├── requirements.txt ├── examples ├── img.png ├── img_1.png ├── cyberdolphin.png ├── cyberdolphin_example.png └── README.md ├── pyproject.toml ├── .github └── workflows │ └── publish.yml ├── __init__.py ├── cyberdolphin_imageneering.py ├── cyberdolphin_gradio.py ├── cyberdolphin_openai_simple.py ├── settings.py ├── cyberdolphin_openai_compatible.py ├── settings.yaml.example ├── openai_client.py ├── cyberdolphin_openai_advanced.py ├── .gitignore ├── README.md └── LICENSE /requirements.txt: -------------------------------------------------------------------------------- 1 | openai ~= 1.2.3 2 | gradio_client 3 | numpy 4 | pillow -------------------------------------------------------------------------------- /examples/img.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/whatbirdisthat/cyberdolphin/HEAD/examples/img.png -------------------------------------------------------------------------------- /examples/img_1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/whatbirdisthat/cyberdolphin/HEAD/examples/img_1.png -------------------------------------------------------------------------------- /examples/cyberdolphin.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/whatbirdisthat/cyberdolphin/HEAD/examples/cyberdolphin.png -------------------------------------------------------------------------------- /examples/cyberdolphin_example.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/whatbirdisthat/cyberdolphin/HEAD/examples/cyberdolphin_example.png -------------------------------------------------------------------------------- /examples/README.md: -------------------------------------------------------------------------------- 1 | # Examples 2 | 3 | ## Cyber Dolphin 4 | 5 | ![cyberdolphin_example.png](cyberdolphin_example.png) 6 | 7 | --- 8 | 9 | Get image prompt from OpenAI or a compatible API. By default `gpt-3.5-turbo` is used. 10 | 11 | ![img.png](img.png) 12 | 13 | --- 14 | 15 | Compare the results of DALL·E and local SD models to see which one is better at generating images from text. 16 | 17 | 18 | ![img_1.png](img_1.png) 19 | --- 20 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [project] 2 | name = "cyberdolphin" 3 | description = "Cyberdolphin nodes for wiring up OpenAI and compatible LLM APIs." 4 | version = "1.0.0" 5 | license = "LICENSE" 6 | dependencies = ["openai ~= 1.2.3", "gradio_client", "numpy", "pillow"] 7 | 8 | [project.urls] 9 | Repository = "https://github.com/whatbirdisthat/cyberdolphin" 10 | # Used by Comfy Registry https://comfyregistry.org 11 | 12 | [tool.comfy] 13 | PublisherId = "whatbirdisthat" 14 | DisplayName = "cyberdolphin" 15 | Icon = "dolphin" 16 | -------------------------------------------------------------------------------- /.github/workflows/publish.yml: -------------------------------------------------------------------------------- 1 | name: Publish to Comfy registry 2 | on: 3 | workflow_dispatch: 4 | push: 5 | branches: 6 | - main 7 | paths: 8 | - "pyproject.toml" 9 | 10 | jobs: 11 | publish-node: 12 | name: Publish Custom Node to registry 13 | runs-on: ubuntu-latest 14 | steps: 15 | - name: Check out code 16 | uses: actions/checkout@v4 17 | - name: Publish Custom Node 18 | uses: Comfy-Org/publish-node-action@main 19 | with: 20 | ## Add your own personal access token to your Github Repository secrets and reference it here. 21 | personal_access_token: ${{ secrets.REGISTRY_ACCESS_TOKEN }} -------------------------------------------------------------------------------- /__init__.py: -------------------------------------------------------------------------------- 1 | from .cyberdolphin_gradio import CyberDolphinGradioApi 2 | from .cyberdolphin_openai_advanced import CyberdolphinOpenAIAdvanced 