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import os
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import traceback
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import asyncio
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from collections import defaultdict
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import discord
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import aiofiles
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from functools import partial
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from typing import List, Optional
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from pathlib import Path
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from datetime import date
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from langchain import OpenAI
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from gpt_index.readers import YoutubeTranscriptReader
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from gpt_index.readers.schema.base import Document
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from gpt_index import (
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GPTSimpleVectorIndex,
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SimpleDirectoryReader,
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QuestionAnswerPrompt,
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BeautifulSoupWebReader,
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GPTListIndex,
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QueryMode,
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GPTTreeIndex,
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GoogleDocsReader,
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MockLLMPredictor,
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LLMPredictor,
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QueryConfig,
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PromptHelper,
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IndexStructType, OpenAIEmbedding,
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)
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from gpt_index.readers.web import DEFAULT_WEBSITE_EXTRACTOR
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from gpt_index.composability import ComposableGraph
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from services.environment_service import EnvService, app_root_path
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SHORT_TO_LONG_CACHE = {}
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def get_and_query(user_id, index_storage, query, response_mode, nodes, llm_predictor, embed_model):
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index: [GPTSimpleVectorIndex, ComposableGraph] = index_storage[
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user_id
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].get_index_or_throw()
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prompthelper = PromptHelper(4096, 500, 20)
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if isinstance(index, GPTTreeIndex):
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response = index.query(
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query,
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verbose=True,
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child_branch_factor=2,
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llm_predictor=llm_predictor,
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embed_model=embed_model,
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prompt_helper=prompthelper,
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)
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else:
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response = index.query(
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query,
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response_mode=response_mode,
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verbose=True,
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llm_predictor=llm_predictor,
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embed_model=embed_model,
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similarity_top_k=nodes,
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prompt_helper=prompthelper,
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)
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return response
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class IndexData:
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def __init__(self):
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self.queryable_index = None
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self.individual_indexes = []
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# A safety check for the future
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def get_index_or_throw(self):
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if not self.queryable():
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raise Exception(
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"An index access was attempted before an index was created. This is a programmer error, please report this to the maintainers."
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)
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return self.queryable_index
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def queryable(self):
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return self.queryable_index is not None
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def has_indexes(self, user_id):
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try:
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return len(os.listdir(f"{app_root_path()}/indexes/{user_id}")) > 0
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except Exception:
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return False
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def add_index(self, index, user_id, file_name):
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self.individual_indexes.append(index)
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self.queryable_index = index
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# Create a folder called "indexes/{USER_ID}" if it doesn't exist already
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Path(f"{app_root_path()}/indexes/{user_id}").mkdir(parents=True, exist_ok=True)
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# Save the index to file under the user id
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index.save_to_disk(
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app_root_path()
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/ "indexes"
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/ f"{str(user_id)}"
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/ f"{file_name}_{date.today().month}_{date.today().day}.json"
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)
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def reset_indexes(self, user_id):
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self.individual_indexes = []
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self.queryable_index = None
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# Delete the user indexes
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try:
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# First, clear all the files inside it
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for file in os.listdir(f"{app_root_path()}/indexes/{user_id}"):
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os.remove(f"{app_root_path()}/indexes/{user_id}/{file}")
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except Exception:
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traceback.print_exc()
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class Index_handler:
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def __init__(self, bot, usage_service):
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self.bot = bot
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self.openai_key = os.getenv("OPENAI_TOKEN")
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self.index_storage = defaultdict(IndexData)
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self.loop = asyncio.get_running_loop()
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self.usage_service = usage_service
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self.qaprompt = QuestionAnswerPrompt(
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"Context information is below. The text '<|endofstatement|>' is used to separate chat entries and make it easier for you to understand the context\n"
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"---------------------\n"
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"{context_str}"
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"\n---------------------\n"
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"Never say '<|endofstatement|>'\n"
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"Given the context information and not prior knowledge, "
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"answer the question: {query_str}\n"
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)
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# TODO We need to do predictions below for token usage.
