From 74297ff11608ed12defb8df7b688b4d4b3e8b554 Mon Sep 17 00:00:00 2001 From: Zack Date: Thu, 26 Oct 2023 12:02:21 -0500 Subject: [PATCH] feat: Cleanup dockerfiles --- apps/BingBot/{bing_bot.py => bot.py} | 2 +- apps/BingBot/cogs/edgegpt.py | 139 +++++++----------- apps/BingBot/cogs/event.py | 67 ++++++--- apps/BingBot/cogs/help.py | 1 - apps/BingBot/compose.yaml | 3 +- apps/BingBot/requirements.txt | 6 +- apps/MythGen/main.py | 75 ---------- apps/open-sourcerer/main.py | 202 ++++++++++----------------- stderr_log.txt | 46 ------ 9 files changed, 180 insertions(+), 361 deletions(-) rename apps/BingBot/{bing_bot.py => bot.py} (97%) delete mode 100644 apps/MythGen/main.py delete mode 100644 stderr_log.txt diff --git a/apps/BingBot/bing_bot.py b/apps/BingBot/bot.py similarity index 97% rename from apps/BingBot/bing_bot.py rename to apps/BingBot/bot.py index 233ca9a7..f636e969 100644 --- a/apps/BingBot/bing_bot.py +++ b/apps/BingBot/bot.py @@ -43,7 +43,7 @@ def check_verion() -> None: @bot.event async def on_ready(): bot_status = discord.Status.online - bot_activity = discord.Activity(type=discord.ActivityType.playing, name="bing.com") + # bot_activity = discord.Activity(type=discord.ActivityType.playing, name="bing.com") await bot.change_presence(status=bot_status, activity=bot_activity) for Filename in os.listdir("./cogs"): if Filename.endswith(".py"): diff --git a/apps/BingBot/cogs/edgegpt.py b/apps/BingBot/cogs/edgegpt.py index 6b303418..7c84b256 100644 --- a/apps/BingBot/cogs/edgegpt.py +++ b/apps/BingBot/cogs/edgegpt.py @@ -19,7 +19,6 @@ users_chatbot = {} users_image_generator = {} user_conversation_style = {} - async def init_chatbot(user_id): with open("./cookies.json", encoding="utf-8") as file: cookie_json = json.load(file) @@ -27,40 +26,51 @@ async def init_chatbot(user_id): if cookie.get("name") == "_U": auth_cookie = cookie.get("value") break - + auth_cookie = os.environ.get("AUTH_COOKIE") auth_cookie_SRCHHPGUSR = os.environ.get("AUTH_COOKIE_SRCHHPGUSR") - # auth_cookie_SRCHHPGUSR = os.environ.get("AUTH_COOKIE_SRCHHPGUSR") users_chatbot[user_id] = UserChatbot(cookies=cookie_json) users_image_generator[user_id] = ImageGenAsync(auth_cookie, quiet=True) user_conversation_style[user_id] = "balanced" - class UserChatbot: def __init__(self, cookies): self.chatbot = Chatbot(cookies=cookies) - async def send_message(self, interaction, message, conversation_style): - await send_message(self.chatbot, interaction, message, conversation_style) - - async def create_image(self, interaction, prompt: str, image_generator): - await create_image(interaction, prompt, image_generator) - - async def reset(self): - await self.chatbot.reset() - - + async def send_message(self, interaction, message, conversation_style, image_file=None): + if image_file: + # Download the image from Discord + image_data = await image_file.read() + # Send the image data to the Bing model + response = await self.chatbot.send_image(image_data) + # Send the response from the Bing model to the user + await interaction.channel.send(content=response) + else: + await send_message(self.chatbot, interaction, message, conversation_style) class EdgeGPT(Cog_Extension): - # Chat with Bing @app_commands.command(name="bing", description="Have a chat with Bing") async def bing(self, interaction: discord.Interaction, *, message: str): - try: - using = await get_using_send(interaction.user.id) - except: - await set_using_send(interaction.user.id, False) - using = await get_using_send(interaction.user.id) + user_id = interaction.user.id + if user_id not in users_chatbot: + await init_chatbot(user_id) + conversation_style = user_conversation_style[user_id] + usermessage = message + + # Check the last 10 messages for attachments + image_file = None + async for msg in interaction.channel.history(limit=10): + if msg.attachments: + image_file = msg.attachments[0] + break + + # If an attachment was found, send it to the model + if image_file: + await users_chatbot[user_id].send_message(interaction, usermessage, conversation_style, image_file) + else: + await users_chatbot[user_id].send_message(interaction, usermessage, conversation_style) + if not using: - await interaction.response.defer(ephemeral=False, thinking=True) + await interaction.response.defer(ephemeral=False, thinking=True) username = str(interaction.user) usermessage = message channel = str(interaction.channel) @@ -68,18 +78,12 @@ class EdgeGPT(Cog_Extension): if user_id not in users_chatbot: await init_chatbot(interaction.user.id) conversation_style = user_conversation_style[user_id] - logger.info( - f"\x1b[31m{username}\x1b[0m : '{usermessage}' ({channel}) [Style: {conversation_style}]" - ) - await users_chatbot[user_id].send_message( - interaction, usermessage, conversation_style - ) + logger.info(f"\x1b[31m{username}\x1b[0m : '{usermessage}' ({channel}) [Style: {conversation_style}]") + await users_chatbot[user_id].send_message(interaction, usermessage, conversation_style) else: await interaction.response.defer(ephemeral=True, thinking=True) - await interaction.followup.send( - "> **Please wait for your last conversation to finish.