3 | from .cyberdolphin_openai_simple import CyberdolphinOpenAISimple 4 | from .cyberdolphin_openai_compatible import CyberdolphinOpenAICompatible 5 | from .cyberdolphin_imageneering import CyberDolphinImageneering 6 | 7 | NODE_CLASS_MAPPINGS = { 8 | "🐬 Gradio ChatInterface": CyberDolphinGradioApi, 9 | "🐬 OpenAI Simple": CyberdolphinOpenAISimple, 10 | "🐬 OpenAI Advanced": CyberdolphinOpenAIAdvanced, 11 | "🐬 OpenAI Compatible": CyberdolphinOpenAICompatible, 12 | "🐬 OpenAI DALL·E": CyberDolphinImageneering, 13 | } 14 | 15 | NODE_DISPLAY_NAME_MAPPINGS = { 16 | "CyberDolphin Gradio": "🐬 CyberDolphin Gradio", 17 | "CyberDolphin GPT-3.5 (Simple)": "🐬 CyberDolphin GPT-3.5 (Simple)", 18 | "CyberDolphin OpenAI (Advanced)": "🐬 CyberDolphin OpenAI (Advanced)", 19 | "CyberDolphin OpenAI Compatible": "🐬 CyberDolphin OpenAI Compatible", 20 | "CyberDolphin OpenAI DALL·E": "🐬 CyberDolphin OpenAI DALL·E", 21 | } 22 | -------------------------------------------------------------------------------- /cyberdolphin_imageneering.py: -------------------------------------------------------------------------------- 1 | from PIL import ImageOps 2 | import torch 3 | import numpy as np 4 | from .openai_client import OpenAiClient, DALL_E_SIZE 5 | 6 | 7 | class CyberDolphinImageneering: 8 | @classmethod 9 | def INPUT_TYPES(s): 10 | return {"required": { 11 | "prompt": ('STRING', {'default': 'darth vader with yoda ears', 'multiline': True}), 12 | "size": (["256x256", "512x512", "1024x1024"], {'default': "1024x1024"}), 13 | }} 14 | 15 | CATEGORY = "🐬 CyberDolphin" 16 | RETURN_TYPES = ("IMAGE", "MASK") 17 | FUNCTION = "load_image" 18 | 19 | def load_image(self, prompt: str, size: DALL_E_SIZE): 20 | i = OpenAiClient.image_create(prompt=prompt, size=size) 21 | # copy/pasted from class LoadImage: 22 | i = ImageOps.exif_transpose(i) 23 | image = i.convert("RGB") 24 | image = np.array(image).astype(np.float32) / 255.0 25 | image = torch.from_numpy(image)[None,] 26 | if 'A' in i.getbands(): 27 | mask = np.array(i.getchannel('A')).astype(np.float32) / 255.0 28 | mask = 1. - torch.from_numpy(mask) 29 | else: 30 | mask = torch.zeros((64, 64), dtype=torch.float32, device="cpu") 31 | return image, mask.unsqueeze(0) 32 | -------------------------------------------------------------------------------- /cyberdolphin_gradio.py: -------------------------------------------------------------------------------- 1 | from gradio_client import Client 2 | 3 | from .settings import load_settings 4 | 5 | 6 | class CyberDolphinGradioApi: 7 | 8 | @classmethod 9 | def INPUT_TYPES(s): 10 | the_settings = load_settings() 11 | prompt_templates = [p for p in the_settings['prompt_templates']] 12 | example_user_prompt = the_settings['example_user_prompt'] 13 | return { 14 | "required": { 15 | "user_prompt": ("STRING", { 16 | "default": example_user_prompt, 17 | "multiline": True, 18 | }), 19 | "llm_prompt": (prompt_templates, "STRING"), 20 | }, 21 | } 22 | 23 | RETURN_TYPES = ("STRING",) 24 | RETURN_NAMES = ("llm_response",) 25 | FUNCTION = "generate" 26 | CATEGORY = "🐬 CyberDolphin" 27 | 28 | def generate(self, user_prompt="", llm_prompt: str = "default_prompt"): 29 | settings = load_settings() 30 | client_src = settings['gradio_chat_interface']['src'] 31 | client = Client(client_src) 32 | prompt_prefix = settings['prompt_templates'][llm_prompt]['prefix'] 33 | prompt_suffix = settings['prompt_templates'][llm_prompt]['suffix'] 34 | prompt = f'{prompt_prefix} {user_prompt} {prompt_suffix}' 35 | result = client.predict(prompt, api_name="/chat") 36 | response = result 37 | return (f'{response}',) 38 | -------------------------------------------------------------------------------- /cyberdolphin_openai_simple.py: -------------------------------------------------------------------------------- 1 | from .openai_client import OpenAiClient 2 | from .settings import load_settings 3 | 4 | 5 | class CyberdolphinOpenAISimple: 6 | 7 | @classmethod 8 | def INPUT_TYPES(s): 9 | settings = load_settings() 10 | return { 11 | 'required': { 12 | 'user_prompt': ('STRING', { 13 | 'multiline': True, 14 | 'default': settings['example_user_prompt'] 15 | }), 16 | 'temperature': ("FLOAT", {"default": 1.0, "min": 0.0, "max": 1.75, "step": 0.01}), 17 | 'model': (['gpt-3.5-turbo', 'gpt-4'], { 18 | 'default': settings['openai_compatible']['openai']['model'] 19 | }), 20 | }, 21 | } 22 | 23 | RETURN_TYPES = ('STRING',) 24 | RETURN_NAMES = ('gpt_response',) 25 | FUNCTION = 'generate' 26 | CATEGORY = '🐬 CyberDolphin' 27 | 28 | def generate(self, user_prompt="", temperature: float = 1.0, model: str = "gpt-3.5-turbo"): 29 | settings = load_settings() 30 | gpt_prompt = settings['prompt_templates']['gpt-3.5-turbo'] 31 | system_content = gpt_prompt['system'] 32 | user_content = f"{gpt_prompt['prefix']} {user_prompt} {gpt_prompt['suffix']}" 33 | response = OpenAiClient.complete( 34 | key='openai', 35 | model=model, 36 | temperature=temperature, 37 | top_p=1.0, 38 | system_content=system_content, 39 | user_content=user_content) 40 | 41 | return (f'{response.choices[0].message.content}',) 42 | -------------------------------------------------------------------------------- /settings.py: -------------------------------------------------------------------------------- 1 | import os 2 | import pathlib 3 | 4 | import yaml 5 | 6 | DEFAULT_SETTINGS = { 7 | "cyberdolphin": { 8 | "openai": { 9 | "organisation": "NO ORG", 10 | "api_key": "NO API KEY", 11 | "model": "gpt-3.5-turbo" 12 | }, 13 | "openai_compatible": { 14 | "organisation": "NO ORG", 15 | "api_key": "NO API KEY", 16 | "api_base": 'http://localhost:8000/v1' 17 | }, 18 | "prompts": { 19 | "example_user_prompt": "{Camel|goldfish|glowing orb},{moss|tree|fern|balloon},{space station|garden shed|glowing laser sword|bowl of petunias|orange taxi|neon sign}", 20 | "default_prompt": { 21 | "system": "You are deeply artistic, understanding of concepts like composition, pallete and color theory, and image psychology.", 22 | "prefix": "Do use objective language. Do not add narrative. Do describe objects visually and in context. \ 23 | Do not describe the purpose of the objects, or any other explanations \"", 24 | "suffix": '"' 25 | } 26 | } 27 | } 28 | } 29 | 30 | 31 | def load_settings(): 32 | path = os.path.join(os.path.dirname(__file__), "settings.yaml") 33 | file_path = pathlib.Path(path) 34 | if not file_path.exists(): 35 | return DEFAULT_SETTINGS['cyberdolphin'] 36 | 37 | with open(path) as settings: 38 | the_yaml = yaml.safe_load(settings) 39 | # print(f'LOADED: {the_yaml["cyberdolphin"]}') 40 | return the_yaml['cyberdolphin'] 41 | 42 | 43 | def api_settings(section: str = "openai"): 44 | openai_settings = load_settings()['openai_compatible'][section] 45 | return openai_settings['api_base'], openai_settings['api_key'], openai_settings['organisation'] 46 | -------------------------------------------------------------------------------- /cyberdolphin_openai_compatible.py: -------------------------------------------------------------------------------- 1 | from .openai_client import OpenAiClient 2 | from .settings import load_settings 3 | 4 | 5 | class CyberdolphinOpenAICompatible: 6 | 7 | @classmethod 8 | def INPUT_TYPES(s): 9 | all_settings = load_settings() 10 | prompt_templates = all_settings['prompt_templates'] 11 | default_user_prompt = all_settings['example_user_prompt'] 12 | available_apis = [a for a in all_settings['openai_compatible']] 13 | available_templates = [t for t in prompt_templates] 14 | default_model = all_settings['openai_compatible']['default']['model'] 15 | 16 | return { 17 | "required": { 18 | "api": (available_apis, { 19 | "default": "default" 20 | }), 21 | "prompt_template": (available_templates, { 22 | "default": 'default' 23 | }), 24 | "model": ("STRING", { 25 | "default": default_model 26 | }), 27 | "user_prompt": ("STRING", { 28 | "multiline": True, 29 | "default": default_user_prompt 30 | }), 31 | "temperature": ("FLOAT", { 32 | "default": 1.0, "min": 0.0, "max": 2.0, "step": 0.01, 33 | }), 34 | }, 35 | "optional": { 36 | "top_p": ("FLOAT", { 37 | "default": 1.0, "min": 0.001, "max": 1.0, "step": 0.01, 38 | }), 39 | } 40 | } 41 | 42 | RETURN_TYPES = ("STRING",) 43 | RETURN_NAMES = ("gpt_response",) 44 | FUNCTION = "generate" 45 | CATEGORY = "🐬 CyberDolphin" 46 | 47 | def generate(self, api: str, prompt_template: str, model: str, temperature: float | None = None, 48 | top_p: float | None = None, user_prompt=""): 49 | this_prompt = load_settings()['prompt_templates'][prompt_template] 50 | system_content = this_prompt['system'] 51 | user_content = f"{this_prompt['prefix']} {user_prompt} {this_prompt['suffix']}" 52 | 53 | response = OpenAiClient.complete( 54 | key=api, 55 | model=model, 56 | temperature=temperature, 57 | top_p=top_p, 58 | system_content=system_content, 59 | user_content=user_content) 60 | 61 | return (f'{response.choices[0].message.content}',) 62 | -------------------------------------------------------------------------------- /settings.yaml.example: -------------------------------------------------------------------------------- 1 | cyberdolphin: 2 | gradio_chat_interface: 3 | src: http://localhost:7860 4 | openai_compatible: 5 | openai: 6 | api_base: 'https://api.openai.com/v1' 7 | organisation: "ORG" 8 | api_key: "KEY" 9 | model: "gpt-3.5-turbo" 10 | default: 11 | api_base: "http://127.0.0.1:8000/v1" 12 | organisation: "NONE" 13 | api_key: "NONE" 14 | model: "Llama-2-13b-chat" 15 | another_openai_api: 16 | api_base: "http://127.0.0.1:8001/v1" 17 | organisation: "NONE" 18 | api_key: "NONE" 19 | model: "another_model" 20 | example_user_prompt: "{Camel|goldfish|glowing orb},{moss|tree|fern|balloon},{space station|garden shed|glowing laser sword|bowl of petunias|orange taxi|neon sign}" 21 | prompt_templates: 22 | # the user prompt is by default a list of objects, such as what might be returned from a resnet node 23 | 24 | default: 25 | system: >- 26 | You are deeply artistic, understanding of concepts like composition, palette and color theory, and image psychology. 27 | prefix: >- 28 | make a list of the things you see. do not explain why you see them. 29 | do explain what the things you see are doing. do explain where they are. 30 | do not explain their purpose, 31 | do not say anything other than the list of things you see. 32 | do use purely objective language: do not say "I see a..." but instead say "there is a..." 33 | SO: 34 | When I provide the list " 35 | suffix: >- 36 | ", 37 | what is this scene - 38 | do not simply repeat the list, do not say "when I provide the list" or similar just project the description. 39 | describe what you see in your mind. 40 | 41 | 42 | prompt_two_example: 43 | system: >- 44 | You are deeply artistic, understanding of concepts like composition, palette and color theory, and image psychology. 45 | prefix: >- 46 | describe a scene using the following list of objects: " 47 | suffix: >- 48 | " - there are many things 49 | and you must list them using a maximum of 25 words. be clear and specific. 50 | use present tense, objective language: do not say, "I see ..." rather say, "there is ..." 