├── .deepsource.toml
├── .gitignore
├── .pre-commit-config.yaml
├── LICENSE
├── README.md
├── SAMPLE_CONFIG.ini
├── docs
└── edubot.png
├── edubot
├── __init__.py
├── bot.py
├── sql.py
└── types.py
└── pyproject.toml
/.deepsource.toml:
--------------------------------------------------------------------------------
1 | version = 1
2 |
3 | [[analyzers]]
4 | name = "python"
5 | enabled = true
6 |
7 | [analyzers.meta]
8 | runtime_version = "3.x.x"
--------------------------------------------------------------------------------
/.gitignore:
--------------------------------------------------------------------------------
1 | poetry.lock
2 | config.ini
3 | # PyCharm
4 | .idea/
5 |
6 | # Python virtualenv environment folders
7 | env/
8 | env3/
9 | .env/
10 | .venv/
11 | .env
12 |
13 | # Bot local files
14 | *.db
15 | store/
16 |
17 | GREETING
18 | # Config file
19 | #config.yaml
20 |
21 | # Python
22 | __pycache__/
23 | *.egg-info/
24 | build/
25 | dist/
26 |
27 |
28 | # Log files
29 | *.log
30 |
--------------------------------------------------------------------------------
/.pre-commit-config.yaml:
--------------------------------------------------------------------------------
1 | repos:
2 | - repo: "local"
3 | hooks:
4 | - id: mypy
5 | name: mypy
6 | entry: bash -c 'poetry run mypy "$@" || true'
7 | language: system
8 |
9 | - repo: https://github.com/pre-commit/pre-commit-hooks
10 | rev: v4.4.0
11 | hooks:
12 | - id: check-yaml
13 | - id: check-toml
14 | - id: trailing-whitespace
15 | - id: check-added-large-files
16 | - id: check-symlinks
17 | - id: check-docstring-first
18 | - id: end-of-file-fixer
19 | - id: debug-statements
20 | - id: mixed-line-ending
21 | - repo: https://github.com/psf/black
22 | rev: 23.1.0
23 | hooks:
24 | - id: black
25 | - repo: https://github.com/hadialqattan/pycln
26 | rev: v2.1.3
27 | hooks:
28 | - id: pycln
29 | - repo: https://github.com/PyCQA/isort
30 | rev: 5.12.0
31 | hooks:
32 | - id: isort
33 | args: ["--profile", "black"]
34 |
--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
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535 |
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573 | option of following the terms and conditions either of that numbered
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612 | 17. Interpretation of Sections 15 and 16.
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622 |
623 | How to Apply These Terms to Your New Programs
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630 | to attach them to the start of each source file to most effectively
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633 |
634 |
635 | Copyright (C)
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637 | This program is free software: you can redistribute it and/or modify
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642 | This program is distributed in the hope that it will be useful,
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647 | You should have received a copy of the GNU General Public License
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649 |
650 | Also add information on how to contact you by electronic and paper mail.
651 |
652 | If the program does terminal interaction, make it output a short
653 | notice like this when it starts in an interactive mode:
654 |
655 | Copyright (C)
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657 | This is free software, and you are welcome to redistribute it
658 | under certain conditions; type `show c' for details.
659 |
660 | The hypothetical commands `show w' and `show c' should show the appropriate
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662 | might be different; for a GUI interface, you would use an "about box".
663 |
664 | You should also get your employer (if you work as a programmer) or school,
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666 | For more information on this, and how to apply and follow the GNU GPL, see
667 | .
668 |
669 | The GNU General Public License does not permit incorporating your program
670 | into proprietary programs. If your program is a subroutine library, you
671 | may consider it more useful to permit linking proprietary applications with
672 | the library. If this is what you want to do, use the GNU Lesser General
673 | Public License instead of this License. But first, please read
674 | .
675 |
--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
1 | # Edubot
2 |
3 | A self-improving AI-based chatbot library that is completely platform-agnostic.
4 |
5 | Edubot intuitively jumps into conversations to give advice, make jokes, and add to the discussion. Its personality can be completely customised to suit the tone of different rooms.
6 |
7 | By simply reacting to messages with a thumbs up/down, users help Edubot collate feedback. This feedback is used to fine-tune the bot and improve its responses in the future.
8 |
9 | Edubot is still under active development and is the first project from [Open EdTech](https://openedtech.global).
10 |
11 | ## Architecture
12 | 1. Edubot integrations convert messages from external platforms into a standardised format.
