API Updates: fleshing out RAG APIs, introduce "llama stack" CLI command (#51)

* add tools to chat completion request

* use templates for generating system prompts

* Moved ToolPromptFormat and jinja templates to llama_models.llama3.api

* <WIP> memory changes

- inlined AgenticSystemInstanceConfig so API feels more ergonomic
- renamed it to AgentConfig, AgentInstance -> Agent
- added a MemoryConfig and `memory` parameter
- added `attachments` to input and `output_attachments` to the response

- some naming changes

* InterleavedTextAttachment -> InterleavedTextMedia, introduce memory tool

* flesh out memory banks API

* agentic loop has a RAG implementation

* faiss provider implementation

* memory client works

* re-work tool definitions, fix FastAPI issues, fix tool regressions

* fix agentic_system utils

* basic RAG seems to work

* small bug fixes for inline attachments

* Refactor custom tool execution utilities

* Bug fix, show memory retrieval steps in EventLogger

* No need for api_key for Remote providers

* add special unicode character ↵ to showcase newlines in model prompt templates

* remove api.endpoints imports

* combine datatypes.py and endpoints.py into api.py

* Attachment / add TTL api

* split batch_inference from inference

* minor import fixes

* use a single impl for ChatFormat.decode_assistant_mesage

* use interleaved_text_media_as_str() utilityt

* Fix api.datatypes imports

* Add blobfile for tiktoken

* Add ToolPromptFormat to ChatFormat.encode_message so that tools are encoded properly

* templates take optional --format={json,function_tag}

* Rag Updates

* Add `api build` subcommand -- WIP

* fix

* build + run image seems to work

* <WIP> adapters

* bunch more work to make adapters work

* api build works for conda now

* ollama remote adapter works

* Several smaller fixes to make adapters work

Also, reorganized the pattern of __init__ inside providers so
configuration can stay lightweight

* llama distribution -> llama stack + containers (WIP)

* All the new CLI for api + stack work

* Make Fireworks and Together into the Adapter format

* Some quick fixes to the CLI behavior to make it consistent

* Updated README phew

* Update cli_reference.md

* llama_toolchain/distribution -> llama_toolchain/core

* Add termcolor

* update paths

* Add a log just for consistency

* chmod +x scripts

* Fix api dependencies not getting added to configuration

* missing import lol

* Delete utils.py; move to agentic system

* Support downloading of URLs for attachments for code interpreter

* Simplify and generalize `llama api build` yay

* Update `llama stack configure` to be very simple also

* Fix stack start

* Allow building an "adhoc" distribution

* Remote `llama api []` subcommands

* Fixes to llama stack commands and update docs

* Update documentation again and add error messages to llama stack start

* llama stack start -> llama stack run

* Change name of build for less confusion

* Add pyopenapi fork to the repository, update RFC assets

* Remove conflicting annotation

* Added a "--raw" option for model template printing

---------

Co-authored-by: Hardik Shah <hjshah@fb.com>
Co-authored-by: Ashwin Bharambe <ashwin@meta.com>
Co-authored-by: Dalton Flanagan <6599399+dltn@users.noreply.github.com>

