diff --git a/README.md b/README.md index 9d6fba71..839bf999 100644 --- a/README.md +++ b/README.md @@ -42,17 +42,18 @@ We also just added experimental support for taking a video/screen recording of a ## 🛠 Getting Started -The app has a React/Vite frontend and a FastAPI backend. +### 使用AWS Bedrock Claude 3/3.5 sonnet注意事项 +- 如果使用Bedrock Claude 3/3.5需要在运行机器上安装 https://aws.amazon.com/cn/cli/， 并配置aws iam 账号的ak sk，另外还需要开通该账号Bedrock Claude 3 访问的权限。 +- 如果使用Bedrock Claude 3/3.5，则无须配置OPENAI_API_KEY 或者 ANTHROPIC_API_KEY 到.env中 -Keys needed: +The app has a React/Vite frontend and a FastAPI backend. You will need an OpenAI API key with access to the GPT-4 Vision API or an Anthropic key if you want to use Claude Sonnet, or for experimental video support. -* [OpenAI API key with access to GPT-4](https://github.com/abi/screenshot-to-code/blob/main/Troubleshooting.md) -* Anthropic key (optional) - only if you want to use Claude Sonnet, or for experimental video support. Run the backend (I use Poetry for package management - `pip install poetry` if you don't have it): ```bash cd backend +# optional echo "OPENAI_API_KEY=sk-your-key" > .env poetry install poetry shell diff --git a/backend/llm.py b/backend/llm.py index 51b7efe1..1b0cfaa4 100644 --- a/backend/llm.py +++ b/backend/llm.py @@ -5,9 +5,27 @@ from openai.types.chat import ChatCompletionMessageParam, ChatCompletionChunk from config import IS_DEBUG_ENABLED from debug.DebugFileWriter import DebugFileWriter - +# import boto3 from utils import pprint_prompt - +import json +import os +import sys +import boto3 +import base64 +import requests +import time +import pprint +from datetime import datetime +from botocore.config import Config + +#get modelARN +REGION = os.environ.get('region','us-east-1') +PROFILE = os.environ.get('profile', 'default') +session = boto3.Session(profile_name=PROFILE,region_name=REGION) +bedrock_runtime = session.client( + service_name="bedrock-runtime", + region_name=REGION +) # Actual model versions that are passed to the LLMs and stored in our logs class Llm(Enum): @@ -15,17 +33,23 @@ class Llm(Enum): GPT_4_TURBO_2024_04_09 = "gpt-4-turbo-2024-04-09" GPT_4O_2024_05_13 = "gpt-4o-2024-05-13" CLAUDE_3_SONNET = "claude-3-sonnet-20240229" + CLAUDE_3_5_SONNET = "claude-3-5-sonnet-20240620" CLAUDE_3_OPUS = "claude-3-opus-20240229" CLAUDE_3_HAIKU = "claude-3-haiku-20240307" CLAUDE_3_5_SONNET_2024_06_20 = "claude-3-5-sonnet-20240620" +BEDROCK_LLM_MODELID_LIST = {Llm.CLAUDE_3_5_SONNET: 'anthropic.claude-3-sonnet-20240229-v1:0', + Llm.CLAUDE_3_SONNET: 'anthropic.claude-3-5-sonnet-20240620-v1:0',} + # Will throw errors if you send a garbage string def convert_frontend_str_to_llm(frontend_str: str) -> Llm: if frontend_str == "gpt_4_vision": return Llm.GPT_4_VISION elif frontend_str == "claude_3_sonnet": return Llm.CLAUDE_3_SONNET + elif frontend_str == "claude_3_5_sonnet": + return Llm.CLAUDE_3_5_SONNET else: return Llm(frontend_str) @@ -38,7 +62,7 @@ async def stream_openai_response( model: Llm, ) -> str: client = AsyncOpenAI(api_key=api_key, base_url=base_url) - + print(f"--stream_openai_response--{model}") # Base parameters params = { "model": model.value, @@ -75,16 +99,15 @@ async def stream_openai_response( return full_response -# TODO: Have a seperate function that translates OpenAI messages to Claude messages async def stream_claude_response( messages: List[ChatCompletionMessageParam], api_key: str, callback: Callable[[str], Awaitable[None]], model: Llm, ) -> str: - - client = AsyncAnthropic(api_key=api_key) - + print(f"--stream_openai_response--{model}") + # client = AsyncAnthropic(api_key=api_key) + modelId = BEDROCK_LLM_MODELID_LIST[model] # Base parameters max_tokens = 4096 temperature = 0.0 @@ -112,28 +135,44 @@ async def stream_claude_response( content["source"] = { "type": "base64", "media_type": media_type, - "data": base64_data, + "data": base64_data } - + payload = { + "modelId": modelId, + "contentType": "application/json", + "accept": "application/json", + "body": { + "anthropic_version": "bedrock-2023-05-31", + "max_tokens": max_tokens, + "messages": claude_messages, + "temperature":temperature, + "system":system_prompt, + } + } + + # Convert the payload to bytes + body_bytes = json.dumps(payload['body']).encode('utf-8') + + # Invoke the model + response = bedrock_runtime.invoke_model_with_response_stream( + body=body_bytes, modelId=payload['modelId'], accept=payload['accept'], contentType=payload['contentType'] + ) + stream = response.get('body') + chunk_obj = {} # Stream Claude response - async with client.messages.stream( - model=model.value, - max_tokens=max_tokens, - temperature=temperature, - system=system_prompt, - messages=claude_messages, # type: ignore - ) as stream: - async for text in stream.text_stream: - await callback(text) - + response_text = '' + if stream: + for event in stream: + chunk = event.get('chunk') + if chunk: + chunk_obj = json.loads(chunk.get('bytes').decode()) + if chunk_obj['delta']['type'] == 'text_delta': + response_text += chunk_obj['delta']['text'] + await callback(chunk_obj['delta']['text']) + # Return final message - response = await stream.get_final_message() - - # Close the Anthropic client - await client.close() - - return response.content[0].text - + response = response_text + return response async def stream_claude_response_native( system_prompt: str, @@ -141,10 +180,11 @@ async def stream_claude_response_native( api_key: str, callback: Callable[[str], Awaitable[None]], include_thinking: bool = False, - model: Llm = Llm.CLAUDE_3_OPUS, + model: Llm = Llm.CLAUDE_3_5_SONNET, ) -> str: - client = AsyncAnthropic(api_key=api_key) + # client = AsyncAnthropic(api_key=api_key) + modelId = BEDROCK_LLM_MODELID_LIST[model] # Base model parameters max_tokens = 4096 @@ -171,22 +211,52 @@ async def stream_claude_response_native( else messages ) - pprint_prompt(messages_to_send) - - async with client.messages.stream( - model=model.value, - max_tokens=max_tokens, - temperature=temperature, - system=system_prompt, - messages=messages_to_send, # type: ignore - ) as stream: - async for text in stream.text_stream: - print(text, end="", flush=True) - full_stream += text - await callback(text) - - response = await stream.get_final_message() - response_text = response.content[0].text + # pprint_prompt(messages_to_send) + + payload = { + "modelId": modelId, + "contentType": "application/json", + "accept": "application/json", + "body": { + "anthropic_version": "bedrock-2023-05-31", + "max_tokens": max_tokens, + "messages": messages_to_send, + "temperature":temperature, + "system":system_prompt, + } + } + # Convert the payload to bytes + body_bytes = json.dumps(payload['body']).encode('utf-8') + + # Invoke the model + response = bedrock_runtime.invoke_model_with_response_stream( + body=body_bytes, modelId=payload['modelId'], accept=payload['accept'], contentType=payload['contentType'] + ) + stream = response.get('body') + chunk_obj = {} + # Stream Claude response + response_text = '' + input_tokens= 0 + output_tokens = 0 + if stream: + for event in stream: + chunk = event.get('chunk') + if chunk: + chunk_obj = json.loads(chunk.get('bytes').decode()) + # print(chunk_obj) + if chunk_obj['type'] == 'message_delta': + print(f"\nStop reason: {chunk_obj['delta']['stop_reason']}") + print(f"Stop sequence: {chunk_obj['delta']['stop_sequence']}") + print(f"Output tokens: {chunk_obj['usage']['output_tokens']}") + output_tokens = chunk_obj['usage']['output_tokens'] + + if chunk_obj['type'] == 'content_block_delta': + if chunk_obj['delta']['type'] == 'text_delta': + print(chunk_obj['delta']['text'], end="") + response_text += chunk_obj['delta']['text'] + await callback(chunk_obj['delta']['text']) + + print(response_text) # Write each pass's code to .html file and thinking to .txt file if IS_DEBUG_ENABLED: @@ -201,7 +271,7 @@ async def stream_claude_response_native( # Set up messages array for next pass messages += [ - {"role": "assistant", "content": str(prefix) + response.content[0].text}, + {"role": "assistant", "content": str(prefix) + response_text}, { "role": "user", "content": "You've done a good job with a first draft. Improve this further based on the original instructions so that the app is fully functional and looks like the original video of the app we're trying to replicate.", @@ -209,11 +279,12 @@ async def stream_claude_response_native( ] print( - f"Token usage: Input Tokens: {response.usage.input_tokens}, Output Tokens: {response.usage.output_tokens}" + f"Token usage: Input Tokens: {input_tokens}, Output Tokens: {output_tokens}" ) + print(messages[-2:]) # Close the Anthropic client - await client.close() + # await client.close() if IS_DEBUG_ENABLED: debug_file_writer.write_to_file("full_stream.txt", full_stream) @@ -221,4 +292,4 @@ async def stream_claude_response_native( if not response: raise Exception("No HTML response found in AI response") else: - return response.content[0].text + return response_text diff --git a/backend/poetry.lock b/backend/poetry.lock index d6b5d027..2ec92670 100644 --- a/backend/poetry.lock +++ b/backend/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. [[package]] name = "anthropic" @@ -67,6 +67,44 @@ charset-normalizer = ["charset-normalizer"] html5lib = ["html5lib"] lxml = ["lxml"] +[[package]] +name = "boto3" +version = "1.34.108" +description = "The AWS SDK for Python" +optional = false +python-versions = ">=3.8" +files = [ + {file = "boto3-1.34.108-py3-none-any.whl", hash = "sha256:3601267d76cac17f1d4595c3d8d968dc15be074b79bfa3985187a02b328a0a5f"}, + {file = "boto3-1.34.108.tar.gz", hash = "sha256:677723295151d29ff9b363598a20c1997c4e2af7e50669d9e428b757fe586a10"}, +] + +[package.dependencies] +botocore = ">=1.34.108,<1.35.0" +jmespath = ">=0.7.1,<2.0.0" +s3transfer = ">=0.10.0,<0.11.0" + +[package.extras] +crt = ["botocore[crt] (>=1.21.0,<2.0a0)"] + +[[package]] +name = "botocore" +version = "1.34.108" +description = "Low-level, data-driven core of boto 3." +optional = false +python-versions = ">=3.8" +files = [ + {file = "botocore-1.34.108-py3-none-any.whl", hash = "sha256:b1b9d00804267669c5fcc36489269f7e9c43580c30f0885fbf669cf73cec720b"}, + {file = "botocore-1.34.108.tar.gz", hash = "sha256:384c9408c447631475dc41fdc9bf2e0f30c29c420d96bfe8b468bdc2bace3e13"}, +] + +[package.dependencies] +jmespath = ">=0.7.1,<2.0.0" +python-dateutil = ">=2.1,<3.0.0" +urllib3 = {version = ">=1.25.4,<2.2.0 || >2.2.0,<3", markers = "python_version >= \"3.10\""} + +[package.extras] +crt = ["awscrt (==0.20.9)"] + [[package]] name = "certifi" version = "2024.2.2" @@ -248,13 +286,13 @@ files = [ [[package]] name = "exceptiongroup" -version = "1.2.0" +version = "1.2.1" description = "Backport of PEP 654 (exception groups)" optional = false python-versions = ">=3.7" files = [ - {file = "exceptiongroup-1.2.0-py3-none-any.whl", hash = "sha256:4bfd3996ac73b41e9b9628b04e079f193850720ea5945fc96a08633c66912f14"}, - {file = "exceptiongroup-1.2.0.tar.gz", hash = "sha256:91f5c769735f051a4290d52edd0858999b57e5876e9f85937691bd4c9fa3ed68"}, + {file = 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(!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "requests"] +test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask-expr", "dask[dataframe,test]", "moto[server] (>4,<5)", "pytest-timeout", "xarray"] +test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"] tqdm = ["tqdm"] [[package]] @@ -345,13 +386,13 @@ files = [ [[package]] name = "httpcore" -version = "1.0.4" +version = "1.0.5" description = "A minimal low-level HTTP client." optional = false python-versions = ">=3.8" files = [ - {file = "httpcore-1.0.4-py3-none-any.whl", hash = "sha256:ac418c1db41bade2ad53ae2f3834a3a0f5ae76b56cf5aa497d2d033384fc7d73"}, - {file = "httpcore-1.0.4.tar.gz", hash = "sha256:cb2839ccfcba0d2d3c1131d3c3e26dfc327326fbe7a5dc0dbfe9f6c9151bb022"}, + {file = "httpcore-1.0.5-py3-none-any.whl", hash = "sha256:421f18bac248b25d310f3cacd198d55b8e6125c107797b609ff9b7a6ba7991b5"}, + {file = "httpcore-1.0.5.tar.gz", hash = "sha256:34a38e2f9291467ee3b44e89dd52615370e152954ba21721378a87b2960f7a61"}, ] [package.dependencies] @@ -362,7 +403,7 @@ h11 = ">=0.13,<0.15" asyncio = ["anyio (>=4.0,<5.0)"] http2 = ["h2 (>=3,<5)"] socks = ["socksio (==1.*)"] -trio = ["trio (>=0.22.0,<0.25.0)"] +trio = ["trio (>=0.22.0,<0.26.0)"] [[package]] name = "httpx" @@ -390,13 +431,13 @@ socks = ["socksio (==1.*)"] [[package]] name = "huggingface-hub" -version = "0.21.4" +version = "0.23.0" description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub" optional = false python-versions = ">=3.8.0" files = [ - {file = "huggingface_hub-0.21.4-py3-none-any.whl", hash = "sha256:df37c2c37fc6c82163cdd8a67ede261687d80d1e262526d6c0ce73b6b3630a7b"}, - {file = "huggingface_hub-0.21.4.tar.gz", hash = "sha256:e1f4968c93726565a80edf6dc309763c7b546d0cfe79aa221206034d50155531"}, + {file = "huggingface_hub-0.23.0-py3-none-any.whl", hash = "sha256:075c30d48ee7db2bba779190dc526d2c11d422aed6f9044c5e2fdc2c432fdb91"}, + {file = "huggingface_hub-0.23.0.tar.gz", hash = "sha256:7126dedd10a4c6fac796ced4d87a8cf004efc722a5125c2c09299017fa366fa9"}, ] [package.dependencies] @@ -409,27 +450,28 @@ tqdm = ">=4.42.1" typing-extensions = ">=3.7.4.3" [package.extras] -all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "mypy (==1.5.1)", "numpy", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.1.3)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"] +all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.3.