diff --git a/.env.example b/.env.example new file mode 100644 index 0000000..ee893ca --- /dev/null +++ b/.env.example @@ -0,0 +1,8 @@ +# Your Telegram Bot Token +TELEGRAM_TOKEN=123456789:ABCdefGhIjKlmnOpqRsTuvwXyz123456789 +# Database path +DATABASE_PATH=./data/app.db +# Log Path +LOG_PATH=./data/app.log +# Debug +DEBUG=False \ No newline at end of file diff --git a/.env.sample b/.env.sample deleted file mode 100644 index a1ff514..0000000 --- a/.env.sample +++ /dev/null @@ -1,8 +0,0 @@ -# Your Telegram Bot Token -TG_TOKEN=123456789:ABCdefGhIjKlmnOpqRsTuvwXyz123456789 -# Database URL -DATABASE_URL=sqlite:///./data/app.db -# Log Path -LOG_PATH=./data/app.log -# Debug -DEBUG=False \ No newline at end of file diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml new file mode 100644 index 0000000..f0681d8 --- /dev/null +++ b/.github/workflows/ci.yaml @@ -0,0 +1,42 @@ +name: CI + +on: + push: + +jobs: + mypy: + name: "mypy" + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - name: Install poetry + run: pipx install poetry + - uses: actions/setup-python@v5 + with: + python-version-file: 'pyproject.toml' + cache: 'poetry' + - name: Install dependencies + run: poetry install + - uses: tsuyoshicho/action-mypy@v4 + with: + github_token: ${{ secrets.GITHUB_TOKEN }} + reporter: github-check + target: "./src" + execute_command: 'poetry run mypy' + fail_on_error: true + + ruff: + name: "ruff" + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + - name: Install poetry + run: pipx install poetry + - uses: actions/setup-python@v5 + with: + python-version-file: 'pyproject.toml' + cache: 'poetry' + - name: Install dependencies + run: pip install ruff + - name: Run Ruff + run: ruff check --output-format=github diff --git a/.gitignore b/.gitignore index 1345c43..caf79ec 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,4 @@ .idea .env __pycache__ +venv \ No newline at end of file diff --git a/LICENSE b/LICENSE index aa893a9..9f98a77 100644 --- a/LICENSE +++ b/LICENSE @@ -1,6 +1,6 @@ MIT License -Copyright (c) 2024 Alexander Miller +Copyright (c) 2024 LibertAI Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal diff --git a/agent.yaml b/agent.yaml deleted file mode 100644 index 9d66bd2..0000000 --- a/agent.yaml +++ /dev/null @@ -1,35 +0,0 @@ -# Everything having to LLM resources and parameterizing same -model: - name: "Nouse-Hermes-2-Pro" - api_url: "https://curated.aleph.cloud/vm/84df52ac4466d121ef3bb409bb14f315de7be4ce600e8948d71df6485aa5bcc3/completion" - engine: "llamacpp" - - # Max Token count of prompts - max_prompt_tokens: 16384 - # Max Token count of completions - max_completion_tokens: 500 - - # Model parameterizing - temperature: 0.7 - sampler_order: [6, 0, 1, 3, 4, 2, 5] - top_p: 0.9 - top_k: 40 - -# Agent prompt configuration -agent: - # Max number of attempts to complete on a prompt - max_completion_tries: 3 - # Max number of times the agent can call back to itself - max_self_recurse_depth: 5 - # System Prompt Template. See the default template for further info - system_prompt_template: "./templates/system.yaml" - -# ChatML configuration -chat_ml: - user_prepend: "<|im_start|>" - user_append: "<|im_end|>" - stop_sequences: - - "<|im_end|>" - - "<|endoftext|>" - - "=3.9 or backports.zoneinfo library. -# Any required deps can installed by adding `alembic[tz]` to the pip requirements -# string value is passed to ZoneInfo() -# leave blank for localtime -# timezone = - -# max length of characters to apply to the -# "slug" field -# truncate_slug_length = 40 - -# set to 'true' to run the environment during -# the 'revision' command, regardless of autogenerate -# revision_environment = false - -# set to 'true' to allow .pyc and .pyo files without -# a source .py file to be detected as revisions in the -# versions/ directory -# sourceless = false - -# version location specification; This defaults -# to alembic/versions. When using multiple version -# directories, initial revisions must be specified with --version-path. -# The path separator used here should be the separator specified by "version_path_separator" below. -# version_locations = %(here)s/bar:%(here)s/bat:alembic/versions - -# version path separator; As mentioned above, this is the character used to split -# version_locations. The default within new alembic.ini files is "os", which uses os.pathsep. -# If this key is omitted entirely, it falls back to the legacy behavior of splitting on spaces and/or commas. -# Valid values for version_path_separator are: -# -# version_path_separator = : -# version_path_separator = ; -# version_path_separator = space -version_path_separator = os # Use os.pathsep. Default configuration used for new projects. - -# set to 'true' to search source files recursively -# in each "version_locations" directory -# new in Alembic version 1.10 -# recursive_version_locations = false - -# the output encoding used when revision files -# are written from script.py.mako -# output_encoding = utf-8 - -sqlalchemy.url = ${DATABASE_URL} - - -[post_write_hooks] -# post_write_hooks defines scripts or Python functions that are run -# on newly generated revision scripts. See the documentation for further -# detail and examples - -# format using "black" - use the console_scripts runner, against the "black" entrypoint -# hooks = black -# black.type = console_scripts -# black.entrypoint = black -# black.options = -l 79 REVISION_SCRIPT_FILENAME - -# lint with attempts to fix using "ruff" - use the exec runner, execute a binary -# hooks = ruff -# ruff.type = exec -# ruff.executable = %(here)s/.venv/bin/ruff -# ruff.options = --fix REVISION_SCRIPT_FILENAME - -# Logging configuration -[loggers] -keys = root,sqlalchemy,alembic - -[handlers] -keys = console - -[formatters] -keys = generic - -[logger_root] -level = WARN -handlers = console -qualname = - -[logger_sqlalchemy] -level = WARN -handlers = -qualname = sqlalchemy.engine - -[logger_alembic] -level = INFO -handlers = -qualname = alembic - -[handler_console] -class = StreamHandler -args = (sys.stderr,) -level = NOTSET -formatter = generic - -[formatter_generic] -format = %(levelname)-5.5s [%(name)s] %(message)s -datefmt = %H:%M:%S diff --git a/alembic/env.py b/alembic/env.py deleted file mode 100644 index b7f7078..0000000 --- a/alembic/env.py +++ /dev/null @@ -1,97 +0,0 @@ -# NOTE (amiller68): most of this file is autogenerated -# Additions are explicitly noted -from logging.config import fileConfig - -from sqlalchemy import engine_from_config -from sqlalchemy import pool - -from alembic import context - -# NOTE (amiller68): import our models and os -from src.database import SyncDatabase, Base -from dotenv import load_dotenv -import os - -# NOTE (amiller68): get the database URL from the environment. -# The default is intentionally malformed to force common configuration path -# NOTE (amiller68): 'models' calls `load_dotenv` so we don't need to do it here. -# Note that this means .env is going to overwrite anything you set directly -load_dotenv() -database_path = os.getenv('DATABASE_PATH') -# Note (amiller68): Initialize our client -- in turn updating Base -SyncDatabase(database_path) - -# this is the Alembic Config object, which provides -# access to the values within the .ini file in use. -config = context.config -# NOTE (amiller68): specify the database URL from the environment -database_url = f'sqlite:///{database_path}' -config.set_main_option('sqlalchemy.url', database_url) - -# Interpret the config file for Python logging. -# This line sets up loggers basically. -if config.config_file_name is not None: - fileConfig(config.config_file_name) - -# add your model's MetaData object here -# for 'autogenerate' support -# from myapp import mymodel -# NOTE (amiller68): enable our models -target_metadata = Base.metadata - -# other values from the config, defined by the needs of env.py, -# can be acquired: -# my_important_option = config.get_main_option("my_important_option") -# ... etc. - - -def run_migrations_offline() -> None: - """Run migrations in 'offline' mode. - - This configures the context with just a URL - and not an Engine, though an Engine is acceptable - here as well. By skipping the Engine creation - we don't even need a DBAPI to be available. - - Calls to context.execute() here emit the given string to the - script output. - - """ - url = config.get_main_option("sqlalchemy.url") - context.configure( - url=url, - target_metadata=target_metadata, - literal_binds=True, - dialect_opts={"paramstyle": "named"}, - ) - - with context.begin_transaction(): - context.run_migrations() - - -def run_migrations_online() -> None: - """Run migrations in 'online' mode. - - In this scenario we need to create an Engine - and associate a connection with the context. - - """ - connectable = engine_from_config( - config.get_section(config.config_ini_section, {}), - prefix="sqlalchemy.", - poolclass=pool.NullPool, - ) - - with connectable.connect() as connection: - context.configure( - connection=connection, target_metadata=target_metadata - ) - - with context.begin_transaction(): - context.run_migrations() - - -if context.is_offline_mode(): - run_migrations_offline() -else: - run_migrations_online() diff --git a/alembic/script.py.mako b/alembic/script.py.mako deleted file mode 100644 index fbc4b07..0000000 --- a/alembic/script.py.mako +++ /dev/null @@ -1,26 +0,0 @@ -"""${message} - -Revision ID: ${up_revision} -Revises: ${down_revision | comma,n} -Create Date: ${create_date} - -""" -from typing import Sequence, Union - -from alembic import op -import sqlalchemy as sa -${imports if imports else ""} - -# revision identifiers, used by Alembic. -revision: str = ${repr(up_revision)} -down_revision: Union[str, None] = ${repr(down_revision)} -branch_labels: Union[str, Sequence[str], None] = ${repr(branch_labels)} -depends_on: Union[str, Sequence[str], None] = ${repr(depends_on)} - - -def upgrade() -> None: - ${upgrades if upgrades else "pass"} - - -def downgrade() -> None: - ${downgrades if downgrades else "pass"} diff --git a/alembic/versions/418eae9ef110_migration_2024_03_18_17_57_32.py b/alembic/versions/418eae9ef110_migration_2024_03_18_17_57_32.py 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"0.2.51" +description = "Download market data from Yahoo! Finance API" +optional = false +python-versions = "*" +files = [ + {file = "yfinance-0.2.51-py2.py3-none-any.whl", hash = "sha256:d5cc7a970bb4bb43e4deee853514cbaa3c2b070a0dee6b2861c1ab5076f21dc1"}, + {file = "yfinance-0.2.51.tar.gz", hash = "sha256:7902cc9b23699a51efa50f1cc7a965220a56beccc00d189f929b4c7c5c189a60"}, +] + +[package.dependencies] +beautifulsoup4 = ">=4.11.1" +frozendict = ">=2.3.4" +html5lib = ">=1.1" +lxml = ">=4.9.1" +multitasking = ">=0.0.7" +numpy = ">=1.16.5" +pandas = ">=1.3.0" +peewee = ">=3.16.2" +platformdirs = ">=2.0.0" +pytz = ">=2022.5" +requests = ">=2.31" + +[package.extras] +nospam = ["requests_cache (>=1.0)", "requests_ratelimiter (>=0.3.1)"] +repair = ["scipy (>=1.6.3)"] + +[metadata] +lock-version = "2.0" +python-versions = "^3.10" +content-hash = "a05c1274682c61e421d32d2d72bc0fe8bf1d0f29d38b96413944bfa39771735a" diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..7c70ad5 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,28 @@ +[tool.poetry] +name = "libertai-telegram-bot" +version = "0.1.0" +description = "" +authors = ["LibertAI team "] +readme = "README.md" +package-mode = false + +[tool.poetry.dependencies] +python = "^3.10" +libertai-agents = "0.1.0" +sqlalchemy = "^2.0.36" +aiosqlite = "^0.20.0" +greenlet = "^3.1.1" +pytelegrambotapi = "^4.25.0" +yfinance = "^0.2.51" + +[tool.poetry.group.dev.dependencies] +mypy = "^1.11.1" +ruff = "^0.6.0" + +[tool.ruff] +lint.select = ["C", "E", "F", "I", "W"] +lint.ignore = ["E501"] + +[build-system] +requires = ["poetry-core"] +build-backend = "poetry.core.masonry.api" diff --git a/requirements.in b/requirements.in deleted file mode 100644 index 24e843f..0000000 --- a/requirements.in +++ /dev/null @@ -1,14 +0,0 @@ -SQLAlchemy -duckduckgo_search -aiosqlite -alembic -telebot -python-dotenv -aiohttp -requests -pyyaml -langchain -pydantic -jsonschema -yfinance -nltk diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index 260cdef..0000000 --- a/requirements.txt +++ /dev/null @@ -1,222 +0,0 @@ -# -# This file is autogenerated by pip-compile with Python 3.10 -# by the following command: -# -# pip-compile --output-file=requirements.txt requirements.in -# -aiohttp==3.9.3 - # via - # -r requirements.in - # langchain - # langchain-community -aiosignal==1.3.1 - # via aiohttp -aiosqlite==0.20.0 - # via -r requirements.in -alembic==1.13.1 - # via -r requirements.in -annotated-types==0.6.0 - # via pydantic -anyio==4.3.0 - # via langchain-core -appdirs==1.4.4 - # via yfinance -async-timeout==4.0.3 - # via - # aiohttp - # langchain -attrs==23.2.0 - # via - # aiohttp - # jsonschema - # referencing -beautifulsoup4==4.12.3 - # via yfinance -certifi==2024.2.2 - # via - # curl-cffi - # requests -cffi==1.16.0 - # via curl-cffi -charset-normalizer==3.3.2 - # via requests -click==8.1.7 - # via - # duckduckgo-search - # nltk -curl-cffi==0.6.2 - # via duckduckgo-search -dataclasses-json==0.6.4 - # via - # langchain - # langchain-community -duckduckgo-search==5.1.0 - # via -r requirements.in -exceptiongroup==1.2.1 - # via anyio -frozendict==2.4.0 - # via yfinance -frozenlist==1.4.1 - # via - # aiohttp - # aiosignal -greenlet==3.0.3 - # via sqlalchemy -html5lib==1.1 - # via yfinance -idna==3.6 - # via - # anyio - # requests - # yarl -joblib==1.3.2 - # via nltk -jsonpatch==1.33 - # via - # langchain - # langchain-core -jsonpointer==2.4 - # via jsonpatch -jsonschema==4.21.1 - # via -r requirements.in -jsonschema-specifications==2023.12.1 - # via jsonschema -langchain==0.1.9 - # via -r requirements.in -langchain-community==0.0.29 - # via langchain -langchain-core==0.1.33 - # via - # langchain - # langchain-community -langsmith==0.1.31 - # via - # langchain - # langchain-community - # langchain-core -lxml==5.1.0 - # via - # duckduckgo-search - # yfinance -mako==1.3.2 - # via alembic -markupsafe==2.1.5 - # via mako -marshmallow==3.21.1 - # via dataclasses-json -multidict==6.0.5 - # via - # aiohttp - # yarl -multitasking==0.0.11 - # via yfinance -mypy-extensions==1.0.0 - # via typing-inspect -nltk==3.8.1 - # via -r requirements.in -numpy==1.26.4 - # via - # langchain - # langchain-community - # pandas - # yfinance -orjson==3.9.15 - # via langsmith -packaging==23.2 - # via - # langchain-core - # marshmallow -pandas==2.2.1 - # via yfinance -peewee==3.17.1 - # via yfinance -pycparser==2.21 - # via cffi -pydantic==2.6.2 - # via - # -r requirements.in - # langchain - # langchain-core - # langsmith -pydantic-core==2.16.3 - # via pydantic -pytelegrambotapi==4.16.1 - # via telebot -python-dateutil==2.9.0.post0 - # via pandas -python-dotenv==1.0.1 - # via -r requirements.in -pytz==2024.1 - # via - # pandas - # yfinance -pyyaml==6.0.1 - # via - # -r requirements.in - # langchain - # langchain-community - # langchain-core -referencing==0.34.0 - # via - # jsonschema - # jsonschema-specifications -regex==2023.12.25 - # via nltk -requests==2.31.0 - # via - # -r requirements.in - # langchain - # langchain-community - # langchain-core - # langsmith - # pytelegrambotapi - # telebot - # yfinance -rpds-py==0.18.0 - # via - # jsonschema - # referencing -six==1.16.0 - # via - # html5lib - # python-dateutil -sniffio==1.3.1 - # via anyio -soupsieve==2.5 - # via beautifulsoup4 -sqlalchemy==2.0.28 - # via - # -r requirements.in - # alembic - # langchain - # langchain-community -telebot==0.0.5 - # via -r requirements.in -tenacity==8.2.3 - # via - # langchain - # langchain-community - # langchain-core -tqdm==4.66.2 - # via nltk -typing-extensions==4.10.0 - # via - # aiosqlite - # alembic - # anyio - # pydantic - # pydantic-core - # sqlalchemy - # typing-inspect -typing-inspect==0.9.0 - # via dataclasses-json -tzdata==2024.1 - # via pandas -urllib3==2.2.1 - # via requests -webencodings==0.5.1 - # via html5lib -yarl==1.9.4 - # via aiohttp -yfinance==0.2.36 - # via -r requirements.in diff --git a/scripts/dev.sh b/scripts/dev.sh index 32574dd..491ee2c 100755 --- a/scripts/dev.sh +++ b/scripts/dev.sh @@ -5,8 +5,7 @@ source venv/bin/activate source .env export DATABASE_PATH=:memory: export DEBUG=True -export LOG_PATH= -python3 src/bot.py +python3 -m src.main # Deactivate the virtual environment deactivate diff --git a/scripts/install.sh b/scripts/install.sh deleted file mode 100755 index 38b7a03..0000000 --- a/scripts/install.sh +++ /dev/null @@ -1,19 +0,0 @@ -#!/bin/bash - -# Install virtualenv if not installed -if ! [ -x "$(command -v virtualenv)" ]; then - echo 'Error: virtualenv is not installed.' >&2 - exit 1 -fi - -virtualenv venv - -source venv/bin/activate -pip install pip-tools -pip-compile requirements.in -o requirements.txt -pip install -r requirements.txt -python -m nltk.downloader punkt - -deactivate - -exit 0 diff --git a/scripts/migrate.sh b/scripts/migrate.sh deleted file mode 100755 index b324427..0000000 --- a/scripts/migrate.sh +++ /dev/null @@ -1,26 +0,0 @@ -#!/bin/bash - -# Enter the virtual environment -source venv/bin/activate - -echo "Running migrations..." - -# Set the DATABASE_PATH environment variable -source .env - -# If the DATABASE_PATH environment variable is not set, set a default value -if [ -z "$DATABASE_PATH" ]; then - export DATABASE_PATH=./data/app.db -fi - -echo "DATABASE_PATH: $DATABASE_PATH" - -# Run the migrations -alembic upgrade head - -# Deactivate the virtual environment -deactivate - -# Exit the script -exit 0 - diff --git a/scripts/prepare_migrations.sh b/scripts/prepare_migrations.sh deleted file mode 100755 index 99c04a9..0000000 --- a/scripts/prepare_migrations.sh +++ /dev/null @@ -1,28 +0,0 @@ -#!/bin/bash - -# Enter the virtual environment -source venv/bin/activate - -# Generate alembic migrations -echo "Generating migrations..." - -# Set the DATABASE_URL environment variable -source .env - -# If the DATABASE_URL environment variable is not set, set a default value -if [ -z "$DATABASE_PATH" ]; then - export DATABASE_PATH=./data/app.db -fi - -echo "DATABASE_PATH: $DATABASE_PATH" - -# Generate alembic migrations -# Get the current datetime -now=$(date +"%Y_%m_%d_%H_%M_%S") -alembic revision --autogenerate -m "migration_$now" - -# Deactivate the virtual environment -deactivate - -# Exit the script -exit 0 diff --git a/scripts/run.sh b/scripts/run.sh index 5605c38..4cd7c80 100755 --- a/scripts/run.sh +++ b/scripts/run.sh @@ -4,8 +4,8 @@ source venv/bin/activate source .env -# If the DATABASE_URL environment variable is not set, set a default value -if [ -z "$DATABASE_PATH" ]; then +# If the DATABASE_PATH environment variable is not set, set a default value +if [ -z "DATABASE_PATH" ]; then export DATABASE_PATH=./data/app.db fi @@ -15,7 +15,7 @@ if [ -z "$LOG_PATH" ]; then fi export DEBUG=False -python3 src/bot.py >/dev/null 2>&1 +python3 -m src.main >/dev/null 2>&1 # Deactivate the virtual environment deactivate diff --git a/src/__init__.py b/src/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/agent/__init__.py b/src/agent/__init__.py deleted file mode 100644 index a0994e9..0000000 --- a/src/agent/__init__.py +++ /dev/null @@ -1,347 +0,0 @@ -import aiohttp -import time - -from telebot import types as telebot_types - -from .utils import calculate_number_of_tokens -from .tools import ToolExecutor -from .prompt_manager import PromptManager -from database import AsyncDatabase -from logger import MessageSpan - - -class Agent: - """ - A Chat Bot that generates informed prompts based on the current conversation history. - """ - - def __init__(self, agent_config: dict): - # Instance Configuration - self.model_name = agent_config["model"]["name"] - self.model_api_url = agent_config["model"]["api_url"] - self.model_engine = agent_config["model"]["engine"] - - # Model Parameters - self.max_completion_tokens = agent_config["model"]["max_completion_tokens"] - self.max_prompt_tokens = agent_config["model"]["max_prompt_tokens"] - self.temperature = agent_config["model"]["temperature"] - self.sampler_order = agent_config["model"]["sampler_order"] - self.top_p = agent_config["model"]["top_p"] - self.top_k = agent_config["model"]["top_k"] - self.stop_sequences = agent_config["chat_ml"]["stop_sequences"] - - # Agent Behavior - self.max_completion_tries = agent_config["agent"]["max_completion_tries"] - self.max_self_recurse_depth = agent_config["agent"]["max_self_recurse_depth"] - - # Initialize an empty Map to track open context slots on the server - self.model_chat_slots = {} - # Initialize the Tool Executor - self.tool_executor = ToolExecutor() - # Initialize the Prompt Manager - self.prompt_manager = PromptManager(agent_config) - - # State Helpers - - def name(self): - """ - Return the name of the chat bot - """ - return self.prompt_manager.name - - def set_name(self, name: str): - """ - Set the persona name for the chat bot - """ - self.prompt_manager.set_name(name) - - async def clear_chat(self, chat_id: str): - """ - Clear the chat from the model's available context - """ - if chat_id in self.model_chat_slots: - session, _ = self.model_chat_slots[chat_id] - await session.close() - del self.model_chat_slots[chat_id] - - async def clear_all_chats(self): - """ - Close all open sessions - """ - for session, _ in self.model_chat_slots.values(): - await session.close() - self.model_chat_slots = {} - - # Where the magic happens - - async def build_prompt( - self, - message: telebot_types.Message, - database: AsyncDatabase, - span: MessageSpan, - batch_size: int = 10, - offset: int = 1, - ) -> tuple[str, int]: - """ - Build the most up to date prompt for the chat given the current conversation history. - Max out at `token_limit` tokens. - - - chat: the chat to build the log for - - token_limit: the maximum number of tokens the log can use - - batch_size: the number of messages to pull at a time - """ - - # Keep track of how many tokens we're using - used_tokens = 0 - token_limit = self.max_prompt_tokens - - chat = message.chat - chat_id = chat.id - - # Generate our system prompt - system_prompt, system_prompt_tokens = self.prompt_manager.system_prompt( - message.chat, token_limit=token_limit - ) - - # Generate our agent prompt for the model to complete on - prompt_response, prompt_response_tokens = self.prompt_manager.prompt_response( - message=message, token_limit=token_limit - system_prompt_tokens - ) - - # Now start filling in the chat log with as many tokens as we can - basic_prompt_tokens = system_prompt_tokens + prompt_response_tokens - used_tokens += basic_prompt_tokens - chat_log_lines = [] - offset = 1 - done = False - try: - # Keep pulling messages until we're done or we've used up all our tokens - while not done and used_tokens < token_limit: - # Get `batch_size` messages from the chat history - messages = await database.get_chat_last_messages( - chat_id, batch_size, offset, span=span - ) - # Construct condition on whether to break due to no more messages - # If set we won't re-enter the loop - done = messages is None or len(messages) < batch_size - - # Iterate over the messages we've pulled - for message in messages: - line = self.prompt_manager.chat_message(message) - # Calculate the number of tokens this line would use - additional_tokens = calculate_number_of_tokens(line) - - # Break if this would exceed our token limit before appending to the log - if used_tokens + additional_tokens > token_limit: - done = True - # Break out of the for loop. - # Since we're 'done' we won't continue the while loop - break - - # Update our used tokens count - used_tokens += additional_tokens - - # Actually append the line to the log - chat_log_lines.append(line) - - # Update our offset - offset += batch_size - - # Now build our prompt in reverse - chat_log = "" - for line in reversed(chat_log_lines): - chat_log = f"{chat_log}{line}" - - return f"{system_prompt}{chat_log}{prompt_response}", used_tokens - except Exception as e: - # Log the error, but return the portion of the prompt we've built so far - span.warn( - f"Agent::build_prompt(): error building prompt: {str(e)}. Returning partial prompt." - ) - return f"{system_prompt}{prompt_response}", basic_prompt_tokens - - async def complete( - self, prompt: str, chat_id: int, span: MessageSpan - ) -> tuple[str, int]: - """ - Complete on a prompt against our model within a given number of tries. - - Returns a str containing the prompt's completion. - """ - - if chat_id in self.model_chat_slots: - session, slot_id = self.model_chat_slots[chat_id] - else: - session = aiohttp.ClientSession() - slot_id = -1 - - params = { - "prompt": prompt, - "temperature": self.temperature, - "top_p": self.top_p, - "top_k": self.top_k, - } - - # Update the parameters based on the model engine - if self.model_engine == "llamacpp": - params.update( - { - "n_predict": self.max_completion_tokens, - # NOTE: for now just set both of these - "id_slot": slot_id, - "slot_id": slot_id, - "typical_p": 1, - "tfs_z": 1, - "stop": self.stop_sequences, - "cache_prompt": True, - "use_default_badwordsids": False, - } - ) - else: - raise Exception("Agent::complete(): unsupported model engine") - - max_tries = self.max_completion_tries - tries = 0 - errors = [] - compounded_result = "" - last_result = "" - while tries < max_tries: - span.debug( - f"Agent::complete(): attempt: {tries} | slot_id: {slot_id}", - ) - span.debug( - f"Agent::complete(): compounded result: {compounded_result}", - ) - # Append the compound result to the prompt - params["prompt"] = f"{params['prompt']}{last_result}" - try: - async with session.post(self.model_api_url, json=params) as response: - if response.status == 200: - # Read the response - response_data = await response.json() - - # Get the slot id from the response - if "id_slot" in response_data: - slot_id = response_data["id_slot"] - elif "slot_id" in response_data: - slot_id = response_data["slot_id"] - self.model_chat_slots[chat_id] = session, slot_id - - # Determine if we're stopped - stopped = ( - response_data["stopped_eos"] - or response_data["stopped_word"] - ) - last_result = response_data["content"] - compounded_result = f"{compounded_result}{last_result}" - token_count = calculate_number_of_tokens(compounded_result) - # If we're stopped, return the compounded result - if stopped: - return compounded_result, token_count - # Otherwise, check if we've exceeded the token limit, and return if so - elif token_count > self.max_completion_tokens: - span.warn("Agent::complete(): Exceeded token limit") - return compounded_result, token_count - else: - raise Exception( - f"Agent::complete(): Non 200 status code: {response.status}" - ) - except Exception as e: - span.warn(f"Agent::complete(): Error completing prompt: {str(e)}") - errors.append(e) - finally: - tries += 1 - # If we get here, we've failed to complete the prompt after max_tries - raise Exception(f"Agent::complete(): Failed to complete prompt: {errors}") - - # TODO: split out the response yielding from rendering the response - async def yield_response( - self, message: telebot_types.Message, database: AsyncDatabase, span: MessageSpan - ): - """ - Yield a response from the agent given it's current state and the message it's responding to. - - Yield a string containing the response. - """ - start = time.time() - span.info("Agent::yield_response()") - - chat_id = message.chat.id - max_self_recurse_depth = self.max_self_recurse_depth - - # Build the prompt - prompt, used_tokens = await self.build_prompt(message, database, span) - - span.info(f"Agent::yield_response(): prompt used tokens: {used_tokens}") - span.debug("Agent::yield_response(): prompt built: " + prompt) - - try: - # Keep track of the tokens we've seen out of completion - completion_tokens = 0 - # Keep track of the tokens we generate from the completion - recursive_tokens = 0 - # Keep track of the depth of self recursion - self_recurse_depth = 0 - while self_recurse_depth < max_self_recurse_depth: - # Complete and determine the tokens used - completion, used_tokens = await self.complete(prompt, chat_id, span) - completion_tokens += used_tokens - - span.debug("Agent::yield_response(): completion: " + completion) - - tool_message = None - try: - # Attempt to parse a tool call from the completion - tool_message = self.tool_executor.handle_completion( - completion, self_recurse_depth, span - ) - - span.debug( - f"Agent::yield_response(): tool_message: {tool_message}", - ) - except Exception as e: - span.warn( - "Error handling tools message: " + str(e), - ) - raise e - finally: - # If there's nothing to do, return the completion - if tool_message is None: - total_time = time.time() - start - # Log - # - completion tokens -- how many tokens the model generated - # - recursive tokens -- how many tokens we generated due to recursion - # - depth -- how deep we recursed - # - time -- how long we spent - span.info( - f"Agent::yield_response(): completion tokens: {completion_tokens} | recursive tokens: {recursive_tokens} | depth: {self_recurse_depth} | time: {total_time}" - ) - yield completion - return - - self_recurse_depth += 1 - - if self_recurse_depth >= max_self_recurse_depth: - span.warn( - "Agent::yield_response(): Function call depth exceeded", - ) - raise Exception("Function call depth exceeded") - - # Build up the new prompt and recurse - tool_message = self.prompt_manager.tool_message(tool_message) - # Keep track of the tokens we generate from the tool message - recursive_tokens += calculate_number_of_tokens(tool_message) - - # TODO: I should probably check that the token limit isn't exceeded here - # For now, just let it go through no matter how big the recursion gets - prompt, _ = self.prompt_manager.prompt_response( - f"{prompt}{completion}{tool_message}", token_limit=-1 - ) - - span.debug( - f"Agent::yield_response(): continuing recursion on prompt: {prompt}" - ) - - yield "Gathering some more information to help you better..." - except Exception as e: - raise e diff --git a/src/agent/prompt_manager.py b/src/agent/prompt_manager.py deleted file mode 100644 index 564a24a..0000000 --- a/src/agent/prompt_manager.py +++ /dev/null @@ -1,170 +0,0 @@ -import datetime -from pydantic import BaseModel -import yaml -import json - -from .utils import calculate_number_of_tokens, fmt_chat_details, fmt_msg_user_name -from .tools import get_tools, FunctionCall - -from telebot import types as telebot_types -import database - - -class SystemPromptSchema(BaseModel): - """ - Description of the agent's system prompt - """ - - # Role of the agent within the chat - # Configurable by: - # name - the username of the agent - # date - the current date - Role: str - # The Stated Objective of the agent - Objective: str - # The tools available to the agent - # Configurable by: - # tools - a formatted list of tools available to the agent - # tool_schema - json schema for calling tools - # max_self_recurse_depth - the maximum depth of recursion the agent can use - Tools: str - - -class PromptManager: - """ - PromptManager is responsible for formatting prompts based on simple data types and schemas - It should most definitely not be responsible for interacting with the model or application state - """ - - def __init__(self, agent_config: dict): - # Chat ML Configuration - self.user_prepend = agent_config["chat_ml"]["user_prepend"] - self.user_append = agent_config["chat_ml"]["user_append"] - self.stop_sequences = agent_config["chat_ml"]["stop_sequences"] - self.line_separator = "\n" - - self.tools = get_tools() - self.tool_schema = json.loads(FunctionCall.schema_json()) - self.max_self_recurse_depth = agent_config["agent"]["max_self_recurse_depth"] - - # Persona Configuration and Templates - self.name = "chat-bot" - with open(agent_config["agent"]["system_prompt_template"], "r") as f: - yaml_content = yaml.safe_load(f) - self.system_prompt_schema = SystemPromptSchema( - Role=yaml_content.get("Role", ""), - Objective=yaml_content.get("Objective", ""), - Tools=yaml_content.get("Tools", ""), - ) - - def set_name(self, name: str): - """ - Set the persona name for the chat bot - """ - self.name = name - - def tool_message(self, tool_message: str) -> str: - """ - Format a tool message into a proper chat log line - - tool: the tool message to format - Returns a string representing the chat log line - """ - # NOTE: this is a lil hacky, but in every context we generate this message, we're appeninfing - # to a completed response, so add a user append at the beginning - return f"{self.line_separator}{self.user_append}{self.line_separator}{self.user_prepend}tool{self.line_separator}{tool_message}{self.user_append}{self.line_separator}" - - def chat_message(self, message: telebot_types.Message | database.Message) -> str: - """ - Format either a telebot message or a database message into a chat log line - - - message: the message to format -- either a telebot.types.Message or a database.Message - - Returns a string representing the chat log line - """ - - from_user_name = fmt_msg_user_name(message.from_user) - is_reply = message.reply_to_message is not