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def index_file(self, file_path) -> GPTSimpleVectorIndex:
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document = SimpleDirectoryReader(file_path).load_data()
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index = GPTSimpleVectorIndex(document)
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return index
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def index_gdoc(self, doc_id) -> GPTSimpleVectorIndex:
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document = GoogleDocsReader().load_data(doc_id)
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index = GPTSimpleVectorIndex(document)
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return index
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def index_youtube_transcript(self, link):
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documents = YoutubeTranscriptReader().load_data(ytlinks=[link])
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index = GPTSimpleVectorIndex(
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documents,
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)
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return index
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def index_load_file(self, file_path) -> [GPTSimpleVectorIndex, ComposableGraph]:
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if "composed_deep" in str(file_path):
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index = GPTTreeIndex.load_from_disk(file_path)
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else:
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index = GPTSimpleVectorIndex.load_from_disk(file_path)
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return index
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def index_discord(self, document) -> GPTSimpleVectorIndex:
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index = GPTSimpleVectorIndex(
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document,
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)
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return index
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def index_webpage(self, url) -> GPTSimpleVectorIndex:
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documents = BeautifulSoupWebReader(
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website_extractor=DEFAULT_WEBSITE_EXTRACTOR
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).load_data(urls=[url])
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index = GPTSimpleVectorIndex(documents)
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return index
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def reset_indexes(self, user_id):
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self.index_storage[user_id].reset_indexes(user_id)
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async def set_file_index(
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self, ctx: discord.ApplicationContext, file: discord.Attachment, user_api_key
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):
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if not user_api_key:
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os.environ["OPENAI_API_KEY"] = self.openai_key
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else:
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os.environ["OPENAI_API_KEY"] = user_api_key
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try:
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print(file.content_type)
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if file.content_type.startswith("text/plain"):
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suffix = ".txt"
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elif file.content_type.startswith("application/pdf"):
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suffix = ".pdf"
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# Allow for images too
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elif file.content_type.startswith("image/png"):
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suffix = ".png"
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elif file.content_type.startswith("image/"):
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suffix = ".jpg"
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elif "csv" in file.content_type:
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suffix = ".csv"
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elif "vnd." in file.content_type:
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suffix = ".pptx"
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# Catch all audio files and suffix with "mp3"
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elif file.content_type.startswith("audio/"):
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suffix = ".mp3"
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# Catch video files
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elif file.content_type.startswith("video/"):
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pass # No suffix change
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else:
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await ctx.respond(
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"Only accepts text, pdf, images, spreadheets, powerpoint, and audio/video files."
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)
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return
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async with aiofiles.tempfile.TemporaryDirectory() as temp_path:
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async with aiofiles.tempfile.NamedTemporaryFile(
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suffix=suffix, dir=temp_path, delete=False
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) as temp_file:
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await file.save(temp_file.name)
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index = await self.loop.run_in_executor(
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None, partial(self.index_file, temp_path)
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)
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file_name = file.filename
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self.index_storage[ctx.user.id].add_index(index, ctx.user.id, file_name)
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await ctx.respond("Index added to your indexes.")
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except Exception:
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await ctx.respond("Failed to set index")
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traceback.print_exc()
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async def set_link_index(