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"] cli = ["InquirerPy (==0.3.4)"] -dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "mypy (==1.5.1)", "numpy", "pydantic (>1.1,<2.0)", "pydantic (>1.1,<3.0)", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.1.3)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", 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= '^1.34.108' +botocore = '^1.34.108' [tool.poetry.group.dev.dependencies] pytest = "^7.4.3" diff --git a/backend/routes/generate_code.py b/backend/routes/generate_code.py index 362f7425..554d9945 100644 --- a/backend/routes/generate_code.py +++ b/backend/routes/generate_code.py @@ -230,30 +230,31 @@ async def process_chunk(content: str): else: try: if validated_input_mode == "video": - if not anthropic_api_key: - await throw_error( - "Video only works with Anthropic models. No Anthropic API key found. Please add the environment variable ANTHROPIC_API_KEY to backend/.env or in the settings dialog" - ) - raise Exception("No Anthropic key") + + # if not ANTHROPIC_API_KEY: + # await throw_error( + # "Video only works with Anthropic models. 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=Llm.CLAUDE_3_OPUS, + model=Llm.CLAUDE_3_5_SONNET, include_thinking=True, ) - exact_llm_version = Llm.CLAUDE_3_OPUS + exact_llm_version = Llm.CLAUDE_3_5_SONNET elif ( code_generation_model == Llm.CLAUDE_3_SONNET or code_generation_model == Llm.CLAUDE_3_5_SONNET_2024_06_20 ): - if not anthropic_api_key: - await throw_error( - "No Anthropic API key found. Please add the environment variable ANTHROPIC_API_KEY to backend/.env or in the settings dialog" - ) - raise Exception("No Anthropic key") +# if not anthropic_api_key: +# await throw_error( +# "No Anthropic API key found. Please add the environment variable ANTHROPIC_API_KEY to backend/.env or in the settings dialog" +# ) +# raise Exception("No Anthropic key") completion = await stream_claude_response( prompt_messages, # type: ignore diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx index 82bd0a07..3ba2eab7 100644 --- a/frontend/src/App.tsx +++ b/frontend/src/App.tsx @@ -437,11 +437,11 @@ function App() { {showBetterModelMessage && (

- Now supporting GPT-4o and Claude Sonnet 3.5. Higher quality and + Now supporting Claude Sonnet 3.5. Higher quality and 2x faster. Give it a try!

- )} + )} {appState !== AppState.CODE_READY && } diff --git a/frontend/src/lib/models.ts b/frontend/src/lib/models.ts index 250953be..6f66a3d6 100644 --- a/frontend/src/lib/models.ts +++ b/frontend/src/lib/models.ts @@ -1,20 +1,22 @@ // Keep in sync with backend (llm.py) // Order here matches dropdown order export enum CodeGenerationModel { - GPT_4O_2024_05_13 = "gpt-4o-2024-05-13", CLAUDE_3_5_SONNET_2024_06_20 = "claude-3-5-sonnet-20240620", + // CLAUDE_3_5_SONNET = "claude_3_5_sonnet", + CLAUDE_3_SONNET = "claude_3_sonnet", + GPT_4O_2024_05_13 = "gpt-4o-2024-05-13", GPT_4_TURBO_2024_04_09 = "gpt-4-turbo-2024-04-09", GPT_4_VISION = "gpt_4_vision", - CLAUDE_3_SONNET = "claude_3_sonnet", } // Will generate a static error if a model in the enum above is not in the descriptions export const CODE_GENERATION_MODEL_DESCRIPTIONS: { [key in CodeGenerationModel]: { name: string; inBeta: boolean }; } = { - "gpt-4o-2024-05-13": { name: "GPT-4o 🌟", inBeta: false }, "claude-3-5-sonnet-20240620": { name: "Claude 3.5 Sonnet 🌟", inBeta: false }, + "gpt-4o-2024-05-13": { name: "GPT-4o 🌟", inBeta: false }, "gpt-4-turbo-2024-04-09": { name: "GPT-4 Turbo (Apr 2024)", inBeta: false }, gpt_4_vision: { name: "GPT-4 Vision (Nov 2023)", inBeta: false }, claude_3_sonnet: { name: "Claude 3 Sonnet", inBeta: false }, + // claude_3_5_sonnet: { name: "Claude 3.5 Sonnet", inBeta: false }, };