diff --git a/backend/custom_types.py b/backend/custom_types.py new file mode 100644 index 0000000..b6c9fee --- /dev/null +++ b/backend/custom_types.py @@ -0,0 +1,7 @@ +from typing import Literal + + +InputMode = Literal[ + "image", + "video", +] diff --git a/backend/mock_llm.py b/backend/mock_llm.py index 0102bad..0c1060d 100644 --- a/backend/mock_llm.py +++ b/backend/mock_llm.py @@ -1,12 +1,20 @@ import asyncio from typing import Awaitable, Callable +from custom_types import InputMode -async def mock_completion(process_chunk: Callable[[str], Awaitable[None]]) -> str: - code_to_return = NO_IMAGES_NYTIMES_MOCK_CODE - for i in range(0, len(code_to_return), 10): - await process_chunk(code_to_return[i : i + 10]) +async def mock_completion( + process_chunk: Callable[[str], Awaitable[None]], input_mode: InputMode +) -> str: + code_to_return = ( + MORTGAGE_CALCULATOR_VIDEO_PROMPT_MOCK + if input_mode == "video" + else NO_IMAGES_NYTIMES_MOCK_CODE + ) + + for i in range(0, len(code_to_return), 100): + await process_chunk(code_to_return[i : i + 100]) await asyncio.sleep(0.01) return code_to_return @@ -206,3 +214,232 @@ NO_IMAGES_NYTIMES_MOCK_CODE = """ """ + +MORTGAGE_CALCULATOR_VIDEO_PROMPT_MOCK = """ + +The user flow in the video seems to be: +1. The calculator starts with some default values for loan amount, loan term, interest rate, etc. +2. The user toggles the "Include taxes & fees" checkbox which shows an explanation tooltip. +3. The user selects different loan terms from the dropdown, which updates the monthly payment amount. +4. The user enters a custom loan amount. +5. The user selects a different loan term (30-yr fixed FHA). +6. The user enters additional details like home price, down payment, state, credit score, property tax, home insurance, and HOA fees. +7. The calculator updates the total monthly payment breakdown. + +To build this: +- Use a container div for the whole calculator +- Have sections for Monthly Payment, Purchase Budget, loan details, additional costs +- Use input fields, dropdowns, and checkboxes for user input +- Update values dynamically using JavaScript when inputs change +- Show/hide explanation tooltip when checkbox is toggled +- Update monthly payment whenever loan amount, interest rate or term is changed +- Allow selecting loan term from a dropdown +- Update total monthly payment breakdown as additional costs are entered +- Style everything to match the screenshots using Tailwind utility classes + + + + + + + + + +
+
Mortgage Calculator
+ +
+
Monthly payment
+
Purchase budget
+
+ +
+ + + + +
+ +
$1,696
+ +
+
Loan amount
+ +
+ +
+
Loan term
+ +
+ +
+
+
Interest
+
7.61 %
+
+ +
+ +
+
+
Home price
+ +
+
+
Down payment
+
+ +
20 %
+
+
+
+ +
+
+
State
+ +
+
+
Credit score
+ +
+
+ +
+
+
Property tax (yearly)
+ +
+
+
Home insurance (yearly)
+ +
+
+
Private mortgage insurance (monthly)
+ +
+
+
Homeowners association (monthly)
+ +
+
+ +
+
+
Total monthly payment
+
$2,036
+
+
+
Loan
+
$1,635
+
Taxes & fees
+
$401
+
+
+ +
+
Disclaimer • Feedback
+
+
+ + + + +""" diff --git a/backend/poetry.lock b/backend/poetry.lock index 663f7a2..61ff096 100644 --- a/backend/poetry.lock +++ b/backend/poetry.lock @@ -2,13 +2,13 @@ [[package]] name = "anthropic" -version = "0.18.0" +version = "0.18.1" description = "The official Python library for the anthropic API" optional = false python-versions = ">=3.7" files = [ - {file = "anthropic-0.18.0-py3-none-any.whl", hash = "sha256:af2a65a48ba4661e3902b49f96710d168782af9deb06d58c12f25e53448fb570"}, - {file = "anthropic-0.18.0.tar.gz", hash = "sha256:80a6134f6562792be8ec30f743e2211476cb1e1f59b01795b901f099ae854825"}, + {file = "anthropic-0.18.1-py3-none-any.whl", hash = "sha256:b85aee64f619ce1b1964ba733a09adc4053e7bc4e6d4186001229ec191099dcf"}, + {file = "anthropic-0.18.1.tar.gz", hash = "sha256:f5d1caafd43f6cc933a79753a93531605095f040a384f6a900c3de9c3fb6694e"}, ] [package.dependencies] @@ -26,52 +26,56 @@ vertex = ["google-auth (>=2,<3)"] [[package]] name = "anyio" -version = "3.7.1" +version = 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[[package]] @@ -1088,4 +1321,4 @@ files = [ [metadata] lock-version = "2.0" python-versions = "^3.10" -content-hash = "17d8bb6d9e4a392f2512e4265df564708d59c1d83b26146f23e2595b6764c711" +content-hash = "274fed55cf4a2f4e9954b3d196c103b72225409c6050759a939f0ca197ae3f79" diff --git a/backend/pyproject.toml b/backend/pyproject.toml index 14009f6..263b4a4 100644 --- a/backend/pyproject.toml +++ b/backend/pyproject.toml @@ -16,6 +16,7 @@ beautifulsoup4 = "^4.12.2" httpx = "^0.25.1" pre-commit = "^3.6.2" anthropic = "^0.18.0" +moviepy = "^1.0.3" [tool.poetry.group.dev.dependencies] pytest = "^7.4.3" diff --git a/backend/routes/generate_code.py b/backend/routes/generate_code.py index d90e82c..2efc7a0 100644 --- a/backend/routes/generate_code.py +++ b/backend/routes/generate_code.py @@ -3,9 +3,12 @@ import traceback from fastapi import APIRouter, WebSocket import openai from config import ANTHROPIC_API_KEY, IS_PROD, SHOULD_MOCK_AI_RESPONSE +from custom_types import InputMode from llm import ( CODE_GENERATION_MODELS, + MODEL_CLAUDE_OPUS, stream_claude_response, + stream_claude_response_native, stream_openai_response, ) from openai.types.chat import ChatCompletionMessageParam @@ -16,9 +19,11 @@ from prompts import assemble_imported_code_prompt, assemble_prompt from access_token import validate_access_token from datetime import datetime import json +from prompts.claude_prompts import VIDEO_PROMPT from prompts.types import Stack -from utils import pprint_prompt # type: ignore +# from utils import pprint_prompt +from video.utils import extract_tag_content, assemble_claude_prompt_video # type: ignore router = APIRouter() @@ -64,6 +69,19 @@ async def stream_code(websocket: WebSocket): generated_code_config = "" if "generatedCodeConfig" in params and params["generatedCodeConfig"]: generated_code_config = params["generatedCodeConfig"] + if not generated_code_config in get_args(Stack): + await throw_error(f"Invalid generated code config: {generated_code_config}") + return + # Cast the variable to the Stack type + valid_stack = cast(Stack, generated_code_config) + + # Validate the input mode + input_mode = params.get("inputMode") + if not input_mode in get_args(InputMode): + await throw_error(f"Invalid input mode: {input_mode}") + raise Exception(f"Invalid input mode: {input_mode}") + # Cast the variable to the right type + validated_input_mode = cast(InputMode, input_mode) # Read the model from the request. Fall back to default if not provided. code_generation_model = params.get("codeGenerationModel", "gpt_4_vision") @@ -72,7 +90,7 @@ async def stream_code(websocket: WebSocket): raise Exception(f"Invalid model: {code_generation_model}") print( - f"Generating {generated_code_config} code using {code_generation_model} model..." + f"Generating {generated_code_config} code for uploaded {input_mode} using {code_generation_model} model..." ) # Get the OpenAI API key from the request. Fall back to environment variable if not provided. @@ -110,13 +128,6 @@ async def stream_code(websocket: WebSocket): ) return - # Validate the generated code config - if not generated_code_config in get_args(Stack): - await throw_error(f"Invalid generated code config: {generated_code_config}") - return - # Cast the variable to the Stack type - valid_stack = cast(Stack, generated_code_config) - # Get the OpenAI Base URL from the request. Fall back to environment variable if not provided. openai_base_url = None # Disable user-specified OpenAI Base URL in prod @@ -203,13 +214,34 @@ async def stream_code(websocket: WebSocket): image_cache = create_alt_url_mapping(params["history"][-2]) - pprint_prompt(prompt_messages) + if validated_input_mode == "video": + video_data_url = params["image"] + prompt_messages = await assemble_claude_prompt_video(video_data_url) + + # pprint_prompt(prompt_messages) # type: ignore if SHOULD_MOCK_AI_RESPONSE: - completion = await mock_completion(process_chunk) + completion = await mock_completion( + process_chunk, input_mode=validated_input_mode + ) else: try: - if code_generation_model == "claude_3_sonnet": + if validated_input_mode == "video": + if not ANTHROPIC_API_KEY: + await throw_error( + "No Anthropic API key found. Please add the environment variable ANTHROPIC_API_KEY to backend/.env" + ) + raise Exception("No Anthropic key") + + completion = await stream_claude_response_native( + system_prompt=VIDEO_PROMPT, + messages=prompt_messages, # type: ignore + api_key=ANTHROPIC_API_KEY, + callback=lambda x: process_chunk(x), + model=MODEL_CLAUDE_OPUS, + include_thinking=True, + ) + elif code_generation_model == "claude_3_sonnet": if not ANTHROPIC_API_KEY: await throw_error( "No Anthropic API key found. Please add the environment variable ANTHROPIC_API_KEY to backend/.env" @@ -217,13 +249,13 @@ async def stream_code(websocket: WebSocket): raise Exception("No Anthropic key") completion = await stream_claude_response( - prompt_messages, + prompt_messages, # type: ignore api_key=ANTHROPIC_API_KEY, callback=lambda x: process_chunk(x), ) else: completion = await stream_openai_response( - prompt_messages, + prompt_messages, # type: ignore api_key=openai_api_key, base_url=openai_base_url, callback=lambda x: process_chunk(x), @@ -263,8 +295,11 @@ async def stream_code(websocket: WebSocket): ) return await throw_error(error_message) + if validated_input_mode == "video": + completion = extract_tag_content("html", completion) + # Write the messages dict into a log so that we can debug later - write_logs(prompt_messages, completion) + write_logs(prompt_messages, completion) # type: ignore try: if should_generate_images: diff --git a/backend/video/utils.py b/backend/video/utils.py new file mode 100644 index 0000000..94501a2 --- /dev/null +++ b/backend/video/utils.py @@ -0,0 +1,134 @@ +# Extract HTML content from the completion string +import base64 +import io +import mimetypes +import os +import tempfile +import uuid +from typing import Union, cast +from moviepy.editor import VideoFileClip # type: ignore +from PIL import Image +import math + + +DEBUG = True +TARGET_NUM_SCREENSHOTS = ( + 20 # Should be max that Claude supports (20) - reduce to save tokens on testing +) + + +async def assemble_claude_prompt_video(video_data_url: str): + images = split_video_into_screenshots(video_data_url) + + # Save images to tmp if we're debugging + if DEBUG: + save_images_to_tmp(images) + + # Validate number of images + print(f"Number of frames extracted from video: {len(images)}") + if len(images) > 20: + print(f"Too many screenshots: {len(images)}") + return + + # Convert images to the message format for Claude + content_messages: list[dict[str, Union[dict[str, str], str]]] = [] + for image in images: + + # Convert Image to buffer + buffered = io.BytesIO() + image.save(buffered, format="JPEG") + + # Encode bytes as base64 + base64_data = base64.b64encode(buffered.getvalue()).decode("utf-8") + media_type = "image/jpeg" + + content_messages.append( + { + "type": "image", + "source": { + "type": "base64", + "media_type": media_type, + "data": base64_data, + }, + } + ) + + return [ + { + "role": "user", + "content": content_messages, + }, + ] + + +# Returns a list of images/frame (RGB format) +def split_video_into_screenshots(video_data_url: str) -> list[Image.Image]: + target_num_screenshots = TARGET_NUM_SCREENSHOTS + + # Decode the base64 URL to get the video bytes + video_encoded_data = video_data_url.split(",")[1] + video_bytes = base64.b64decode(video_encoded_data) + + mime_type = video_data_url.split(";")[0].split(":")[1] + suffix = mimetypes.guess_extension(mime_type) + + with tempfile.NamedTemporaryFile(suffix=suffix, delete=True) as