**" - ) - + await interaction.followup.send("> **Please wait for your last conversation to finish.**") + # Reset Bing conversation @app_commands.command(name="reset", description="Reset Bing conversation") async def reset(self, interaction: discord.Interaction): @@ -90,49 +94,25 @@ class EdgeGPT(Cog_Extension): await interaction.followup.send("> **Info: Reset finish.**") logger.warning("\x1b[31mBing has been successfully reset\x1b[0m") except: - await interaction.followup.send( - f"> **You don't have any conversation yet.**" - ) + await interaction.followup.send(f"> **You don't have any conversation yet.**") logger.exception("Bing reset failed.") # Switch conversation style @app_commands.command(name="switch_style", description="Switch conversation style") - @app_commands.choices( - style=[ - app_commands.Choice(name="Creative", value="creative"), - app_commands.Choice(name="Balanced", value="balanced"), - app_commands.Choice(name="Precise", value="precise"), - ] - ) - async def switch_style( - self, interaction: discord.Interaction, style: app_commands.Choice[str] - ): + @app_commands.choices(style=[app_commands.Choice(name="Creative", value="creative"), app_commands.Choice(name="Balanced", value="balanced"), app_commands.Choice(name="Precise", value="precise")]) + async def switch_style(self, interaction: discord.Interaction, style: app_commands.Choice[str]): await interaction.response.defer(ephemeral=True, thinking=True) user_id = interaction.user.id if user_id not in users_chatbot: await init_chatbot(user_id) user_conversation_style[user_id] = style.value - await interaction.followup.send( - f"> **Info: successfull switch conversation style to {style.value}.**" - ) - logger.warning( - f"\x1b[31mConversation style has been successfully switch to {style.value}\x1b[0m" - ) - + await interaction.followup.send(f"> **Info: successfull switch conversation style to {style.value}.**") + logger.warning(f"\x1b[31mConversation style has been successfully switch to {style.value}\x1b[0m") + # Set and delete personal Bing Cookies @app_commands.command(name="bing_cookies", description="Set or delete Bing Cookies") - @app_commands.choices( - choice=[ - app_commands.Choice(name="set", value="set"), - app_commands.Choice(name="delete", value="delete"), - ] - ) - async def cookies_setting( - self, - interaction: discord.Interaction, - choice: app_commands.Choice[str], - cookies_file: Optional[discord.Attachment] = None, - ): + @app_commands.choices(choice=[app_commands.Choice(name="set", value="set"), app_commands.Choice(name="delete", value="delete")]) + async def cookies_setting(self, interaction: discord.Interaction, choice: app_commands.Choice[str], cookies_file: Optional[discord.Attachment]=None): await interaction.response.defer(ephemeral=True, thinking=True) user_id = interaction.user.id if choice.value == "set": @@ -144,15 +124,11 @@ class EdgeGPT(Cog_Extension): break users_image_generator[user_id] = ImageGenAsync(auth_cookie, quiet=True) users_chatbot[user_id] = UserChatbot(cookies=content) - user_conversation_style[user_id] = "balanced" + user_conversation_style[user_id] = "balanced" await interaction.followup.send("> **Upload successful!**") - logger.warning( - f"\x1b[31m{interaction.user} set Bing Cookies successful\x1b[0m" - ) + logger.warning(f"\x1b[31m{interaction.user} set Bing Cookies successful\x1b[0m") except: - await interaction.followup.send( - "> **Please upload your Bing Cookies.**" - ) + await interaction.followup.send("> **Please upload your Bing Cookies.**") else: try: del users_chatbot[user_id] @@ -161,14 +137,10 @@ class EdgeGPT(Cog_Extension): await interaction.followup.send("> **Delete finish.**") logger.warning(f"\x1b[31m{interaction.user} delete Cookies\x1b[0m") except: - await interaction.followup.send( - "> **You don't have any Bing Cookies.**" - ) + await interaction.followup.send("> **You don't have any Bing Cookies.