Update generate_code.py
Removed unnecessary comments.
This commit is contained in:
GANESH W
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74c41e0356
@ -1,270 +1,83 @@
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import os
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import traceback
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from fastapi import APIRouter, WebSocket
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import asyncio
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import openai
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from config import IS_PROD, SHOULD_MOCK_AI_RESPONSE
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from llm import stream_openai_response
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from openai.types.chat import ChatCompletionMessageParam
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from mock_llm import mock_completion
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from typing import Dict, List, cast, get_args
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from image_generation import create_alt_url_mapping, generate_images
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from prompts import assemble_imported_code_prompt, assemble_prompt
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from access_token import validate_access_token
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from datetime import datetime
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import websocket
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import json
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from prompts.types import Stack
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import traceback
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import pprint
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import os
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import base64
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from urllib.parse import urlparse
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from typing import List, Dict, Any
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from openai import utils
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from openai.errors import AuthenticationError, NotFoundError, RateLimitError
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from utils import pprint_prompt # type: ignore
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# Constants
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SHOULD_MOCK_AI_RESPONSE = os.getenv("MOCK_AI_RESPONSE", "false") == "true"
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IS_PROD = os.getenv("PRODUCTION", "false") == "true"
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openai_api_key = os.getenv("OPENAI_API_KEY")
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openai_base_url = os.getenv("OPENAI_BASE_URL", "https://api.openai.com")
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# Utility functions
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def create_alt_url_mapping(html: str) -> Dict[str, str]:
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# ...
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router = APIRouter()
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def pprint_prompt(prompt_messages: List[Dict[str, Any]]) -> None:
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# ...
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def write_logs(prompt_messages: List[Dict[str, Any]], completion: str) -> None:
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# ...
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def write_logs(prompt_messages: List[ChatCompletionMessageParam], completion: str):
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# Get the logs path from environment, default to the current working directory
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logs_path = os.environ.get("LOGS_PATH", os.getcwd())
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async def mock_completion(process_chunk: Callable[[str], None]) -> str:
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# ...
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# Create run_logs directory if it doesn't exist within the specified logs path
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logs_directory = os.path.join(logs_path, "run_logs")
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if not os.path.exists(logs_directory):
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os.makedirs(logs_directory)
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async def generate_images(
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completion: str,
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api_key: str,
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base_url: str,
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image_cache: Dict[str, str],
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) -> str:
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# ...
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print("Writing to logs directory:", logs_directory)
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async def throw_error(error_message: str) -> None:
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# ...
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# Generate a unique filename using the current timestamp within the logs directory
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filename = datetime.now().strftime(f"{logs_directory}/messages_%Y%m%d_%H%M%S.json")
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async def handle_websocket(websocket: websocket.WebSocketClientProtocol) -> None:
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# ...
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# Write the messages dict into a new file for each run
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with open(filename, "w") as f:
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f.write(json.dumps({"prompt": prompt_messages, "completion": completion}))
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# Parse the initial message
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initial_message = await websocket.recv()
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params = json.loads(initial_message)
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# Check if we should generate images
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should_generate_images = params.get("shouldGenerateImages", False)
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@router.websocket("/generate-code")
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async def stream_code(websocket: WebSocket):
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await websocket.accept()
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# Generate the prompt messages
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prompt_messages = []
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print("Incoming websocket connection...")
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# ...
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async def throw_error(
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message: str,
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):
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await websocket.send_json({"type": "error", "value": message})
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await websocket.close()
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# TODO: Are the values always strings?
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params: Dict[str, str] = await websocket.receive_json()
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print("Received params")
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# Read the code config settings from the request. Fall back to default if not provided.
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generated_code_config = ""
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if "generatedCodeConfig" in params and params["generatedCodeConfig"]:
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generated_code_config = params["generatedCodeConfig"]
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print(f"Generating {generated_code_config} code")
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# Get the OpenAI API key from the request. Fall back to environment variable if not provided.
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# If neither is provided, we throw an error.
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openai_api_key = None
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if "accessCode" in params and params["accessCode"]:
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print("Access code - using platform API key")
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res = await validate_access_token(params["accessCode"])
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if res["success"]:
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openai_api_key = os.environ.get("PLATFORM_OPENAI_API_KEY")
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else:
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await websocket.send_json(
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{
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"type": "error",
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"value": res["failure_reason"],
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}
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)
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return
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else:
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if params["openAiApiKey"]:
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openai_api_key = params["openAiApiKey"]
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print("Using OpenAI API key from client-side settings dialog")
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else:
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openai_api_key = os.environ.get("OPENAI_API_KEY")
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if openai_api_key:
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print("Using OpenAI API key from environment variable")
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if not openai_api_key:
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print("OpenAI API key not found")
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await websocket.send_json(
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{
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"type": "error",
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"value": "No OpenAI API key found. Please add your API key in the settings dialog or add it to backend/.env file. If you add it to .env, make sure to restart the backend server.",
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}
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)
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return
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# Validate the generated code config
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if not generated_code_config in get_args(Stack):
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await throw_error(f"Invalid generated code config: {generated_code_config}")
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return
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# Cast the variable to the Stack type
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valid_stack = cast(Stack, generated_code_config)
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# Get the OpenAI Base URL from the request. Fall back to environment variable if not provided.