temp_video_file: + print(temp_video_file.name) + temp_video_file.write(video_bytes) + temp_video_file.flush() + clip = VideoFileClip(temp_video_file.name) + images: list[Image.Image] = [] + total_frames = cast(int, clip.reader.nframes) # type: ignore + + # Calculate frame skip interval by dividing total frames by the target number of screenshots + # Ensuring a minimum skip of 1 frame + frame_skip = max(1, math.ceil(total_frames / target_num_screenshots)) + + # Iterate over each frame in the clip + for i, frame in enumerate(clip.iter_frames()): + # Save every nth frame + if i % frame_skip == 0: + frame_image = Image.fromarray(frame) # type: ignore + images.append(frame_image) + # Ensure that we don't capture more than the desired number of frames + if len(images) >= target_num_screenshots: + break + + # Close the video file to release resources + clip.close() + + return images + + +# Save a list of PIL images to a random temporary directory +def save_images_to_tmp(images: list[Image.Image]): + + # Create a unique temporary directory + unique_dir_name = f"screenshots_{uuid.uuid4()}" + tmp_screenshots_dir = os.path.join(tempfile.gettempdir(), unique_dir_name) + os.makedirs(tmp_screenshots_dir, exist_ok=True) + + for idx, image in enumerate(images): + # Generate a unique image filename using index + image_filename = f"screenshot_{idx}.jpg" + tmp_filepath = os.path.join(tmp_screenshots_dir, image_filename) + image.save(tmp_filepath, format="JPEG") + + print("Saved to " + tmp_screenshots_dir) + + +def extract_tag_content(tag: str, text: str) -> str: + """ + Extracts content for a given tag from the provided text. + + :param tag: The tag to search for. + :param text: The text to search within. + :return: The content found within the tag, if any. + """ + tag_start = f"<{tag}>" + tag_end = f"" + start_idx = text.find(tag_start) + end_idx = text.find(tag_end, start_idx) + if start_idx != -1 and end_idx != -1: + return text[start_idx : end_idx + len(tag_end)] + return "" diff --git a/backend/video_to_app.py b/backend/video_to_app.py index 7fb7c44..597cbbf 100644 --- a/backend/video_to_app.py +++ b/backend/video_to_app.py @@ -1,19 +1,21 @@ # Load environment variables first -import base64 -import shutil + from dotenv import load_dotenv load_dotenv() + +import base64 +import mimetypes import time import subprocess import os -from typing import Union import asyncio from datetime import datetime -from prompts.claude_prompts import VIDEO_PROMPT, VIDEO_PROMPT_ALPINE_JS +from prompts.claude_prompts import VIDEO_PROMPT from utils import pprint_prompt from config import ANTHROPIC_API_KEY +from video.utils import extract_tag_content, assemble_claude_prompt_video from llm import ( MODEL_CLAUDE_OPUS, # MODEL_CLAUDE_SONNET, @@ -28,11 +30,12 @@ OUTPUTS_DIR = "./video_evals/outputs" async def main(): - - video_filename = "mortgage-calculator.mov" - screenshot_interval = 850 + video_filename = "shortest.mov" is_followup = False + if not ANTHROPIC_API_KEY: + raise ValueError("ANTHROPIC_API_KEY is not set") + # Get previous HTML previous_html = "" if is_followup: @@ -44,72 +47,22 @@ async def main(): ], key=os.path.getctime, ) - print(previous_html_file) with open(previous_html_file, "r") as file: previous_html = file.read() - if not ANTHROPIC_API_KEY: - raise ValueError("ANTHROPIC_API_KEY is not set") - - # Create the SCREENSHOTS_DIR if it doesn't exist - if not os.path.exists(SCREENSHOTS_DIR): - os.makedirs(SCREENSHOTS_DIR) - - # Clear out the SCREENSHOTS_DIR before generating new screenshots - for filename in os.listdir(SCREENSHOTS_DIR): - file_path = os.path.join(SCREENSHOTS_DIR, filename) - try: - if os.path.isfile(file_path) or os.path.islink(file_path): - os.unlink(file_path) - elif os.path.isdir(file_path): - shutil.rmtree(file_path) - except Exception as e: - print(f"Failed to delete {file_path}. Reason: {e}") - - # Split the