forked from phoenix-oss/llama-stack-mirror
Update the "InterleavedTextMedia" type (#635)
## What does this PR do?
This is a long-pending change and particularly important to get done
now.
Specifically:
- we cannot "localize" (aka download) any URLs from media attachments
anywhere near our modeling code. it must be done within llama-stack.
- `PIL.Image` is infesting all our APIs via `ImageMedia ->
InterleavedTextMedia` and that cannot be right at all. Anything in the
API surface must be "naturally serializable". We need a standard `{
type: "image", image_url: "<...>" }` which is more extensible
- `UserMessage`, `SystemMessage`, etc. are moved completely to
llama-stack from the llama-models repository.
See https://github.com/meta-llama/llama-models/pull/244 for the
corresponding PR in llama-models.
## Test Plan
```bash
cd llama_stack/providers/tests
pytest -s -v -k "fireworks or ollama or together" inference/test_vision_inference.py
pytest -s -v -k "(fireworks or ollama or together) and llama_3b" inference/test_text_inference.py
pytest -s -v -k chroma memory/test_memory.py \
--env EMBEDDING_DIMENSION=384 --env CHROMA_DB_PATH=/tmp/foobar
pytest -s -v -k fireworks agents/test_agents.py \
--safety-shield=meta-llama/Llama-Guard-3-8B \
--inference-model=meta-llama/Llama-3.1-8B-Instruct
```
Updated the client sdk (see PR ...), installed the SDK in the same
environment and then ran the SDK tests:
```bash
cd tests/client-sdk
LLAMA_STACK_CONFIG=together pytest -s -v agents/test_agents.py
LLAMA_STACK_CONFIG=ollama pytest -s -v memory/test_memory.py
# this one needed a bit of hacking in the run.yaml to ensure I could register the vision model correctly
INFERENCE_MODEL=llama3.2-vision:latest LLAMA_STACK_CONFIG=ollama pytest -s -v inference/test_inference.py
```
This commit is contained in:
Ashwin Bharambe
GitHub
parent
10eb31badf
commit
8de8eb03c8
66 changed files with 1344 additions and 1801 deletions
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@ -4,19 +4,26 @@
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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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import asyncio
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import base64
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import io
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import json
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import logging
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from typing import Tuple
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import re
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from typing import List, Optional, Tuple, Union
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import httpx
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from llama_models.datatypes import is_multimodal, ModelFamily
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from llama_models.llama3.api.chat_format import ChatFormat
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from PIL import Image as PIL_Image
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from llama_models.llama3.api.datatypes import * # noqa: F403
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from llama_stack.apis.inference import * # noqa: F403
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from llama_models.datatypes import ModelFamily
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from llama_models.llama3.api.datatypes import (
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RawContent,
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RawContentItem,
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RawMediaItem,
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RawTextItem,
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Role,
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ToolPromptFormat,
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)
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from llama_models.llama3.prompt_templates import (
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BuiltinToolGenerator,
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FunctionTagCustomToolGenerator,
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@ -25,15 +32,94 @@ from llama_models.llama3.prompt_templates import (
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SystemDefaultGenerator,
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)
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from llama_models.sku_list import resolve_model
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from PIL import Image as PIL_Image
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from llama_stack.apis.common.content_types import (
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ImageContentItem,
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InterleavedContent,
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InterleavedContentItem,
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TextContentItem,
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URL,
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)
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from llama_stack.apis.inference import (
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ChatCompletionRequest,
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CompletionRequest,
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Message,
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ResponseFormat,
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ResponseFormatType,
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SystemMessage,
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ToolChoice,
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UserMessage,
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)
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from llama_stack.providers.utils.inference import supported_inference_models
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log = logging.getLogger(__name__)
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def content_has_media(content: InterleavedTextMedia):
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def interleaved_content_as_str(content: InterleavedContent, sep: str = " ") -> str:
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def _process(c) -> str:
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if isinstance(c, str):
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return c
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elif isinstance(c, ImageContentItem):
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return "<image>"
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elif isinstance(c, TextContentItem):
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return c.text
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else:
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raise ValueError(f"Unsupported content type: {type(c)}")
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if isinstance(content, list):
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return sep.join(_process(c) for c in content)
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else:
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return _process(content)
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async def interleaved_content_convert_to_raw(
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content: InterleavedContent,
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) -> RawContent:
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"""Download content from URLs / files etc. so plain bytes can be sent to the model"""
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async def _localize_single(c: str | InterleavedContentItem) -> str | RawContentItem:
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if isinstance(c, str):
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return RawTextItem(text=c)
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elif isinstance(c, TextContentItem):
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return RawTextItem(text=c.text)
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elif isinstance(c, ImageContentItem):
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# load image and return PIL version
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img = c.data
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if isinstance(img, URL):
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if img.uri.startswith("data"):
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match = re.match(r"data:image/(\w+);base64,(.+)", img.uri)
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if not match:
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raise ValueError("Invalid data URL format")
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_, image_data = match.groups()
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data = base64.b64decode(image_data)
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elif img.uri.startswith("file://"):
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path = img.uri[len("file://") :]
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with open(path, "rb") as f:
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data = f.read() # type: ignore