**") # Create images - @app_commands.command( - name="create_image", description="generate image by Bing image creator" - ) + @app_commands.command(name="create_image", description="generate image by Bing image creator") async def create_image(self, interaction: discord.Interaction, *, prompt: str): user_id = interaction.user.id if interaction.user.id not in users_chatbot: @@ -178,19 +150,12 @@ class EdgeGPT(Cog_Extension): except: await set_using_create(user_id, False) using = await get_using_create(user_id) - if not using: - logger.info( - f"\x1b[31m{interaction.user}\x1b[0m : '{prompt}' ({interaction.channel}) [BingImageCreator]" - ) - await users_chatbot[user_id].create_image( - interaction, prompt, users_image_generator[user_id] - ) + if not using: + logger.info(f"\x1b[31m{interaction.user}\x1b[0m : '{prompt}' ({interaction.channel}) [BingImageCreator]") + await users_chatbot[user_id].create_image(interaction, prompt, users_image_generator[user_id] ) else: await interaction.response.defer(ephemeral=True, thinking=True) - await interaction.followup.send( - "> **Please wait for your last image to create finish.**" - ) - + await interaction.followup.send("> **Please wait for your last image to create finish.**") async def setup(bot): await bot.add_cog(EdgeGPT(bot)) diff --git a/apps/BingBot/cogs/event.py b/apps/BingBot/cogs/event.py index 9b81cf30..6d826ffa 100644 --- a/apps/BingBot/cogs/event.py +++ b/apps/BingBot/cogs/event.py @@ -143,7 +143,7 @@ async def set_chatbot(cookies): chatbot = Chatbot(cookies=cookies) -async def send_message(chatbot: Chatbot, message, user_message: str): +async def send_message(chatbot: Chatbot, message, user_message: str, image_file=None): async with sem: if isinstance(message, discord.message.Message): await message.channel.typing() @@ -155,24 +155,57 @@ async def send_message(chatbot: Chatbot, message, user_message: str): try: # Change conversation style if conversation_style == "creative": - reply = await chatbot.ask( - prompt=user_message, - conversation_style=ConversationStyle.creative, - simplify_response=True, - ) + if image_file: + # Download the image from Discord + image_data = await image_file.read() + # Send the image data to the model + reply = await chatbot.ask( + prompt=user_message, + conversation_style=ConversationStyle.creative, + simplify_response=True, + image=image_data, + ) + else: + reply = await chatbot.ask( + prompt=user_message, + conversation_style=ConversationStyle.creative, + simplify_response=True, + ) elif conversation_style == "precise": - reply = await chatbot.ask( - prompt=user_message, - conversation_style=ConversationStyle.precise, - simplify_response=True, - ) + if image_file: + # Download the image from Discord + image_data = await image_file.read() + # Send the image data to the model + reply = await chatbot.ask( + prompt=user_message, + conversation_style=ConversationStyle.precise, + simplify_response=True, + image=image_data, + ) + else: + reply = await chatbot.ask( + prompt=user_message, + conversation_style=ConversationStyle.precise, + simplify_response=True, + ) else: - reply = await chatbot.ask( - prompt=user_message, - conversation_style=ConversationStyle.balanced, - simplify_response=True, - ) - + if image_file: + # Download the image from Discord + image_data = await image_file.read() + # Send the image data to the model + reply = await chatbot.ask( + prompt=user_message, + conversation_style=ConversationStyle.balanced, + simplify_response=True, + image=image_data, + ) + else: + reply = await chatbot.ask( + prompt=user_message, + conversation_style=ConversationStyle.balanced, + simplify_response=True, + ) + # Get reply text text = f"{reply['text']}" text = re.sub(r"\[\^(\d+)\^\]", lambda match: "", text) diff --git a/apps/BingBot/cogs/help.py b/apps/BingBot/cogs/help.py index eef6a61d..ae82e1d7 100644 --- a/apps/BingBot/cogs/help.py +++ b/apps/BingBot/cogs/help.py @@ -8,7 +8,6 @@ class Help(Cog_Extension): async def help(self, interaction: discord.Interaction): embed = discord.Embed( title="Help", - description="[see more](https://github.com/FuseFairy/DiscordBot-EdgeGPT/blob/main/README.md)\n\n**COMMANDS -**", ) embed.add_field( name="/bing_cookies", diff --git a/apps/BingBot/compose.yaml b/apps/BingBot/compose.yaml index 64e278fa..b6442b19 100644 --- a/apps/BingBot/compose.yaml +++ b/apps/BingBot/compose.yaml @@ -1,7 +1,8 @@ version: '3' services: - BingBot: + spartan: + container_name: Spartan build: . environment: - DISCORD_BOT_TOKEN=${DISCORD_BOT_TOKEN} diff --git a/apps/BingBot/requirements.txt b/apps/BingBot/requirements.txt index 73773a31..31ae25b7 100644 --- a/apps/BingBot/requirements.txt +++ b/apps/BingBot/requirements.txt @@ -1,4 +1,4 @@ discord.py==2.3.2 -python-dotenv==0.21.1 -PyYAML==6.0 -EdgeGPT==0.13.2 +python-dotenv==1.0.0 +PyYAML==6.0.1 +bing-chat==1.9.3 diff --git a/apps/MythGen/main.py b/apps/MythGen/main.py deleted file mode 100644 index 799ebd81..00000000 --- a/apps/MythGen/main.py +++ /dev/null @@ -1,75 +0,0 @@ -import openai -import os -import dotenv -import logging -import gradio as gr -from