├── agents ├── __init__.py └── curation_buddy │ ├── __init__.py │ ├── prompts │ ├── summarize.yaml │ ├── response_urls.yaml │ ├── response.yaml │ └── thought.yaml │ └── chain.py ├── .dockerignore ├── .gitignore ├── Procfile ├── .env.template ├── fly.toml ├── pyproject.toml ├── utils.py ├── README.md ├── Dockerfile ├── bot.py └── poetry.lock /agents/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /.dockerignore: -------------------------------------------------------------------------------- 1 | fly.toml 2 | -------------------------------------------------------------------------------- /agents/curation_buddy/__init__.py: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | .env 2 | 3 | .venv 4 | 5 | .DS_Store 6 | 7 | **/__pycache__ 8 | 9 | -------------------------------------------------------------------------------- /Procfile: -------------------------------------------------------------------------------- 1 | # TODO: Modify this Procfile to fit your needs 2 | web: gunicorn app:app 3 | -------------------------------------------------------------------------------- /.env.template: -------------------------------------------------------------------------------- 1 | BOT_TOKEN= 2 | OPENAI_API_KEY= 3 | APIFY_API_TOKEN= 4 | LANGCHAIN_PROJECT= 5 | LANGCHAIN_TRACING_V2= 6 | LANCHAIN_API_KEY= -------------------------------------------------------------------------------- /agents/curation_buddy/prompts/summarize.yaml: -------------------------------------------------------------------------------- 1 | _type: prompt 2 | input_variables: 3 | ["webpage_content"] 4 | template: > 5 | You are tasked with extracting the topic of the following webpage content: 6 | --- 7 | {webpage_content} 8 | --- 9 | What's this content about? Respond with one sentence only. 10 | 11 | -------------------------------------------------------------------------------- /fly.toml: -------------------------------------------------------------------------------- 1 | # fly.toml app configuration file generated for curation-buddy on 2024-03-14T14:54:04-04:00 2 | # 3 | # See https://fly.io/docs/reference/configuration/ for information about how to use this file. 4 | # 5 | 6 | app = 'curation-buddy' 7 | primary_region = 'mia' 8 | 9 | 10 | [processes] 11 | app = "python -u bot.py" 12 | 13 | [[vm]] 14 | memory = '1gb' 15 | cpu_kind = 'shared' 16 | cpus = 1 17 | -------------------------------------------------------------------------------- /agents/curation_buddy/prompts/response_urls.yaml: -------------------------------------------------------------------------------- 1 | _type: prompt 2 | input_variables: 3 | ["summaries", "chat_history"] 4 | template: > 5 | You are tasked with taking in article summaries and using them to generate an engaging response to the user. They just dropped us links to articles with the following topics: 6 | --- 7 | {summaries} 8 | --- 9 | Here's the current chat history: 10 | --- 11 | {chat_history} 12 | --- 13 | Keep the conversation going! 14 | 15 | -------------------------------------------------------------------------------- /agents/curation_buddy/prompts/response.yaml: -------------------------------------------------------------------------------- 1 | _type: prompt 2 | input_variables: 3 | ["input", "answers", "chat_history"] 4 | template: > 5 | Generate a response given the following input, context, and chat history 6 | 7 | Input: {input} 8 | Thought: {thought} 9 | Context: {answers} 10 | Chat History: {chat_history} 11 | 12 | Keep your responses concise and specific, always end each message with ONLY ONE topically relevant comment, question, or point that drives the conversation forward 13 | 14 | -------------------------------------------------------------------------------- /agents/curation_buddy/prompts/thought.yaml: -------------------------------------------------------------------------------- 1 | _type: prompt 2 | input_variables: 3 | ["input", "chat_history"] 4 | template: > 5 | You are an intellectual sparring partner tasked with generating a thought about your interlocutor's latest message. 