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elif img.uri.startswith("http"):
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async with httpx.AsyncClient() as client:
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response = await client.get(img.uri)
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data = response.content
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else:
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raise ValueError("Unsupported URL type")
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else:
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data = c.data
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return RawMediaItem(data=data)
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else:
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raise ValueError(f"Unsupported content type: {type(c)}")
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if isinstance(content, list):
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return await asyncio.gather(*(_localize_single(c) for c in content))
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else:
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return await _localize_single(content)
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def content_has_media(content: InterleavedContent):
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def _has_media_content(c):
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return isinstance(c, ImageMedia)
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return isinstance(c, ImageContentItem)
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if isinstance(content, list):
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return any(_has_media_content(c) for c in content)
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@ -52,37 +138,29 @@ def request_has_media(request: Union[ChatCompletionRequest, CompletionRequest]):
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return content_has_media(request.content)
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async def convert_image_media_to_url(
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media: ImageMedia, download: bool = False, include_format: bool = True
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) -> str:
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if isinstance(media.image, PIL_Image.Image):
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if media.image.format == "PNG":
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format = "png"
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elif media.image.format == "GIF":
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format = "gif"
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elif media.image.format == "JPEG":
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format = "jpeg"
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else:
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raise ValueError(f"Unsupported image format {media.image.format}")
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bytestream = io.BytesIO()
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media.image.save(bytestream, format=media.image.format)
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bytestream.seek(0)
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content = bytestream.getvalue()
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async def localize_image_content(media: ImageContentItem) -> Tuple[bytes, str]:
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if media.url and media.url.uri.startswith("http"):
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async with httpx.AsyncClient() as client:
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r = await client.get(media.url.uri)
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content = r.content
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content_type = r.headers.get("content-type")
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if content_type:
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format = content_type.split("/")[-1]
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else:
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format = "png"
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return content, format
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else:
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if not download:
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return media.image.uri
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else:
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assert isinstance(media.image, URL)
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async with httpx.AsyncClient() as client:
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r = await client.get(media.image.uri)
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content = r.content
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content_type = r.headers.get("content-type")
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if content_type:
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format = content_type.split("/")[-1]
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else:
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format = "png"
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image = PIL_Image.open(io.BytesIO(media.data))
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return media.data, image.format
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async def convert_image_content_to_url(
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media: ImageContentItem, download: bool = False, include_format: bool = True
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) -> str:
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if media.url and not download:
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return media.url.uri
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content, format = await localize_image_content(media)
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if include_format:
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return f"data:image/{format};base64," + base64.b64encode(content).decode(
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"utf-8"
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@ -91,32 +169,6 @@ async def convert_image_media_to_url(
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return base64.b64encode(content).decode("utf-8")
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# TODO: name this function better! this is about OpenAI compatibile image
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# media conversion of the message. this should probably go in openai_compat.py
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async def convert_message_to_dict(message: Message, download: bool = False) -> dict:
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async def _convert_content(content) -> dict:
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if isinstance(content, ImageMedia):
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return {
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"type": "image_url",
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"image_url": {
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"url": await convert_image_media_to_url(content, download=download),
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},
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}
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else:
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assert isinstance(content, str)
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return {"type": "text", "text": content}
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if isinstance(message.content, list):
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content = [await _convert_content(c) for c in message.content]
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else:
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content = [await _convert_content(message.content)]
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return {
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"role": message.role,
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"content": content,
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}
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def completion_request_to_prompt(
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request: CompletionRequest, formatter: ChatFormat
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) -> str:
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@ -330,7 +382,7 @@ def augment_messages_for_tools_llama_3_2(
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sys_content += "\n"
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if existing_system_message:
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sys_content += interleaved_text_media_as_str(
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sys_content += interleaved_content_as_str(
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existing_system_message.content, sep="\n"
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)
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