51 | 52 | 53 | gpt-3.5-turbo: 54 | system: >- 55 | You are deeply artistic, understanding of concepts like composition, palette and color theory, and image psychology. 56 | prefix: >- 57 | describe a scene using the following list of objects: " 58 | suffix: >- 59 | " - there are many things 60 | and you must list them using a maximum of 25 words. be clear and specific. 61 | use present tense, objective language: do not say, "I see ..." rather say, "there is ..." 62 | 63 | -------------------------------------------------------------------------------- /openai_client.py: -------------------------------------------------------------------------------- 1 | from typing import Literal, TypeAlias 2 | 3 | import PIL.Image 4 | from openai import OpenAI 5 | 6 | from custom_nodes.cyberdolphin.settings import api_settings 7 | 8 | DALL_E_SIZE: TypeAlias = Literal["256x256", "512x512", "1024x1024", "1792x1024", "1024x1792"] 9 | 10 | 11 | def validation(temperature: float, top_p: float = None) -> list[str]: 12 | errors_list = [] 13 | if temperature is None and top_p is None: 14 | errors_list.append('Must contain a temperature or a top_p') 15 | if top_p < 0 or top_p > 1: 16 | errors_list.append('top_p must be a number between 0 and 1') 17 | if temperature < 0 or temperature > 2: 18 | errors_list.append( 19 | """Temperature should be a value between 0.0 and 2.0 20 | - openai says higher values like 0.8 will make the output more random, 21 | lower values like 0.2 make it more focused and deterministic. 22 | """) 23 | return errors_list 24 | 25 | 26 | def convert_bson_to_image(image_bson: str) -> PIL.Image.Image: 27 | import base64 28 | import io 29 | from PIL import Image 30 | image_bytes = base64.b64decode(image_bson) 31 | image = Image.open(io.BytesIO(image_bytes)) 32 | return image 33 | 34 | 35 | class OpenAiClient: 36 | 37 | @staticmethod 38 | def create_client(key: str = "openai"): 39 | api_base, api_key, organization = api_settings(key) 40 | the_client = OpenAI( 41 | base_url=api_base, 42 | api_key=api_key, 43 | organization=organization, 44 | ) 45 | return the_client 46 | 47 | @staticmethod 48 | def model_list(): 49 | the_client = OpenAiClient.create_client() 50 | the_models = the_client.models.list() 51 | return [m.id for m in the_models.data] 52 | 53 | @staticmethod 54 | def image_create(prompt: str, size: DALL_E_SIZE = "1024x1024", ) -> PIL.Image.Image: 55 | the_client = OpenAiClient.create_client() 56 | response = the_client.images.generate( 57 | n=1, 58 | size=size, 59 | prompt=prompt, 60 | response_format="b64_json" 61 | ) 62 | image_bson = response.data[0].b64_json 63 | i = convert_bson_to_image(image_bson) 64 | return i 65 | 66 | @staticmethod 67 | def complete(key: str, model: str, temperature: float, top_p: float, system_content: str, user_content: str): 68 | errors = validation(temperature, top_p) 69 | if errors: 70 | error_report = "\n".join([e for e in errors]) 71 | raise RuntimeError(f"There were problems with the parameters:\n{error_report}") 72 | the_client = OpenAiClient.create_client(key) 73 | response = the_client.chat.completions.create( 74 | model=model, 75 | temperature=temperature, 76 | top_p=top_p, 77 | messages=[ 78 | {"role": "system", "content": system_content}, 79 | {"role": "user", "content": user_content} 80 | ] 81 | ) 82 | return response 83 | -------------------------------------------------------------------------------- /cyberdolphin_openai_advanced.py: -------------------------------------------------------------------------------- 1 | from .openai_client import OpenAiClient 2 | from .settings import load_settings 3 | 4 | 5 | class CyberdolphinOpenAIAdvanced: 6 | the_settings = None 7 | 8 | @classmethod 9 | def INPUT_TYPES(s): 10 | openai_model_list = OpenAiClient.model_list() 11 | the_settings = load_settings() 12 | gpt_prompt = the_settings['prompt_templates']['gpt-3.5-turbo'] 13 | example_system_prompt = gpt_prompt['system'] 14 | example_user_prompt = f"{gpt_prompt['prefix']}{the_settings['example_user_prompt']}{gpt_prompt['suffix']}" 15 | 16 | return { 17 | "required": { 18 | "model": (openai_model_list, { 19 | "default": "gpt-3.5-turbo"}), 20 | "system_prompt": ('STRING', { 21 | "multiline": True, 22 | "default": example_system_prompt 23 | }), 24 | "user_prompt": ("STRING", { 25 | "multiline": True, 26 | "default": example_user_prompt 27 | }), 28 | "temperature": ("FLOAT", { 29 | "default": 1.0, "min": 0.0, "max": 2.0, "step": 0.01, 30 | "help": """ 31 | What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the 32 | output more random, while lower values like 0.2 will make it more focused and deterministic. 33 | 34 | We generally recommend altering this or top_p but not both. 35 | """ 36 | 37 | }), 38 | }, 39 | "optional": { 40 | "top_p": ("FLOAT", { 41 | "default": 1.0, "min": 0.001, "max": 1.0, "step": 0.01, 42 | "help": """ 43 | An alternative to sampling with temperature, called nucleus sampling, where the model 44 | considers the results of the tokens with top_p probability mass. 45 | So 0.1 means only the tokens comprising the top 10% probability mass are considered. 46 | 47 | We generally recommend altering this or `temperature` but not both. 48 | """ 49 | }), 50 | } 51 | } 52 | 53 | RETURN_TYPES = ("STRING",) 54 | RETURN_NAMES = ("gpt_response",) 55 | FUNCTION = "generate" 56 | CATEGORY = "🐬 CyberDolphin" 57 | 58 | def generate(self, model: str, system_prompt: str, user_prompt="", 59 | temperature: float | None = None, top_p: float | None = None): 60 | system_content = system_prompt 61 | user_content = user_prompt 62 | 63 | response = OpenAiClient.complete( 64 | key="openai", 65 | model=model, 66 | temperature=temperature, 67 | top_p=top_p, 68 | system_content=system_content, 69 | user_content=user_content) 70 | 71 | return (f'{response.choices[0].message.content}',) 72 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | share/python-wheels/ 24 | *.egg-info/ 25 | .installed.cfg 26 | *.egg 27 | MANIFEST 28 | 29 | # PyInstaller 30 | # Usually these files are written by a python script from a template 31 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 32 | *.manifest 33 | *.spec 34 | 35 | # Installer logs 36 | pip-log.txt 37 | pip-delete-this-directory.txt 38 | 39 | # Unit test / coverage reports 40 | htmlcov/ 41 | .tox/ 42 | .nox/ 43 | .coverage 44 | .coverage.* 45 | .cache 46 | nosetests.xml 47 | coverage.xml 48 | *.cover 49 | *.py,cover 50 | .hypothesis/ 51 | .pytest_cache/ 52 | cover/ 53 | 54 | # Translations 55 | *.mo 56 | *.pot 57 | 58 | # Django stuff: 59 | *.log 60 | local_settings.py 61 | db.sqlite3 62 | db.sqlite3-journal 63 | 64 | # Flask stuff: 65 | instance/ 66 | .webassets-cache 67 | 68 | # Scrapy stuff: 69 | .scrapy 70 | 71 | # Sphinx documentation 72 | docs/_build/ 73 | 74 | # PyBuilder 75 | .pybuilder/ 76 | target/ 77 | 78 | # Jupyter Notebook 79 | .ipynb_checkpoints 80 | 81 | # IPython 82 | profile_default/ 83 | ipython_config.py 84 | 85 | # pyenv 86 | # For a library or package, you might want to ignore these files since the code is 87 | # intended to run in multiple environments; otherwise, check them in: 88 | # .python-version 89 | 90 | # pipenv 91 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 92 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 93 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 94 | # install all needed dependencies. 95 | #Pipfile.lock 96 | 97 | # poetry 98 | # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. 