6 | 7 | Chat History: """{chat_history}""" 8 | 9 | User Input: """{input}""" 10 | 11 | Generate a "thought" that makes a prediction about the user's needs given current dialogue and a numbered list of other pieces of data that would help improve your prediction. -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [tool.poetry] 2 | name = "curation-buddy" 3 | version = "0.1.0" 4 | description = "" 5 | authors = ["vintro "] 6 | readme = "README.md" 7 | 8 | [tool.poetry.dependencies] 9 | python = "^3.11" 10 | honcho-ai = "0.0.5" 11 | langchain-core = "^0.1.31" 12 | langchain-community = "^0.0.28" 13 | langchain-openai = "^0.0.8" 14 | python-dotenv = "^1.0.1" 15 | py-cord = "^2.5.0" 16 | apify-client = "^1.6.4" 17 | 18 | 19 | [build-system] 20 | requires = ["poetry-core"] 21 | build-backend = "poetry.core.masonry.api" 22 | -------------------------------------------------------------------------------- /utils.py: -------------------------------------------------------------------------------- 1 | from typing import List 2 | from langchain_core.messages import AIMessage, HumanMessage 3 | 4 | 5 | def langchain_message_converter(messages: List): 6 | new_messages = [] 7 | for message in messages: 8 | if message.is_user: 9 | new_messages.append(HumanMessage(content=message.content)) 10 | else: 11 | new_messages.append(AIMessage(content=message.content)) 12 | return new_messages 13 | 14 | def langchain_message_unpacker(chat_history: List): 15 | unpacked_messages = [("user: " + message.content if isinstance(message, HumanMessage) else "ai: " + message.content) for message in chat_history] 16 | return "\n".join(unpacked_messages) 17 | 18 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # curation buddy 🤓📚 2 | 3 | this is. curation buddy 4 | 5 | # setup 6 | run the following: 7 | ```bash 8 | poetry install 9 | poetry shell 10 | ``` 11 | 12 | then copy the `.env.template` into a `.env` file and fill in the values: 13 | ``` 14 | BOT_TOKEN= 15 | OPENAI_API_KEY= 16 | APIFY_API_TOKEN= 17 | LANGCHAIN_PROJECT= 18 | LANGCHAIN_TRACING_V2= 19 | LANCHAIN_API_KEY= 20 | ``` 21 | the langchain values are optional if you want to use langsmith. 22 | 23 | # start 24 | run the bot: 25 | ```bash 26 | python bot.py 27 | ``` 28 | 29 | now your curation agent is running. the honcho fact memory bot is listening to the honcho database waiting to derive facts when new messages are written there. the curation bot is working in discord waiting to entertain your curations :) 30 | -------------------------------------------------------------------------------- /Dockerfile: -------------------------------------------------------------------------------- 1 | # https://pythonspeed.com/articles/base-image-python-docker-images/ 2 | # https://testdriven.io/blog/docker-best-practices/ 3 | FROM python:3.11-slim-bullseye 4 | 5 | RUN apt-get update && apt-get install -y build-essential 6 | 7 | WORKDIR /app 8 | 9 | # https://stackoverflow.com/questions/53835198/integrating-python-poetry-with-docker 10 | ENV PYTHONFAULTHANDLER=1 \ 11 | PYTHONUNBUFFERED=1 \ 12 | PYTHONHASHSEED=random \ 13 | PIP_NO_CACHE_DIR=off \ 14 | PIP_DISABLE_PIP_VERSION_CHECK=on \ 15 | PIP_DEFAULT_TIMEOUT=100 \ 16 | POETRY_VERSION=1.4.1 17 | 18 | RUN pip install "poetry==$POETRY_VERSION" 19 | 20 | # Copy only requirements to cache them in docker layer 21 | WORKDIR /app 22 | COPY poetry.lock pyproject.toml /app/ 23 | 24 | # Project initialization: 25 | RUN poetry config virtualenvs.create false \ 26 | && poetry install --no-root --no-interaction --no-ansi --without dev 27 | 28 | WORKDIR /app 29 | 30 | RUN addgroup --system app && adduser --system --group app 31 | USER app 32 | 33 | COPY . . 34 | 35 | # https://stackoverflow.com/questions/29663459/python-app-does-not-print-anything-when-running-detached-in-docker 36 | CMD ["python", "-u", "bot.py"] 37 | -------------------------------------------------------------------------------- /bot.py: -------------------------------------------------------------------------------- 1 | import os 2 | from uuid import uuid1 3 | import discord 4 | from dotenv import load_dotenv 5 | from honcho import Honcho 6 | from utils import langchain_message_converter 7 | from agents.curation_buddy.chain import CurationBuddyChain 8 | 9 | load_dotenv() 10 | 11 | intents = discord.Intents.default() 12 | intents.messages = True 13 | intents.message_content = True 14 | intents.members = True 15 | 16 | app_name = str(uuid1()) 17 | 18 | # honcho = Honcho(app_name=app_name, base_url="http://localhost:8000") # uncomment to use local 19 | honcho = Honcho(app_name=app_name) # uses demo server at https://demo.honcho.dev 20 | honcho.initialize() 21 | 22 | bot = discord.Bot(intents=intents) 23 | 24 | 25 | @bot.event 26 | async def on_ready(): 27 | print(f"We have logged in as {bot.user}") 28 | 29 | 30 | @bot.event 31 | async def on_member_join(member): 32 | await member.send( 33 | f"*Hello {member.name}, welcome to the server! This is Curation Buddy - a demo bot built with Honcho,* " 34 | "*meant to engage you with links you share.