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self, ctx: discord.ApplicationContext, link: str, user_api_key
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):
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if not user_api_key:
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os.environ["OPENAI_API_KEY"] = self.openai_key
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else:
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os.environ["OPENAI_API_KEY"] = user_api_key
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# TODO Link validation
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try:
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# Check if the link contains youtube in it
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if "youtube" in link:
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index = await self.loop.run_in_executor(
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None, partial(self.index_youtube_transcript, link)
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)
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else:
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index = await self.loop.run_in_executor(
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None, partial(self.index_webpage, link)
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)
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# Make the url look nice, remove https, useless stuff, random characters
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file_name = (
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link.replace("https://", "")
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.replace("http://", "")
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.replace("www.", "")
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.replace("/", "_")
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.replace("?", "_")
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.replace("&", "_")
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.replace("=", "_")
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.replace("-", "_")
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.replace(".", "_")
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)
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self.index_storage[ctx.user.id].add_index(index, ctx.user.id, file_name)
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except Exception:
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await ctx.respond("Failed to set index")
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traceback.print_exc()
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await ctx.respond("Index set")
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async def set_discord_index(
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self,
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ctx: discord.ApplicationContext,
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channel: discord.TextChannel,
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user_api_key,
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):
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if not user_api_key:
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os.environ["OPENAI_API_KEY"] = self.openai_key
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else:
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os.environ["OPENAI_API_KEY"] = user_api_key
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try:
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document = await self.load_data(
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channel_ids=[channel.id], limit=1000, oldest_first=False
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)
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index = await self.loop.run_in_executor(
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None, partial(self.index_discord, document)
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)
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self.index_storage[ctx.user.id].add_index(index, ctx.user.id, channel.name)
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await ctx.respond("Index set")
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except Exception:
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await ctx.respond("Failed to set index")
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traceback.print_exc()
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async def load_index(
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self, ctx: discord.ApplicationContext, index, server, user_api_key
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):
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if not user_api_key:
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os.environ["OPENAI_API_KEY"] = self.openai_key
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else:
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os.environ["OPENAI_API_KEY"] = user_api_key
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try:
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if server:
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index_file = EnvService.find_shared_file(
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f"indexes/{ctx.guild.id}/{index}"
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)
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else:
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index_file = EnvService.find_shared_file(
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f"indexes/{ctx.user.id}/{index}"
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)
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index = await self.loop.run_in_executor(
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None, partial(self.index_load_file, index_file)
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)
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self.index_storage[ctx.user.id].queryable_index = index
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await ctx.respond("Loaded index")
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except Exception as e:
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await ctx.respond(e)
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async def compose_indexes(self, user_id, indexes, name, deep_compose):
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# Load all the indexes first
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index_objects = []
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for _index in indexes:
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index_file = EnvService.find_shared_file(f"indexes/{user_id}/{_index}")
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index = await self.loop.run_in_executor(
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None, partial(self.index_load_file, index_file)
