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https://github.com/meta-llama/llama-stack.git
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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>
This commit is contained in:
Ashwin Bharambe
GitHub
parent
35093c0b6f
commit
7bc7785b0d
141 changed files with 8252 additions and 4032 deletions
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@ -4,5 +4,4 @@
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from .datatypes import * # noqa: F401 F403
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from .endpoints import * # noqa: F401 F403
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from .api import * # noqa: F401 F403
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@ -5,12 +5,79 @@
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# the root directory of this source tree.
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from datetime import datetime
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from typing import Any, Dict, List, Optional, Protocol
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from enum import Enum
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from typing import Any, Dict, List, Optional, Protocol, Union
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from llama_models.schema_utils import json_schema_type, webmethod
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from pydantic import BaseModel
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from llama_models.llama3.api.datatypes import * # noqa: F403
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from .datatypes import * # noqa: F403
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@json_schema_type
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class ExperimentStatus(Enum):
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NOT_STARTED = "not_started"
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RUNNING = "running"
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COMPLETED = "completed"
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FAILED = "failed"
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@json_schema_type
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class Experiment(BaseModel):
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id: str
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name: str
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status: ExperimentStatus
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created_at: datetime
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updated_at: datetime
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metadata: Dict[str, Any]
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@json_schema_type
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class Run(BaseModel):
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id: str
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experiment_id: str
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status: str
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started_at: datetime
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ended_at: Optional[datetime]
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metadata: Dict[str, Any]
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@json_schema_type
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class Metric(BaseModel):
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name: str
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value: Union[float, int, str, bool]
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timestamp: datetime
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run_id: str
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@json_schema_type
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class Log(BaseModel):
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message: str
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level: str
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timestamp: datetime
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additional_info: Dict[str, Any]
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@json_schema_type
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class ArtifactType(Enum):
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MODEL = "model"
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DATASET = "dataset"
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CHECKPOINT = "checkpoint"
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PLOT = "plot"
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METRIC = "metric"
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CONFIG = "config"
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CODE = "code"
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OTHER = "other"
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@json_schema_type
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class Artifact(BaseModel):
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id: str
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name: str
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type: ArtifactType
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size: int
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created_at: datetime
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metadata: Dict[str, Any]
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@json_schema_type
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@ -1,80 +0,0 @@
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# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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from datetime import datetime
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from enum import Enum
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from typing import Any, Dict, Optional, Union
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from llama_models.schema_utils import json_schema_type
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from pydantic import BaseModel
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@json_schema_type
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class ExperimentStatus(Enum):
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NOT_STARTED = "not_started"
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RUNNING = "running"
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COMPLETED = "completed"
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FAILED = "failed"
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@json_schema_type
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class Experiment(BaseModel):
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id: str
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name: str
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status: ExperimentStatus
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created_at: datetime
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updated_at: datetime
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metadata: Dict[str, Any]
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@json_schema_type
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class Run(BaseModel):
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id: str
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experiment_id: str
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status: str
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started_at: datetime
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ended_at: Optional[datetime]
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metadata: Dict[str, Any]
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@json_schema_type
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class Metric(BaseModel):
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name: str
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value: Union[float, int, str, bool]
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timestamp: datetime
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run_id: str
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@json_schema_type
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class Log(BaseModel):
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message: str
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level: str
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timestamp: datetime
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additional_info: Dict[str, Any]
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@json_schema_type
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class ArtifactType(Enum):
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MODEL = "model"
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DATASET = "dataset"
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CHECKPOINT = "checkpoint"
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PLOT = "plot"
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METRIC = "metric"
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CONFIG = "config"
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CODE = "code"
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OTHER = "other"
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@json_schema_type
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class Artifact(BaseModel):
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id: str
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name: str
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type: ArtifactType
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size: int
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created_at: datetime
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metadata: Dict[str, Any]
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