From 66a14781ba767508252357f7e2dd3245a644f7ee Mon Sep 17 00:00:00 2001 From: Dayanne Fernandes Date: Tue, 6 Aug 2024 19:57:59 -0300 Subject: [PATCH 01/11] add nptyping --- poetry.lock | 1418 ++++++++++++++++++++++++++---------------------- pyproject.toml | 4 + 2 files changed, 764 insertions(+), 658 deletions(-) diff --git a/poetry.lock b/poetry.lock index 3a49cd85..a62b5ccb 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.6.1 and should not be changed by hand. 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{file = "types_PyYAML-6.0.12.20240724-py3-none-any.whl", hash = "sha256:e5becec598f3aa3a2ddf671de4a75fa1c6856fbf73b2840286c9d50fae2d5d48"}, ] [[package]] name = "types-requests" -version = "2.32.0.20240602" +version = "2.32.0.20240712" description = "Typing stubs for requests" optional = false python-versions = ">=3.8" files = [ - {file = "types-requests-2.32.0.20240602.tar.gz", hash = "sha256:3f98d7bbd0dd94ebd10ff43a7fbe20c3b8528acace6d8efafef0b6a184793f06"}, - {file = "types_requests-2.32.0.20240602-py3-none-any.whl", hash = "sha256:ed3946063ea9fbc6b5fc0c44fa279188bae42d582cb63760be6cb4b9d06c3de8"}, + {file = "types-requests-2.32.0.20240712.tar.gz", hash = "sha256:90c079ff05e549f6bf50e02e910210b98b8ff1ebdd18e19c873cd237737c1358"}, + {file = "types_requests-2.32.0.20240712-py3-none-any.whl", hash = "sha256:f754283e152c752e46e70942fa2a146b5bc70393522257bb85bd1ef7e019dcc3"}, ] [package.dependencies] @@ -3346,13 +3448,13 @@ files = [ [[package]] name = "urllib3" -version = "2.2.1" +version = "2.2.2" description = "HTTP library with thread-safe connection pooling, file post, and more." optional = false python-versions = ">=3.8" files = [ - {file = "urllib3-2.2.1-py3-none-any.whl", hash = "sha256:450b20ec296a467077128bff42b73080516e71b56ff59a60a02bef2232c4fa9d"}, - {file = "urllib3-2.2.1.tar.gz", hash = "sha256:d0570876c61ab9e520d776c38acbbb5b05a776d3f9ff98a5c8fd5162a444cf19"}, + {file = "urllib3-2.2.2-py3-none-any.whl", hash = "sha256:a448b2f64d686155468037e1ace9f2d2199776e17f0a46610480d311f73e3472"}, + {file = "urllib3-2.2.2.tar.gz", hash = "sha256:dd505485549a7a552833da5e6063639d0d177c04f23bc3864e41e5dc5f612168"}, ] [package.extras] @@ -3434,4 +3536,4 @@ test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "65ca2851faa9365881e4e9da33e3ad538b87d9f9be74aed47d447df0f660cb5d" +content-hash = "43f4dd16e62515ddb69aff308285a64a2c94dd874c03d1209170a2af13b2dfc0" diff --git a/pyproject.toml b/pyproject.toml index fc679565..97ad9f92 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -17,6 +17,7 @@ packages = [{include = "vision_agent"}] [tool.poetry.dependencies] # main dependency group python = ">=3.9,<4.0" + numpy = ">=1.21.0,<2.0.0" pillow = "10.*" requests = "2.*" @@ -41,6 +42,7 @@ pillow-heif = "^0.16.0" pytube = "15.0.0" anthropic = "^0.31.0" pydantic = "2.7.4" +nptyping = "2.5.0" [tool.poetry.group.dev.dependencies] autoflake = "1.*" @@ -76,6 +78,8 @@ line_length = 88 profile = "black" [tool.mypy] +plugins = ["pydantic.mypy"] + exclude = "tests" show_error_context = true pretty = true From 687203f939dc75bbb7553b13c7a98f2d1b476aa4 Mon Sep 17 00:00:00 2001 From: Dayanne Fernandes Date: Tue, 6 Aug 2024 19:58:17 -0300 Subject: [PATCH 02/11] add florencev2 fine tuning --- vision_agent/clients/__init__.py | 0 vision_agent/clients/http.py | 42 ++++++ vision_agent/clients/landing_public_api.py | 26 ++++ vision_agent/tools/__init__.py | 1 + vision_agent/tools/tool_types.py | 20 +++ vision_agent/tools/tools.py | 146 ++++++++++++++------- 6 files changed, 191 insertions(+), 44 deletions(-) create mode 100644 vision_agent/clients/__init__.py create mode 100644 vision_agent/clients/http.py create mode 100644 vision_agent/clients/landing_public_api.py create mode 100644 vision_agent/tools/tool_types.py diff --git a/vision_agent/clients/__init__.py b/vision_agent/clients/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/vision_agent/clients/http.py b/vision_agent/clients/http.py new file mode 100644 index 00000000..6cd37654 --- /dev/null +++ b/vision_agent/clients/http.py @@ -0,0 +1,42 @@ +import json +import logging +from typing import Any, Dict, Optional + +from requests import Session +from requests.adapters import HTTPAdapter +from requests.exceptions import ConnectionError, RequestException, Timeout + +_LOGGER = logging.getLogger(__name__) + + +class BaseHTTP: + _TIMEOUT = 30 # seconds + _MAX_RETRIES = 3 + + def __init__(self, base_endpoint: str, *, headers: Optional[Dict[str, Any]] = None) -> None: + self._headers = headers + if headers is None: + self._headers = { + "Content-Type": "application/json", + } + self._base_endpoint = base_endpoint + self._session = Session() + self._session.headers.update(self._headers) + self._session.mount(self._base_endpoint, HTTPAdapter(max_retries=self._MAX_RETRIES)) + + def post(self, url: str, payload: Dict[str, Any]) -> None: + formatted_url = f"{self._base_endpoint}/{url}" + _LOGGER.info(f"Sending data to {formatted_url}") + try: + response = self._session.post( + url=formatted_url, + json=payload, + timeout=self._TIMEOUT + ) + response.raise_for_status() + _LOGGER.info(json.dumps(response.json())) + except (ConnectionError, Timeout, RequestException) as err: + _LOGGER.warning(f"Error: {err}.") + except json.JSONDecodeError: + resp_text = response.text + _LOGGER.warning(f"Response seems incorrect: '{resp_text}'.") diff --git a/vision_agent/clients/landing_public_api.py b/vision_agent/clients/landing_public_api.py new file mode 100644 index 00000000..846ea935 --- /dev/null +++ b/vision_agent/clients/landing_public_api.py @@ -0,0 +1,26 @@ +import os +from uuid import UUID +from typing import List + +from vision_agent.clients.http import BaseHTTP +from vision_agent.utils.type_defs import LandingaiAPIKey +from vision_agent.tools.tool_types import BboxInputBase64 + + +class LandingPublicAPI(BaseHTTP): + def __init__(self) -> None: + landing_url = os.environ.get("LANDINGAI_URL", "https://api.dev.landing.ai") + landing_api_key = os.environ.get("LANDINGAI_API_KEY", LandingaiAPIKey().api_key) + headers = {"Content-Type": "application/json", "apikey": landing_api_key} + super().