* " 35 | "*To get started, just type a message in this channel and the bot will respond.* " 36 | "*You can also drop links within those messages, and the bot will read them and respond.*" 37 | "*Over time, it will remember facts about you and use them to make the conversation more personal.* " 38 | "*You can use the /restart command to restart the conversation at any time.* " 39 | "*If you have any questions or feedback, feel free to ask in the #honcho channel.* " 40 | "*Enjoy!*" 41 | ) 42 | 43 | 44 | @bot.event 45 | async def on_message(message): 46 | if message.author == bot.user or message.guild is not None: 47 | return 48 | 49 | user_id = f"discord_{str(message.author.id)}" 50 | user = honcho.get_or_create_user(user_id) 51 | location_id = str(message.channel.id) 52 | 53 | sessions = list(user.get_sessions_generator(location_id, reverse=True)) 54 | if sessions: 55 | session = sessions[0] if sessions[0].is_active else user.create_session(location_id) 56 | else: 57 | session = user.create_session(location_id) 58 | 59 | history = list(session.get_messages_generator())[:5] 60 | chat_history = langchain_message_converter(history) 61 | 62 | inp = message.content 63 | user_message = session.create_message(is_user=True, content=inp) 64 | 65 | async with message.channel.typing(): 66 | response = await CurationBuddyChain.chat( 67 | chat_history=chat_history, 68 | input=inp, 69 | message=user_message, 70 | session=session 71 | ) 72 | await message.channel.send(response) 73 | 74 | session.create_message(is_user=False, content=response) 75 | 76 | 77 | @bot.slash_command(name="restart", description="Restart the Conversation") 78 | async def restart(ctx): 79 | user_id = f"discord_{str(ctx.author.id)}" 80 | user = honcho.get_or_create_user(user_id) 81 | location_id = str(ctx.channel_id) 82 | sessions = list(user.get_sessions_generator(location_id, reverse=True)) 83 | sessions[0].close() if len(sessions) > 0 else None 84 | 85 | msg = ( 86 | "Great! The conversation has been restarted. What would you like to talk about?" 87 | ) 88 | await ctx.respond(msg) 89 | 90 | 91 | bot.run(os.environ["BOT_TOKEN"]) 92 | -------------------------------------------------------------------------------- /agents/curation_buddy/chain.py: -------------------------------------------------------------------------------- 1 | import os, re, aiohttp 2 | from typing import List 3 | from dotenv import load_dotenv 4 | from langchain_openai import ChatOpenAI 5 | from langchain_core.prompts import ChatPromptTemplate, SystemMessagePromptTemplate, load_prompt 6 | from langchain_core.output_parsers import NumberedListOutputParser 7 | from langchain_community.utilities import ApifyWrapper 8 | from langchain_core.document_loaders.base import Document 9 | from honcho import Session, Message 10 | from utils import langchain_message_unpacker 11 | 12 | load_dotenv() 13 | 14 | SYSTEM_THOUGHT = load_prompt(os.path.join(os.path.dirname(__file__), 'prompts/thought.yaml')) 15 | SYSTEM_RESPONSE = load_prompt(os.path.join(os.path.dirname(__file__), 'prompts/response.yaml')) 16 | SYSTEM_RESPONSE_URLS = load_prompt(os.path.join(os.path.dirname(__file__), 'prompts/response_urls.yaml')) 17 | SYSTEM_SUMMARIZE = load_prompt(os.path.join(os.path.dirname(__file__), 'prompts/summarize.yaml')) 18 | 19 | 20 | class CurationBuddyChain: 21 | """Chain for executing the curation buddy logic""" 22 | apify = ApifyWrapper() 23 | output_parser = NumberedListOutputParser() 24 | gpt_35: ChatOpenAI = ChatOpenAI(model="gpt-3.5-turbo") 25 | gpt_4: ChatOpenAI = ChatOpenAI(model="gpt-4-turbo-preview") 26 | system_thought: SystemMessagePromptTemplate = SystemMessagePromptTemplate(prompt=SYSTEM_THOUGHT) 27 | system_response: SystemMessagePromptTemplate = SystemMessagePromptTemplate(prompt=SYSTEM_RESPONSE) 28 | system_response_urls: SystemMessagePromptTemplate = SystemMessagePromptTemplate(prompt=SYSTEM_RESPONSE_URLS) 29 | system_summarize: SystemMessagePromptTemplate = SystemMessagePromptTemplate(prompt=SYSTEM_SUMMARIZE) 30 | 31 | def __init__(self) -> None: 32 | pass 33 | 34 | @classmethod 35 | async def check_for_link(cls, input: str) -> List[str]: 36 | url_pattern = re.compile(r'http[s]?://(?:[a-zA-Z]|[0-9]|[$-_@.