop_reason,
+            )
+            yield ChatCompletionResponse(
+                completion_message=completion_message,
+                logprobs=None,
+            )
+        else:
+            yield ChatCompletionResponseStreamChunk(
+                event=ChatCompletionResponseEvent(
+                    event_type=ChatCompletionResponseEventType.start,
+                    delta="",
+                )
+            )
+
+            buffer = ""
+            ipython = False
+            stop_reason = None
+
+            for chunk in self.client.chat.completions.create(
+                model=together_model,
+                messages=self._messages_to_together_messages(request.messages),
+                stream=True,
+                **options,
+            ):
+                if chunk.choices[0].finish_reason:
+                    if (
+                        stop_reason is None and chunk.choices[0].finish_reason == "stop"
+                    ) or (
+                        stop_reason is None and chunk.choices[0].finish_reason == "eos"
+                    ):
+                        stop_reason = StopReason.end_of_turn
+                    elif (
+                        stop_reason is None
+                        and chunk.choices[0].finish_reason == "length"
+                    ):
+                        stop_reason = StopReason.out_of_tokens
+                    break
+
+                text = chunk.choices[0].delta.content
+                if text is None:
+                    continue
+
+                # check if its a tool call ( aka starts with <|python_tag|> )
+                if not ipython and text.startswith("<|python_tag|>"):
+                    ipython = True
+                    yield ChatCompletionResponseStreamChunk(
+                        event=ChatCompletionResponseEvent(
+                            event_type=ChatCompletionResponseEventType.progress,
+                            delta=ToolCallDelta(
+                                content="",
+                                parse_status=ToolCallParseStatus.started,
+                            ),
+                        )
+                    )
+                    buffer += text
+                    continue
+
+                if ipython:
+                    if text == "<|eot_id|>":
+                        stop_reason = StopReason.end_of_turn
+                        text = ""
+                        continue
+                    elif text == "<|eom_id|>":
+                        stop_reason = StopReason.end_of_message
+                        text = ""
+                        continue
+
+                    buffer += text
+                    delta = ToolCallDelta(
+                        content=text,
+                        parse_status=ToolCallParseStatus.in_progress,
+                    )
+
+                    yield ChatCompletionResponseStreamChunk(
+                        event=ChatCompletionResponseEvent(
+                            event_type=ChatCompletionResponseEventType.progress,
+                            delta=delta,
+                            stop_reason=stop_reason,
+                        )
+                    )
+                else:
+                    buffer += text
+                    yield ChatCompletionResponseStreamChunk(
+                        event=ChatCompletionResponseEvent(
+                            event_type=ChatCompletionResponseEventType.progress,
+                            delta=text,
+                            stop_reason=stop_reason,
+                        )
+                    )
+
+            # parse tool calls and report errors
+            message = decode_assistant_message_from_content(buffer, stop_reason)
+            parsed_tool_calls = len(message.tool_calls) > 0
+            if ipython and not parsed_tool_calls:
+                yield ChatCompletionResponseStreamChunk(
+                    event=ChatCompletionResponseEvent(
+                        event_type=ChatCompletionResponseEventType.progress,
+                        delta=ToolCallDelta(
+                            content="",
+                            parse_status=ToolCallParseStatus.failure,
+                        ),
+                        stop_reason=stop_reason,
+                    )
+                )
+
+            for tool_call in message.tool_calls:
+                yield ChatCompletionResponseStreamChunk(
+                    event=ChatCompletionResponseEvent(
+                        event_type=ChatCompletionResponseEventType.progress,
+                        delta=ToolCallDelta(
+                            content=tool_call,
+                            parse_status=ToolCallParseStatus.success,
+                        ),
+                        stop_reason=stop_reason,
+                    )
+                )
+
+            yield ChatCompletionResponseStreamChunk(
+                event=ChatCompletionResponseEvent(
+                    event_type=ChatCompletionResponseEventType.complete,
+                    delta="",
+                    stop_reason=stop_reason,
+                )
+            )
+
+
+# TODO: Consolidate this with impl in llama-models
+def decode_assistant_message_from_content(
+    content: str,
+    stop_reason: StopReason,
+) -> CompletionMessage:
+    ipython = content.startswith("<|python_tag|>")
+    if ipython:
+        content = content[len("<|python_tag|>") :]
+
+    if content.endswith("<|eot_id|>"):
+        content = content[: -len("<|eot_id|>")]
+        stop_reason = StopReason.end_of_turn
+    elif content.endswith("<|eom_id|>"):
+        content = content[: -len("<|eom_id|>")]
+        stop_reason = StopReason.end_of_message
+
+    tool_name = None
+    tool_arguments = {}
+
+    custom_tool_info = ToolUtils.maybe_extract_custom_tool_call(content)
+    if custom_tool_info is not None:
+        tool_name, tool_arguments = custom_tool_info
+        # Sometimes when agent has custom tools alongside builin tools
+        # Agent responds for builtin tool calls in the format of the custom tools
+        # This code tries to handle that case
+        if tool_name in BuiltinTool.__members__:
+            tool_name = BuiltinTool[tool_name]
+            tool_arguments = {
+                "query": list(tool_arguments.values())[0],
+            }
+    else:
+        builtin_tool_info = ToolUtils.maybe_extract_builtin_tool_call(content)
+        if builtin_tool_info is not None:
+            tool_name, query = builtin_tool_info
+            tool_arguments = {
+                "query": query,
+            }
+            if tool_name in BuiltinTool.__members__:
+                tool_name = BuiltinTool[tool_name]
+        elif ipython:
+            tool_name = BuiltinTool.code_interpreter
+            tool_arguments = {
+                "code": content,
+            }
+
+    tool_calls = []
+    if tool_name is not None and tool_arguments is not None:
+        call_id = str(uuid.uuid4())
+        tool_calls.append(
+            ToolCall(
+                call_id=call_id,
+                tool_name=tool_name,
+                arguments=tool_arguments,
+            )
+        )
+        content = ""
+
+    if stop_reason is None:
+        stop_reason = StopReason.out_of_tokens
+
+    return CompletionMessage(
+        content=content,
+        stop_reason=stop_reason,
+        tool_calls=tool_calls,
+    )