video into screenshots - split_video_into_screenshots( - os.path.join(VIDEO_DIR, video_filename), SCREENSHOTS_DIR, screenshot_interval + video_file = os.path.join(VIDEO_DIR, video_filename) + mime_type = mimetypes.guess_type(video_file)[0] + with open(video_file, "rb") as file: + video_content = file.read() + video_data_url = ( + f"data:{mime_type};base64,{base64.b64encode(video_content).decode('utf-8')}" ) - # Get all the screenshots in the directory - screenshots = [f for f in os.listdir(SCREENSHOTS_DIR) if f.endswith(".jpg")] + prompt_messages = await assemble_claude_prompt_video(video_data_url) - if len(screenshots) > 20: - print(f"Too many screenshots: {len(screenshots)}") - return - - input_image_urls: list[str] = [] - sorted_screenshots = sorted(screenshots, key=lambda x: int(x.split(".")[0])) - for filename in sorted_screenshots: - filepath = os.path.join(SCREENSHOTS_DIR, filename) - data_url = await image_to_data_url(filepath) - print(filename) - input_image_urls.append(data_url) - - # Convert images to the message format for Claude - content_messages: list[dict[str, Union[dict[str, str], str]]] = [] - for url in input_image_urls: - media_type = url.split(";")[0].split(":")[1] - base64_data = url.split(",")[1] - content_messages.append( - { - "type": "image", - "source": { - "type": "base64", - "media_type": media_type, - "data": base64_data, - }, - } - ) - - prompt_messages = [ - { - "role": "user", - "content": content_messages, - }, - # {"role": "assistant", "content": SECOND_MESSAGE}, - # {"role": "user", "content": "continue"}, - ] + # Tell the model to continue + # {"role": "assistant", "content": SECOND_MESSAGE}, + # {"role": "user", "content": "continue"}, if is_followup: prompt_messages += [ @@ -161,66 +114,10 @@ async def main(): with open(output_path, "w") as file: file.write(html_content) + print(f"Output file path: {output_path}") + # Show a notification subprocess.run(["osascript", "-e", 'display notification "Coding Complete"']) -# Extract HTML content from the completion string -def extract_tag_content(tag: str, text: str) -> str: - """ - Extracts content for a given tag from the provided text. - - :param tag: The tag to search for. - :param text: The text to search within. - :return: The content found within the tag, if any. - """ - tag_start = f"<{tag}>" - tag_end = f"" - start_idx = text.find(tag_start) - end_idx = text.find(tag_end, start_idx) - if start_idx != -1 and end_idx != -1: - return text[start_idx : end_idx + len(tag_end)] - return "" - - -def split_video_into_screenshots(video_path: str, output_dir: str, interval: int): - # Create the output directory if it doesn't exist - os.makedirs(output_dir, exist_ok=True) - - # Calculate the number of zeros needed for padding - # duration = float( - # subprocess.check_output( - # [ - # "ffprobe", - # "-v", - # "error", - # "-show_entries", - # "format=duration", - # "-of", - # "default=noprint_wrappers=1:nokey=1", - # video_path, - # ] - # ) - # ) - - # Run the ffmpeg command to extract screenshots - subprocess.call( - [ - "ffmpeg", - "-i", - video_path, - "-vf", - f"fps=1/{interval/1000}", - f"{output_dir}/%d.jpg", - ] - ) - - -# TODO: Don't hard-code the media type -async def image_to_data_url(filepath: str): - with open(filepath, "rb") as image_file: - encoded_string = base64.b64encode(image_file.read()).decode() - return f"data:image/jpeg;base64,{encoded_string}" - - asyncio.run(main()) diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx index 6a2a38c..f0825a8 100644 --- a/frontend/src/App.tsx +++ b/frontend/src/App.tsx @@ -44,6 +44,8 @@ function App() { const [appState, setAppState] = useState(AppState.INITIAL); const [generatedCode, setGeneratedCode] = useState(""); + const [inputMode, setInputMode] = useState<"image" | "video">("image"); + const [referenceImages, setReferenceImages] = useState([]); const [executionConsole, setExecutionConsole] = useState([]); const [updateInstruction, setUpdateInstruction] = useState(""); @@ -140,6 +142,10 @@ function App() { cancelCodeGenerationAndReset(); }; + const shouldDisablePreview = inputMode === "video"; + const previewCode = + shouldDisablePreview && appState === AppState.CODING ? "" : generatedCode; + const cancelCodeGenerationAndReset = () => { // When this is the first version, reset the entire app state if (currentVersion === null) { @@ -219,16 +225,18 @@ function App() { } // Initial version creation - function doCreate(referenceImages: string[]) { + function doCreate(referenceImages: string[], inputMode: "image" | "video") { // Reset any existing state reset(); setReferenceImages(referenceImages); + setInputMode(inputMode); if (referenceImages.length > 0) { doGenerateCode( { generationType: "create", image: referenceImages[0], + inputMode, }, currentVersion ); @@ -261,6 +269,7 @@ function App() { doGenerateCode( { generationType: "update", + inputMode, image: referenceImages[0], resultImage: resultImage, history: updatedHistory, @@ -272,6 +281,7 @@ function App() { doGenerateCode( { generationType: "update", + inputMode, image: referenceImages[0], history: updatedHistory, isImportedFromCode, @@ -519,14 +529,14 @@ function App() { - + - + diff --git a/frontend/src/components/ImageUpload.tsx b/frontend/src/components/ImageUpload.tsx index ff97466..520f595 100644 --- a/frontend/src/components/ImageUpload.tsx +++ b/frontend/src/components/ImageUpload.tsx @@ -51,7 +51,10 @@ type FileWithPreview = { } & File; interface Props { - setReferenceImages: (referenceImages: string[]) => void; + setReferenceImages: ( + referenceImages: string[], + inputMode: "image" | "video" + ) => void; } function ImageUpload({ setReferenceImages }: Props) { @@ -59,11 +62,13 @@ function ImageUpload({ setReferenceImages }: Props) { const { getRootProps, getInputProps, isFocused, isDragAccept, isDragReject } = useDropzone({ maxFiles: 1, - maxSize: 1024 * 1024 * 5, // 5 MB + maxSize: 1024 * 1024 * 20, // 20 MB accept: { "image/png": [".png"], "image/jpeg": [".jpeg"], "image/jpg": [".jpg"], + "video/quicktime": [".mov"], + "video/mp4": [".mp4"], }, onDrop: (acceptedFiles) => { // Set up the preview thumbnail images @@ -78,7 +83,14 @@ function ImageUpload({ setReferenceImages }: Props) { // Convert images to data URLs and set the prompt images state Promise.all(acceptedFiles.map((file) => fileToDataURL(file))) .then((dataUrls) => { - setReferenceImages(dataUrls.map((dataUrl) => dataUrl as string)); + if (dataUrls.length > 0) { + setReferenceImages( + dataUrls.map((dataUrl) => dataUrl as string), + (dataUrls[0] as string).startsWith("data:video") + ? "video" + : "image" + ); + } }) .catch((error) => { toast.error("Error reading files" + error); diff --git a/frontend/src/components/UrlInputSection.tsx b/frontend/src/components/UrlInputSection.tsx index e2137e1..35ad622 100644 --- a/frontend/src/components/UrlInputSection.tsx +++ b/frontend/src/components/UrlInputSection.tsx @@ -6,7 +6,7 @@ import { toast } from "react-hot-toast"; interface Props { screenshotOneApiKey: string | null; - doCreate: (urls: string[]) => void; + doCreate: (urls: string[], inputMode: "image" | "video") => void; } export function UrlInputSection({ doCreate, screenshotOneApiKey }: Props) { @@ -46,7 +46,7 @@ export function UrlInputSection({ doCreate, screenshotOneApiKey }: Props) { } const res = await response.json(); - doCreate([res.url]); + doCreate([res.url], "image"); } catch (error) { console.error(error); toast.error( diff --git a/frontend/src/types.ts b/frontend/src/types.ts index 4308f47..89440fe 100644 --- a/frontend/src/types.ts +++ b/frontend/src/types.ts @@ -27,6 +27,7 @@ export enum AppState { export interface CodeGenerationParams { generationType: "create" | "update"; + inputMode: "image" | "video"; image: string; resultImage?: string; history?: string[];