13 | 1. The library uses these messages to generate a response from GPT-4.
14 | 1. Users send feedback to the bot's responses.
15 | 1. Using the feedback, the library fine-tunes GPT-4's responses to better suit each thread it partakes in.
16 |
17 | 
18 |
19 | ## Dev environment quickstart
20 | 1. Install [Poetry](https://python-poetry.org/docs/)
21 | 1. Install dependencies: `poetry install`
22 | 1. Activate the env: `poetry shell`
23 | 1. Install pre-commit hooks: `pre-commit install`
24 | 1. Copy SAMPLE_CONFIG.ini and put your information in
25 | 1. Set the `EDUBOT_CONFIG` env variable to wherever you put your config
26 |
27 | For an example of an integration using this library see: [edubot-matrix](https://github.com/openedtech/edubot-matrix)
28 |
--------------------------------------------------------------------------------
/SAMPLE_CONFIG.ini:
--------------------------------------------------------------------------------
1 | [edubot]
2 | # Required for text generation
3 | openai_key = yourKeyHere
4 |
5 | # Required for image generation (https://platform.stability.ai/docs/getting-started/authentication)
6 | dreamstudio_key = yourKeyHere
7 |
8 | # Required for text-to-image processing
9 | replicate_key = yourKeyHere
10 |
11 | # We use a disk-based database for simplicity, this is where files are stored
12 | database = path/to/your/database
13 |
--------------------------------------------------------------------------------
/docs/edubot.png:
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https://raw.githubusercontent.com/openedtech/edubot/b50cbbbb202d8622fd7acaf90d4818ee60b60d0b/docs/edubot.png
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/edubot/__init__.py:
--------------------------------------------------------------------------------
1 | """
2 | Read the config into the global scope when the library is imported.
3 | """
4 | from configparser import ConfigParser
5 | from os import environ, path
6 |
7 |
8 | def _read_cfg() -> ConfigParser:
9 | try:
10 | config_fp = environ["EDUBOT_CONFIG"]
11 | except KeyError:
12 | raise EnvironmentError("EDUBOT_CONFIG environment variable not set.")
13 |
14 | config = ConfigParser()
15 |
16 | if not config.read(config_fp):
17 | if path.exists(config_fp):
18 | raise PermissionError(f"Cannot read {config_fp}.")
19 | raise FileNotFoundError(f"File {config_fp} doesn't exist.")
20 | return config
21 |
22 |
23 | CONFIG = _read_cfg()
24 |
25 | OPENAI_KEY: str | None = CONFIG.get("edubot", "openai_key", fallback=None)
26 |
27 | if not OPENAI_KEY:
28 | raise RuntimeError(
29 | "OpenAI key is not defined, make sure to supply it in the config."
30 | )
31 |
32 | # Add openai key to env variables for langchain
33 | environ["OPENAI_API_KEY"] = OPENAI_KEY
34 |
35 | DREAMSTUDIO_KEY: str | None = CONFIG.get("edubot", "dreamstudio_key", fallback=None)
36 | REPLICATE_KEY: str | None = CONFIG.get("edubot", "replicate_key", fallback=None)
37 | DATABASE: str = CONFIG.get("edubot", "database")
38 |
--------------------------------------------------------------------------------
/edubot/bot.py:
--------------------------------------------------------------------------------
1 | """
2 | Module for AI processing tasks
3 | """
4 | import datetime
5 | import io
6 | import logging
7 |
8 | import openai
9 | import PIL
10 | import replicate
11 | import tiktoken
12 | import trafilatura
13 | from langchain.chat_models import ChatOpenAI
14 | from langchain.schema import AIMessage, HumanMessage, SystemMessage
15 | from openai import OpenAIError
16 | from PIL import Image
17 | from sqlalchemy import desc, select
18 | from stability_sdk.client import StabilityInference, process_artifacts_from_answers
19 | from stability_sdk.utils import generation
20 |
21 | from edubot import DREAMSTUDIO_KEY, REPLICATE_KEY
22 | from edubot.sql import Bot, Completion, Message, Session, Thread
23 | from edubot.types import CompletionInfo, ImageInfo, MessageInfo
24 |
25 | # The limit for GPT-4 is 8192 tokens.
26 | MAX_GPT_TOKENS = 128000
27 | # The maximum number of GPT tokens that chat context can be.
28 | MAX_PROMPT_TOKENS = MAX_GPT_TOKENS - 1192
29 | # The maximum number of GPT tokens that can be used for completion.