99 | # This is especially recommended for binary packages to ensure reproducibility, and is more 100 | # commonly ignored for libraries. 101 | # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control 102 | #poetry.lock 103 | 104 | # pdm 105 | # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. 106 | #pdm.lock 107 | # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it 108 | # in version control. 109 | # https://pdm.fming.dev/#use-with-ide 110 | .pdm.toml 111 | 112 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm 113 | __pypackages__/ 114 | 115 | # Celery stuff 116 | celerybeat-schedule 117 | celerybeat.pid 118 | 119 | # SageMath parsed files 120 | *.sage.py 121 | 122 | # Environments 123 | .env 124 | .venv 125 | env/ 126 | venv/ 127 | ENV/ 128 | env.bak/ 129 | venv.bak/ 130 | 131 | # Spyder project settings 132 | .spyderproject 133 | .spyproject 134 | 135 | # Rope project settings 136 | .ropeproject 137 | 138 | # mkdocs documentation 139 | /site 140 | 141 | # mypy 142 | .mypy_cache/ 143 | .dmypy.json 144 | dmypy.json 145 | 146 | # Pyre type checker 147 | .pyre/ 148 | 149 | # pytype static type analyzer 150 | .pytype/ 151 | 152 | # Cython debug symbols 153 | cython_debug/ 154 | 155 | # PyCharm 156 | # JetBrains specific template is maintained in a separate JetBrains.gitignore that can 157 | # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore 158 | # and can be added to the global gitignore or merged into this file. For a more nuclear 159 | # option (not recommended) you can uncomment the following to ignore the entire idea folder. 160 | #.idea/ 161 | settings.yaml -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # cyberdolphin 2 | 3 | The dolphin is wiring up OpenAI and local LLMs. OpenAI v1.2.3 is required. 4 | 5 | ![cyberdolphin.png](examples/cyberdolphin.png) 6 | 7 | 8 | ## Installation 9 | 10 | Git clone this repo into the `custom_nodes` folder. 11 | If necessary, check the pip requirements. It will be necessary. 12 | 13 | ## Examples 14 | 15 | There are workflows in the [examples folder](./examples) 16 | ![img.png](examples/img.png) 17 | --- 18 | 19 | ## Nodes 20 | 21 | The nodes all share a config file at `settings.yaml`. Provided with the repo is the 22 | `settings.yaml.example` which can be copied to a new file called `settings.yaml` 23 | for editing. The `settings.yaml` file is ignored by git. 24 | 25 | ### OpenAI GPT Node 26 | 27 | **REQUIRES** STRING `user_prompt` 28 | 29 | The text is the user portion of the gpt prompt. 30 | _Generates_ an engineered prompt 31 | from a user-editable template config file with the user text embedded. 32 | Dropdown select from available OpenAI models. Most of these will not work. 33 | The models that DO work at the time of writing are at least, including but not limited to 34 | **gpt-3.5-turbo** and **gpt-4**. 35 | Runs the prompt gpt-3.5-turbo (or a user-selected alternative) with the text. 36 | 37 | **PRODUCES** STRING. 38 | 39 | ### OpenAI Compatible Node 40 | 41 | **REQUIRES** STRING `text` 42 | 43 | The text is embedded in the user prompt. 44 | Generates an "engineered" prompt from template. 45 | The user text is embedded in the engineered prompt. 46 | Calls for completion of the prompt to the user-defined URL. 47 | 48 | **PRODUCES** STRING 49 | 50 | ### OpenAI DALL·E Node 51 | 52 | **REQUIRES** STRING `text` 53 | 54 | Calls OpenAI DALL·E with the text. 55 | 56 | **PRODUCES** IMAGE 57 | 58 | 59 | --- 60 | 61 | ### Pip requirements 62 | 63 | This collection has some extra requirements that are not present in the ComfyUI distribution. 64 | Things like openai, gradio-client and technologist tools. 65 | 66 | ### Experimental 67 | 68 | This is an experimental collection of nodes. This project needs validation on MacOS, Windows and Linux. 