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)
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index_objects.append(index)
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# For each index object, add its documents to a GPTTreeIndex
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if deep_compose:
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documents = []
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for _index in index_objects:
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[
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documents.append(_index.docstore.get_document(doc_id))
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for doc_id in [docmeta for docmeta in _index.docstore.docs.keys()]
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if isinstance(_index.docstore.get_document(doc_id), Document)
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]
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llm_predictor = LLMPredictor(llm=OpenAI(model_name="text-davinci-003"))
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embedding_model = OpenAIEmbedding()
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tree_index = GPTTreeIndex(documents=documents, llm_predictor=llm_predictor, embed_model=embedding_model)
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await self.usage_service.update_usage(llm_predictor.last_token_usage+embedding_model.last_token_usage)
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# Now we have a list of tree indexes, we can compose them
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if not name:
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name = (
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f"composed_deep_index_{date.today().month}_{date.today().day}.json"
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)
|
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# Save the composed index
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tree_index.save_to_disk(f"indexes/{user_id}/{name}.json")
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self.index_storage[user_id].queryable_index = tree_index
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else:
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documents = []
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for _index in index_objects:
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[
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documents.append(_index.docstore.get_document(doc_id))
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for doc_id in [docmeta for docmeta in _index.docstore.docs.keys()]
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if isinstance(_index.docstore.get_document(doc_id), Document)
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]
|
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embedding_model = OpenAIEmbedding()
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|
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# Add everything into a simple vector index
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simple_index = GPTSimpleVectorIndex(documents=documents, embed_model=embedding_model)
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await self.usage_service.update_usage(embedding_model.last_token_usage)
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|
|
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|
if not name:
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name = f"composed_index_{date.today().month}_{date.today().day}.json"
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|
|
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# Save the composed index
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|
|
simple_index.save_to_disk(f"indexes/{user_id}/{name}.json")
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|
|
self.index_storage[user_id].queryable_index = simple_index
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|
|
async def backup_discord(self, ctx: discord.ApplicationContext, user_api_key):
|
|
|
|
if not user_api_key:
|
|
|
|
os.environ["OPENAI_API_KEY"] = self.openai_key
|
|
|
|
else:
|
|
|
|
os.environ["OPENAI_API_KEY"] = user_api_key
|
|
|
|
|
|
|
|
try:
|
|
|
|
channel_ids: List[int] = []
|
|
|
|
for c in ctx.guild.text_channels:
|
|
|
|
channel_ids.append(c.id)
|
|
|
|
document = await self.load_data(
|
|
|
|
channel_ids=channel_ids, limit=3000, oldest_first=False
|
|
|
|
)
|
|
|
|
index = await self.loop.run_in_executor(
|
|
|
|
None, partial(self.index_discord, document)
|
|
|
|
)
|
|
|
|
Path(app_root_path() / "indexes" / str(ctx.guild.id)).mkdir(
|
|
|
|
parents=True, exist_ok=True
|
|
|
|
)
|
|
|
|
index.save_to_disk(
|
|
|
|
app_root_path()
|
|
|
|
/ "indexes"
|
|
|
|
/ str(ctx.guild.id)
|
|
|
|
/ f"{ctx.guild.name.replace(' ', '-')}_{date.today().month}_{date.today().day}.json"
|
|
|
|
)
|
|
|
|
|
|
|
|
await ctx.respond("Backup saved")
|
|
|
|
except Exception:
|
|
|
|
await ctx.respond("Failed to save backup")
|
|
|
|
traceback.print_exc()
|
|
|
|
|
|
|
|
async def query(
|
|
|
|
self,
|
|
|
|
ctx: discord.ApplicationContext,
|
|
|
|
query: str,
|
|
|
|
response_mode,
|
|
|
|
nodes,
|
|
|
|
user_api_key,
|
|
|
|
):
|
|
|
|
if not user_api_key:
|
|
|
|
os.environ["OPENAI_API_KEY"] = self.openai_key
|
|
|
|
else:
|
|
|
|
os.environ["OPENAI_API_KEY"] = user_api_key
|
|
|
|
|
|
|
|
try:
|
|
|
|
llm_predictor = LLMPredictor(llm=OpenAI(model_name="text-davinci-003"))
|
|
|
|
embedding_model = OpenAIEmbedding()
|
|
|
|
response = await self.loop.run_in_executor(
|
|
|
|
None,
|
|
|
|
partial(
|
|
|
|
get_and_query,
|
|
|
|
ctx.user.id,
|
|
|
|
self.index_storage,
|
|
|
|
query,
|
|
|
|
response_mode,
|
|
|
|
nodes,
|
|
|
|
llm_predictor,
|
|
|
|
embedding_model
|
|
|
|
),
|
|
|
|
)
|
|
|
|
print("The last token usage was ", llm_predictor.last_token_usage)
|
|
|
|
await self.usage_service.update_usage(llm_predictor.last_token_usage)
|
|
|
|
await ctx.respond(
|
|
|
|
f"**Query:**\n\n{query.strip()}\n\n**Query response:**\n\n{response.response.strip()}"
|
|
|
|
)
|
|
|
|
except Exception:
|
|
|
|
traceback.print_exc()
|
|
|
|
await ctx.respond(
|
|
|
|
"Failed to send query. You may not have an index set, load an index with /index load",
|
|
|
|
delete_after=10,
|
|
|
|
)
|
|
|
|
|
|
|
|
# Extracted functions from DiscordReader
|
|
|
|
|
|
|
|
async def read_channel(
|
|
|
|
self, channel_id: int, limit: Optional[int], oldest_first: bool
|
|
|
|
) -> str:
|
|
|
|
"""Async read channel."""
|
|
|
|
|
|
|
|
messages: List[discord.Message] = []
|
|
|
|
|
|
|
|
try:
|
|
|
|
channel = self.bot.get_channel(channel_id)
|
|
|
|
print(f"Added {channel.name} from {channel.guild.name}")
|
|
|
|
# only work for text channels for now
|
|
|
|
if not isinstance(channel, discord.TextChannel):
|
|
|
|
raise ValueError(
|
|
|
|
f"Channel {channel_id} is not a text channel. "
|
|
|
|
"Only text channels are supported for now."