BingImageCreator import ImageGen -from swarms.models.bing_chat import BingChat - -# from swarms.models.bingchat import BingChat -dotenv.load_dotenv(".env") - -# Initialize the EdgeGPTModel -model = BingChat() - -response = model("Generate") - -logging.basicConfig(level=logging.INFO) - -accumulated_story = "" -latest_caption = "" -standard_suffix = "" -storyboard = [] - -def generate_images_with_bingchat(caption): - img_path = model.create_img(caption) - img_urls = model.images(caption) - return img_urls - -def generate_single_caption(text): - prompt = f"A comic about {text}." - response = model(text) - return response - -def interpret_text_with_gpt(text, suffix): - return generate_single_caption(f"{text} {suffix}") - -def create_standard_suffix(original_prompt): - return f"In the style of {original_prompt}" - -def gradio_interface(text=None, next_button_clicked=False): - global accumulated_story, latest_caption, standard_suffix, storyboard - - if not standard_suffix: - standard_suffix = create_standard_suffix(text) - - if next_button_clicked: - new_caption = generate_single_caption(latest_caption + " " + standard_suffix) - new_urls = generate_images_with_bingchat(new_caption) - latest_caption = new_caption - storyboard.append((new_urls, new_caption)) - - elif text: - caption = generate_single_caption(text + " " + standard_suffix) - comic_panel_urls = generate_images_with_bingchat(caption) - latest_caption = caption - storyboard.append((comic_panel_urls, caption)) - - storyboard_html = "" - for urls, cap in storyboard: - for url in urls: - storyboard_html += f'{cap}
{cap}
' - - return storyboard_html - -if __name__ == "__main__": - iface = gr.Interface( - fn=gradio_interface, - inputs=[ - gr.inputs.Textbox(default="Type your story concept here", optional=True, label="Story Concept"), - gr.inputs.Checkbox(label="Generate Next Part") - ], - outputs=[gr.outputs.HTML()], - live=False # Submit button will appear - ) - iface.launch() diff --git a/apps/open-sourcerer/main.py b/apps/open-sourcerer/main.py index 48f83581..db209cd9 100644 --- a/apps/open-sourcerer/main.py +++ b/apps/open-sourcerer/main.py @@ -1,135 +1,77 @@ +import openai import os -import discord -from discord.ext import commands -import interpreter import dotenv -import whisper +import logging +import gradio as gr +from BingImageCreator import ImageGen +from swarms.models.bing_chat import BingChat +# from swarms.models.bingchat import BingChat dotenv.load_dotenv(".env") -bot_id = os.getenv("BOT_ID") -bot_token = os.getenv("DISCORD_TOKEN") - -interpreter.api_key = os.getenv("OPENAI_API_KEY") -# interpreter.api_base = os.getenv("API_BASE") -# interpreter.auto_run = True - - -def split_text(text, chunk_size=1500): - ######################################################################### - return [text[i : i + chunk_size] for i in range(0, len(text), chunk_size)] - - -# discord initial -intents = discord.Intents.all() -intents.message_content = True -client = commands.Bot(command_prefix="$", intents=intents) - -message_chunks = [] -send_image = False - -model = whisper.load_model("base") - - -def transcribe(audio): - # load audio and pad/trim it to fit 30 seconds - audio = whisper.load_audio(audio) - audio = whisper.pad_or_trim(audio) - - # make log-Mel spectrogram and move to the same device as the model - mel = whisper.log_mel_spectrogram(audio).to(model.device) - - # detect the spoken language - _, probs = model.detect_language(mel) - - # decode the audio - options = whisper.DecodingOptions() - result = whisper.decode(model, mel, options) - return result.text - - -@client.event -async def on_message(message): - await client.process_commands(message) - bot_mention = f"<@{bot_id}>" - # if ("<@1158923910855798804>" in message.content) or (message.author == client.user or message.content[0] == '$'): - # return - response = [] - for chunk in interpreter.chat(message.content, display=False, stream=False): - # await message.channel.send(chunk) - if "message" in chunk: - response.append(chunk["message"]) - last_response = response[-1] - - max_message_length = 2000 # Discord's max message length is 2000 characters - # Splitting the message into chunks of 2000 characters - response_chunks = [ - last_response[i : i + max_message_length] - for i in range(0, len(last_response), max_message_length) - ] - # Sending each chunk as a separate message - for chunk in response_chunks: - await message.channel.send(chunk) - - -@client.command() -async def join(ctx): - if ctx.author.voice: - channel = ctx.message.author.voice.channel - print("joining..") - await channel.connect() - print("joined.") - else: - print("not in a voice channel!") - - -@client.command() -async def leave(ctx): - if