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129 lines
3.3 KiB
Python
129 lines
3.3 KiB
Python
from typing import Dict, List, TypedDict
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import re
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import uvicorn
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import torch
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from fastapi import FastAPI
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from fastapi.staticfiles import StaticFiles
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from pydantic import BaseModel
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from env import settings
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from core.prompts.error import ERROR_PROMPT
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from core.agents.manager import AgentManager
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from core.tools.base import BaseToolSet
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from core.tools.terminal import Terminal
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from core.tools.editor import CodeEditor
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from core.tools.cpu import (
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RequestsGet,
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WineDB,
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ExitConversation,
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)
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from core.tools.gpu import (
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ImageEditing,
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InstructPix2Pix,
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Text2Image,
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VisualQuestionAnswering,
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)
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from core.handlers.base import BaseHandler, FileHandler, FileType
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from core.handlers.image import ImageCaptioning
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from core.handlers.dataframe import CsvToDataframe
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from core.upload import StaticUploader
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from logger import logger
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app = FastAPI()
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app.mount("/static", StaticFiles(directory=StaticUploader.STATIC_DIR), name="static")
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uploader = StaticUploader.from_settings(settings)
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use_gpu = settings["USE_GPU"] and torch.cuda.is_available()
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toolsets: List[BaseToolSet] = [
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Terminal(),
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CodeEditor(),
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RequestsGet(),
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ExitConversation(),
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]
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if use_gpu:
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toolsets.extend(
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[
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Text2Image("cuda"),
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ImageEditing("cuda"),
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InstructPix2Pix("cuda"),
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VisualQuestionAnswering("cuda"),
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]
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)
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handlers: Dict[FileType, BaseHandler] = {}
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handlers[FileType.DATAFRAME] = CsvToDataframe()
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if use_gpu:
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handlers[FileType.IMAGE] = ImageCaptioning("cuda")
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if settings["WINEDB_HOST"] and settings["WINEDB_PASSWORD"]:
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toolsets.append(WineDB())
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agent_manager = AgentManager.create(toolsets=toolsets)
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file_handler = FileHandler(handlers=handlers)
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class Request(BaseModel):
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key: str
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query: str
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files: List[str]
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class Response(TypedDict):
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response: str
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files: List[str]
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@app.get("/")
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async def index():
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return {"message": f"Hello World. I'm {settings['BOT_NAME']}."}
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@app.post("/command")
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async def command(request: Request) -> Response:
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query = request.query
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files = request.files
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session = request.key
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logger.info("=============== Running =============")
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logger.info(f"Query: {query}, Files: {files}")
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executor = agent_manager.get_or_create_executor(session)
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logger.info(f"======> Previous memory:\n\t{executor.memory}")
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promptedQuery = "\n".join([file_handler.handle(file) for file in files])
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promptedQuery += query
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logger.info(f"======> Prompted Text:\n\t{promptedQuery}")
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try:
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res = executor({"input": promptedQuery})
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except Exception as e:
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logger.error(f"error while processing request: {str(e)}")
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try:
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res = executor(
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{
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"input": ERROR_PROMPT.format(promptedQuery=promptedQuery, e=str(e)),
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}
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)
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except Exception as e:
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return {"response": str(e), "files": []}
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images = re.findall("(image/\S*png)", res["output"])
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dataframes = re.findall("(dataframe/\S*csv)", res["output"])
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return {
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"response": res["output"],
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"files": [uploader.upload(image) for image in images]
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+ [uploader.upload(dataframe) for dataframe in dataframes],
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}
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def serve():
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uvicorn.run("api.main:app", host="0.0.0.0", port=settings["PORT"])
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