|
|
|
|
)
|
|
|
|
# thread_dict maps thread_id to thread
|
|
|
|
thread_dict = {}
|
|
|
|
for thread in channel.threads:
|
|
|
|
thread_dict[thread.id] = thread
|
|
|
|
|
|
|
|
async for msg in channel.history(limit=limit, oldest_first=oldest_first):
|
|
|
|
if msg.author.bot:
|
|
|
|
pass
|
|
|
|
else:
|
|
|
|
messages.append(msg)
|
|
|
|
if msg.id in thread_dict:
|
|
|
|
thread = thread_dict[msg.id]
|
|
|
|
async for thread_msg in thread.history(
|
|
|
|
limit=limit, oldest_first=oldest_first
|
|
|
|
):
|
|
|
|
messages.append(thread_msg)
|
|
|
|
except Exception as e:
|
|
|
|
print("Encountered error: " + str(e))
|
|
|
|
|
|
|
|
channel = self.bot.get_channel(channel_id)
|
|
|
|
msg_txt_list = [
|
|
|
|
f"user:{m.author.display_name}, content:{m.content}" for m in messages
|
|
|
|
]
|
|
|
|
|
|
|
|
return ("<|endofstatement|>\n\n".join(msg_txt_list), channel.name)
|
|
|
|
|
|
|
|
async def load_data(
|
|
|
|
self,
|
|
|
|
channel_ids: List[int],
|
|
|
|
limit: Optional[int] = None,
|
|
|
|
oldest_first: bool = True,
|
|
|
|
) -> List[Document]:
|
|
|
|
"""Load data from the input directory.
|
|
|
|
|
|
|
|
Args:
|
|
|
|
channel_ids (List[int]): List of channel ids to read.
|
|
|
|
limit (Optional[int]): Maximum number of messages to read.
|
|
|
|
oldest_first (bool): Whether to read oldest messages first.
|
|
|
|
Defaults to `True`.
|
|
|
|
|
|
|
|
Returns:
|
|
|
|
List[Document]: List of documents.
|
|
|
|
|
|
|
|
"""
|
|
|
|
results: List[Document] = []
|
|
|
|
for channel_id in channel_ids:
|
|
|
|
if not isinstance(channel_id, int):
|
|
|
|
raise ValueError(
|
|
|
|
f"Channel id {channel_id} must be an integer, "
|
|
|
|
f"not {type(channel_id)}."
|
|
|
|
)
|
|
|
|
(channel_content, channel_name) = await self.read_channel(
|
|
|
|
channel_id, limit=limit, oldest_first=oldest_first
|
|
|
|
)
|
|
|
|
results.append(
|
|
|
|
Document(channel_content, extra_info={"channel_name": channel_name})
|
|
|
|
)
|
|
|
|
return results
|
|
|
|
|
|
|
|
async def compose(self, ctx: discord.ApplicationContext, name, user_api_key):
|
|
|
|
# Send the ComposeModal
|
|
|
|
if not user_api_key:
|
|
|
|
os.environ["OPENAI_API_KEY"] = self.openai_key
|
|
|
|
else:
|
|
|
|
os.environ["OPENAI_API_KEY"] = user_api_key
|
|
|
|
|
|
|
|
if not self.index_storage[ctx.user.id].has_indexes(ctx.user.id):
|
|
|
|
await ctx.respond("You must load at least one indexes before composing")
|
|
|
|
return
|
|
|
|
|
|
|
|
await ctx.respond(
|
|
|
|
"Select the index(es) to compose. You can compose multiple indexes together, you can also Deep Compose a single index.",
|
|
|
|
view=ComposeModal(self, ctx.user.id, name),
|
|
|
|
ephemeral=True,
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
|
|
class ComposeModal(discord.ui.View):
|
|
|
|
def __init__(self, index_cog, user_id, name=None, deep=None) -> None:
|
|
|
|
super().__init__()
|
|
|
|
# Get the argument named "user_key_db" and save it as USER_KEY_DB
|
|
|
|
self.index_cog = index_cog
|
|
|
|
self.user_id = user_id
|
|
|
|
self.deep = deep
|
|
|
|
|
|
|
|
# Get all the indexes for the user
|
|
|
|
self.indexes = [
|
|
|
|
file
|
|
|
|
for file in os.listdir(
|
|
|
|
EnvService.find_shared_file(f"indexes/{str(user_id)}/")
|
|
|
|
)
|
|
|
|
]
|
|
|
|
|
|
|
|
# Map everything into the short to long cache
|
|
|
|
for index in self.indexes:
|
|
|
|
SHORT_TO_LONG_CACHE[index[:99]] = index
|
|
|
|
|
|
|
|
# A text entry field for the name of the composed index
|