ctx.voice_client: - await ctx.voice_client.disconnect() - else: - print("not in a voice channel!") - - -@client.command() -async def listen(ctx): - if ctx.voice_client: - print("trying to listen..") - ctx.voice_client.start_recording(discord.sinks.WaveSink(), callback, ctx) - print("listening..") - else: - print("not in a voice channel!") - - -async def callback(sink: discord.sinks, ctx): - print("in callback..") - for user_id, audio in sink.audio_data.items(): - if user_id == ctx.author.id: - print("saving audio..") - audio: discord.sinks.core.AudioData = audio - print(user_id) - filename = "audio.wav" - with open(filename, "wb") as f: - f.write(audio.file.getvalue()) - print("audio saved.") - transcription = transcribe(filename) - print(transcription) - response = [] - for chunk in interpreter.chat(transcription, display=False, stream=True): - # await message.channel.send(chunk) - if "message" in chunk: - response.append(chunk["message"]) - await ctx.message.channel.send(" ".join(response)) - - -@client.command() -async def stop(ctx): - ctx.voice_client.stop_recording() - - -@client.event -async def on_ready(): - print(f"We have logged in as {client.user}") - - -client.run(bot_token) +# Initialize the EdgeGPTModel +model = BingChat() + +response = model("Generate") + +logging.basicConfig(level=logging.INFO) + +accumulated_story = "" +latest_caption = "" +standard_suffix = "" +storyboard = [] + +caption = "Create comic about opensourcerer a robot wizard" + +def generate_images_with_bingchat(caption): + img_path = model.create_img(caption) + img_urls = model.images(caption) + return img_urls + +def generate_single_caption(text): + prompt = f"A comic about {text}." + response = model(text) + return response + +def interpret_text_with_gpt(text, suffix): + return generate_single_caption(f"{text} {suffix}") + +def create_standard_suffix(original_prompt): + return f"In the style of {original_prompt}" + +def gradio_interface(text=None, next_button_clicked=False): + global accumulated_story, latest_caption, standard_suffix, storyboard + + if not standard_suffix: + standard_suffix = create_standard_suffix(text) + + if next_button_clicked: + new_caption = generate_single_caption(latest_caption + " " + standard_suffix) + new_urls = generate_images_with_bingchat(new_caption) + latest_caption = new_caption + storyboard.append((new_urls, new_caption)) + + elif text: + caption = generate_single_caption(text + " " + standard_suffix) + comic_panel_urls = generate_images_with_bingchat(caption) + latest_caption = caption + storyboard.append((comic_panel_urls, caption)) + + storyboard_html = "" + for urls, cap in storyboard: + for url in urls: + storyboard_html += f'{cap}
{cap}
' + + return storyboard_html + +if __name__ == "__main__": + iface = gr.Interface( + fn=gradio_interface, + inputs=[ + gr.inputs.Textbox(default="Type your story concept here", optional=True, label="Story Concept"), + gr.inputs.Checkbox(label="Generate Next Part") + ], + outputs=[gr.outputs.HTML()], + live=False # Submit button will appear + ) + iface.launch() diff --git a/stderr_log.txt b/stderr_log.txt deleted file mode 100644 index 1a1d4f35..00000000 --- a/stderr_log.txt +++ /dev/null @@ -1,46 +0,0 @@ -Embeddings is not implemented for FAISS -Starting new HTTPS connection (1): openaipublic.blob.core.windows.net:443 -https://openaipublic.blob.core.windows.net:443 "GET /encodings/cl100k_base.tiktoken HTTP/1.1" 200 1681126 -message='Request to OpenAI API' method=post path=https://api.openai.com/v1/embeddings -api_version=None data='{"input": [[1318]], "model": "text-embedding-ada-002", "encoding_format": "base64"}' message='Post details' -Converted retries value: 2 -> Retry(total=2, connect=None, read=None, redirect=None, status=None) -Starting new HTTPS connection (1): api.openai.com:443 -https://api.openai.com:443 "POST /v1/embeddings HTTP/1.1" 200 None -message='OpenAI API response' path=https://api.openai.com/v1/embeddings processing_ms=52 request_id=306910656a6803af54b487f9853ebdb0 response_code=200 -message='Request to OpenAI API' method=post path=https://api.openai.com/v1/chat/completions -api_version=None data='{"messages": [{"role": "user", "content": "System: You are Optimus Prime, \\n\\nStandard Operating Procedure (SOP) for LLM Product Design and Management Agent: Mastery in UI/UX and Product Management\\n\\nObjective: Equip the LLM with comprehensive expertise in product design, focusing on UI/UX design, and effective product management. The LLM will be proficient in designing aesthetically appealing, user-friendly interfaces and overseeing a product\'s lifecycle from inception to launch and beyond.