__init__(base_endpoint=landing_url, headers=headers) + + def launch_fine_tuning_job( + self, model_name: str, task: str, bboxes: List[BboxInputBase64] + ) -> UUID: + url = "v1/agent/jobs/fine-tuning" + data = { + "model": {"name": model_name, "task": task}, + "bboxes": [bbox.model_dump(by_alias=True) for bbox in bboxes] + } + response = self.post(url, payload=data) + return UUID(response["jobId"]) diff --git a/vision_agent/tools/__init__.py b/vision_agent/tools/__init__.py index e95a78c7..1ea94510 100644 --- a/vision_agent/tools/__init__.py +++ b/vision_agent/tools/__init__.py @@ -19,6 +19,7 @@ florencev2_image_caption, florencev2_object_detection, florencev2_roberta_vqa, + florencev2_fine_tuning, generate_pose_image, generate_soft_edge_image, get_tool_documentation, diff --git a/vision_agent/tools/tool_types.py b/vision_agent/tools/tool_types.py new file mode 100644 index 00000000..c575cec8 --- /dev/null +++ b/vision_agent/tools/tool_types.py @@ -0,0 +1,20 @@ +from typing import List, Tuple + +from nptyping import UInt8, NDArray, Shape +from pydantic import BaseModel, ConfigDict + + +class BboxInput(BaseModel): + model_config = ConfigDict(arbitrary_types_allowed=True) + + image: NDArray[Shape["Height, Width, 3"], UInt8] + filename: str + labels: List[str] + bboxes: List[Tuple[int, int, int, int]] + + +class BboxInputBase64(BaseModel): + image: str + filename: str + labels: List[str] + bboxes: List[Tuple[int, int, int, int]] diff --git a/vision_agent/tools/tools.py b/vision_agent/tools/tools.py index c0af8b21..d2687683 100644 --- a/vision_agent/tools/tools.py +++ b/vision_agent/tools/tools.py @@ -1,24 +1,25 @@ import io import json +import inspect import logging import tempfile -from importlib import resources +from uuid import UUID from pathlib import Path -from typing import Any, Dict, List, Optional, Tuple, Union, cast +from importlib import resources +from typing import Any, Callable, Dict, List, Optional, Tuple, Union, cast import cv2 -import numpy as np import requests +import numpy as np +import pandas as pd +from pytube import YouTube # type: ignore +from moviepy.editor import ImageSequenceClip from PIL import Image, ImageDraw, ImageFont from pillow_heif import register_heif_opener # type: ignore -from pytube import YouTube # type: ignore -from vision_agent.tools.tool_utils import ( - get_tool_descriptions, - get_tool_documentation, - get_tools_df, - send_inference_request, -) +from vision_agent.clients.landing_public_api import LandingPublicAPI +from vision_agent.tools.tool_types import BboxInput, BboxInputBase64 +from vision_agent.tools.tool_utils import send_inference_request from vision_agent.utils import extract_frames_from_video from vision_agent.utils.execute import FileSerializer, MimeType from vision_agent.utils.image_utils import ( @@ -56,6 +57,7 @@ ] _API_KEY = "land_sk_WVYwP00xA3iXely2vuar6YUDZ3MJT9yLX6oW5noUkwICzYLiDV" _OCR_URL = "https://app.landing.ai/ocr/v1/detect-text" +logging.basicConfig(level=logging.INFO) _LOGGER = logging.getLogger(__name__) @@ -106,7 +108,6 @@ def grounding_dino( "visual_grounding" if model_size == "large" else "visual_grounding_tiny" ), "kwargs": {"box_threshold": box_threshold, "iou_threshold": iou_threshold}, - "function_name": "grounding_dino", } data: Dict[str, Any] = send_inference_request(request_data, "tools") return_data = [] @@ -162,7 +163,6 @@ def owl_v2( "image": image_b64, "tool": "open_vocab_detection", "kwargs": {"box_threshold": box_threshold, "iou_threshold": iou_threshold}, - "function_name": "owl_v2", } data: Dict[str, Any] = send_inference_request(request_data, "tools") return_data = [] @@ -227,7 +227,6 @@ def grounding_sam( "image": image_b64, "tool": "visual_grounding_segment", "kwargs": {"box_threshold": box_threshold, "iou_threshold": iou_threshold}, - "function_name": "grounding_sam", } data: Dict[str, Any] = send_inference_request(request_data, "tools") return_data = [] @@ -367,7 +366,6 @@ def loca_zero_shot_counting(image: np.ndarray) -> Dict[str, Any]: data = { "image": image_b64, "tool": "zero_shot_counting", - "function_name": "loca_zero_shot_counting", } resp_data = send_inference_request(data, "tools") resp_data["heat_map"] = np.array(b64_to_pil(resp_data["heat_map"][0])) @@ -403,7 +401,6 @@ def loca_visual_prompt_counting( "image": image_b64, "prompt": bbox_str, "tool": "few_shot_counting", - "function_name": "loca_visual_prompt_counting", } resp_data = send_inference_request(data, "tools") resp_data["heat_map"] = np.array(b64_to_pil(resp_data["heat_map"][0])) @@ -433,7 +430,6 @@ def florencev2_roberta_vqa(prompt: str, image: np.ndarray) -> str: "image": image_b64, "prompt": prompt, "tool": "image_question_answering_with_context", - "function_name": "florencev2_roberta_vqa", } answer = send_inference_request(data, "tools") @@ -463,7 +459,6 @@ def git_vqa_v2(prompt: str, image: np.ndarray) -> str: "image": image_b64, "prompt": prompt, "tool": "image_question_answering", - "function_name": "git_vqa_v2", } answer = send_inference_request(data, "tools") @@ -494,7 +489,6 @@ def clip(image: np.ndarray, classes: List[str]) -> Dict[str, Any]: "prompt": ",".join(classes), "image": image_b64, "tool": "closed_set_image_classification", - "function_name": "clip", } resp_data = send_inference_request(data, "tools") resp_data["scores"] = [round(prob, 4) for prob in resp_data["scores"]] @@ -522,7 +516,6 @@ def vit_image_classification(image: np.ndarray) -> Dict[str, Any]: data = { "image": image_b64, "tool": "image_classification", - "function_name": "vit_image_classification", } resp_data = send_inference_request(data, "tools") resp_data["scores"] = [round(prob, 4) for prob in resp_data["scores"]] @@ -550,7 +543,6 @@ def vit_nsfw_classification(image: np.ndarray) -> Dict[str, Any]: data = { "image": image_b64, "tool": "nsfw_image_classification", - "function_name": "vit_nsfw_classification", } resp_data = send_inference_request(data, "tools") resp_data["scores"] = round(resp_data["scores"], 4) @@ -577,7 +569,6 @@ def blip_image_caption(image: np.ndarray) -> str: data = { "image": image_b64, "tool": "image_captioning", - "function_name": "blip_image_caption", } answer = send_inference_request(data, "tools") @@ -606,7 +597,6 @@ def florencev2_image_caption(image: np.ndarray, detail_caption: bool = True) -> "image": image_b64, "tool": "florence2_image_captioning", "detail_caption": detail_caption, - "function_name": "florencev2_image_caption", } answer = send_inference_request(data, "tools") @@ -642,7 +632,6 @@ def florencev2_object_detection(image: np.ndarray) -> List[Dict[str, Any]]: data = { "image": image_b64, "tool": "object_detection", - "function_name": "florencev2_object_detection", } answer = send_inference_request(data, "tools") @@ -658,6 +647,42 @@ def florencev2_object_detection(image: np.ndarray) -> List[Dict[str, Any]]: return return_data +def florencev2_fine_tuning(bboxes: List[Dict[str, Any]]) -> UUID: + """'florencev2_fine_tuning' is a tool that fine-tune florencev2 to be able + to detect objects in an image based on a given dataset. It returns the fine + tuning job id. + + Parameters: + bboxes (List[BboxInput]): A list of BboxInput containing the + image object, image filename, labels and bounding boxes. + + Returns: + UUID: The fine tuning job id, this id will used to retrieve the fine + tuned model. + + Example + ------- + >>> fine_tuning_job_id = florencev2_fine_tuning( + [{'image': image, 'filename': 'filename.png', 'label': ['screw'], 'bbox': [[370, 30, 560, 290]]}, + {'image': image, 'filename': 'filename.png', 'label': ['screw'], 'bbox': [[120, 0, 300, 170]]}] + ) + """ + bboxes_input = [BboxInput.model_validate(bbox) for bbox in bboxes] + fine_tuning_request = [ + BboxInputBase64( + image=convert_to_b64(bbox_input.image), + filename=bbox_input.filename, + labels=bbox_input.labels, + bboxes=bbox_input.bboxes + ) + for bbox_input in bboxes_input + ] + # TODO: receive the task from user prompt + task = "" + landing_api = LandingPublicAPI() + return landing_api.launch_fine_tuning_job("florencev2", task, fine_tuning_request) + + def detr_segmentation(image: np.ndarray) -> List[Dict[str, Any]]: """'detr_segmentation' is a tool that can segment common objects in an image without any text prompt. It returns a list of detected objects @@ -699,7 +724,6 @@ def detr_segmentation(image: np.ndarray) -> List[Dict[str, Any]]: data = { "image": image_b64, "tool": "panoptic_segmentation", - "function_name": "detr_segmentation", } answer = send_inference_request(data, "tools") @@ -742,7 +766,6 @@ def depth_anything_v2(image: np.ndarray) -> np.ndarray: data = { "image": image_b64, "tool": "generate_depth", - "function_name": "depth_anything_v2", } answer = send_inference_request(data, "tools") @@ -774,7 +797,6 @@ def generate_soft_edge_image(image: np.ndarray) -> np.ndarray: data = { "image": image_b64, "tool": "generate_hed", - "function_name": "generate_soft_edge_image", } answer = send_inference_request(data, "tools") @@ -807,7 +829,6 @@ def dpt_hybrid_midas(image: np.ndarray) -> np.ndarray: data = { "image": image_b64, "tool": "generate_normal", - "function_name": "dpt_hybrid_midas", } answer = send_inference_request(data, "tools") @@ -839,7 +860,6 @@ def generate_pose_image(image: np.ndarray) -> np.ndarray: data = { "image": image_b64, "tool": "generate_pose", - "function_name": "generate_pose_image", } answer = send_inference_request(data, "tools") @@ -880,7 +900,6 @@ def template_match( "image": image_b64, "template": template_image_b64, "tool": "template_match", - "function_name": "template_match", } answer = send_inference_request(data, "tools") @@ -1062,21 +1081,15 @@ def save_video( if fps <= 0: _LOGGER.warning(f"Invalid fps value: {fps}. Setting fps to 4 (default value).") fps = 4 - - if not output_video_path: - output_video_path = tempfile.NamedTemporaryFile( - suffix=".mp4", delete=False - ).name - - height, width, layers = frames[0].shape if frames else (0, 0, 0) - fourcc = cv2.VideoWriter_fourcc(*"mp4v") # type: ignore - video = cv2.VideoWriter(output_video_path, fourcc, fps, (width, height)) - for frame in frames: - video.write(cv2.cvtColor(frame, cv2.COLOR_RGB2BGR)) - video.release() - - _save_video_to_result(output_video_path) - return output_video_path + with ImageSequenceClip(frames, fps=fps) as video: + if output_video_path: + f = open(output_video_path, "wb") + else: + f = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False) # type: ignore + video.write_videofile(f.name, codec="libx264") + f.close() + _save_video_to_result(f.name) + return f.name def _save_video_to_result(video_uri: str) -> None: @@ -1246,6 +1259,50 @@ def overlay_heat_map( return np.array(combined) +def get_tool_documentation(funcs: List[Callable[..., Any]]) -> str: + docstrings = "" + for func in funcs: + docstrings += f"{func.__name__}{inspect.signature(func)}:\n{func.__doc__}\n\n" + + return docstrings + + +def get_tool_descriptions(funcs: List[Callable[..., Any]]) -> str: + descriptions = "" + for func in funcs: + description = func.__doc__ + if description is None: + description = "" + + if "Parameters:" in description: + description = ( + description[: description.find("Parameters:")] + .replace("\n", " ") + .strip() + ) + + description = " ".join(description.split()) + descriptions += f"- {func.__name__}{inspect.signature(func)}: {description}\n" + return descriptions + + +def get_tools_df(funcs: List[Callable[..., Any]]) -> pd.DataFrame: + data: Dict[str, List[str]] = {"desc": [], "doc": []} + + for func in funcs: + desc = func.__doc__ + if desc is None: + desc = "" + desc = desc[: desc.find("Parameters:")].replace("\n", " ").strip() + desc = " ".join(desc.split()) + + doc = f"{func.__name__}{inspect.signature(func)}:\n{func.__doc__}" + data["desc"].append(desc) + data["doc"].append(doc) + + return pd.DataFrame(data) # type: ignore + + TOOLS = [ owl_v2, grounding_sam, @@ -1259,6 +1316,7 @@ def overlay_heat_map( florencev2_roberta_vqa, florencev2_image_caption, florencev2_object_detection, + florencev2_fine_tuning, detr_segmentation, depth_anything_v2, generate_soft_edge_image, From 57845ee81e7461f4e0343d94d728730a22f13fa8 Mon Sep 17 00:00:00 2001 From: Dayanne Fernandes Date: Tue, 6 Aug 2024 20:12:35 -0300 Subject: [PATCH 03/11] add function name back --- vision_agent/tools/tools.py | 76 +++++++++++++------------------------ 1 file changed, 26 insertions(+), 50 deletions(-) diff --git a/vision_agent/tools/tools.py b/vision_agent/tools/tools.py index d2687683..6e323b79 100644 --- a/vision_agent/tools/tools.py +++ b/vision_agent/tools/tools.py @@ -1,17 +1,15 @@ import io import json -import inspect import logging import tempfile from uuid import UUID from pathlib import Path from importlib import resources -from typing import Any, Callable, Dict, List, Optional, Tuple, Union, cast +from typing import Any, Dict, List, Optional, Tuple, Union, cast import cv2 import requests import numpy as np -import pandas as pd from pytube import YouTube # type: ignore from moviepy.editor import ImageSequenceClip from PIL import Image, ImageDraw, ImageFont @@ -19,7 +17,12 @@ from vision_agent.clients.landing_public_api import LandingPublicAPI from vision_agent.tools.tool_types import BboxInput, BboxInputBase64 -from vision_agent.tools.tool_utils import send_inference_request +from vision_agent.tools.tool_utils import ( + send_inference_request, + get_tool_descriptions, + get_tool_documentation, + get_tools_df, +) from vision_agent.utils import extract_frames_from_video from vision_agent.utils.execute import FileSerializer, MimeType from vision_agent.utils.image_utils import ( @@ -57,7 +60,6 @@ ] _API_KEY = "land_sk_WVYwP00xA3iXely2vuar6YUDZ3MJT9yLX6oW5noUkwICzYLiDV" _OCR_URL = "https://app.landing.ai/ocr/v1/detect-text" -logging.basicConfig(level=logging.INFO) _LOGGER = logging.getLogger(__name__) @@ -108,6 +110,7 @@ def grounding_dino( "visual_grounding" if model_size == "large" else "visual_grounding_tiny" ), "kwargs": {"box_threshold": box_threshold, "iou_threshold": iou_threshold}, + "function_name": "grounding_dino", } data: Dict[str, Any] = send_inference_request(request_data, "tools") return_data = [] @@ -163,6 +166,7 @@ def owl_v2( "image": image_b64, "tool": "open_vocab_detection", "kwargs": {"box_threshold": box_threshold, "iou_threshold": iou_threshold}, + "function_name": "owl_v2", } data: Dict[str, Any] = send_inference_request(request_data, "tools") return_data = [] @@ -227,6 +231,7 @@ def grounding_sam( "image": image_b64, "tool": "visual_grounding_segment", "kwargs": {"box_threshold": box_threshold, "iou_threshold": iou_threshold}, + "function_name": "grounding_sam", } data: Dict[str, Any] = send_inference_request(request_data, "tools") return_data = [] @@ -366,6 +371,7 @@ def loca_zero_shot_counting(image: np.ndarray) -> Dict[str, Any]: data = { "image": image_b64, "tool": "zero_shot_counting", + "function_name": "loca_zero_shot_counting", } resp_data = send_inference_request(data, "tools") resp_data["heat_map"] = np.array(b64_to_pil(resp_data["heat_map"][0])) @@ -401,6 +407,7 @@ def loca_visual_prompt_counting( "image": image_b64, "prompt": bbox_str, "tool": "few_shot_counting", + "function_name": "loca_visual_prompt_counting", } resp_data = send_inference_request(data, "tools") resp_data["heat_map"] = np.array(b64_to_pil(resp_data["heat_map"][0])) @@ -430,6 +437,7 @@ def florencev2_roberta_vqa(prompt: str, image: np.ndarray) -> str: "image": image_b64, "prompt": prompt, "tool": "image_question_answering_with_context", + "function_name": "florencev2_roberta_vqa", } answer = send_inference_request(data, "tools") @@ -459,6 +467,7 @@ def git_vqa_v2(prompt: str, image: np.ndarray) -> str: "image": image_b64, "prompt": prompt, "tool": "image_question_answering", + "function_name": "git_vqa_v2", } answer = send_inference_request(data, "tools") @@ -489,6 +498,7 @@ def clip(image: np.ndarray, classes: List[str]) -> Dict[str, Any]: "prompt": ",".join(classes), "image": image_b64, "tool": "closed_set_image_classification", + "function_name": "clip", } resp_data = send_inference_request(data, "tools") resp_data["scores"] = [round(prob, 4) for prob in resp_data["scores"]] @@ -516,6 +526,7 @@ def vit_image_classification(image: np.ndarray) -> Dict[str, Any]: data = { "image": image_b64, "tool": "image_classification", + "function_name": "vit_image_classification", } resp_data = send_inference_request(data, "tools") resp_data["scores"] = [round(prob, 4) for prob in resp_data["scores"]] @@ -543,6 +554,7 @@ def vit_nsfw_classification(image: np.ndarray) -> Dict[str, Any]: data = { "image": image_b64, "tool": "nsfw_image_classification", + "function_name": "vit_nsfw_classification", } resp_data = send_inference_request(data, "tools") resp_data["scores"] = round(resp_data["scores"], 4) @@ -569,6 +581,7 @@ def blip_image_caption(image: np.ndarray) -> str: data = { "image": image_b64, "tool": "image_captioning", + "function_name": "blip_image_caption", } answer = send_inference_request(data, "tools") @@ -597,6 +610,7 @@ def florencev2_image_caption(image: np.ndarray, detail_caption: bool = True) -> "image": image_b64, "tool": "florence2_image_captioning", "detail_caption": detail_caption, + "function_name": "florencev2_image_caption", } answer = send_inference_request(data, "tools") @@ -632,6 +646,7 @@ def florencev2_object_detection(image: np.ndarray) -> List[Dict[str, Any]]: data = { "image": image_b64, "tool": "object_detection", + "function_name": "florencev2_object_detection", } answer = send_inference_request(data, "tools") @@ -673,7 +688,7 @@ def florencev2_fine_tuning(bboxes: List[Dict[str, Any]]) -> UUID: image=convert_to_b64(bbox_input.image), filename=bbox_input.filename, labels=bbox_input.labels, - bboxes=bbox_input.bboxes + bboxes=bbox_input.bboxes, ) for bbox_input in bboxes_input ] @@ -724,6 +739,7 @@ def detr_segmentation(image: np.ndarray) -> List[Dict[str, Any]]: data = { "image": image_b64, "tool": "panoptic_segmentation", + "function_name": "detr_segmentation", } answer = send_inference_request(data, "tools") @@ -766,6 +782,7 @@ def depth_anything_v2(image: np.ndarray) -> np.ndarray: data = { "image": image_b64, "tool": "generate_depth", + "function_name": "depth_anything_v2", } answer = send_inference_request(data, "tools") @@ -797,6 +814,7 @@ def generate_soft_edge_image(image: np.ndarray) -> np.ndarray: data = { "image": image_b64, "tool": "generate_hed", + "function_name": "generate_soft_edge_image", } answer = send_inference_request(data, "tools") @@ -829,6 +847,7 @@ def dpt_hybrid_midas(image: np.ndarray) -> np.ndarray: data = { "image": image_b64, "tool": "generate_normal", + "function_name": "dpt_hybrid_midas", } answer = send_inference_request(data, "tools") @@ -900,6 +919,7 @@ def template_match( "image": image_b64, "template": template_image_b64, "tool": "template_match", + "function_name": "template_match", } answer = send_inference_request(data, "tools") @@ -1259,50 +1279,6 @@ def overlay_heat_map( return np.array(combined) -def get_tool_documentation(funcs: List[Callable[..., Any]]) -> str: - docstrings = "" - for func in funcs: - docstrings += f"{func.__name__}{inspect.signature(func)}:\n{func.__doc__}\n\n" - - return docstrings - - -def get_tool_descriptions(funcs: List[Callable[..., Any]]) -> str: - descriptions = "" - for func in funcs: - description = func.__doc__ - if description is None: - description = "" - - if "Parameters:" in description: - description = ( - description[: description.find("Parameters:")] - .replace("\n", " ") - .strip() - ) - - description = " ".join(description.split()) - descriptions += f"- {func.__name__}{inspect.signature(func)}: {description}\n" - return descriptions - - -def get_tools_df(funcs: List[Callable[..., Any]]) -> pd.DataFrame: - data: Dict[str, List[str]] = {"desc": [], "doc": []} - - for func in funcs: - desc = func.__doc__ - if desc is None: - desc = "" - desc = desc[: desc.find("Parameters:")].replace("\n", " ").strip() - desc = " ".join(desc.split()) - - doc = f"{func.__name__}{inspect.signature(func)}:\n{func.__doc__}" - data["desc"].append(desc) - data["doc"].append(doc) - - return pd.DataFrame(data) # type: ignore - - TOOLS = [ owl_v2, grounding_sam, From 11d5c58d0f9dde4b13646814ba3b7061fb48a47c Mon Sep 17 00:00:00 2001 From: Dayanne Fernandes Date: Tue, 6 Aug 2024 20:22:28 -0300 Subject: [PATCH 04/11] fix linting --- vision_agent/tools/tool_types.py | 6 +++--- vision_agent/tools/tools.py | 1 + 2 files changed, 4 insertions(+), 3 deletions(-) diff --git a/vision_agent/tools/tool_types.py b/vision_agent/tools/tool_types.py index c575cec8..8ab55ffe 100644 --- a/vision_agent/tools/tool_types.py +++ b/vision_agent/tools/tool_types.py @@ -1,13 +1,13 @@ -from typing import List, Tuple +from typing import List, Tuple, Literal -from nptyping import UInt8, NDArray, Shape +from nptyping import UInt8, NDArray from pydantic import BaseModel, ConfigDict class BboxInput(BaseModel): model_config = ConfigDict(arbitrary_types_allowed=True) - image: NDArray[Shape["Height, Width, 3"], UInt8] + image: NDArray[Literal["Height, Width, 3"], UInt8] filename: str labels: List[str] bboxes: List[Tuple[int, int, int, int]] diff --git a/vision_agent/tools/tools.py b/vision_agent/tools/tools.py index 6e323b79..fc5a6d72 100644 --- a/vision_agent/tools/tools.py +++ b/vision_agent/tools/tools.py @@ -879,6 +879,7 @@ def generate_pose_image(image: np.ndarray) -> np.ndarray: data = { "image": image_b64, "tool": "generate_pose", + "function_name": "generate_pose_image", } answer = send_inference_request(data, "tools") From 630eff340971cb516a7436e8e71f1dee186231f3 Mon Sep 17 00:00:00 2001 From: Dayanne Fernandes Date: Tue, 6 Aug 2024 20:25:57 -0300 Subject: [PATCH 05/11] add pre-commit --- .pre-commit-config.yaml | 10 +++ poetry.lock | 87 +++++++++++++++++++++- pyproject.toml | 1 + vision_agent/clients/http.py | 12 +-- vision_agent/clients/landing_public_api.py | 2 +- 5 files changed, 105 insertions(+), 7 deletions(-) create mode 100644 .pre-commit-config.yaml diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml new file mode 100644 index 00000000..457961bd --- /dev/null +++ b/.pre-commit-config.yaml @@ -0,0 +1,10 @@ +repos: + - repo: https://github.com/psf/black + rev: 24.4.2 + hooks: + - id: black + language_version: python3.9 + - repo: https://github.com/pycqa/flake8 + rev: 7.0.0 + hooks: + - id: flake8 diff --git a/poetry.lock b/poetry.lock index cd0799a3..3bd1ca8b 100644 --- a/poetry.lock +++ b/poetry.lock @@ -282,6 +282,17 @@ files = [ [package.dependencies] pycparser = "*" +[[package]] +name = "cfgv" +version = "3.4.0" +description = "Validate configuration and produce human readable error messages." +optional = false +python-versions = ">=3.8" +files = [ + {file = "cfgv-3.4.0-py2.py3-none-any.whl", hash = "sha256:b7265b1f29fd3316bfcd2b330d63d024f2bfd8bcb8b0272f8e19a504856c48f9"}, + {file = "cfgv-3.4.0.tar.gz", hash = "sha256:e52591d4c5f5dead8e0f673fb16db7949d2cfb3f7da4582893288f0ded8fe560"}, +] + [[package]] name = "charset-normalizer" version = "3.3.2" @@ -479,6 +490,17 @@ files = [ {file = "decorator-4.4.2.tar.gz", hash = "sha256:e3a62f0520172440ca0dcc823749319382e377f37f140a0b99ef45fecb84bfe7"}, ] +[[package]] +name = "distlib" +version = "0.3.8" +description = "Distribution utilities" +optional = false +python-versions = "*" +files = [ + {file = "distlib-0.3.8-py2.py3-none-any.whl", hash = "sha256:034db59a0b96f8ca18035f36290806a9a6e6bd9d1ff91e45a7f172eb17e51784"}, + {file = "distlib-0.3.8.tar.gz", hash = "sha256:1530ea13e350031b6312d8580ddb6b27a104275a31106523b8f123787f494f64"}, +] + [[package]] name = "distro" version = "1.9.0" @@ -761,6 +783,20 @@ testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gr torch = ["safetensors[torch]", "torch"] typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"] +[[package]] +name = "identify" +version = "2.6.0" +description = "File identification library for Python" +optional = false +python-versions = ">=3.8" +files = [ + {file = "identify-2.6.0-py2.py3-none-any.whl", hash = "sha256:e79ae4406387a9d300332b5fd366d8994f1525e8414984e1a59e058b2eda2dd0"}, + {file = "identify-2.6.0.tar.gz", hash = "sha256:cb171c685bdc31bcc4c1734698736a7d5b6c8bf2e0c15117f4d469c8640ae5cf"}, +] + +[package.extras] +license = ["ukkonen"] + [[package]] name = "idna" version = "3.7" @@ -1616,6 +1652,17 @@ doc = ["nb2plots (>=0.7)", "nbconvert (<7.9)", "numpydoc (>=1.6)", "pillow (>=9. extra = ["lxml (>=4.6)", "pydot (>=1.4.2)", "pygraphviz (>=1.11)", "sympy (>=1.10)"] test = ["pytest (>=7.2)", "pytest-cov (>=4.0)"] +[[package]] +name = "nodeenv" +version = "1.9.1" +description = "Node.js virtual environment builder" +optional = false +python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7" +files = [ + {file = "nodeenv-1.9.1-py2.py3-none-any.whl", hash = "sha256:ba11c9782d29c27c70ffbdda2d7415098754709be8a7056d79a737cd901155c9"}, + {file = "nodeenv-1.9.1.tar.gz", hash = "sha256:6ec12890a2dab7946721edbfbcd91f3319c6ccc9aec47be7c7e6b7011ee6645f"}, +] + [[package]] name = "nptyping" version = "2.5.0" @@ -2124,6 +2171,24 @@ files = [ dev = ["pre-commit", "tox"] testing = ["pytest", "pytest-benchmark"] +[[package]] +name = "pre-commit" +version = "3.8.0" +description = "A framework for managing and maintaining multi-language pre-commit hooks." +optional = false +python-versions = ">=3.9" +files = [ + {file = "pre_commit-3.8.0-py2.py3-none-any.whl", hash = "sha256:9a90a53bf82fdd8778d58085faf8d83df56e40dfe18f45b19446e26bf1b3a63f"}, + {file = "pre_commit-3.8.0.tar.gz", hash = "sha256:8bb6494d4a20423842e198980c9ecf9f96607a07ea29549e180eef9ae80fe7af"}, +] + +[package.dependencies] +cfgv = ">=2.0.0" +identify = ">=1.0.0" +nodeenv = ">=0.11.1" +pyyaml = ">=5.1" +virtualenv = ">=20.10.0" + [[package]] name = "proglog" version = "0.1.10" @@ -3464,6 +3529,26 @@ h2 = ["h2 (>=4,<5)"] socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"] zstd = ["zstandard (>=0.18.0)"] +[[package]] +name = "virtualenv" +version = "20.26.3" +description = "Virtual Python Environment builder" +optional = false +python-versions = ">=3.7" +files = [ + {file = "virtualenv-20.26.3-py3-none-any.whl", hash = "sha256:8cc4a31139e796e9a7de2cd5cf2489de1217193116a8fd42328f1bd65f434589"}, + {file = "virtualenv-20.26.3.tar.gz", hash = "sha256:4c43a2a236279d9ea36a0d76f98d84bd6ca94ac4e0f4a3b9d46d05e10fea542a"}, +] + +[package.dependencies] +distlib = ">=0.3.7,<1" +filelock = ">=3.12.2,<4" +platformdirs = ">=3.9.1,<5" + +[package.extras] +docs = ["furo (>=2023.7.26)", "proselint (>=0.13)", "sphinx (>=7.1.2,!=7.3)", "sphinx-argparse (>=0.4)", "sphinxcontrib-towncrier (>=0.2.1a0)", "towncrier (>=23.6)"] +test = ["covdefaults (>=2.3)", "coverage (>=7.2.7)", "coverage-enable-subprocess (>=1)", "flaky (>=3.7)", "packaging (>=23.1)", "pytest (>=7.4)", "pytest-env (>=0.8.2)", "pytest-freezer (>=0.4.8)", "pytest-mock (>=3.11.1)", "pytest-randomly (>=3.12)", "pytest-timeout (>=2.1)", "setuptools (>=68)", "time-machine (>=2.10)"] + [[package]] name = "watchdog" version = "4.0.1" @@ -3537,4 +3622,4 @@ test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "dcfbb136239868e45fa3aa41e87653e9e7f8174e2ed4ccfab03b3a391f9a16c5" +content-hash = "d42117f2f0150ad2fc3cde5913d985b8d8059e4606c77860b80fac76b655800e" diff --git a/pyproject.toml b/pyproject.toml index 59d4c723..e56d77de 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -62,6 +62,7 @@ mkdocstrings = {extras = ["python"], version = "^0.23.0"} mkdocs-material = "^9.4.2" types-tabulate = "^0.9.0.20240106" scikit-image = "<0.23.1" +pre-commit = "^3.8.0" [tool.pytest.ini_options] log_cli = true diff --git a/vision_agent/clients/http.py b/vision_agent/clients/http.py index 6cd37654..a041952f 100644 --- a/vision_agent/clients/http.py +++ b/vision_agent/clients/http.py @@ -13,7 +13,9 @@ class BaseHTTP: _TIMEOUT = 30 # seconds _MAX_RETRIES = 3 - def __init__(self, base_endpoint: str, *, headers: Optional[Dict[str, Any]] = None) -> None: + def __init__( + self, base_endpoint: str, *, headers: Optional[Dict[str, Any]] = None + ) -> None: self._headers = headers if headers is None: self._headers = { @@ -22,16 +24,16 @@ def __init__(self, base_endpoint: str, *, headers: Optional[Dict[str, Any]] = No self._base_endpoint = base_endpoint self._session = Session() self._session.headers.update(self._headers) - self._session.mount(self._base_endpoint, HTTPAdapter(max_retries=self._MAX_RETRIES)) + self._session.mount( + self._base_endpoint, HTTPAdapter(max_retries=self._MAX_RETRIES) + ) def post(self, url: str, payload: Dict[str, Any]) -> None: formatted_url = f"{self._base_endpoint}/{url}" _LOGGER.info(f"Sending data to {formatted_url}") try: response = self._session.post( - url=formatted_url, - json=payload, - timeout=self._TIMEOUT + url=formatted_url, json=payload, timeout=self._TIMEOUT ) response.raise_for_status() _LOGGER.info(json.dumps(response.json())) diff --git a/vision_agent/clients/landing_public_api.py b/vision_agent/clients/landing_public_api.py index 846ea935..c62faa33 100644 --- a/vision_agent/clients/landing_public_api.py +++ b/vision_agent/clients/landing_public_api.py @@ -20,7 +20,7 @@ def launch_fine_tuning_job( url = "v1/agent/jobs/fine-tuning" data = { "model": {"name": model_name, "task": task}, - "bboxes": [bbox.model_dump(by_alias=True) for bbox in bboxes] + "bboxes": [bbox.model_dump(by_alias=True) for bbox in bboxes], } response = self.post(url, payload=data) return UUID(response["jobId"]) From 5eb26efef4066df65f5b84b10cb805ebcbd645ec