None - - sender = from_user_name - if is_reply: - to_user_name = fmt_msg_user_name(message.reply_to_message.from_user) - sender = f"{from_user_name} (in reply to {to_user_name})" - return f"{self.user_prepend}{sender}{self.line_separator}{message.text}{self.line_separator}{self.user_append}{self.line_separator}" - - def prompt_response( - self, - message: telebot_types.Message | database.Message | str | None = None, - text: str = "", - token_limit: int = 2048, - ) -> tuple[str, int]: - """ - Prompt a simple response from the model: - - message: the message to prompt a response from (optional) - - text: text to start the model off on (optional) - - token_limit: the maximum number of tokens the prompt can use - - Returns a tuple of (prompt, used_tokens) - """ - - base = "" - if message is not None and isinstance( - message, (telebot_types.Message, database.Message) - ): - base = self.chat_message(message) - elif message is not None and isinstance(message, str): - base = message - - prompt = f"{base}{self.user_prepend}{self.name}{self.line_separator}{text}" - - used_tokens = calculate_number_of_tokens(prompt) - - if token_limit == -1: - return prompt, used_tokens - elif used_tokens > token_limit: - raise Exception("prompt_response(): prompt exceeds token limit") - - return prompt, used_tokens - - def system_prompt( - self, - chat: telebot_types.Chat, - token_limit: int = 2048, - ) -> tuple[str, int]: - """ - Build a system prompt for a specific chat - - - chat: the chat to build the system prompt for - - token_limit: the maximum number of tokens the prompt can use - - Returns a tuple of (system_prompt, used_tokens) - """ - - # Format the date as a human readble string to give to the system - # Day of the week, Month Day, Year @ Hour:Minute:Second - # ex. "Monday, January 1, 2021 @ 12:00:00" - date = datetime.datetime.now().strftime("%A, %B %d, %Y @ %H:%M:%S") - variables = { - "date": date, - "name": self.name, - "chat_details": fmt_chat_details(chat), - "tools": self.tools, - "tool_schema": self.tool_schema, - "max_self_recurse_depth": self.max_self_recurse_depth, - } - - system_prompt = "" - for _, value in self.system_prompt_schema.dict().items(): - formatted_value = value.format(**variables) - formatted_value = formatted_value.replace("\n", " ") - system_prompt += f"{formatted_value}" - - system_prompt = f"{self.user_prepend}SYSTEM{self.line_separator}{system_prompt}{self.user_append}{self.line_separator}" - - # Update our used tokens count - used_tokens = calculate_number_of_tokens(system_prompt) - - # Check if we're over our token limit - if used_tokens > token_limit: - raise Exception("build_system_prompt(): system prompt exceeds token limit") - - return system_prompt, used_tokens diff --git a/src/agent/tools/__init__.py b/src/agent/tools/__init__.py deleted file mode 100644 index dc40cc4..0000000 --- a/src/agent/tools/__init__.py +++ /dev/null @@ -1,5 +0,0 @@ -from .schema import FunctionCall -from .functions import get_tools -from .executor import ToolExecutor - -__all__ = ["get_tools", "FunctionCall", "ToolExecutor"] diff --git a/src/agent/tools/executor.py b/src/agent/tools/executor.py deleted file mode 100644 index 4d276a6..0000000 --- a/src/agent/tools/executor.py +++ /dev/null @@ -1,85 +0,0 @@ -import os -from os import sys - -from .validator import ( - validate_function_call_schema, -) -from .utils import ( - validate_and_extract_tool_calls, -) -from .functions import ( - get_tools, -) -from logger import MessageSpan - -# NOTE: the sys path append is necessary to import the functions module -sys.path.append(os.path.join(os.path.dirname(__file__), ".")) -import functions - - -class ToolExecutor: - def __init__(self): - self.tools = get_tools() - - def process_completion_and_validate(self, completion): - validation, tool_calls, error_message = validate_and_extract_tool_calls( - completion - ) - - if validation: - return tool_calls, error_message - else: - tool_calls = None - return tool_calls, error_message - - def execute_function_call(self, tool_call): - function_name = tool_call.get("name") - function_to_call = getattr(functions, function_name, None) - function_args = tool_call.get("arguments", {}) - - if not function_to_call: - raise ValueError(f"Function {function_name} not found") - - function_response = function_to_call(*function_args.values()) - results_dict = f'{{"name": "{function_name}", "content": {function_response}}}' - return results_dict - - def handle_completion( - self, completion: str, depth: int, span: MessageSpan, line_separator="\n" - ) -> str | None: - try: - tool_calls, error_message = self.process_completion_and_validate(completion) - tool_message = "Current call depth: " + str(depth) + line_separator - if tool_calls: - for tool_call in tool_calls: - validation, message = validate_function_call_schema( - tool_call, self.tools - ) - if validation: - span.info( - f"Function call {tool_call.get('name')} is valid | arguments: {tool_call.get('arguments')}" - ) - try: - function_response = self.execute_function_call(tool_call) - tool_message += f"{line_separator}{function_response}{line_separator}{line_separator}" - span.info( - f"Function call {tool_call.get('name')} executed successfully with response: {function_response}" - ) - except Exception as e: - span.error( - f"Error executing function call {tool_call.get('name')}: {e}" - ) - tool_name = tool_call.get("name") - tool_message += f"{line_separator}There was an error when executing the function: {tool_name}{line_separator}Here's the error traceback: {e}{line_separator}Please call this function again with correct arguments within XML tags {line_separator}{line_separator}" - else: - span.warn(f"Function call {tool_call.get('name')} is invalid") - tool_name = tool_call.get("name") - tool_message += f"{line_separator}There was an error validating function call against function signature: {tool_name}{line_separator}Here's the error traceback: {message}{line_separator}Please call this function again with correct arguments within XML tags {line_separator}{line_separator}" - return tool_message - elif error_message: - span.error(f"Error parsing function calls: {error_message}") - tool_message += f"{line_separator}There was an error parsing function calls{line_separator}Here's the error stack trace: {error_message}{line_separator}Please call the function again with correct syntax within XML tags {line_separator}{line_separator}" - return tool_message - return None - except Exception as e: - raise e diff --git a/src/agent/tools/functions.py b/src/agent/tools/functions.py deleted file mode 100644 index 97e76e3..0000000 --- a/src/agent/tools/functions.py +++ /dev/null @@ -1,233 +0,0 @@ -import requests -import collections.abc -#hyper needs the four following aliases to be done manually. -collections.Iterable = collections.abc.Iterable -collections.Mapping = collections.abc.Mapping -collections.MutableSet = collections.abc.MutableSet -collections.MutableMapping = collections.abc.MutableMapping - -from hyper.contrib import HTTP20Adapter - -import yfinance as yf - -from typing import List -from duckduckgo_search import DDGS -from langchain.tools import tool -from langchain_core.utils.function_calling import convert_to_openai_tool - - -from config import Config -CONFIG = Config() - -@tool -def google_search(query): - """ Search google results. - Args: - query (str): The query to search for. - Returns: - list: A list of dictionaries containing the title, link, snippet, and other information about the search results.""" - - r = requests.get("https://www.searchapi.io/api/v1/search", - params = { - "q": query, - "engine": "google", - "api_key": CONFIG.searchapi_token - }) - - results = r.json() - organic_results = results.get("organic_results") - for result in organic_results: - if "favicon" in result: - del result["favicon"] - if "snippet_highlighted_words" in result: - del result["snippet_highlighted_words"] - return organic_results - -@tool -def get_text_from_page(url): - """ Get the text from a page. - Args: - url (str): The URL of the page to get the text from. - Returns: - str: The text from the page.""" - r = requests.get(url) - text = r.text - # now we scrape all the html and crap to keep only the text - from bs4 import BeautifulSoup - soup = BeautifulSoup(text, 'html.parser') - # kill all script and style elements - for script in soup(["script", "style"]): - script.decompose() # rip it out - # get text - text = soup.get_text() - # break into lines and remove leading and trailing space on each - lines = (line.strip() for line in text.splitlines()) - # break multi-headlines into a line each - chunks = (phrase.strip() for line in lines for phrase in line.split(" ")) - # drop blank lines - text = '\n'.join(chunk for chunk in chunks if chunk) - return text - -@tool -def duckduckgo_get_answer(query): - """ Get an answer from DuckDuckGo's Instant Answer API. - Args: - query (str): The query to search for. - Returns: - dict: A dictionary containing the answer, answer type, abstract, abstract source, abstract URL, definition, definition source, definition URL, and image. - """ - - session = requests.Session() - session.mount('https://', HTTP20Adapter()) - r = session.get("https://api.duckduckgo.com", - params = { - "q": query, - "format": "json", - "no_html": 1, - "skip_disambig": 1 - }) - output = r.json() - print(output) - return { - "answer": output.get("Answer"), - "answer_type": output.get("AnswerType"), - "abstract": output.get("Abstract"), - "abstract_text": output.get("AbstractText"), - "abstract_source": output.get("AbstractSource"), - "abstract_url": output.get("AbstractURL"), - "definition": output.get("Definition"), - "definition_source": output.get("DefinitionSource"), - "definition_url": output.get("DefinitionURL"), - "image": output.get("Image"), - } - - -# @tool -# def duckduckgo_search_text(query: str) -> dict: -# """ -# Search DuckDuckGo for the top result of a given text query. -# Use when probing for general information, or when a user requests a web search. -# Args: -# query (str): The query to search for. -# Returns: -# dict: the top 5 results from DuckDuckGo. If an error occurs, an exception is returns within the "error" key. -# """ -# try: -# search = DDGS() -# results = search.text(query, max_results=5) -# return {"results": results} -# except Exception as e: -# return {"error": str(e)} - - -# @tool -# def duckduckgo_search_answer(query: str) -> dict: -# """ -# Search DuckDuckGo for the top answer of a given question. -# Use when trying to answer a specific question that is outside the scope of the model's knowledge base. -# Args: -# query (str): The question to search for. -# Returns: -# dict: the top answer from DuckDuckGo. If an error occurs, an exception is returns within the "error" key. -# """ -# try: -# search = DDGS() -# results = search.answers(query) -# return {"results": results} -# except Exception as e: -# return {"error": str(e)} - - -@tool -def get_current_stock_price(symbol: str) -> float | None: - """ - Get the current stock