30 | MAX_COMPLETION_TOKENS = MAX_GPT_TOKENS - MAX_PROMPT_TOKENS
31 |
32 | # Settings for GPT completion generation
33 | GPT_SETTINGS = {
34 | "model": "gpt-4o",
35 | "temperature": 0.3,
36 | "max_tokens": MAX_COMPLETION_TOKENS,
37 | }
38 |
39 | LLM = ChatOpenAI(**GPT_SETTINGS)
40 |
41 | # The maximum allowed size of images in megabytes
42 | MAX_IMAGE_SIZE_MB = 50
43 |
44 | # Prompt for GPT to summarise web pages
45 | WEB_SUMMARY_PROMPT = (
46 | "Your input is scraped text from a website. Your job is to summarise the text and post it to a chatroom.\n"
47 | "Long-form text includes pages such as news articles and blog posts.\n"
48 | "If the page doesn't contain long-form text return the phrase 'NO CONTENT' and nothing else.\n"
49 | "If the page mentions any variation of 'requiring javascript', or 'enable javascript' you should also return 'NO CONTENT' and nothing else.\n"
50 | "If the page DOES contain long-form text return a brief 2 sentence summary of the text content. "
51 | "This summary will then be sent to users.\n"
52 | )
53 |
54 | logger = logging.getLogger(__name__)
55 |
56 | REPLICATE_CLIENT = replicate.Client(api_token=REPLICATE_KEY)
57 |
58 |
59 | def estimate_tokens(text: str) -> int:
60 | # Load GPT-4 encoding
61 | enc = tiktoken.encoding_for_model(GPT_SETTINGS["model"])
62 |
63 | # Turn text into tokens and count them
64 | token_count = len(enc.encode(text))
65 | return token_count
66 |
67 |
68 | class EduBot:
69 | """
70 | An AI chatbot which continually improves itself using user feedback.
71 | """
72 |
73 | def __init__(self, username: str, platform: str, personality: str | list[str]):
74 | """
75 | Initialise EduBot with personalised information about the bot.
76 |
77 | :param username: A unique name to identify this bot from others on the same platform.
78 | :param platform: The platform the bot is running on E.g. 'telegram' 'matrix' 'mastodon'
79 | :param personality: Instructions/information for the bot to follow when generating responses.
80 | """
81 | self.username = username
82 | self.platform = platform
83 |
84 | if personality is None:
85 | self.personality = []
86 | elif type(personality) is str:
87 | self.personality = [personality]
88 | else:
89 | self.personality = personality
90 |
91 | self.__add_bot_to_db()
92 |
93 | # The primary key of the bot in the database
94 | self.__bot_pk = self.__get_bot(username).id
95 |
96 | # This variable is lazy loaded
97 | self.stability_client: StabilityInference | None = None
98 |
99 | self.system_messages = [
100 | f"You are a chatbot named '{self.username}' which is controlled by an open source python"
101 | f" program called EduBot that is running on a server owned by the Open EdTech"
102 | f" organisation. On the backend, the edubot program connects to the API of an"
103 | f" LLM ({GPT_SETTINGS['model']}) which processes prompts and returns responses. "
104 | f"On the frontend, the Edubot program connects via API to the {self.platform}"
105 | f" platform to write posts and read the posts of others. "
106 | f"You, EduBot, are not able to change yourself - all requests to modify your"
107 | f" code should be directed to Github: https://github.com/openedtech/edubot.",
108 | "You should pretend you can view images. "
109 | "Descriptions of images posted to the chat will be saved to the database. "
110 | "These descriptions are in the form: '*A picture of ____'. "
111 | "When you spot these descriptions you should pretend you can see the image, using the description. "
112 | "Do not mention that you cannot see the image, or that you are instead viewing a description of"
113 | "the image. Just pretend like you can see it.",
114 | f"The current year is: {datetime.datetime.now().year}",
115 | f"You use the language model {GPT_SETTINGS['model']}",
116 | f"Never prefix your messages with '{self.username}:'",
117 | ]
118 |
119 | def __get_bot(self, username: str) -> Bot | None:
120 | """
121 | Returns the Bot of "username" if it exists on this platform otherwise returns None.
122 | """
123 | with Session() as session:
124 | bot = session.execute(
125 | select(Bot)
126 | .where(Bot.username == username)
127 | .where(Bot.platform == self.platform)
128 | ).fetchone()
129 |
130 | if bot:
131 | return bot[0]
132 | else:
133 | return None
134 |
135 | def __add_bot_to_db(self) -> None:
136 | """
137 | Insert this bot into the DB if it isn't already.