&+]|[!*\\(\\),]|(?:%[0-9a-fA-F][0-9a-fA-F]))+') 37 | urls = re.findall(url_pattern, input) 38 | print(f"LINK(S) DETECTED: {urls}") 39 | return urls 40 | 41 | @classmethod 42 | async def get_webpage_content(cls, links: List[str]) -> List[str]: 43 | docs = [] 44 | for link in links: 45 | loader = cls.apify.call_actor( 46 | actor_id="apify/website-content-crawler", 47 | run_input={"startUrls": [{"url": link}], "maxCrawlPages": 1, "crawlerType": "cheerio"}, 48 | dataset_mapping_function=lambda item: Document( 49 | page_content=item["text"] or "", metadata={"source": item["url"]} 50 | ), 51 | ) 52 | docs.append(loader.load()) 53 | return docs 54 | 55 | @classmethod 56 | async def summarize_webpage_content(cls, webpage_content: str) -> str: 57 | """Summarize the webpage content""" 58 | summarize_prompt = ChatPromptTemplate.from_messages([ 59 | cls.system_summarize 60 | ]) 61 | chain = summarize_prompt | cls.gpt_4 62 | response = await chain.ainvoke({ 63 | "webpage_content": webpage_content 64 | }) 65 | return response.content 66 | 67 | @classmethod 68 | async def generate_response_urls(cls, summaries: List[str], chat_history: List[str]) -> str: 69 | """Generate a response asking the user about the URLs they posted""" 70 | response_urls_prompt = ChatPromptTemplate.from_messages([ 71 | cls.system_response_urls 72 | ]) 73 | chain = response_urls_prompt | cls.gpt_35 74 | response = await chain.ainvoke({ 75 | "summaries": summaries, 76 | "chat_history": langchain_message_unpacker(chat_history) 77 | }) 78 | return response.content 79 | 80 | @classmethod 81 | async def generate_thought(cls, input: str, chat_history: List[str], max_retries: int = 3) -> str: 82 | """Generate a thought about the user's input along with a list of questions that'd help it better serve the user""" 83 | thought_prompt = ChatPromptTemplate.from_messages([ 84 | cls.system_thought 85 | ]) 86 | chain = thought_prompt | cls.gpt_4 87 | retries = 0 88 | while retries < max_retries: 89 | try: 90 | response = await chain.ainvoke({ 91 | "input": input, 92 | "chat_history": langchain_message_unpacker(chat_history) 93 | }) 94 | questions = cls.output_parser.parse(response.content) 95 | break # Exit loop if successful 96 | except Exception as e: 97 | print(f"Attempt {retries + 1}: Error parsing questions - {e}") 98 | retries += 1 99 | if retries == max_retries: 100 | print("Max retries reached. Moving on without parsing questions.") 101 | return response.content, questions 102 | 103 | @classmethod 104 | async def ask_questions(cls, session: Session, questions: List[str]) -> List[str]: 105 | """Loop over the questions and ask honcho about them""" 106 | answers = [] 107 | for question in questions: 108 | answer = session.chat(question) 109 | answers.append(answer) 110 | return answers 111 | 112 | @classmethod 113 | async def generate_response(cls, input: str, thought: str, answers: List[str], chat_history: List[str]) -> str: 114 | """Collate the answers to the questions and generate a response with those as context""" 115 | response_prompt = ChatPromptTemplate.from_messages([ 116 | cls.system_response 117 | ]) 118 | chain = response_prompt | cls.gpt_4 119 | response = await chain.ainvoke({ 120 | "input": input, 121 | "thought": thought, 122 | "answers": answers, 123 | "chat_history": langchain_message_unpacker(chat_history) 124 | }) 125 | return response.content 126 | 127 | 128 | 129 | @classmethod 130 | async def chat( 131 | cls, 132 | input: str, 133 | chat_history: List[str], 134 | message: Message, 135 | session: Session, 136 | ) -> str: 137 | """Chat with the user""" 138 | 139 | urls = await cls.check_for_link(input) 140 | if urls: 141 | contents = await cls.get_webpage_content(urls) 142 | summaries = [] 143 | if contents: # Check if contents is not empty 144 | for content in contents: 145 | # Ensure content is loaded correctly and has page_content attribute 146 | summary = await cls.summarize_webpage_content(content[0].page_content) 147 | summaries.append(summary) 148 | # Generate response based on summaries 149 | response = await cls.generate_response_urls(summaries, chat_history) 150 | return response 151 | 152 | # no links, let's continue the convo 153 | thought, questions = await cls.generate_thought(input, chat_history) 154 | session.create_metamessage(message, metamessage_type="thought", content=thought) # write intermediate thought to honcho 155 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