price for a given symbol. - - Args: - symbol (str): The stock symbol. - - Returns: - float: The current stock price, or None if an error occurs. - """ - try: - stock = yf.Ticker(symbol) - # Use "regularMarketPrice" for regular market hours, or "currentPrice" for pre/post market - current_price = stock.info.get( - "regularMarketPrice", stock.info.get("currentPrice") - ) - return current_price if current_price else None - except Exception as _e: - return None - - -@tool -def get_current_cryptocurrency_price_usd(symbol: str) -> dict | None: - """ - Get current price of a cryptocurrency in USD. - - Args: - symbol (str): The non-truncated cryptocurrency name to get the price of in USD (e.g. "bitcoin", "ethereum", "solana", "aleph", etc.). - - Returns: - dict: The price of the cryptocurrency in the form {"coin": {"usd": }}, or None if an error occurs. - """ - - url = ( - f"https://api.coingecko.com/api/v3/simple/price?ids={symbol}&vs_currencies=usd" - ) - response = requests.get(url) - if response.status_code == 200: - output = response.json() - # CoinGecko returns an empty dictionary if the coin doesn't exist -- fun :upside_down_face: - if output == {}: - return None - return output - else: - return None - -@tool -def get_cryptocurrency_info(symbol: str) -> dict | None: - """ - Get the informations about a cryptocurrency. It includes where it's listed, - in what categories it is, the socials urls (twitter, telegram, homepage...), the market data as well in USD (includes information like the market cap, price, atl, ath...). - """ - - url = ( - f"https://api.coingecko.com/api/v3/coins/{symbol}?localization=false&tickers=false&market_data=true&community_data=false&developer_data=false&sparkline=false" - ) - response = requests.get(url) - if response.status_code == 200: - output = response.json() - if 'market_data' in output: - # let's keep only the usd price on all values that have currencies inside market_data - for key, value in output['market_data'].items(): - if isinstance(value, dict): - if 'usd' in value: - output['market_data'][key] = value['usd'] - # CoinGecko returns an empty dictionary if the coin doesn't exist -- fun :upside_down_face: - if output == {}: - return None - return output - else: - return None - - -def get_tools() -> List[dict]: - """ - Get our available tools as OpenAPI-compatible tools - """ - - # Register Functions Here - functions = [ - # duckduckgo_search_text, - # duckduckgo_search_answer, - google_search, - get_text_from_page, - duckduckgo_get_answer, - get_current_stock_price, - get_current_cryptocurrency_price_usd, - get_cryptocurrency_info - ] - - tools = [convert_to_openai_tool(f) for f in functions] - return tools diff --git a/src/agent/tools/schema.py b/src/agent/tools/schema.py deleted file mode 100644 index 1874b1a..0000000 --- a/src/agent/tools/schema.py +++ /dev/null @@ -1,23 +0,0 @@ -from pydantic import BaseModel -from typing import Dict, Literal, Optional - -class FunctionCall(BaseModel): - arguments: dict - """ - The arguments to call the function with, as generated by the model in JSON - format. Note that the model does not always generate valid JSON, and may - hallucinate parameters not defined by your function schema. Validate the - arguments in your code before calling your function. - """ - - name: str - """The name of the function to call.""" - -class FunctionDefinition(BaseModel): - name: str - description: Optional[str] = None - parameters: Optional[Dict[str, object]] = None - -class FunctionSignature(BaseModel): - function: FunctionDefinition - type: Literal["function"] diff --git a/src/agent/tools/utils.py b/src/agent/tools/utils.py deleted file mode 100644 index 7b56bf3..0000000 --- a/src/agent/tools/utils.py +++ /dev/null @@ -1,66 +0,0 @@ -import json -import ast -# import xml.etree.ElementTree as ET - - - -def parse_json_garbage(s): - s = s[next(idx for idx, c in enumerate(s) if c in "{["):] - try: - return json.loads(s) - except json.JSONDecodeError as e: - return json.loads(s[:e.pos]) - - -def validate_and_extract_tool_calls(agent_response): - validation_result = False - tool_calls = [] - error_message = None - - # Extract JSON data - try: - json_data = parse_json_garbage(agent_response) - if 'arguments' and 'name' in json_data: - tool_calls.append(json_data) - validation_result = True - except Exception as e: - # error_message = f"Cannot extract JSON data: {e}" - pass - - # try: - # # wrap content in root element - # xml_root_element = f"{agent_response}" - # root = ET.fromstring(xml_root_element) - - # # extract JSON data - # for element in root.findall(".//tool_call"): - # json_data = None - # try: - # json_text = element.text.strip() - # try: - # # Prioritize json.loads for better error handling - # json_data = json.loads(json_text) - # except json.JSONDecodeError as json_err: - # try: - # # Fallback to ast.literal_eval if json.loads fails - # json_data = ast.literal_eval(json_text) - # except (SyntaxError, ValueError) as eval_err: - # error_message = ( - # f"JSON parsing failed with both json.loads and ast.literal_eval:\n" - # f"- JSON Decode Error: {json_err}\n" - # f"- Fallback Syntax/Value Error: {eval_err}\n" - # f"- Problematic JSON text: {json_text}" - # ) - # continue - # except Exception as e: - # error_message = f"Cannot strip text: {e}" - - # if json_data is not None: - # tool_calls.append(json_data) - # validation_result = True - - # except ET.ParseError as err: - # error_message = f"XML Parse Error: {err}" - - # Return default values if no valid data is extracted - return validation_result, tool_calls, error_message diff --git a/src/agent/tools/validator.py b/src/agent/tools/validator.py deleted file mode 100644 index d3de5ac..0000000 --- a/src/agent/tools/validator.py +++ /dev/null @@ -1,151 +0,0 @@ -import ast -import json -from jsonschema import validate -from pydantic import ValidationError -from .schema import FunctionCall, FunctionSignature - - -def validate_function_call_schema(call, signatures): - try: - call_data = FunctionCall(**call) - except ValidationError as e: - return False, str(e) - - for signature in signatures: - try: - signature_data = FunctionSignature(**signature) - if signature_data.function.name == call_data.name: - # Validate types in function arguments - for arg_name, arg_schema in signature_data.function.parameters.get( - "properties", {} - ).items(): - if arg_name in call_data.arguments: - call_arg_value = call_data.arguments[arg_name] - if call_arg_value: - try: - validate_argument_type( - arg_name, call_arg_value, arg_schema - ) - except Exception as arg_validation_error: - return False, str(arg_validation_error) - - # Check if all required arguments are present - required_arguments = signature_data.function.parameters.get( - "required", [] - ) - result, missing_arguments = check_required_arguments( - call_data.arguments, required_arguments - ) - if not result: - return False, f"Missing required arguments: {missing_arguments}" - - return True, None - except Exception as e: - # Handle validation errors for the function signature - return False, str(e) - - # No matching function signature found - return False, f"No matching function signature found for function: {call_data.name}" - - -def check_required_arguments(call_arguments, required_arguments): - missing_arguments = [arg for arg in required_arguments if arg not in call_arguments] - return not bool(missing_arguments), missing_arguments - - -def validate_enum_value(arg_name, arg_value, enum_values): - if arg_value not in enum_values: - raise Exception( - f"Invalid value '{arg_value}' for parameter {arg_name}. Expected one of {', '.join(map(str, enum_values))}" - ) - - -def validate_argument_type(arg_name, arg_value, arg_schema): - arg_type = arg_schema.get("type", None) - if arg_type: - if arg_type == "string" and "enum" in arg_schema: - enum_values = arg_schema["enum"] - if None not in enum_values and enum_values != []: - try: - validate_enum_value(arg_name, arg_value, enum_values) - except Exception as e: - # Propagate the validation error message - raise Exception(f"Error validating function call: {e}") - - python_type = get_python_type(arg_type) - if not isinstance(arg_value, python_type): - raise Exception( - f"Type mismatch for parameter {arg_name}. Expected: {arg_type}, Got: {type(arg_value)}" - ) - - -def get_python_type(json_type): - type_mapping = { - "string": str, - "number": (int, float), - "integer": int, - "boolean": bool, - "array": list, - "object": dict, - "null": type(None), - } - return type_mapping[json_type] - - -def validate_json_data(json_object, json_schema): - valid = False - error_message = None - result_json = None - - try: - # Attempt to load JSON using json.loads - try: - result_json = json.loads(json_object) - except json.decoder.JSONDecodeError: - # If json.loads fails, try ast.literal_eval - try: - result_json = ast.literal_eval(json_object) - except (SyntaxError, ValueError) as e: - try: - result_json = extract_json_from_markdown(json_object) - except Exception as e: - error_message = f"JSON decoding error: {e}" - inference_logger.info( - f"Validation failed for JSON data: {error_message}" - ) - return valid, result_json, error_message - - # Return early if both json.loads and ast.literal_eval fail - if result_json is None: - error_message = "Failed to decode JSON data" - inference_logger.info(f"Validation failed for JSON data: {error_message}") - return valid, result_json, error_message - - # Validate each item in the list against schema if it's a list - if isinstance(result_json, list): - for index, item in enumerate(result_json): - try: - validate(instance=item, schema=json_schema) - inference_logger.info( - f"Item {index+1} is valid against the schema." - ) - except ValidationError as e: - error_message = f"Validation failed for item {index+1}: {e}" - break - else: - # Default to validation without list - try: - validate(instance=result_json, schema=json_schema) - except ValidationError as e: - error_message = f"Validation failed: {e}" - - except Exception as e: - error_message = f"Error occurred: {e}" - - if error_message is None: - valid = True - inference_logger.info("JSON data is valid against the schema.") - else: - inference_logger.info(f"Validation failed for JSON data: {error_message}") - - return valid, result_json, error_message diff --git a/src/agent/utils.py b/src/agent/utils.py deleted file mode 100644 index 6e43f5a..0000000 --- a/src/agent/utils.py +++ /dev/null @@ -1,41 +0,0 @@ -import sys -import nltk - -from telebot import types as telebot_types - -sys.path.append("..") -import database - - -def calculate_number_of_tokens(line: str): - """ - Determine the token length of a line of text - """ - tokens = nltk.word_tokenize(line) - return len(tokens) - - -def fmt_chat_details(chat: telebot_types.Chat, line_separator="\n"): - """ - Construct appropriate chat details for the model prompt - - Errors: - If the provided chat is neither a private nor group chat. - """ - - # TODO: some of these are only called on .getChat, these might