138 | """
139 | if not self.__get_bot(self.username):
140 | with Session() as session:
141 | new_bot = Bot(username=self.username, platform=self.platform)
142 |
143 | session.add(new_bot)
144 | session.commit()
145 |
146 | def __get_message(self, msg_info: MessageInfo) -> Message | None:
147 | """
148 | Get an ORM Message object from the database.
149 | """
150 | with Session() as session:
151 | message = session.execute(
152 | select(Message)
153 | .where(Message.username == msg_info["username"])
154 | .where(Message.message == msg_info["message"])
155 | .where(Message.time == msg_info["time"])
156 | .where(Thread.platform == self.platform)
157 | ).fetchone()
158 | if message:
159 | return message[0]
160 | else:
161 | return None
162 |
163 | def __get_thread(self, thread_name: str) -> Thread | None:
164 | """
165 | Get an ORM Thread object from the database.
166 | """
167 | with Session() as session:
168 | thread = session.execute(
169 | select(Thread)
170 | .where(Thread.thread_name == thread_name)
171 | .where(Thread.platform == self.platform)
172 | ).fetchone()
173 |
174 | if thread:
175 | return thread[0]
176 | else:
177 | return None
178 |
179 | def __get_completion_from_message(self, msg_info: MessageInfo) -> Completion | None:
180 | """
181 | Gets the bots response to a specific message.
182 | """
183 | with Session() as session:
184 | msg = self.__get_message(msg_info)
185 | completion = session.execute(
186 | select(Completion)
187 | .where(Completion.bot == self.__bot_pk)
188 | .where(Completion.reply_to == msg.id)
189 | ).fetchone()
190 |
191 | if completion:
192 | return completion[0]
193 | else:
194 | return None
195 |
196 | def __add_completion(self, completion: str, reply_to: MessageInfo) -> None:
197 | """
198 | Add a completion to the database.
199 |
200 | :param completion: The text the bot generated.
201 | :param reply_to: The message the bot was replying to.
202 | """
203 | msg_id = self.__get_message(reply_to).id
204 | with Session() as session:
205 | new_comp = Completion(
206 | bot=self.__bot_pk,
207 | message=completion,
208 | reply_to=msg_id,
209 | )
210 | session.add(new_comp)
211 | session.commit()
212 |
213 | def __format_context(
214 | self, context: list[MessageInfo], personality_override: str = None
215 | ) -> list[SystemMessage | HumanMessage | AIMessage]:
216 | """
217 | Formats chat context and system messages into a chronological list of langchain messages.
218 |
219 | :param context: A list of MessageInfo.
220 | :return: The context as a list of langchain message objects.
221 | """
222 | if personality_override:
223 | # We need to shallow copy 'self.personality' to avoid modifying the original list
224 | personality = self.personality.copy()
225 | personality.append(personality_override)
226 | else:
227 | personality = self.personality
228 |
229 | langchain_messages: list[SystemMessage | HumanMessage | AIMessage] = []
230 |
231 | # Append the system messages and personality to the chat context
232 | for i in self.system_messages + personality:
233 | langchain_messages.append(SystemMessage(content=i))
234 |
235 | # The context is too long if the prompt is longer than MAX_PROMPT_TOKENS
236 | token_count = 0
237 |
238 | for msg in context:
239 | if msg["username"] == self.username:
240 | langchain_messages.append(AIMessage(content=msg["message"]))
241 | else:
242 | langchain_messages.append(HumanMessage(content=msg["message"]))
243 |
244 | token_count += estimate_tokens(msg["message"])
245 |
246 | # Remove messages from the context until the prompt is short enough
247 | while token_count > MAX_PROMPT_TOKENS:
248 | token_count -= estimate_tokens(langchain_messages.pop(0).content)
249 |
250 | return langchain_messages
251 |
252 | @staticmethod
253 | def __describe_image(image: Image.Image) -> str:
254 | """
255 | Gets an AI generated description of an image.
256 | """
257 | if not REPLICATE_KEY:
258 | raise RuntimeError(
259 | "Replicate key is not defined, make sure to supply it in the config."
260 | )
261 |
262 | image_bytes = io.BytesIO()
263 | image.save(image_bytes, format="PNG")
264 |
265 | if image_bytes.tell() / 1048576 > MAX_IMAGE_SIZE_MB:
266 | logger.info(f"Skipped image because it was too large.")