69 | So far, it works on my machine which is a Linux distribution. 70 | 71 | ## Contributions 72 | 73 | Looking for participants, happy to work on PRs! 74 | 75 | **Guidelines for the Dolphin:** 76 | 77 | * Keep it small - PRs should be quick and easy. 78 | * Large things must be compositions of smaller things. 79 | * Dependencies should be external - i.e. loaded by a node 80 | * For example: 81 | * _the Llava loader node passes the Llava model to the recogniser node which uses the Llava model to emit a list of 82 | objects_ 83 | * _and not, the "Llava node does everything"_ 84 | 85 | **Keep it small** 86 | 87 | In the spirit of "Keep it small", I'm trying to make sure my big ideas for the dolphin 88 | stay within the realm of LLMs - 89 | 90 | Here are some big ideas that didn't make it into the roadmap for CyberDolphin: 91 | 92 | #### Big Ideas I have for future things that are not the dolphin: 93 | 94 | **Cam Nodes** 95 | 96 | * **Webcam Node** for phone/laptop 97 | * **Cam Node** for HDMI type input devices 98 | * **Live Stream Node** to capture vision from a _Thing of the Internet_ 99 | 100 | **Speech to Text** 101 | 102 | * **Microphone node** Captures spoken instructions into **audio node** 103 | * Instructions are transcribed using 104 | * **OpenAI-Whisper node** or 105 | * _TTS model_ loaded by the **TTS node** 106 | 107 | **The Simple Storybook Production Kit** 108 | 109 | Where "LLM-node" is short for "LLM powered node": 110 | 111 | ```text 112 | LLM-node dreams up the story type 113 | LLM-node dreams up the character names, their badge 114 | LLM-node dreams up the story title 115 | LLM-node dreams up chapter summaries 116 | 117 | LLM-node generates a page in "the story" 118 | 119 | LLM-node generates images of characters: 120 | id badge, 121 | smiling photo, 122 | frowning photo, 123 | 'character' shot 124 | 125 | LLM-node generates prompt for page illustration 126 | LLM-node generates page text 127 | ``` 128 | 129 | ## License 130 | 131 | GPL 3. -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. 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EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT 593 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY 594 | OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, 595 | THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR 596 | PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM 597 | IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF 598 | ALL NECESSARY SERVICING, REPAIR OR CORRECTION. 599 | 600 | 16. Limitation of Liability. 601 | 602 | IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING 603 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS 604 | THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY 605 | GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE 606 | USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF 607 | DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD 608 | PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), 609 | EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF 610 | SUCH DAMAGES. 611 | 612 | 17. Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | 623 | How to Apply These Terms to Your New Programs 624 | 625 | If you develop a new program, and you want it to be of the greatest 626 | possible use to the public, the best way to achieve this is to make it 627 | free software which everyone can redistribute and change under these terms. 628 | 629 | To do so, attach the following notices to the program. It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | --------------------------------------------------------------------------------