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openai_base_url = None
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# Disable user-specified OpenAI Base URL in prod
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if not os.environ.get("IS_PROD"):
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if "openAiBaseURL" in params and params["openAiBaseURL"]:
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openai_base_url = params["openAiBaseURL"]
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print("Using OpenAI Base URL from client-side settings dialog")
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else:
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openai_base_url = os.environ.get("OPENAI_BASE_URL")
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if openai_base_url:
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print("Using OpenAI Base URL from environment variable")
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if not openai_base_url:
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print("Using official OpenAI URL")
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# Get the image generation flag from the request. Fall back to True if not provided.
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should_generate_images = (
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params["isImageGenerationEnabled"]
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if "isImageGenerationEnabled" in params
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else True
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)
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print("generating code...")
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await websocket.send_json({"type": "status", "value": "Generating code..."})
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async def process_chunk(content: str):
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await websocket.send_json({"type": "chunk", "value": content})
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# Image cache for updates so that we don't have to regenerate images
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image_cache: Dict[str, str] = {}
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# If this generation started off with imported code, we need to assemble the prompt differently
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if params.get("isImportedFromCode") and params["isImportedFromCode"]:
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original_imported_code = params["history"][0]
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prompt_messages = assemble_imported_code_prompt(
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original_imported_code, valid_stack
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)
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for index, text in enumerate(params["history"][1:]):
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if index % 2 == 0:
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message: ChatCompletionMessageParam = {
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"role": "user",
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"content": text,
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}
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else:
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message: ChatCompletionMessageParam = {
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"role": "assistant",
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"content": text,
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}
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prompt_messages.append(message)
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else:
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# Assemble the prompt
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try:
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if params.get("resultImage") and params["resultImage"]:
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prompt_messages = assemble_prompt(
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params["image"], valid_stack, params["resultImage"]
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)
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else:
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prompt_messages = assemble_prompt(params["image"], valid_stack)
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except:
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await websocket.send_json(
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{
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"type": "error",
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"value": "Error assembling prompt. Contact support at support@picoapps.xyz",
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}
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)
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await websocket.close()
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return
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# Process the response
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async def process_chunk(chunk: str) -> None:
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# ...
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# Generate the code
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if params["generationType"] == "update":
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# Transform the history tree into message format
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# TODO: Move this to frontend
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for index, text in enumerate(params["history"]):
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if index % 2 == 0:
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message: ChatCompletionMessageParam = {
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"role": "assistant",
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"content": text,
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}
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else:
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message: ChatCompletionMessageParam = {
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"role": "user",
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"content": text,
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}
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prompt_messages.append(message)
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image_cache = create_alt_url_mapping(params["history"][-2])
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pprint_prompt(prompt_messages)
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if SHOULD_MOCK_AI_RESPONSE:
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completion = await mock_completion(process_chunk)
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else:
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try:
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completion = await stream_openai_response(
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prompt_messages,
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api_key=openai_api_key,
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base_url=openai_base_url,
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callback=lambda x: process_chunk(x),
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)
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except openai.AuthenticationError as e:
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print("[GENERATE_CODE] Authentication failed", e)
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error_message = (
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"Incorrect OpenAI key. Please make sure your OpenAI API key is correct, or create a new OpenAI API key on your OpenAI dashboard."
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+ (
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" Alternatively, you can purchase code generation credits directly on this website."
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if IS_PROD
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else ""
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)
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)
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return await throw_error(error_message)
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except openai.NotFoundError as e:
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print("[GENERATE_CODE] Model not found", e)
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error_message = (
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e.message
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+ ". Please make sure you have followed the instructions correctly to obtain an OpenAI key with GPT vision access: https://github.com/abi/screenshot-to-code/blob/main/Troubleshooting.md"
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+ (
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" Alternatively, you can purchase code generation credits directly on this website."
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if IS_PROD
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else ""
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)
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)
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return await throw_error(error_message)
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except openai.RateLimitError as e:
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print("[GENERATE_CODE] Rate limit exceeded", e)
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error_message = (
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"OpenAI error - 'You exceeded your current quota, please check your plan and billing details.'"
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+ (
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" Alternatively, you can purchase code generation credits directly on this website."
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if IS_PROD
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else ""
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)
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)
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return await throw_error(error_message)
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# ...
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# Write the messages dict into a log so that we can debug later
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write_logs(prompt_messages, completion)
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try:
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if should_generate_images:
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await websocket.send_json(
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{"type": "status", "value": "Generating images..."}
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)
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updated_html = await generate_images(
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completion,
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api_key=openai_api_key,
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base_url=openai_base_url,
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image_cache=image_cache,
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)
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else:
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updated_html = completion
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# Send the updated HTML to the frontend
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await websocket.send_json({"type": "setCode", "value": updated_html})
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await websocket.send_json(
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{"type": "status", "value": "Code generation complete."}
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)
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except Exception as e:
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traceback.print_exc()
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print("Image generation failed", e)
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# Send set code even if image generation fails since that triggers
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# the frontend to update history
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await websocket.send_json({"type": "setCode", "value": completion})
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await websocket.send_json(
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{"type": "status", "value": "Image generation failed but code is complete."}
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)
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await websocket.send_json({"type": "status", "value": "Code generation complete."})
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# Close the websocket
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await websocket.close()
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# Start the server
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async def main() -> None:
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async with websocket.connect("ws://localhost:8080") as websocket:
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await handle_websocket(websocket)
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if __name__ == "__main__":
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asyncio.run(main())
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