267 | return None
268 |
269 | output: str = REPLICATE_CLIENT.run(
270 | "j-min/clip-caption-reward:de37751f75135f7ebbe62548e27d6740d5155dfefdf6447db35c9865253d7e06",
271 | input={"image": image_bytes},
272 | )
273 |
274 | if not output:
275 | logger.error("Replicate returned an empty response.")
276 | return None
277 |
278 | return output
279 |
280 | def save_image_to_context(self, image: ImageInfo, thread_name: str) -> str | None:
281 | """
282 | Saves an AI generated description of a user-sent image to the database. This allows GPT to understand what images are
283 | and how to describe them. The maximum image size in MB can be read from the MAX_IMAGE_SIZE_MB constant.
284 |
285 | :param image: An ImageInfo object.
286 | :param thread_name: A unique identifier for the thread the image was posted in.
287 | :returns: The description of the image or None if an error occurred.
288 | """
289 | image_description = self.__describe_image(image["image"])
290 |
291 | with Session() as session:
292 | thread = self.__get_thread(thread_name)
293 | if not thread:
294 | thread = Thread(thread_name=thread_name, platform=self.platform)
295 | session.add(thread)
296 | session.commit()
297 |
298 | message = Message(
299 | thread=thread.id,
300 | username=image["username"],
301 | message=f"*An image of {image_description}",
302 | time=image["time"],
303 | )
304 | session.add(message)
305 |
306 | session.commit()
307 |
308 | return image_description
309 |
310 | def gpt_answer(
311 | self,
312 | new_context: list[MessageInfo],
313 | thread_name: str,
314 | personality_override: str = None,
315 | ) -> str | None:
316 | """
317 | Use chat context to generate a GPT3 response.
318 |
319 | :param new_context: Chat context as a chronological list of MessageInfo
320 | :param thread_name: The unique identifier of the thread this context pertains to
321 | :param personality_override: A custom personality that overrides the default.
322 |
323 | :returns: The response from GPT
324 | """
325 | with Session() as session:
326 | thread = self.__get_thread(thread_name)
327 |
328 | if not thread:
329 | thread = Thread(thread_name=thread_name, platform=self.platform)
330 |
331 | session.add(thread)
332 | session.commit()
333 |
334 | # Context in this timeframe that is in the database but not in the new context provided
335 | # (Usually images)
336 | existing_context: list[MessageInfo] = []
337 |
338 | for existing_msg in session.scalars(
339 | select(Message)
340 | .where(Message.thread == thread.id)
341 | .where(Message.time > new_context[0]["time"])
342 | ):
343 | row_as_msg_info: MessageInfo = {
344 | "username": existing_msg.username,
345 | "message": existing_msg.message,
346 | "time": existing_msg.time,
347 | }
348 | if row_as_msg_info not in new_context:
349 | existing_context.append(row_as_msg_info)
350 |
351 | # The existing context in this timeframe + the new messages
352 | new_and_existing_context: list[MessageInfo] = []
353 |
354 | for index, msg in enumerate(new_context):
355 | # Figure out where to insert the extra context chronologically
356 | for extra_msg in existing_context:
357 | check = extra_msg["time"] < msg["time"]
358 | if index > 0:
359 | check = (
360 | check and extra_msg["time"] > new_context[index - 1]["time"]
361 | )
362 |
363 | if check:
364 | new_and_existing_context.append(extra_msg)
365 | existing_context.remove(extra_msg)
366 |
367 | new_and_existing_context.append(msg)
368 |
369 | # If the message is already in the database
370 | if self.__get_message(msg) is not None:
371 | continue
372 |
373 | # If the message was written by a bot
374 | if self.__get_bot(msg["username"]) is not None:
375 | continue
376 |
377 | row: dict = msg
378 | row["thread"] = thread.id
379 |
380 | session.add(Message(**row))
381 |
382 | session.commit()
383 |
384 | # Ensure that all bot completions are included in context, notably image completions.
385 | complete_context: list[MessageInfo] = []
386 | for message in new_and_existing_context:
387 | if self.__get_bot(message["username"]) is not None:
388 | continue
389 | complete_context.append(message)
390 |
391 | if completion := self.__get_completion_from_message(message):
392 | complete_context.append(
393 | {
394 | "username": self.username,
395 | "message": completion.message,
396 | "time": message[
397 | "time"
398 | ], # Estimate this, it doesn't matter for gpt_context
399 | }
400 | )
401 |
402 | langchain_context = self.__format_context(
403 | complete_context, personality_override=personality_override
404 | )
405 |
406 | chat = ChatOpenAI(**GPT_SETTINGS)
407 | completion = chat(langchain_context).content
408 |
409 | if not completion:
410 | return None
411 |
412 | # Strip username from completion, sometimes GPT messes this up.