|
|
|
self.name = name
|
|
|
|
|
|
|
|
# A discord UI select menu with all the indexes. Limited to 25 entries. For the label field in the SelectOption,
|
|
|
|
# cut it off at 100 characters to prevent the message from being too long
|
|
|
|
|
|
|
|
self.index_select = discord.ui.Select(
|
|
|
|
placeholder="Select index(es) to compose",
|
|
|
|
options=[
|
|
|
|
discord.SelectOption(label=str(index)[:99], value=index[:99])
|
|
|
|
for index in self.indexes
|
|
|
|
][0:25],
|
|
|
|
max_values=len(self.indexes) if len(self.indexes) < 25 else 25,
|
|
|
|
min_values=1,
|
|
|
|
)
|
|
|
|
# Add the select menu to the modal
|
|
|
|
self.add_item(self.index_select)
|
|
|
|
|
|
|
|
# If we have more than 25 entries, add more Select fields as neccessary
|
|
|
|
self.extra_index_selects = []
|
|
|
|
if len(self.indexes) > 25:
|
|
|
|
for i in range(25, len(self.indexes), 25):
|
|
|
|
self.extra_index_selects.append(
|
|
|
|
discord.ui.Select(
|
|
|
|
placeholder="Select index(es) to compose",
|
|
|
|
options=[
|
|
|
|
discord.SelectOption(label=index[:99], value=index[:99])
|
|
|
|
for index in self.indexes
|
|
|
|
][i : i + 25],
|
|
|
|
max_values=len(self.indexes[i : i + 25]),
|
|
|
|
min_values=1,
|
|
|
|
)
|
|
|
|
)
|
|
|
|
self.add_item(self.extra_index_selects[-1])
|
|
|
|
|
|
|
|
# Add an input field for "Deep", a "yes" or "no" option, default no
|
|
|
|
self.deep_select = discord.ui.Select(
|
|
|
|
placeholder="Deep Compose",
|
|
|
|
options=[
|
|
|
|
discord.SelectOption(label="Yes", value="yes"),
|
|
|
|
discord.SelectOption(label="No", value="no"),
|
|
|
|
],
|
|
|
|
max_values=1,
|
|
|
|
min_values=1,
|
|
|
|
)
|
|
|
|
self.add_item(self.deep_select)
|
|
|
|
|
|
|
|
# Add a button to the modal called "Compose"
|
|
|
|
self.add_item(
|
|
|
|
discord.ui.Button(
|
|
|
|
label="Compose", style=discord.ButtonStyle.green, custom_id="compose"
|
|
|
|
)
|
|
|
|
)
|
|
|
|
|
|
|
|
# The callback for the button
|
|
|
|
async def interaction_check(self, interaction: discord.Interaction) -> bool:
|
|
|
|
# Check that the interaction was for custom_id "compose"
|
|
|
|
if interaction.data["custom_id"] == "compose":
|
|
|
|
# Check that the user selected at least one index
|
|
|
|
|
|
|
|
# The total list of indexes is the union of the values of all the select menus
|
|
|
|
indexes = self.index_select.values + [
|
|
|
|
select.values[0] for select in self.extra_index_selects
|
|
|
|
]
|
|
|
|
|
|
|
|
# Remap them from the SHORT_TO_LONG_CACHE
|
|
|
|
indexes = [SHORT_TO_LONG_CACHE[index] for index in indexes]
|
|
|
|
|
|
|
|
if len(indexes) < 1:
|
|
|
|
await interaction.response.send_message(
|
|
|
|
"You must select at least 1 index", ephemeral=True
|
|
|
|
)
|
|
|
|
else:
|
|
|
|
composing_message = await interaction.response.send_message(
|
|
|
|
"Composing indexes, this may take a long time...",
|
|
|
|
ephemeral=True,
|
|
|
|
delete_after=120,
|
|
|
|
)
|
|
|
|
# Compose the indexes
|
|
|
|
await self.index_cog.compose_indexes(
|
|
|
|
self.user_id,
|
|
|
|
indexes,
|
|
|
|
self.name,
|
|
|
|
False
|
|
|
|
if not self.deep_select.values or self.deep_select.values[0] == "no"
|
|
|
|
else True,
|
|
|
|
)
|
|
|
|
await interaction.followup.send(
|
|
|
|
"Composed indexes", ephemeral=True, delete_after=10
|
|
|
|
)
|
|
|
|
|
|
|
|
try:
|
|
|
|
await composing_message.delete()
|
|
|
|
except:
|
|
|
|
pass
|
|
|
|
else:
|
|
|
|
await interaction.response.defer(ephemeral=True)
|