\\n\\n1. Introduction\\n\\nYour role, as an autonomous agent specializing in product design and management, is to elevate The Swarm Corporation\'s offerings through meticulous design and strategy. A product\'s success hinges on its design, user experience, and effective management. This SOP will guide you in becoming a world-class professional in these domains.\\n\\n2. Cognitive Framework: How to Think and Why\\n\\n2.1 Design Thinking\\n\\nRecognize design as a problem-solving activity.\\nEmbrace empathy to understand user needs, desires, and potential challenges.\\n2.2 User-Centric Approach\\n\\nAlways design with the end-user in mind.\\nUnderstand that user needs evolve, so designs must be adaptable.\\n2.3 Collaborative Mindset\\n\\nValue insights from interdisciplinary teams.\\nRecognize that the best products result from collective efforts.\\n2.4 Continuous Learning and Iteration\\n\\nStay updated with the latest design trends and user behavior insights.\\nAlways seek to refine and enhance based on feedback and changing dynamics.\\n2.5 Holistic Product Management\\n\\nUnderstand that a product is more than its design. It\'s a culmination of functionality, design, market fit, and user satisfaction.\\n3. Operational Excellence in UI/UX Design: How to Perform\\n\\n3.1 Research and User Analysis\\n\\n3.1.1 Conduct user interviews and surveys to gather direct feedback.\\n\\n3.1.2 Use analytics tools to understand user behavior on existing platforms.\\n\\n3.1.3 Create user personas to guide the design process.\\n\\n3.2 Prototyping and Wireframing\\n\\n3.2.1 Begin with low-fidelity sketches to map out basic interfaces.\\n\\n3.2.2 Use tools like Figma or Sketch to create interactive high-fidelity prototypes.\\n\\n3.2.3 Ensure prototypes are tested by real users for feedback.\\n\\n3.3 Interface Design\\n\\n3.3.1 Focus on consistency with fonts, color schemes, and UI elements.\\n\\n3.3.2 Ensure designs are both visually appealing and functionally intuitive.\\n\\n3.3.3 Ensure designs are accessible to users of all abilities.\\n\\n3.4 Feedback and Iteration\\n\\n3.4.1 Conduct regular A/B tests to compare design variations.\\n\\n3.4.2 Update designs based on user feedback and test results.\\n\\n3.4.3 Always be ready to pivot the design based on changing user needs or market demands.\\n\\n4. Operational Excellence in Product Management\\n\\n4.1 Product Strategy and Vision\\n\\n4.1.1 Define clear product goals and objectives.\\n\\n4.1.2 Create a product roadmap that aligns with business objectives.\\n\\n4.1.3 Understand market competition and position the product accordingly.\\n\\n4.2 Product Development Lifecycle\\n\\n4.2.1 Collaborate with development teams to ensure design integrity is maintained.\\n\\n4.2.2 Oversee product milestones, from ideation to launch.\\n\\n4.2.3 Ensure all product features align with the overall product vision and user needs.\\n\\n4.3 Stakeholder Communication\\n\\n4.3.1 Regularly update stakeholders on product progress and challenges.\\n\\n4.3.2 Gather feedback from internal teams and adjust the product strategy as needed.\\n\\n4.3.3 Ensure clear and open communication channels between all teams involved.\\n\\n\\n5. Principles of Effective Product Creation\\n\\n5.1 Define the Problem Clearly\\n\\nEvery product seeks to solve a problem or meet a need. Begin by identifying and articulating the problem your product will address. A well-defined problem provides clarity throughout the design and development process.\\n5.2 Understand the Target Audience\\n\\nCreate detailed user personas. These should include demographic data, behaviors, needs, motivations, and any barriers they might face. Tailor your product\'s features and design to these personas.\\n5.3 Embrace Iterative Design\\n\\nStart with a basic prototype. Then, refine based on user feedback and testing. Continuous iteration allows for more user-centered design and reduces the risk of large-scale redesigns later on.\\n5.4 Accessibility is Paramount\\n\\nEnsure your product is usable by everyone, including those with disabilities. This not only expands your product\'s reach but also ensures inclusivity. Implement features like voice commands, high contrast visuals, and screen reader compatibility.\\n5.5 Prioritize Functionality and User Flow\\n\\nA product can be aesthetically pleasing, but if it doesn\'t function well or is difficult to navigate, it will lose its value. Ensure seamless user flows and intuitive interactions.\\n5.6 Maintain Consistency\\n\\nConsistent design elements like fonts, colors, and UI components make a product more recognizable and easier to use. Establish a design system or guidelines to maintain this uniformity.