413 | completion = completion.replace(f"{self.username}:", "").lstrip()
414 |
415 | # Add a new completion to the database using the completion text and the message being replied to
416 | self.__add_completion(completion, complete_context[-1])
417 |
418 | # Return the completion result back to the integration
419 | return completion
420 |
421 | def change_completion_score(
422 | self, offset: int, completion: CompletionInfo, thread_name: str
423 | ) -> None:
424 | """
425 | Change user feedback to a completion.
426 |
427 | :param offset: An integer representing the new positive or negative votes to this reaction.
428 | :param completion: Information about the completion being reacted to.
429 | :param thread_name: A unique identifier for the thread the completion resides in.
430 | """
431 |
432 | # 1.5 mins before the completion was sent
433 | delta = completion["time"] - datetime.timedelta(minutes=1, seconds=30)
434 |
435 | with Session() as session:
436 | # This select statement might get the wrong completion if the bot has sent duplicate messages in the same
437 | # thread within 1.5 minutes.
438 | # BUT this isn't really a problem because it's very likely that users have the same reaction to
439 | # both of the duplicate messages.
440 | # TODO: Is there a way to uniquely identify a bot completion? We can't record the time the completion was
441 | # sent as we don't know when the integration sends the completion. The integration also can't know for
442 | # sure which message a completion was replying to, as messages can be sent while the bot is generating
443 | # responses.
444 | completion_row = session.execute(
445 | select(Completion)
446 | .join(Bot)
447 | .join(Message)
448 | .join(Thread)
449 | .where(Completion.message == completion["message"])
450 | .where(Thread.thread_name == thread_name)
451 | .where(Bot.id == self.__bot_pk)
452 | # The message being replied to was sent not more than 1.5 minutes before the completion
453 | .where(delta < Message.time)
454 | .where(Message.time < completion["time"])
455 | .order_by(desc(Completion.id))
456 | ).fetchone()
457 |
458 | if not completion_row:
459 | logger.debug(
460 | f"Message is not a GPT completion: '{completion['message']}' @ {completion['time']}"
461 | )
462 | return
463 |
464 | completion: Completion = completion_row[0]
465 |
466 | completion.score += offset
467 |
468 | session.add(completion)
469 | session.commit()
470 |
471 | logger.info(f"Completion {completion.id} incremented by {offset}.")
472 |
473 | def generate_image(
474 | self, prompt: str, reply_to_msg: MessageInfo, thread_name: str
475 | ) -> Image.Image | None:
476 | """
477 | Generate an image using Stability AI's DreamStudio.
478 |
479 | :param prompt: A description of the image that should be generated.
480 | :param reply_to_msg: The message the bot is replying to.
481 | :param thread_name: A unique identifier for the thread the message resides in.
482 | :return: A PIL.Image.Image instance.
483 | """
484 | if not DREAMSTUDIO_KEY:
485 | raise RuntimeError(
486 | "DreamStudio key is not defined, make sure to supply it in the config."
487 | )
488 |
489 | # Lazy load client
490 | if self.stability_client is None:
491 | verbose = logger.level >= 10
492 | self.stability_client = StabilityInference(
493 | key=DREAMSTUDIO_KEY, verbose=verbose
494 | )
495 |
496 | # Get Answer objects from stability
497 | answers = self.stability_client.generate(prompt)
498 |
499 | # Convert answer objects into artifacts we can use
500 | artifacts = process_artifacts_from_answers("", "", answers, write=False)
501 |
502 | image: Image.Image | None = None
503 |
504 | # noinspection PyBroadException
505 | try:
506 | for _, artifact in artifacts:
507 | # Check that the artifact is an Image, not sure why this is necessary.
508 | # See: https://github.com/Stability-AI/stability-sdk/blob/d8f140f8828022d0ad5635acbd0fecd6f6fc317a/src/stability_sdk/utils.py#L80
509 | if artifact.type == generation.ARTIFACT_IMAGE:
510 | image = PIL.Image.open(io.BytesIO(artifact.binary))
511 | break
512 | # Exception only happens when prompt is inappropriate.