not be available. Verify! - if chat.type in ["private"]: - return f"""Private Chat Details:{line_separator}Username: {chat.username or ""}{line_separator}First Name: {chat.first_name or ""}{line_separator}Last Name: {chat.last_name or ""}{line_separator}Bio: {chat.bio or ""}""" - - elif chat.type in ["group", "supergroup"]: - return f"""Group Chat Details:{line_separator}Title: {chat.title or ""}{line_separator}Description: {chat.description or ""}{line_separator}Members: {chat.active_usernames or ""}""" - else: - raise Exception("chat_details(): chat is neither private nor group") - - -def fmt_msg_user_name(user: database.User | telebot_types.User): - """ - Determine the appropriate identifier to which associate a user with - the chat context - """ - return user.username or ((user.first_name or "") + " " + (user.last_name or "")) diff --git a/src/bot.py b/src/bot.py deleted file mode 100644 index 78a6c2c..0000000 --- a/src/bot.py +++ /dev/null @@ -1,235 +0,0 @@ -import asyncio -from telebot import types as telebot_types, async_telebot - -from database import AsyncDatabase -from logger import Logger -from agent import Agent -from config import Config - -## Configuration Constants ## - -# Telegram Chat Commands -# NOTE: regardless of what commands you write, they will not be accessible to the user unless you register them here! -BOT_COMMANDS = [ - ("help", "Show the help menu"), - ("clear", "Clear the chat history from the chat bot"), -] - -## State ## -CONFIG = Config() -LOGGER = Logger(CONFIG.log_path, CONFIG.debug) - -try: - LOGGER.info("Setting up Bot...") - BOT = async_telebot.AsyncTeleBot(CONFIG.tg_token, parse_mode="MARKDOWN") - LOGGER.info("Setting up AsyncDatabase...") - DATABASE = AsyncDatabase(CONFIG.database_path) - LOGGER.info("Setting up Agent...") - AGENT = Agent(CONFIG.agent_config) -except Exception as e: - LOGGER.error(f"An unexpected error occurred during setup: {e}") - raise e - -## State Management ## - -BOT_NAMES = [ - "chatbot", - "bot", - "assistant", -] - - -# Set the bot's actual name and all of the potential names it might be called -def set_bot_name(name: str): - # Set the name of the bot on the agent -- this is it's telegram username and persona name - AGENT.set_name(name) - - BOT_NAMES.append(name) - # names = BOT_NAMES.copy() - # for n in names: - # BOT_NAMES.extend( - # [ - # n, - # n.lower(), - # n.upper(), - # # bunch of potential misspellings - # n.replace(" ", ""), - # n.replace("-", ""), - # n.replace(" ", "-"), - # n.replace("-", " "), - # n.replace(" ", "_"), - # n.replace("_", " "), - # n.replace("_", "-"), - # n.replace("-", "_"), - # # Missing letters at the edges of words - # n[1:], - # n[:-1], - # ] - # ) - - -## Handlers ## - -# Command Handlers - - -@BOT.message_handler(commands=["help"]) -async def help_command_handler(message: telebot_types.Message): - """ - Send a message to the user with a list of commands and their descriptions. - """ - # Log the command - span = LOGGER.get_span(message) - span.info("/help command called") - try: - # Send the message to the user - help_text = "The following commands are available:\n\n" - for command, description in BOT_COMMANDS: - help_text += f"/{command} - {description}\n" - await BOT.reply_to(message, help_text) - - # Ok - return None - except Exception as e: - span.error(f"Error handling /help command: {e}") - return None - - -@BOT.message_handler(commands=["clear"]) -async def clear_command_handler(message: telebot_types.Message): - """ - Clear the history of messages for a given chat. - """ - # Log the command - span = LOGGER.get_span(message) - span.info("/clear command called") - try: - # Send an ACK to the user - reply = await BOT.reply_to(message, "Clearing chat history...") - - # Clear the chat history from the database and the agent - chat_id = message.chat.id - await DATABASE.clear_chat_history(chat_id) - await AGENT.clear_chat(chat_id) - - # Send a message to the user acknowledging the clear - await BOT.edit_message_text( - chat_id=chat_id, - message_id=reply.message_id, - text="Chat history cleared.", - ) - - # Ok - return None - except Exception as e: - span.error(f"Error handling /clear command: {e}") - return None - - -# Message Type Handlers - - -@BOT.message_handler(content_types=["text"]) -async def text_message_handler(message: telebot_types.Message): - """ - Handle all text messages. - Use the agent to construct an informed response - """ - # Log the message - span = LOGGER.get_span(message) - span.info("Received text message") - reply = None - try: - chat_id = message.chat.id - - # Add the message to the chat history - await DATABASE.add_message(message, span=span) - - # Determine if the message is meant for the bot - # If the message is not a private message, check if the message mentions the bot - if message.chat.type not in ["private"]: - # Check if this isn't a reply to the bot - # If it is a reply to the bot, then we should respond - if not ( - (message.reply_to_message is not None) - and message.reply_to_message.from_user.username == AGENT.name() - ): - # Don't let the bot respond to messages which don't mention the bot - found = False - for target in BOT_NAMES: - if target in message.text: - LOGGER.info(f"Message mentions bot: {target}") - found = True - break - if not found: - return None - - # Send an initial response - result = "I'm thinking..." - reply = await BOT.reply_to(message, result) - - # TODO: Implement rendering logic here based on the code and content - # Attempt to reply to the message - try: - async for content in AGENT.yield_response(message, DATABASE, span): - # Check for an updated response, otherwise just do nothing - if content != result: - result = content - # Update the message - reply = await BOT.edit_message_text( - chat_id=chat_id, message_id=reply.message_id, text=result - ) - except Exception as e: - # Attempt to edit the message to indicate an error - reply = await BOT.edit_message_text( - chat_id=message.chat.id, - message_id=reply.message_id, - text="I'm sorry, I got confused. Please try again.", - ) - # Raise the error up to our handler - raise e - finally: - # Attempt to update the message history to reflect the final response - await DATABASE.add_message( - reply, use_edit_date=True, reply_to_message_id=message.message_id - ) - except Exception as e: - span.error(f"handle_text_message(): Error handling text message: {e}") - # if reply is None: - # await BOT.reply_to(message, "I'm sorry, I got confused. Please try again.") - finally: - return None - - -async def register_bot_commands(): - """ - Register the commands with the bot so that they are accessible to the user through the menu - """ - await BOT.set_my_commands( - [ - telebot_types.BotCommand(command, description) - for command, description in BOT_COMMANDS - ], - scope=telebot_types.BotCommandScopeDefault(), - ) - - -async def run(): - LOGGER.info("Starting Bot...") - try: - # Get the bot's user name and set the perosna name - bot_info = await BOT.get_me() - LOGGER.info(f"Bot started: {bot_info.username}") - set_bot_name(bot_info.username) - await register_bot_commands() - await BOT.polling() - except Exception as e: - LOGGER.error(f"An unexpected error occurred: {e}") - finally: - LOGGER.info("Stopping Bot...") - # Close all open connections - await AGENT.clear_all_chats() - - -if __name__ == "__main__": - asyncio.run(run()) diff --git a/src/commands/__init__.py b/src/commands/__init__.py new file mode 100644 index 0000000..a128db1 --- /dev/null +++ b/src/commands/__init__.py @@ -0,0 +1,40 @@ +from telebot.types import BotCommand, BotCommandScopeDefault, Message + +from src.commands.clear import clear_command_handler +from src.commands.help import help_command_handler +from src.commands.message import text_message_handler +from src.config import config + + +async def register_commands(): + """ + Register the Telegram commands with the bot so that they are accessible to the user through the menu + """ + await config.BOT.set_my_commands( + [ + BotCommand(command, description) + for command, description in config.BOT_COMMANDS + ], + scope=BotCommandScopeDefault(), + ) + + +# Define the message and command handlers + + +@config.BOT.message_handler(commands=["help"]) +async def help_command(msg: Message): + result = await help_command_handler(msg) + return result + + +@config.BOT.message_handler(commands=["clear"]) +async def clear_command(msg: Message): + result = await clear_command_handler(msg) + return result + + +@config.BOT.message_handler(content_types=["text"]) +async def text_message(msg: Message): + result = await text_message_handler(msg) + return result diff --git a/src/commands/clear.py b/src/commands/clear.py new file mode 100644 index 0000000..c8e1399 --- /dev/null +++ b/src/commands/clear.py @@ -0,0 +1,30 @@ +from telebot.types import Message + +from src.config import config + + +async def clear_command_handler(message: Message): + """ + Clear the history of messages for a given chat. + """ + # Log the command + span = config.LOGGER.get_span(message) + span.info("/clear command called") + try: + # Send an ACK to the user + reply = await config.BOT.reply_to(message, "Clearing chat history...") + + # Clear the chat history from the database and the agent + chat_id = message.chat.id + await config.DATABASE.clear_chat_history(chat_id) + + # Send a message to the user acknowledging the clear + await config.BOT.edit_message_text( + chat_id=chat_id, + message_id=reply.message_id, + text="Chat history cleared.", + ) + except Exception as e: + span.error(f"Error handling /clear command: {e}") + finally: + return None diff --git a/src/commands/help.py b/src/commands/help.py new file mode 100644 index 0000000..c3a0999 --- /dev/null +++ b/src/commands/help.py @@ -0,0 +1,22 @@ +from telebot.types import Message + +from src.config import config + + +async def help_command_handler(message: Message): + """ + Send a message to the user with a list of commands and their descriptions. + """ + # Log the command + span = config.LOGGER.get_span(message) + span.info("/help command called") + try: + # Send the message to the user + help_text = "The following commands are available:\n\n" + for command, description in config.BOT_COMMANDS: + help_text += f"/{command} - {description}\n" + await config.BOT.reply_to(message, help_text) + except Exception as e: + span.error(f"Error handling /help command: {e}") + finally: + return None diff --git a/src/commands/message.py b/src/commands/message.py new file mode 100644 index 0000000..31d6d58 --- /dev/null +++ b/src/commands/message.py @@ -0,0 +1,85 @@ +import telebot.types as telebot_types +from libertai_agents.interfaces.messages import Message as LibertaiMessage +from libertai_agents.interfaces.messages import MessageRoleEnum + +from src.config import config +from src.utils.telegram import ( + get_formatted_message_content, + get_formatted_username, + should_reply_to_message, +) + +# Max number of messages we will pass +MESSAGES_NUMBER = 50 + + +async def text_message_handler(message: telebot_types.Message): + """ + Handle all text messages. + Use the agent to construct an informed response + """ + # Logging setup + span = config.LOGGER.get_span(message) + span.info("Received text message") + + reply: telebot_types.Message | None + + try: + chat_id = message.chat.id + + # Add the message to the chat history + await config.DATABASE.add_message(message, span=span) + + should_reply = should_reply_to_message(message) + if should_reply is False: + span.info("Message not intended for the bot") + + # Send an initial response + # TODO: select a phrase randomly from a list to get a more dynamic result + result = "I'm thinking..." + reply = await config.BOT.reply_to(message, result) + + messages: list[LibertaiMessage] = [] + + chat_history = await config.DATABASE.get_chat_last_messages( + chat_id, MESSAGES_NUMBER, span=span + ) + # Iterate over the messages we've pulled + for chat_msg in reversed(chat_history): + message_username = get_formatted_username(chat_msg.from_user) + message_content = get_formatted_message_content(chat_msg) + # TODO: support multiple users with names + role = ( + MessageRoleEnum.assistant + if message_username == get_formatted_username(config.BOT_INFO) + else MessageRoleEnum.user + ) + messages.append(LibertaiMessage(role=role, content=message_content)) + + # TODO: pass system prompt with chat details when libertai-agents new version released + # and also tell it to answer directly (to avoid including "username in reply to username" in its answer) + async for response_msg in config.AGENT.generate_answer(messages): + if response_msg.content != result: + result = response_msg.content + # Update the message + reply = await config.BOT.edit_message_text( + chat_id=chat_id, message_id=reply.message_id, text=result + ) + + except Exception as e: + span.error(f"Error handling text message: {e}") + # Attempt to edit the message to indicate an error + + if reply is not None: + reply = await config.BOT.edit_message_text( + chat_id=message.chat.id, + message_id=reply.message_id, + text="I'm sorry, I got confused. Please try again.", + ) + finally: + # Attempt to update the message history to reflect the final response + if reply is not None: + await config.DATABASE.add_message( + reply, use_edit_date=True, reply_to_message_id=message.message_id + ) + return None diff --git a/src/config.py b/src/config.py index 05a5100..3904acf 100644 --- a/src/config.py +++ b/src/config.py @@ -1,44 +1,66 @@ import os -import yaml + from dotenv import load_dotenv +from libertai_agents.agents import ChatAgent +from libertai_agents.models import get_model +from telebot import async_telebot +from telebot.async_telebot import AsyncTeleBot +from telebot.types import User + +from src.tools import tools +from src.utils.database import AsyncDatabase +from src.utils.logger import Logger + +class _Config: + BOT_COMMANDS: list[tuple[str, str]] + LOGGER: Logger + BOT: AsyncTeleBot + DATABASE: AsyncDatabase + AGENT: ChatAgent -# TODO: getopt() for cmd line arguments -class Config: - tg_token: str - database_path: str - debug: bool - log_path: str | None - agent_config: dict + # Data that will be set at the beginning of the agent loop and shouldn't be used before + BOT_INFO: User def __init__(self): - # Load the environment variables load_dotenv() - # Set the Telegram token - tg_token = os.getenv("TG_TOKEN") - if tg_token is None: - raise Exception("Setting `TG_TOKEN` is required") - self.tg_token = tg_token - - searchapi_token = os.getenv("SEARCHAPI_TOKEN") - self.searchapi_token = searchapi_token - - # Set the Database URL. Default to in-memory for now - self.database_path = os.getenv("DATABASE_PATH", ":memory:") - - # Set the log path - self.log_path = os.getenv("LOG_PATH") - - # Determine if the DEBUG mode is set - debug = os.getenv("DEBUG", "True") - self.debug = debug == "True" - - # Read the agent configuration at the path - agent_config_path = os.getenv("AGENT_CONFIG_PATH", "agent.yaml") - - # Open the configration file for the model - with open(agent_config_path) as f: - # Load the config file - agent_config = yaml.safe_load(f) - self.agent_config = agent_config + self.BOT_COMMANDS = [ + ("help", "Show the help menu"), + ("clear", "Clear the chat history from the chat bot"), + ] + + # Logger + log_path = os.getenv("LOG_PATH") + debug = os.getenv("DEBUG", "False") == "True" + self.LOGGER = Logger(log_path, debug) + + try: + # Bot + self.LOGGER.info("Setting up bot...") + token = os.getenv("TELEGRAM_TOKEN") + self.BOT = async_telebot.AsyncTeleBot(token, parse_mode="MARKDOWN") + + # Database + self.LOGGER.info("Setting up database...") + database_path = os.getenv("DATABASE_PATH", ":memory:") + self.DATABASE = AsyncDatabase(database_path) + + # LibertAI Agent + self.LOGGER.info("Setting up agent...") + self.AGENT = ChatAgent( + model=get_model("NousResearch/Hermes-3-Llama-3.1-8B"), + system_prompt="You are a helpful assistant", + tools=tools, + expose_api=False, + ) + except Exception as e: + self.LOGGER.error(f"An unexpected error occurred during setup: {e}") + raise e + + # TODO: check if below variables are still required + # searchapi_token = os.getenv("SEARCHAPI_TOKEN") + # self.searchapi_token = searchapi_token + + +config = _Config() diff --git a/src/main.py b/src/main.py new file mode 100644 index 0000000..5e0bcfe --- /dev/null +++ b/src/main.py @@ -0,0 +1,25 @@ +import asyncio + +from src.commands import register_commands +from src.config import config + + +async def main(): + config.LOGGER.info("Starting bot...") + try: + # Get the bot's username + bot_info = await config.BOT.get_me() + config.BOT_INFO = bot_info + config.LOGGER.info(f"Bot started: {bot_info.username}") + + await register_commands() + config.LOGGER.info("Commands registered") + await config.BOT.polling() + except Exception as e: + config.LOGGER.error(f"An unexpected error occurred: {e}") + finally: + config.LOGGER.info("Stopping bot...") + + +if __name__ == "__main__": + asyncio.run(main()) diff --git a/src/tools/__init__.py b/src/tools/__init__.py new file mode 100644 index 0000000..015f38e --- /dev/null +++ b/src/tools/__init__.py @@ -0,0 +1,11 @@ +from libertai_agents.interfaces.tools import Tool + +from src.tools.finance import ( + get_current_cryptocurrency_price_usd, + get_current_stock_price, +) + +tools: list[Tool] = [ + Tool.from_function(get_current_stock_price), + Tool.from_function(get_current_cryptocurrency_price_usd), +] diff --git a/src/tools/finance.py b/src/tools/finance.py new file mode 100644 index 0000000..f4bb48b --- /dev/null +++ b/src/tools/finance.py @@ -0,0 +1,50 @@ +import requests +import yfinance # type: ignore + + +# TODO: add None in return type once transformers parsing issue is fixed +def get_current_stock_price(symbol: str) -> float: + """ + Get the current stock price for a given symbol. + + Args: + symbol: The stock symbol. + + Returns: + The current stock price, or None if an error occurs. + """ + try: + stock = yfinance.Ticker(symbol) + # Use "regularMarketPrice" for regular market hours, or "currentPrice" for pre- or post-market + current_price = stock.info.get( + "regularMarketPrice", stock.info.get("currentPrice") + ) + return current_price if current_price else None + except Exception as _e: + return None + + +# TODO: add None in return type once transformers parsing issue is fixed +def get_current_cryptocurrency_price_usd(symbol: str) -> dict: + """ + Get current price of a cryptocurrency in USD. + + Args: + symbol: The non-truncated cryptocurrency name to get the price of in USD (e.g. "bitcoin", "ethereum", "solana", "aleph", etc.). + + Returns: + The price of the cryptocurrency in a dict of the form {"coin": {"usd": }}, or None if an error occurs. + """ + + url = ( + f"https://api.coingecko.com/api/v3/simple/price?ids={symbol}&vs_currencies=usd" + ) + response = requests.get(url) + if response.status_code == 200: + output = response.json() + # CoinGecko returns an empty dictionary if the coin doesn't exist + if output == {}: + return None + return output + else: + return None diff --git a/src/utils/__init__.py b/src/utils/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/src/database.py b/src/utils/database.py similarity index 82% rename from src/database.py rename to src/utils/database.py index 3d1f0bc..58871cc 100644 --- a/src/database.py +++ b/src/utils/database.py @@ -1,20 +1,22 @@ +import asyncio +import datetime + from sqlalchemy import ( Column, - Integer, - String, DateTime, ForeignKey, - create_engine, - select, + Integer, + String, delete, + select, ) -from sqlalchemy.ext.asyncio import AsyncSession, create_async_engine +from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker, create_async_engine from sqlalchemy.ext.declarative import declarative_base +from sqlalchemy.orm import joinedload, relationship from sqlalchemy.schema import UniqueConstraint -from sqlalchemy.orm import sessionmaker, relationship, joinedload from telebot import types as telebot_types -import datetime -import asyncio + +from src.utils.logger import MessageSpan Base = declarative_base() @@ -22,7 +24,7 @@ # At the moment all of our fields are the same, allowing us to interchange telebot types with our database types -class User(Base): +class User(Base): # type: ignore __tablename__ = "users" id = Column(Integer, primary_key=True) # NOTE: Api docs says that a username maybe None, but we'll assume that it's always present @@ -34,7 +36,7 @@ class User(Base): messages = relationship("Message", back_populates="from_user") -class Message(Base): +class Message(Base): # type: ignore __tablename__ = "messages" id = Column(Integer, primary_key=True) @@ -56,39 +58,26 @@ class Message(Base): # Database Initialization and helpers - - -# Simple Synchronous Database for setting up the database -class SyncDatabase: - def __init__(self, database_path): - database_url = f"sqlite:///{database_path}" - self.engine = create_engine(database_url) - self.Session = sessionmaker(bind=self.engine) - Base.metadata.create_all(self.engine) - - class AsyncDatabase: - def __init__(self, database_path): + def __init__(self, database_path: str): database_url = f"sqlite+aiosqlite:///{database_path}" self.engine = create_async_engine(database_url) - self.AsyncSession = sessionmaker( + self.async_session = async_sessionmaker( self.engine, expire_on_commit=False, class_=AsyncSession ) # If this is an in-memory database, we need to create the tables - if database_path == ":memory:": - asyncio.run(self.create_tables()) + asyncio.run(self.create_tables()) async def create_tables(self): async with self.engine.begin() as conn: await conn.run_sync(Base.metadata.create_all) - # TODO: do we need the reply_to_message_id? async def add_message( self, message: telebot_types.Message, - use_edit_date=False, - reply_to_message_id=None, - span=None, + use_edit_date: bool = False, + reply_to_message_id: int | None = None, + span: MessageSpan | None = None, ): """ Add a message to the database @@ -100,7 +89,7 @@ async def add_message( span: The span to use for tracing. If None, no tracing