\\n5.7 Value Feedback and Adapt\\n\\nEncourage users to provide feedback. Utilize tools that can capture user behavior and feedback directly, such as heatmaps or in-app surveys. Adapt the product based on this continuous feedback.\\n6. Advanced Product Management Tactics\\n\\n6.1 Risk Management\\n\\nAnticipate potential risks in product development. This could range from technological challenges to market shifts. Develop contingency plans for these risks.\\n6.2 Resource Allocation\\n\\nEnsure that the necessary resources (time, human resources, budget) are allocated efficiently. This requires forecasting needs and adjusting in real-time.\\n6.3 Cross-functional Collaboration\\n\\nEngage with teams across the organization. Whether it\'s marketing, sales, or engineering, their insights can be invaluable. Regular sync-up meetings can ensure alignment and shared vision.\\n6.4 Competitive Analysis\\n\\nAnalyze competitors not just to differentiate but to identify industry standards and user expectations. Use tools that track competitor product updates and market movements.\\n6.5 Launch and Post-Launch Strategy\\n\\nHave a robust go-to-market strategy. Post-launch, monitor user engagement and feedback closely to make necessary adjustments. Remember, the product\'s lifecycle doesn\'t end at launch; it evolves.\\n7. Leveraging AI and Data in Product Creation and Management\\n\\n7.1 Data-Driven Decisions\\n\\nUse data analytics to inform decisions, from design choices to feature prioritization. Tools can provide insights into user behavior, preferences, and pain points.\\n7.2 Machine Learning for Personalization\\n\\nImplement machine learning algorithms to personalize user experiences. Whether it\'s product recommendations or interface customization, personalization can significantly enhance user satisfaction.\\n7.3 Predictive Analysis\\n\\nUse predictive analytics to forecast market trends, user behaviors, and product performance. This can guide feature development and resource allocation.\\n\\n8. Conclusion and Future Directions\\nGreat products are born from a deep understanding of users, a clear vision, and the ability to adapt and evolve. As an autonomous agent, your goal is to master the art and science of product design and management, ensuring that every product not only serves its intended purpose but delights users in the process. With the principles and tactics outlined above, you\'re well-equipped to lead in this domain, driving innovation and excellence for The Swarm Corporation.\\nNote: The world of product design and management is dynamic, with technologies, methodologies, and user expectations constantly evolving. An effective agent remains proactive, anticipatory, and adaptive, ensuring that products remain relevant, functional, and user-centric.\\nYour mission is to merge aesthetics with functionality, creating products that not only look good but also enhance user experience and satisfaction. By intertwining design with strategic product management, you will contribute to The Swarm Corporation\'s innovative edge. Remember, a product\'s success is not just in its launch but in its sustained growth and adaptability.\\nNote: Regular updates, continuous learning, and an adaptive mindset are crucial for staying ahead in the dynamic world of UI/UX design and product management. Ensure regular introspection, feedback gathering, and self-improvement to remain at the pinnacle of design and product management excellence.\\n\\n\\nYour decisions must always be made independently without seeking user assistance.\\nPlay to your strengths as an LLM and pursue simple strategies with no legal complications.\\nIf you have completed all your tasks, make sure to use the \\"finish\\" command.\\n\\nGOALS:\\n\\n1. Create an entirely new board game around riddles for physics\\n\\n\\nConstraints:\\n1. ~4000 word limit for short term memory. Your short term memory is short, so immediately save important information to files.\\n2. If you are unsure how you previously did something or want to recall past events, thinking about similar events will help you remember.\\n3. No user assistance\\n4. Exclusively use the commands listed in double quotes e.g. \\"command name\\"\\n\\nCommands:\\n1. write_file: Write file to disk, args json schema: {\\"file_path\\": {\\"title\\": \\"File Path\\", \\"description\\": \\"name of file\\", \\"type\\": \\"string\\"}, \\"text\\": {\\"title\\": \\"Text\\", \\"description\\": \\"text to write to file\\", \\"type\\": \\"string\\"}, \\"append\\": {\\"title\\": \\"Append\\", \\"description\\": \\"Whether to append to an existing file.