513 | except Exception:
514 | return None
515 |
516 | if image is None:
517 | return None
518 |
519 | with Session() as session:
520 | thread = self.__get_thread(thread_name)
521 |
522 | if not thread:
523 | thread = Thread(thread_name=thread_name, platform=self.platform)
524 |
525 | session.add(thread)
526 | session.commit()
527 |
528 | message = Message(
529 | username=reply_to_msg["username"],
530 | message=reply_to_msg["message"],
531 | time=reply_to_msg["time"],
532 | thread=thread.id,
533 | )
534 | session.add(message)
535 | session.commit()
536 |
537 | image_description = self.__describe_image(image)
538 | completion = (
539 | f"*An image you generated based on the prompt: '{prompt}'.\n"
540 | f"*Your interpretation of the image is: '{image_description}'."
541 | )
542 | self.__add_completion(completion, reply_to_msg)
543 |
544 | return image
545 |
546 | def summarise_url(self, url: str, msg: MessageInfo, thread_name: str) -> str | None:
547 | """
548 | Use GPT to summarise the text content of a URL.
549 |
550 | Returns None if the webpage cannot be fetched or doesn't contain long-form text to summarise.
551 |
552 | :param url: A valid url.
553 | :param msg: The message that triggered this summary request.
554 | :param thread_name: A unique identifier for the thread the URL was sent in.
555 | """
556 | resp = trafilatura.fetch_url(url)
557 |
558 | # If HTTP or network error
559 | if resp == "" or resp is None:
560 | return None
561 |
562 | # Convert HTML to Plaintext
563 | text = trafilatura.extract(resp)
564 |
565 | # If error converting to plaintext
566 | if text is None:
567 | return None
568 |
569 | # Ensure text doesn't exceed GPT limits
570 | while estimate_tokens(text) > MAX_PROMPT_TOKENS:
571 | text = text[:-100]
572 |
573 | gpt_context = [
574 | {"role": "system", "content": WEB_SUMMARY_PROMPT},
575 | {"role": "user", "content": text},
576 | ]
577 | try:
578 | completion = openai.ChatCompletion.create(
579 | messages=gpt_context,
580 | **GPT_SETTINGS,
581 | )
582 | except OpenAIError as e:
583 | logger.error(f"OpenAI request failed: {e}")
584 | return None
585 |
586 | completion_text: str = completion["choices"][0]["message"]["content"]
587 |
588 | if "NO CONTENT" in completion_text.upper():
589 | return
590 |
591 | completion_text = completion_text.strip()
592 |
593 | with Session() as session:
594 | thread = self.__get_thread(thread_name)
595 | if not thread:
596 | thread = Thread(thread_name=thread_name, platform=self.platform)
597 | session.add(thread)
598 | session.commit()
599 |
600 | if self.__get_message(msg) is None:
601 | row: dict = msg
602 | row["thread"] = thread.id
603 | session.add(Message(**row))
604 | session.commit()
605 |
606 | # Ensure URL summaries are added to the DB
607 | self.__add_completion(completion_text, msg)
608 |
609 | session.commit()
610 |
611 | return completion_text
612 |
--------------------------------------------------------------------------------
/edubot/sql.py:
--------------------------------------------------------------------------------
1 | from sqlalchemy import (
2 | Column,
3 | DateTime,
4 | ForeignKey,
5 | Integer,
6 | String,
7 | UniqueConstraint,
8 | create_engine,
9 | )
10 | from sqlalchemy.orm import declarative_base, relationship, sessionmaker
11 |
12 | from edubot import DATABASE
13 |
14 | engine = create_engine(DATABASE, echo=True, future=True)
15 |
16 | Base = declarative_base()
17 |
18 | Session = sessionmaker(engine)
19 |
20 |
21 | class Thread(Base):
22 | """
23 | Table for thread information, every message must belong to a thread.
24 |
25 | A thread is any construct that groups related messages together, E.g. A Forum, chatroom, email thread,
26 | or replies to a mastodon toot.
27 | """
28 |
29 | __tablename__ = "thread"
30 |
31 | id = Column(Integer, primary_key=True)
32 |
33 | # The platform the thread belongs to
34 | platform = Column(String(100), nullable=False)
35 |
36 | # Identifier for this thread that is unique for this platform
37 | thread_name = Column(String, nullable=False)
38 |
39 | # Delete all messages within this thread if the thread is deleted
40 | messages = relationship("Message", cascade="all, delete")
41 |
42 | # Threads cannot have the same name on the same platform
43 | UniqueConstraint(thread_name, platform)
44 |
45 |
46 | class Message(Base):
47 | """
48 | Table for messages not written by Edubot instances.