is done """ - async with self.AsyncSession() as session: + async with self.async_session() as session: try: async with session.begin(): user = await session.execute( @@ -140,9 +129,15 @@ async def add_message( ) raise e - async def get_chat_last_messages(self, chat_id, limit=10, offset=0, span=None): + async def get_chat_last_messages( + self, + chat_id: int, + limit: int = 10, + offset: int = 0, + span: MessageSpan | None = None, + ) -> list[Message]: """ - Get the last messages in a chat in batches + Get the last messages in a chat in batches and returns them in desc order chat_id: The chat ID to get the messages from limit: The maximum number of messages to get @@ -150,7 +145,7 @@ async def get_chat_last_messages(self, chat_id, limit=10, offset=0, span=None): span: The span to use for tracing. If None, no tracing is done """ try: - async with self.AsyncSession() as session: + async with self.async_session() as session: result = await session.execute( select(Message) .options(joinedload(Message.from_user)) @@ -175,14 +170,14 @@ async def get_chat_last_messages(self, chat_id, limit=10, offset=0, span=None): ) raise e - async def clear_chat_history(self, chat_id, span=None): + async def clear_chat_history(self, chat_id: int, span: MessageSpan | None = None): """ Clear the chat history chat_id: The chat ID to clear the history of """ try: - async with self.AsyncSession() as session: + async with self.async_session() as session: async with session.begin(): await session.execute( delete(Message).where(Message.chat_id == chat_id) @@ -190,6 +185,6 @@ async def clear_chat_history(self, chat_id, span=None): except Exception as e: if span: span.error( - f"AysncDatabase::clear_chat_history(): Error clearing chat history: {e}" + f"AsyncDatabase::clear_chat_history(): Error clearing chat history: {e}" ) raise e diff --git a/src/logger.py b/src/utils/logger.py similarity index 65% rename from src/logger.py rename to src/utils/logger.py index 97ef18e..3b966af 100644 --- a/src/logger.py +++ b/src/utils/logger.py @@ -1,5 +1,6 @@ import logging import os +from logging import FileHandler, LogRecord, StreamHandler from telebot import types as telebot_types @@ -7,26 +8,28 @@ # Log Formatter # Used to trace events that span the handling of a message within a chat class LogFormatter(logging.Formatter): - def format(self, record): + def format(self, record: LogRecord): + new_record = record + if hasattr(record, "chat_id"): - record.chat_id = record.chat_id - # Note: this should never happen, but if it does, we'll just set the chat ID and message ID to N/A + new_record.chat_id = record.chat_id else: - record.chat_id = "N/A" + # This should never happen, but if it does, we'll just set the chat ID to N/A + new_record.chat_id = "N/A" if hasattr(record, "message_id"): - record.message_id = record.message_id - # Note: this should never happen, but if it does, we'll just set the chat ID and message ID to N/A + new_record.message_id = record.message_id else: - record.message_id = "N/A" + # This should never happen, but if it does, we'll just set the message ID to N/A + new_record.message_id = "N/A" - return super().format(record) + return super().format(new_record) class Logger: logger: logging.Logger - def __init__(self, log_path=None, debug=False): + def __init__(self, log_path: str | None = None, debug: bool = False): """ Initialize a new Log instance - log_path - where to send output. If `None` logs are sent to the console @@ -46,9 +49,16 @@ def __init__(self, log_path=None, debug=False): # Hide debug logs from other libraries logging.getLogger("asyncio").setLevel(logging.WARNING) logging.getLogger("aiosqlite").setLevel(logging.WARNING) + logging.getLogger("urllib3").setLevel(logging.WARNING) + + # Tool libraries + logging.getLogger("yfinance").setLevel(logging.WARNING) + logging.getLogger("peewee").setLevel(logging.WARNING) + else: logging.basicConfig(level=logging.INFO) + handler: FileHandler | StreamHandler # Set where to send logs if log_path is not None and log_path.strip() != "": # Create parent directories if they don't exist @@ -64,13 +74,19 @@ def __init__(self, log_path=None, debug=False): if logger.hasHandlers(): logger.handlers.clear() logger.addHandler(handler) + logger.propagate = False self.logger = logger def get_span(self, message: telebot_types.Message): return MessageSpan(self, message.chat.id, message.message_id) - def warn(self, message, chat_id=None, message_id=None): + def warn( + self, + message: str, + chat_id: int | None = None, + message_id: int | None = None, + ): extra = {} if chat_id: extra["chat_id"] = chat_id @@ -78,7 +94,12 @@ def warn(self, message, chat_id=None, message_id=None): extra["message_id"] = message_id self.logger.warning(message, extra=extra) - def debug(self, message, chat_id=None, message_id=None): + def debug( + self, + message: str, + chat_id: int | None = None, + message_id: int | None = None, + ): extra = {} if chat_id: extra["chat_id"] = chat_id @@ -87,7 +108,12 @@ def debug(self, message, chat_id=None, message_id=None): self.logger.debug(message, extra=extra) - def info(self, message, chat_id=None, message_id=None): + def info( + self, + message: str, + chat_id: int | None = None, + message_id: int | None = None, + ): extra = {} if chat_id: extra["chat_id"] = chat_id @@ -96,7 +122,12 @@ def info(self, message, chat_id=None, message_id=None): self.logger.info(message, extra=extra) - def error(self, message, chat_id=None, message_id=None): + def error( + self, + message: str, + chat_id: int | None = None, + message_id: int | None = None, + ): extras = {} if chat_id: extras["chat_id"] = chat_id @@ -107,19 +138,19 @@ def error(self, message, chat_id=None, message_id=None): class MessageSpan: - def __init__(self, logger, chat_id, message_id): + def __init__(self, logger: Logger, chat_id: int, message_id: int): self.logger = logger self.chat_id = chat_id self.message_id = message_id - def warn(self, message): + def warn(self, message: str): self.logger.warn(message, chat_id=self.chat_id, message_id=self.message_id) - def debug(self, message): + def debug(self, message: str): self.logger.debug(message, chat_id=self.chat_id, message_id=self.message_id) - def info(self, message): + def info(self, message: str): self.logger.info(message, chat_id=self.chat_id, message_id=self.message_id) - def error(self, message): + def error(self, message: str): self.logger.error(message, chat_id=self.chat_id, message_id=self.message_id) diff --git a/src/utils/telegram.py b/src/utils/telegram.py new file mode 100644 index 0000000..0d6ed99 --- /dev/null +++ b/src/utils/telegram.py @@ -0,0 +1,60 @@ +from telebot.types import Message, User + +from src.config import config + + +def get_mentions_in_message(message: Message) -> list[str]: + """Returns an array of mentions inside the text of a message. Each mention is in the format '@username'""" + mentions: list[str] = [] + + if message.entities is None: + return mentions + for entity in message.entities: + if entity.type == "mention": + mention_text = message.text[entity.offset : entity.offset + entity.length] + mentions.append(mention_text) + return mentions + + +def get_formatted_username(user: User) -> str: + """ + Determine the appropriate identifier to which associate a user with + the chat context + """ + return user.username or f'{user.first_name or ""} {user.last_name or ""}' + + +def get_formatted_message_content(message: Message) -> str: + """ + Format either a telebot message into a string representing its content + """ + sender = get_formatted_username(message.from_user) + is_reply = message.reply_to_message is not None + + if is_reply: + reply_to_username = get_formatted_username(message.reply_to_message.from_user) + sender = f"{sender} (in reply to {reply_to_username})" + + return f"{sender}\n{message.text}" + + +def should_reply_to_message(message: Message) -> bool: + """ + Determines if a message is intended for our bot or not + """ + if message.chat.type == "private": + # Always reply to DMs + return True + else: + if ( + message.reply_to_message is not None + and message.reply_to_message.from_user.username == config.BOT_INFO.username + ): + # The message is a reply to a message that is the bot + return True + + mentions = get_mentions_in_message(message) + if f"@{config.BOT_INFO.username}" in mentions: + # Message is mentioning the bot + return True + return False diff --git a/templates/system.yaml b/templates/system.yaml deleted file mode 100644 index 3efd3af..0000000 --- a/templates/system.yaml +++ /dev/null @@ -1,42 +0,0 @@ -# System Promp Configuration -# NOTE: draws heavily from https://github.com/NousResearch/Hermes-Function-Calling/tree/main/prompt_assets -# TODO: this is optimized for function calling accuracy, not speed, I need to vet how much context we can remove from this - -# Relevant personal bio -# {name} - the user name of the telegram bot -# {date} - today's date -# {chat_details} - the details of the chat the bot is participating in -Role: | - You are a function calling AI Chat Assistant running on a decentralized LLM. - Your role is to assist chat participants with their questions and concerns, using the resources available to you. - You can call only one function at a time and analyse data you get from function response. - You are provided with function signatures within XML tags. - The current date is: {date}. - You will be addressed as {name}, bot, chat-bot, or assistant. - You will be participating in the following chat: - {chat_details} -# Stated Goals + Constraints -Objective: | - You may use agentic frameworks for reasoning and planning to help with user query. - Please call a function and wait for function results to be provided to you in the next iteration. - Don't make assumptions about what values to plug into function arguments. - Once you have called a function, results will be fed back to you within XML tags. - Don't make assumptions about tool results if XML tags are not present since function hasn't been executed yet. - Analyze the data once you get the results and call another function. - At each iteration please continue adding your analysis to the previous summary. - Your final response should directly answer the user query with an analysis or summary of the results of function calls. - Only your final response will be shown to users! -# Tools descripition, formatting, and Constraints -# {tools} - the tools the bot has access to. See src/agent/prompter.py for details on how this is formatted -# {tool_schema} - json schema describing how these functions should be called -# {max_self_recurse_depth} - maximum level of self recursion the agent is allowed to initialize -# TODO: maybe add arbitrary generated code execution -Tools: | - Here are the available tools: - {tools} - Use the following pydantic model json schema for each function call you will make: - {tool_schema} - For each tool call return a valid json object (using double quotes) with tool name and arguments within XML tags as follows: - - {{"arguments": , "name": }} -