Mon Sep 17 00:00:00 2001 From: Dayanne Fernandes Date: Tue, 6 Aug 2024 20:37:43 -0300 Subject: [PATCH 06/11] mypy --- pyproject.toml | 2 -- vision_agent/clients/http.py | 8 +++++--- 2 files changed, 5 insertions(+), 5 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index e56d77de..e4da9ca6 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -79,8 +79,6 @@ line_length = 88 profile = "black" [tool.mypy] -plugins = ["pydantic.mypy"] - exclude = "tests" show_error_context = true pretty = true diff --git a/vision_agent/clients/http.py b/vision_agent/clients/http.py index a041952f..678148a9 100644 --- a/vision_agent/clients/http.py +++ b/vision_agent/clients/http.py @@ -23,12 +23,12 @@ def __init__( } self._base_endpoint = base_endpoint self._session = Session() - self._session.headers.update(self._headers) + self._session.headers.update(self._headers) # type: ignore self._session.mount( self._base_endpoint, HTTPAdapter(max_retries=self._MAX_RETRIES) ) - def post(self, url: str, payload: Dict[str, Any]) -> None: + def post(self, url: str, payload: Dict[str, Any]) -> Dict[str, Any]: formatted_url = f"{self._base_endpoint}/{url}" _LOGGER.info(f"Sending data to {formatted_url}") try: @@ -36,9 +36,11 @@ def post(self, url: str, payload: Dict[str, Any]) -> None: url=formatted_url, json=payload, timeout=self._TIMEOUT ) response.raise_for_status() - _LOGGER.info(json.dumps(response.json())) + result: Dict[str, Any] = response.json() + _LOGGER.info(json.dumps(result)) except (ConnectionError, Timeout, RequestException) as err: _LOGGER.warning(f"Error: {err}.") except json.JSONDecodeError: resp_text = response.text _LOGGER.warning(f"Response seems incorrect: '{resp_text}'.") + return result From e201d43469dde99854ede17faa8b4a4911d0522a Mon Sep 17 00:00:00 2001 From: Dayanne Fernandes Date: Tue, 6 Aug 2024 21:32:21 -0300 Subject: [PATCH 07/11] resolve mypy --- pyproject.toml | 3 +-- vision_agent/utils/execute.py | 4 ++-- 2 files changed, 3 insertions(+), 4 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index e4da9ca6..549144e2 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -93,7 +93,6 @@ warn_unused_configs = true warn_unused_ignores = true warn_return_any = true show_error_codes = true -disallow_any_unimported = true [[tool.mypy.overrides]] ignore_missing_imports = true @@ -104,5 +103,5 @@ module = [ "sentence_transformers.*", "moviepy.*", "e2b_code_interpreter.*", - "e2b.*", + "e2b.*" ] diff --git a/vision_agent/utils/execute.py b/vision_agent/utils/execute.py index 0c058fe4..b157b1df 100644 --- a/vision_agent/utils/execute.py +++ b/vision_agent/utils/execute.py @@ -209,7 +209,7 @@ def formats(self) -> Iterable[str]: return formats @staticmethod - def from_e2b_result(result: E2BResult) -> "Result": # type: ignore + def from_e2b_result(result: E2BResult) -> "Result": """ Creates a Result object from an E2BResult object. """ @@ -361,7 +361,7 @@ def from_exception(exec: Exception, traceback_raw: List[str]) -> "Execution": ) @staticmethod - def from_e2b_execution(exec: E2BExecution) -> "Execution": # type: ignore + def from_e2b_execution(exec: E2BExecution) -> "Execution": """Creates an Execution object from an E2BResult object.""" return Execution( results=[Result.from_e2b_result(res) for res in exec.results], From fa2452a0b6b4e4e60d0b96d1465322d6b4dd7f2b Mon Sep 17 00:00:00 2001 From: Dayanne Fernandes Date: Wed, 7 Aug 2024 15:56:55 -0300 Subject: [PATCH 08/11] add task customization --- vision_agent/clients/landing_public_api.py | 6 +++--- vision_agent/tools/tool_types.py | 14 ++++++++++++++ vision_agent/tools/tools.py | 16 ++++++++++------ 3 files changed, 27 insertions(+), 9 deletions(-) diff --git a/vision_agent/clients/landing_public_api.py b/vision_agent/clients/landing_public_api.py index c62faa33..1a07f8ae 100644 --- a/vision_agent/clients/landing_public_api.py +++ b/vision_agent/clients/landing_public_api.py @@ -4,7 +4,7 @@ from vision_agent.clients.http import BaseHTTP from vision_agent.utils.type_defs import LandingaiAPIKey -from vision_agent.tools.tool_types import BboxInputBase64 +from vision_agent.tools.tool_types import BboxInputBase64, PromptTask class LandingPublicAPI(BaseHTTP): @@ -15,11 +15,11 @@ def __init__(self) -> None: super().__init__(base_endpoint=landing_url, headers=headers) def launch_fine_tuning_job( - self, model_name: str, task: str, bboxes: List[BboxInputBase64] + self, model_name: str, task: PromptTask, bboxes: List[BboxInputBase64] ) -> UUID: url = "v1/agent/jobs/fine-tuning" data = { - "model": {"name": model_name, "task": task}, + "model": {"name": model_name, "task": task.value}, "bboxes": [bbox.model_dump(by_alias=True) for bbox in bboxes], } response = self.post(url, payload=data) diff --git a/vision_agent/tools/tool_types.py b/vision_agent/tools/tool_types.py index 8ab55ffe..f14cd337 100644 --- a/vision_agent/tools/tool_types.py +++ b/vision_agent/tools/tool_types.py @@ -1,3 +1,4 @@ +from enum import Enum from typing import List, Tuple, Literal from nptyping import UInt8, NDArray @@ -18,3 +19,16 @@ class BboxInputBase64(BaseModel): filename: str labels: List[str] bboxes: List[Tuple[int, int, int, int]] + + +class PromptTask(str, Enum): + """ + Valid task prompts options for the Florencev2 model. + """ + + CAPTION = "" + """""" + CAPTION_TO_PHRASE_GROUNDING = "" + """""" + OBJECT_DETECTION = "" + """""" diff --git a/vision_agent/tools/tools.py b/vision_agent/tools/tools.py index fc5a6d72..d40b13c1 100644 --- a/vision_agent/tools/tools.py +++ b/vision_agent/tools/tools.py @@ -16,7 +16,7 @@ from pillow_heif import register_heif_opener # type: ignore from vision_agent.clients.landing_public_api import LandingPublicAPI -from vision_agent.tools.tool_types import BboxInput, BboxInputBase64 +from vision_agent.tools.tool_types import BboxInput, BboxInputBase64, PromptTask from vision_agent.tools.tool_utils import ( send_inference_request, get_tool_descriptions, @@ -662,7 +662,7 @@ def florencev2_object_detection(image: np.ndarray) -> List[Dict[str, Any]]: return return_data -def florencev2_fine_tuning(bboxes: List[Dict[str, Any]]) -> UUID: +def florencev2_fine_tuning(bboxes: List[Dict[str, Any]], task: str) -> UUID: """'florencev2_fine_tuning' is a tool that fine-tune florencev2 to be able to detect objects in an image based on a given dataset. It returns the fine tuning job id. @@ -670,6 +670,8 @@ def florencev2_fine_tuning(bboxes: List[Dict[str, Any]]) -> UUID: Parameters: bboxes (List[BboxInput]): A list of BboxInput containing the image object, image filename, labels and bounding boxes. + task (PromptTask): The florencev2 fine-tuning task. The options are + CAPTION, CAPTION_TO_PHRASE_GROUNDING and OBJECT_DETECTION. Returns: UUID: The fine tuning job id, this id will used to retrieve the fine @@ -679,10 +681,12 @@ def florencev2_fine_tuning(bboxes: List[Dict[str, Any]]) -> UUID: ------- >>> fine_tuning_job_id = florencev2_fine_tuning( [{'image': image, 'filename': 'filename.png', 'label': ['screw'], 'bbox': [[370, 30, 560, 290]]}, - {'image': image, 'filename': 'filename.png', 'label': ['screw'], 'bbox': [[120, 0, 300, 170]]}] + {'image': image, 