llama_toolchain/observability/api/api.py

@@ -0,0 +1,175 @@
+# 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 datetime import datetime
+from enum import Enum
+
+from typing import Any, Dict, List, Optional, Protocol, Union
+
+from llama_models.schema_utils import json_schema_type, webmethod
+
+from pydantic import BaseModel
+
+
+@json_schema_type
+class ExperimentStatus(Enum):
+    NOT_STARTED = "not_started"
+    RUNNING = "running"
+    COMPLETED = "completed"
+    FAILED = "failed"
+
+
+@json_schema_type
+class Experiment(BaseModel):
+    id: str
+    name: str
+    status: ExperimentStatus
+    created_at: datetime
+    updated_at: datetime
+    metadata: Dict[str, Any]
+
+
+@json_schema_type
+class Run(BaseModel):
+    id: str
+    experiment_id: str
+    status: str
+    started_at: datetime
+    ended_at: Optional[datetime]
+    metadata: Dict[str, Any]
+
+
+@json_schema_type
+class Metric(BaseModel):
+    name: str
+    value: Union[float, int, str, bool]
+    timestamp: datetime
+    run_id: str
+
+
+@json_schema_type
+class Log(BaseModel):
+    message: str
+    level: str
+    timestamp: datetime
+    additional_info: Dict[str, Any]
+
+
+@json_schema_type
+class ArtifactType(Enum):
+    MODEL = "model"
+    DATASET = "dataset"
+    CHECKPOINT = "checkpoint"
+    PLOT = "plot"
+    METRIC = "metric"
+    CONFIG = "config"
+    CODE = "code"
+    OTHER = "other"
+
+
+@json_schema_type
+class Artifact(BaseModel):
+    id: str
+    name: str
+    type: ArtifactType
+    size: int
+    created_at: datetime
+    metadata: Dict[str, Any]
+
+
+@json_schema_type
+class CreateExperimentRequest(BaseModel):
+    name: str
+    metadata: Optional[Dict[str, Any]] = None
+
+
+@json_schema_type
+class UpdateExperimentRequest(BaseModel):
+    experiment_id: str
+    status: Optional[ExperimentStatus] = None
+    metadata: Optional[Dict[str, Any]] = None
+
+
+@json_schema_type
+class CreateRunRequest(BaseModel):
+    experiment_id: str
+    metadata: Optional[Dict[str, Any]] = None
+
+
+@json_schema_type
+class UpdateRunRequest(BaseModel):
+    run_id: str
+    status: Optional[str] = None
+    ended_at: Optional[datetime] = None
+    metadata: Optional[Dict[str, Any]] = None
+
+
+@json_schema_type
+class LogMetricsRequest(BaseModel):
+    run_id: str
+    metrics: List[Metric]
+
+
+@json_schema_type
+class LogMessagesRequest(BaseModel):
+    logs: List[Log]
+    run_id: Optional[str] = None
+
+
+@json_schema_type
+class UploadArtifactRequest(BaseModel):
+    experiment_id: str
+    name: str
+    artifact_type: str
+    content: bytes
+    metadata: Optional[Dict[str, Any]] = None
+
+
+@json_schema_type
+class LogSearchRequest(BaseModel):
+    query: str
+    filters: Optional[Dict[str, Any]] = None
+
+
+class Observability(Protocol):
+    @webmethod(route="/experiments/create")
+    def create_experiment(self, request: CreateExperimentRequest) -> Experiment: ...
+
+    @webmethod(route="/experiments/list")
+    def list_experiments(self) -> List[Experiment]: ...
+
+    @webmethod(route="/experiments/get")
+    def get_experiment(self, experiment_id: str) -> Experiment: ...
+
+    @webmethod(route="/experiments/update")
+    def update_experiment(self, request: UpdateExperimentRequest) -> Experiment: ...
+
+    @webmethod(route="/experiments/create_run")
+    def create_run(self, request: CreateRunRequest) -> Run: ...
+
+    @webmethod(route="/runs/update")
+    def update_run(self, request: UpdateRunRequest) -> Run: ...
+
+    @webmethod(route="/runs/log_metrics")
+    def log_metrics(self, request: LogMetricsRequest) -> None: ...
+
+    @webmethod(route="/runs/metrics", method="GET")
+    def get_metrics(self, run_id: str) -> List[Metric]: ...
+
+    @webmethod(route="/logging/log_messages")
+    def log_messages(self, request: LogMessagesRequest) -> None: ...
+
+    @webmethod(route="/logging/get_logs")
+    def get_logs(self, request: LogSearchRequest) -> List[Log]: ...
+
+    @webmethod(route="/experiments/artifacts/upload")
+    def upload_artifact(self, request: UploadArtifactRequest) -> Artifact: ...
+
+    @webmethod(route="/experiments/artifacts/get")
+    def list_artifacts(self, experiment_id: str) -> List[Artifact]: ...
+
+    @webmethod(route="/artifacts/get")
+    def get_artifact(self, artifact_id: str) -> Artifact: ...