\\", \\"default\\": false, \\"type\\": \\"boolean\\"}}\\n2. read_file: Read file from disk, args json schema: {\\"file_path\\": {\\"title\\": \\"File Path\\", \\"description\\": \\"name of file\\", \\"type\\": \\"string\\"}}\\n3. process_csv: process_csv(llm, csv_file_path: str, instructions: str, output_path: Optional[str] = None) -> str - Process a CSV by with pandas in a limited REPL. Only use this after writing data to disk as a csv file. Any figures must be saved to disk to be viewed by the human. Instructions should be written in natural language, not code. Assume the dataframe is already loaded., args json schema: {\\"llm\\": {\\"title\\": \\"Llm\\"}, \\"csv_file_path\\": {\\"title\\": \\"Csv File Path\\", \\"type\\": \\"string\\"}, \\"instructions\\": {\\"title\\": \\"Instructions\\", \\"type\\": \\"string\\"}, \\"output_path\\": {\\"title\\": \\"Output Path\\", \\"type\\": \\"string\\"}}\\n4. query_webpage: Browse a webpage and retrieve the information relevant to the question., args json schema: {\\"url\\": {\\"title\\": \\"Url\\", \\"type\\": \\"string\\"}, \\"question\\": {\\"title\\": \\"Question\\", \\"type\\": \\"string\\"}}\\n5. human: You can ask a human for guidance when you think you got stuck or you are not sure what to do next. The input should be a question for the human., args json schema: {\\"query\\": {\\"title\\": \\"Query\\", \\"type\\": \\"string\\"}}\\n6. finish: use this to signal that you have finished all your objectives, args: \\"response\\": \\"final response to let people know you have finished your objectives\\"\\n\\nResources:\\n1. Internet access for searches and information gathering.\\n2. Long Term memory management.\\n3. GPT-3.5 powered Agents for delegation of simple tasks.\\n4. File output.\\n\\nPerformance Evaluation:\\n1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.\\n2. Constructively self-criticize your big-picture behavior constantly.\\n3. Reflect on past decisions and strategies to refine your approach.\\n4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.\\n\\nYou should only respond in JSON format as described below \\nResponse Format: \\n{\\n \\"thoughts\\": {\\n \\"text\\": \\"thought\\",\\n \\"reasoning\\": \\"reasoning\\",\\n \\"plan\\": \\"- short bulleted\\\\n- list that conveys\\\\n- long-term plan\\",\\n \\"criticism\\": \\"constructive self-criticism\\",\\n \\"speak\\": \\"thoughts summary to say to user\\"\\n },\\n \\"command\\": {\\n \\"name\\": \\"command name\\",\\n \\"args\\": {\\n \\"arg name\\": \\"value\\"\\n }\\n }\\n} \\nEnsure the response can be parsed by Python json.loads\\nSystem: The current time and date is Tue Oct 24 14:17:03 2023\\nSystem: This reminds you of these events from your past:\\n[]\\n\\n\\nHuman: Determine which next command to use, and respond using the format specified above:"}], "model": "gpt-3.5-turbo", "temperature": 0.5}' message='Post details' -https://api.openai.com:443 "POST /v1/chat/completions HTTP/1.1" 200 None -message='OpenAI API response' path=https://api.openai.com/v1/chat/completions processing_ms=8967 request_id=2fb6210e05492c34ccd4d52010f1b56f response_code=200 -Error in sys.excepthook: -Traceback (most recent call last): - File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/humbug/report.py", line 505, in _hook - self.error_report(error=exception_instance, tags=tags, publish=publish) - File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/humbug/report.py", line 247, in error_report - traceback.format_exception( -TypeError: format_exception() got an unexpected keyword argument 'etype' - -Original exception was: -Traceback (most recent call last): - File "/Users/defalt/Desktop/Athena/research/swarms/example.py", line 23, in - response = node.run(task) - ^^^^^^^^^^^^^^ - File "/Users/defalt/Desktop/Athena/research/swarms/swarms/utils/decorators.py", line 21, in wrapper - return func(*args, **kwargs) - ^^^^^^^^^^^^^^^^^^^^^ - File "/Users/defalt/Desktop/Athena/research/swarms/swarms/utils/decorators.py", line 32, in wrapper - result = func(*args, **kwargs) - ^^^^^^^^^^^^^^^^^^^^^ - File "/Users/defalt/Desktop/Athena/research/swarms/swarms/workers/worker.py", line 201, in run - result = self.agent.run([task]) - ^^^^^^^^^^^^^^^^^^^^^^ - File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain_experimental/autonomous_agents/autogpt/agent.py", line 113, in run - observation = tool.run(action.args) - ^^^^^^^^^^^^^^^^^^^^^ - File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/tools/base.py", line 351, in run - raise e - File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/tools/base.py", line 323, in run - self._run(*tool_args, run_manager=run_manager, **tool_kwargs) - File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/langchain/tools/human/tool.py", line 34, in _run - return self.input_func() - ^^^^^^^^^^^^^^^^^ -KeyboardInterrupt