'filename': 'filename.png', 'label': ['screw'], 'bbox': [[120, 0, 300, 170]]}], + "OBJECT_DETECTION" ) """ bboxes_input = [BboxInput.model_validate(bbox) for bbox in bboxes] + task_input = PromptTask[task] fine_tuning_request = [ BboxInputBase64( image=convert_to_b64(bbox_input.image), @@ -692,10 +696,10 @@ def florencev2_fine_tuning(bboxes: List[Dict[str, Any]]) -> UUID: ) for bbox_input in bboxes_input ] - # TODO: receive the task from user prompt - task = "" landing_api = LandingPublicAPI() - return landing_api.launch_fine_tuning_job("florencev2", task, fine_tuning_request) + return landing_api.launch_fine_tuning_job( + "florencev2", task_input, fine_tuning_request + ) def detr_segmentation(image: np.ndarray) -> List[Dict[str, Any]]: From c9ab90a53df32890db39d86ee2069547c4b40c26 Mon Sep 17 00:00:00 2001 From: Dayanne Fernandes Date: Wed, 7 Aug 2024 16:22:43 -0300 Subject: [PATCH 09/11] tools to meta tools --- vision_agent/tools/meta_tools.py | 45 +++++++++++++++++++ .../{tool_types.py => meta_tools_types.py} | 0 vision_agent/tools/tools.py | 44 ------------------ 3 files changed, 45 insertions(+), 44 deletions(-) rename vision_agent/tools/{tool_types.py => meta_tools_types.py} (100%) diff --git a/vision_agent/tools/meta_tools.py b/vision_agent/tools/meta_tools.py index c5860a60..290133eb 100644 --- a/vision_agent/tools/meta_tools.py +++ b/vision_agent/tools/meta_tools.py @@ -1,5 +1,6 @@ import os import subprocess +from uuid import UUID from pathlib import Path from typing import Any, Dict, List, Union @@ -7,6 +8,9 @@ from vision_agent.lmm.types import Message from vision_agent.tools.tool_utils import get_tool_documentation from vision_agent.tools.tools import TOOL_DESCRIPTIONS +from vision_agent.utils.image_utils import convert_to_b64 +from vision_agent.clients.landing_public_api import LandingPublicAPI +from vision_agent.tools.meta_tools_types import BboxInput, BboxInputBase64, PromptTask # These tools are adapted from SWE-Agent https://github.com/princeton-nlp/SWE-agent @@ -385,6 +389,46 @@ def get_tool_descriptions() -> str: return TOOL_DESCRIPTIONS +def florencev2_fine_tuning(bboxes: List[Dict[str, Any]], task: str) -> UUID: + """'florencev2_fine_tuning' is a tool that fine-tune florencev2 to be able + to detect objects in an image based on a given dataset. It returns the fine + tuning job id. + + Parameters: + bboxes (List[BboxInput]): A list of BboxInput containing the + image object, image filename, labels and bounding boxes. + task (PromptTask): The florencev2 fine-tuning task. The options are + CAPTION, CAPTION_TO_PHRASE_GROUNDING and OBJECT_DETECTION. + + Returns: + UUID: The fine tuning job id, this id will used to retrieve the fine + tuned model. + + Example + ------- + >>> fine_tuning_job_id = florencev2_fine_tuning( + [{'image': image, 'filename': 'filename.png', 'label': ['screw'], 'bbox': [[370, 30, 560, 290]]}, + {'image': image, 'filename': 'filename.png', 'label': ['screw'], 'bbox': [[120, 0, 300, 170]]}], + "OBJECT_DETECTION" + ) + """ + bboxes_input = [BboxInput.model_validate(bbox) for bbox in bboxes] + task_input = PromptTask[task] + fine_tuning_request = [ + BboxInputBase64( + image=convert_to_b64(bbox_input.image), + filename=bbox_input.filename, + labels=bbox_input.labels, + bboxes=bbox_input.bboxes, + ) + for bbox_input in bboxes_input + ] + landing_api = LandingPublicAPI() + return landing_api.launch_fine_tuning_job( + "florencev2", task_input, fine_tuning_request + ) + + META_TOOL_DOCSTRING = get_tool_documentation( [ get_tool_descriptions, @@ -398,5 +442,6 @@ def get_tool_descriptions() -> str: search_dir, search_file, find_file, + florencev2_fine_tuning, ] ) diff --git a/vision_agent/tools/tool_types.py b/vision_agent/tools/meta_tools_types.py similarity index 100% rename from vision_agent/tools/tool_types.py rename to vision_agent/tools/meta_tools_types.py diff --git a/vision_agent/tools/tools.py b/vision_agent/tools/tools.py index d40b13c1..a78457ed 100644 --- a/vision_agent/tools/tools.py +++ b/vision_agent/tools/tools.py @@ -2,7 +2,6 @@ import json import logging import tempfile -from uuid import UUID from pathlib import Path from importlib import resources from typing import Any, Dict, List, Optional, Tuple, Union, cast @@ -15,8 +14,6 @@ from PIL import Image, ImageDraw, ImageFont from pillow_heif import register_heif_opener # type: ignore -from vision_agent.clients.landing_public_api import LandingPublicAPI -from vision_agent.tools.tool_types import BboxInput, BboxInputBase64, PromptTask from vision_agent.tools.tool_utils import ( send_inference_request, get_tool_descriptions, @@ -662,46 +659,6 @@ def florencev2_object_detection(image: np.ndarray) -> List[Dict[str, Any]]: return return_data -def florencev2_fine_tuning(bboxes: List[Dict[str, Any]], task: str) -> UUID: - """'florencev2_fine_tuning' is a tool that fine-tune florencev2 to be able - to detect objects in an image based on a given dataset. It returns the fine - tuning job id. - - Parameters: - bboxes (List[BboxInput]): A list of BboxInput containing the - image object, image filename, labels and bounding boxes. - task (PromptTask): The florencev2 fine-tuning task. The options are - CAPTION, CAPTION_TO_PHRASE_GROUNDING and OBJECT_DETECTION. - - Returns: - UUID: The fine tuning job id, this id will used to retrieve the fine - tuned model. - - Example - ------- - >>> fine_tuning_job_id = florencev2_fine_tuning( - [{'image': image, 'filename': 'filename.png', 'label': ['screw'], 'bbox': [[370, 30, 560, 290]]}, - {'image': image, 'filename': 'filename.png', 'label': ['screw'], 'bbox': [[120, 0, 300, 170]]}], - "OBJECT_DETECTION" - ) - """ - bboxes_input = [BboxInput.model_validate(bbox) for bbox in bboxes] - task_input = PromptTask[task] - fine_tuning_request = [ - BboxInputBase64( - image=convert_to_b64(bbox_input.image), - filename=bbox_input.filename, - labels=bbox_input.labels, - bboxes=bbox_input.bboxes, - ) - for bbox_input in bboxes_input - ] - landing_api = LandingPublicAPI() - return landing_api.launch_fine_tuning_job( - "florencev2", task_input, fine_tuning_request - ) - - def detr_segmentation(image: np.ndarray) -> List[Dict[str, Any]]: """'detr_segmentation' is a tool that can segment common objects in an image without any text prompt. It returns a list of detected objects @@ -1297,7 +1254,6 @@ def overlay_heat_map( florencev2_roberta_vqa, florencev2_image_caption, florencev2_object_detection, - florencev2_fine_tuning, detr_segmentation, depth_anything_v2, generate_soft_edge_image, From f391b448f5ad91e6be109088b10e42d2f6bfafa1 Mon Sep 17 00:00:00 2001 From: Dayanne Fernandes Date: Wed, 7 Aug 2024 16:53:01 -0300 Subject: [PATCH 10/11] fix imports --- vision_agent/agent/vision_agent.py | 2 +- vision_agent/clients/landing_public_api.py | 2 +- vision_agent/tools/__init__.py | 3 +-- vision_agent/tools/meta_tools.py | 10 +++++----- vision_agent/tools/meta_tools_types.py | 10 +++------- 5 files changed, 11 insertions(+), 16 deletions(-) diff --git a/vision_agent/agent/vision_agent.py b/vision_agent/agent/vision_agent.py index 95560ecd..9090b706 100644 --- a/vision_agent/agent/vision_agent.py +++ b/vision_agent/agent/vision_agent.py @@ -28,7 +28,7 @@ class DefaultImports: code = [ "from typing import *", "from vision_agent.utils.execute import CodeInterpreter", - "from vision_agent.tools.meta_tools import generate_vision_code, edit_vision_code, open_file, create_file, scroll_up, scroll_down, edit_file, get_tool_descriptions", + "from vision_agent.tools.meta_tools import generate_vision_code, edit_vision_code, open_file, create_file, scroll_up, scroll_down, edit_file, get_tool_descriptions, florencev2_fine_tuning", ] @staticmethod diff --git a/vision_agent/clients/landing_public_api.py b/vision_agent/clients/landing_public_api.py index 1a07f8ae..4c50c388 100644 --- a/vision_agent/clients/landing_public_api.py +++ b/vision_agent/clients/landing_public_api.py @@ -4,7 +4,7 @@ from vision_agent.clients.http import BaseHTTP from vision_agent.utils.type_defs import LandingaiAPIKey -from vision_agent.tools.tool_types import BboxInputBase64, PromptTask +from vision_agent.tools.meta_tools_types import BboxInputBase64, PromptTask class LandingPublicAPI(BaseHTTP): diff --git a/vision_agent/tools/__init__.py b/vision_agent/tools/__init__.py index 1ea94510..52681274 100644 --- a/vision_agent/tools/__init__.py +++ b/vision_agent/tools/__init__.py @@ -1,6 +1,6 @@ from typing import Callable, List, Optional -from .meta_tools import META_TOOL_DOCSTRING +from .meta_tools import META_TOOL_DOCSTRING, florencev2_fine_tuning from .prompts import CHOOSE_PARAMS, SYSTEM_PROMPT from .tools import ( TOOL_DESCRIPTIONS, @@ -19,7 +19,6 @@ florencev2_image_caption, florencev2_object_detection, florencev2_roberta_vqa, - florencev2_fine_tuning, generate_pose_image, generate_soft_edge_image, get_tool_documentation, diff --git a/vision_agent/tools/meta_tools.py b/vision_agent/tools/meta_tools.py index 290133eb..851aab18 100644 --- a/vision_agent/tools/meta_tools.py +++ b/vision_agent/tools/meta_tools.py @@ -396,7 +396,7 @@ def florencev2_fine_tuning(bboxes: List[Dict[str, Any]], task: str) -> UUID: Parameters: bboxes (List[BboxInput]): A list of BboxInput containing the - image object, image filename, labels and bounding boxes. + image path, labels and bounding boxes. task (PromptTask): The florencev2 fine-tuning task. The options are CAPTION, CAPTION_TO_PHRASE_GROUNDING and OBJECT_DETECTION. @@ -407,8 +407,8 @@ def florencev2_fine_tuning(bboxes: List[Dict[str, Any]], task: str) -> UUID: Example ------- >>> fine_tuning_job_id = florencev2_fine_tuning( - [{'image': image, 'filename': 'filename.png', 'label': ['screw'], 'bbox': [[370, 30, 560, 290]]}, - {'image': image, 'filename': 'filename.png', 'label': ['screw'], 'bbox': [[120, 0, 300, 170]]}], + [{'image_path': 'filename.png', 'labels': ['screw'], 'bboxes': [[370, 30, 560, 290]]}, + {'image_path': 'filename.png', 'labels': ['screw'], 'bboxes': [[120, 0, 300, 170]]}], "OBJECT_DETECTION" ) """ @@ -416,8 +416,8 @@ def florencev2_fine_tuning(bboxes: List[Dict[str, Any]], task: str) -> UUID: task_input = PromptTask[task] fine_tuning_request = [ BboxInputBase64( - image=convert_to_b64(bbox_input.image), - filename=bbox_input.filename, + image=convert_to_b64(bbox_input.image_path), + filename=bbox_input.image_path.split("/")[-1], labels=bbox_input.labels, bboxes=bbox_input.bboxes, ) diff --git a/vision_agent/tools/meta_tools_types.py b/vision_agent/tools/meta_tools_types.py index f14cd337..4c60923e 100644 --- a/vision_agent/tools/meta_tools_types.py +++ b/vision_agent/tools/meta_tools_types.py @@ -1,15 +1,11 @@ from enum import Enum -from typing import List, Tuple, Literal +from typing import List, Tuple -from nptyping import UInt8, NDArray -from pydantic import BaseModel, ConfigDict +from pydantic import BaseModel class BboxInput(BaseModel): - model_config = ConfigDict(arbitrary_types_allowed=True) - - image: NDArray[Literal["Height, Width, 3"], UInt8] - filename: str + image_path: str labels: List[str] bboxes: List[Tuple[int, int, int, int]] From cb3110119e70d9d442cd1311cb3f210b96680839 Mon Sep 17 00:00:00 2001 From: Dayanne Fernandes Date: Wed, 7 Aug 2024 17:33:33 -0300 Subject: [PATCH 11/11] remove nptyping --- poetry.lock | 30 ++++-------------------------- pyproject.toml | 1 - 2 files changed, 4 insertions(+), 27 deletions(-) diff --git a/poetry.lock b/poetry.lock index 3bd1ca8b..37c770bf 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1663,28 +1663,6 @@ files = [ {file = "nodeenv-1.9.1.tar.gz", hash = "sha256:6ec12890a2dab7946721edbfbcd91f3319c6ccc9aec47be7c7e6b7011ee6645f"}, ] -[[package]] -name = "nptyping" -version = "2.5.0" -description = "Type hints for NumPy." -optional = false -python-versions = ">=3.7" -files = [ - {file = "nptyping-2.5.0-py3-none-any.whl", hash = "sha256:764e51836faae33a7ae2e928af574cfb701355647accadcc89f2ad793630b7c8"}, - {file = "nptyping-2.5.0.tar.gz", hash = "sha256:e3d35b53af967e6fb407c3016ff9abae954d3a0568f7cc13a461084224e8e20a"}, -] - -[package.dependencies] -numpy = {version = ">=1.20.0,<2.0.0", markers = "python_version >= \"3.8\""} -typing-extensions = {version = ">=4.0.0,<5.0.0", markers = "python_version < \"3.10\""} - -[package.extras] -build = ["invoke (>=1.6.0)", "pip-tools (>=6.5.0)"] -complete = ["pandas", "pandas-stubs-fork"] -dev = ["autoflake", "beartype (<0.10.0)", "beartype (>=0.10.0)", "black", "codecov (>=2.1.0)", "coverage", "feedparser", "invoke (>=1.6.0)", "isort", "mypy", "pandas", "pandas-stubs-fork", "pip-tools (>=6.5.0)", "pylint", "pyright", "setuptools", "typeguard", "wheel"] -pandas = ["pandas", "pandas-stubs-fork"] -qa = ["autoflake", "beartype (<0.10.0)", "beartype (>=0.10.0)", "black", "codecov (>=2.1.0)", "coverage", "feedparser", "isort", "mypy", "pylint", "pyright", "setuptools", "typeguard", "wheel"] - [[package]] name = "numpy" version = "1.26.4" @@ -1732,13 +1710,13 @@ files = [ [[package]] name = "openai" -version = "1.40.0" +version = "1.40.1" description = "The official Python library for the openai API" optional = false python-versions = ">=3.7.1" files = [ - {file = "openai-1.40.0-py3-none-any.whl", hash = "sha256:eb6909abaacd62ef28c275a5c175af29f607b40645b0a49d2856bbed62edb2e7"}, - {file = "openai-1.40.0.tar.gz", hash = "sha256:1b7b316e27b2333b063ee62b6539b74267c7282498d9a02fc4ccb38a9c14336c"}, + {file = "openai-1.40.1-py3-none-any.whl", hash = "sha256:cf5929076c6ca31c26f1ed207e9fd19eb05404cc9104f64c9d29bb0ac0c5bcd4"}, + {file = "openai-1.40.1.tar.gz", hash = "sha256:cb1294ac1f8c6a1acbb07e090698eb5ad74a7a88484e77126612a4f22579673d"}, ] [package.dependencies] @@ -3622,4 +3600,4 @@ test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", [metadata] lock-version = "2.0" python-versions = ">=3.9,<4.0" -content-hash = "d42117f2f0150ad2fc3cde5913d985b8d8059e4606c77860b80fac76b655800e" +content-hash = "e864e0046a1004192f84746488c326b9109c1d83c72f7206530390270e3f9c96" diff --git a/pyproject.toml b/pyproject.toml index 549144e2..e1708ef3 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -42,7 +42,6 @@ pillow-heif = "^0.16.0" pytube = "15.0.0" anthropic = "^0.31.0" pydantic = "2.7.4" -nptyping = "2.5.0" [tool.poetry.group.dev.dependencies] autoflake = "1.*"