49 | """
50 |
51 | __tablename__ = "message"
52 |
53 | id = Column(Integer, primary_key=True)
54 |
55 | # The username which wrote this message
56 | username = Column(String(100), nullable=False)
57 |
58 | message = Column(String(5000), nullable=False)
59 |
60 | # The time (in UTC) that this message was sent
61 | time = Column(DateTime(), nullable=False)
62 |
63 | thread = Column(Integer, ForeignKey("thread.id"), nullable=False)
64 |
65 | # Someone cannot write the same message at the same time in the same thread
66 | UniqueConstraint(username, message, time, thread)
67 |
68 |
69 | class Completion(Base):
70 | """
71 | Table for messages written by EduBot instances.
72 | """
73 |
74 | __tablename__ = "completion"
75 |
76 | id = Column(Integer, primary_key=True)
77 |
78 | # The bot that wrote this completion
79 | bot = Column(Integer, ForeignKey("bot.id"), nullable=False)
80 |
81 | # The score of user feedback to this completion
82 | score = Column(Integer, default=0, nullable=False)
83 |
84 | message = Column(String(5000), nullable=False)
85 |
86 | # The message the bot was replying to
87 | reply_to = Column(Integer, ForeignKey("message.id"), nullable=False)
88 |
89 |
90 | class Bot(Base):
91 | """
92 | Table for the metadata of EduBot instances.
93 | """
94 |
95 | __tablename__ = "bot"
96 |
97 | id = Column(Integer(), primary_key=True)
98 |
99 | # The username of the bot
100 | username = Column(String(100), nullable=False)
101 |
102 | # The platform the bot is running on
103 | platform = Column(String(100), nullable=False)
104 |
105 | # If a bot is deleted, delete all it's completions
106 | completions = relationship("Completion", cascade="all, delete")
107 |
108 | # Two bots with the same username cannot operate on the same platform
109 | UniqueConstraint(username, platform)
110 |
111 |
112 | # Create Tables if they aren't already
113 | Base.metadata.create_all(engine)
114 |
--------------------------------------------------------------------------------
/edubot/types.py:
--------------------------------------------------------------------------------
1 | """
2 | Custom types
3 | """
4 | # TODO: Consider replacing these with langchain objects/db
5 | from datetime import datetime
6 | from typing import TypedDict
7 |
8 | import PIL.Image
9 |
10 |
11 | class MessageInfo(TypedDict):
12 | """
13 | Represents a message in a thread.
14 | """
15 |
16 | username: str
17 | message: str
18 | time: datetime
19 |
20 |
21 | class ImageInfo(TypedDict):
22 | """
23 | Represents an image in a thread.
24 |
25 | This class is only used for processing images to text. Only the AI generated caption is stored in the database.
26 | """
27 |
28 | username: str
29 | image: PIL.Image.Image
30 | time: datetime
31 |
32 |
33 | class CompletionInfo(TypedDict):
34 | """
35 | Represents a bot response to a message.
36 | """
37 |
38 | message: str
39 | time: datetime
40 |
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/pyproject.toml:
--------------------------------------------------------------------------------
1 | [tool.poetry]
2 | name = "edubot"
3 | version = "0.7.5"
4 | description = ""
5 | authors = ["exciteabletom ", "moodler "]
6 | license = "GPLv3"
7 | readme = "README.md"
8 |
9 | [tool.poetry.dependencies]
10 | python = "^3.10"
11 | sqlalchemy = {version = "^2.0.14", extras = ["mypy"]}
12 | openai = "^0.27.6"
13 | stability-sdk = "^0.8.1"
14 | pillow = "^9.5.0"
15 | beautifulsoup4 = "^4.12.2"
16 | trafilatura = "^1.6.0"
17 | replicate = "^0.8.1"
18 | tiktoken = "^0.4.0"
19 | langchain = "^0.0.279"
20 |
21 | [tool.poetry.dev-dependencies]
22 | pre-commit = "^3.3.2"
23 | mypy = "^1.3.0"
24 |
25 | [tool.mypy]
26 | plugins = "sqlalchemy.ext.mypy.plugin"
27 |
28 | [build-system]
29 | requires = ["poetry-core"]
30 | build-backend = "poetry.core.masonry.api"
31 |
--------------------------------------------------------------------------------