nodes/MinusZoneAI-ComfyUI-Prompt-MZ
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This commit is contained in:
wailovet
2024-05-23 23:12:05 +08:00
parent aed7d31ed5
commit 0f5148e901
2 changed files with 131 additions and 49 deletions
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__init__.py
+40 -49
View File
@@ -10,6 +10,8 @@ import shutil
import comfy.samplers
WEB_DIRECTORY = "./web"
AUTHOR_NAME = u"MinusZone"
CATEGORY_NAME = f"{AUTHOR_NAME} - Prompt"
@@ -156,6 +158,7 @@ class MZ_LLama3CLIPTextEncode:
RETURN_TYPES = ("STRING", "CONDITIONING",)
RETURN_NAMES = ("text", "conditioning",)
OUTPUT_NODE = True
FUNCTION = "encode"
CATEGORY = CATEGORY_NAME
@@ -173,7 +176,7 @@ class MZ_LLama3CLIPTextEncode:
cond, pooled = clip.encode_from_tokens(tokens, return_pooled=True,)
conditionings = [[cond, {"pooled_output": pooled}]]
return (text, conditionings)
return {"ui": {"string": [text,]}, "result": (text, conditionings)}
NODE_CLASS_MAPPINGS["MZ_LLama3CLIPTextEncode"] = MZ_LLama3CLIPTextEncode
@@ -212,6 +215,7 @@ class MZ_Phi3CLIPTextEncode:
RETURN_TYPES = ("STRING", "CONDITIONING",)
RETURN_NAMES = ("text", "conditioning",)
OUTPUT_NODE = True
FUNCTION = "encode"
CATEGORY = CATEGORY_NAME
@@ -229,7 +233,7 @@ class MZ_Phi3CLIPTextEncode:
cond, pooled = clip.encode_from_tokens(tokens, return_pooled=True,)
conditionings = [[cond, {"pooled_output": pooled}]]
return (text, conditionings)
return {"ui": {"string": [text,]}, "result": (text, conditionings)}
NODE_CLASS_MAPPINGS["MZ_Phi3CLIPTextEncode"] = MZ_Phi3CLIPTextEncode
@@ -259,6 +263,7 @@ class MZ_BaseLLamaCPPCLIPTextEncode:
return result
RETURN_TYPES = ("STRING", "CONDITIONING",)
RETURN_NAMES = ("text", "conditioning",)
OUTPUT_NODE = True
FUNCTION = "encode"
CATEGORY = CATEGORY_NAME
@@ -276,7 +281,7 @@ class MZ_BaseLLamaCPPCLIPTextEncode:
cond, pooled = clip.encode_from_tokens(tokens, return_pooled=True,)
conditionings = [[cond, {"pooled_output": pooled}]]
return (text, conditionings)
return {"ui": {"string": [text,]}, "result": (text, conditionings)}
NODE_CLASS_MAPPINGS["MZ_BaseLLamaCPPCLIPTextEncode"] = MZ_BaseLLamaCPPCLIPTextEncode
@@ -322,6 +327,7 @@ class MZ_LLavaImageInterrogator:
}}
RETURN_TYPES = ("STRING", "CONDITIONING",)
RETURN_NAMES = ("text", "conditioning",)
OUTPUT_NODE = True
FUNCTION = "interrogate"
CATEGORY = CATEGORY_NAME
@@ -335,14 +341,14 @@ class MZ_LLavaImageInterrogator:
kwargs["image"] = Utils.tensor2pil(kwargs["image"])
response = mz_llava.image_interrogator(kwargs)
text = mz_llava.image_interrogator(kwargs)
conditionings = None
clip = kwargs.get("clip", None)
if clip is not None:
tokens = clip.tokenize(response)
tokens = clip.tokenize(text)
cond, pooled = clip.encode_from_tokens(tokens, return_pooled=True,)
conditionings = [[cond, {"pooled_output": pooled}]]
return (response, conditionings)
return {"ui": {"string": [text,]}, "result": (text, conditionings)}
NODE_CLASS_MAPPINGS["MZ_LLavaImageInterrogator"] = MZ_LLavaImageInterrogator
@@ -369,6 +375,7 @@ class MZ_BaseLLavaImageInterrogator:
}}
RETURN_TYPES = ("STRING", "CONDITIONING",)
RETURN_NAMES = ("text", "conditioning",)
OUTPUT_NODE = True
FUNCTION = "interrogate"
CATEGORY = CATEGORY_NAME
@@ -377,14 +384,14 @@ class MZ_BaseLLavaImageInterrogator:
kwargs["image"] = Utils.tensor2pil(kwargs["image"])
response = mz_llava.base_image_interrogator(kwargs)
text = mz_llava.base_image_interrogator(kwargs)
conditionings = None
clip = kwargs.get("clip", None)
if clip is not None:
tokens = clip.tokenize(response)
tokens = clip.tokenize(text)
cond, pooled = clip.encode_from_tokens(tokens, return_pooled=True,)
conditionings = [[cond, {"pooled_output": pooled}]]
return (response, conditionings)
return {"ui": {"string": [text,]}, "result": (text, conditionings)}
NODE_CLASS_MAPPINGS["MZ_BaseLLavaImageInterrogator"] = MZ_BaseLLavaImageInterrogator
@@ -392,38 +399,6 @@ NODE_DISPLAY_NAME_MAPPINGS[
"MZ_BaseLLavaImageInterrogator"] = f"{AUTHOR_NAME} - ImageInterrogator(BaseLLava)"
class MZ_LLamaCPPInterrogator:
@classmethod
def INPUT_TYPES(s):
return {
"required": {
"model_file": ("STRING", {"default": ""}),
"use_system": ([True, False], {"default": True}),
"system": ("STRING", {"multiline": True, "default": "You are a helpful assistant."}),
"prompt": ("STRING", {"multiline": True, }),
"n_gpu_layers": ("INT", {"default": -1, "min": -1, "max": 0xffffffffffffffff}),
},
}
RETURN_TYPES = ("STRING",)
RETURN_NAMES = ("text",)
FUNCTION = "simple_interrogator"
CATEGORY = CATEGORY_NAME
def simple_interrogator(self, model_file, prompt, use_system=True, system="You are a helpful assistant.", n_gpu_layers=-1):
importlib.reload(mz_llama_cpp)
result = mz_llama_cpp.llama_cpp_simple_interrogator(
model_file,
n_gpu_layers=n_gpu_layers,
use_system=use_system,
system=system,
question=prompt,
)
return (result,)
# NODE_CLASS_MAPPINGS["MZ_LLamaCPPInterrogator"] = MZ_LLamaCPPInterrogator
# NODE_DISPLAY_NAME_MAPPINGS["MZ_LLamaCPPInterrogator"] = f"{AUTHOR_NAME} - LLamaCPP simple interrogator"
class MZ_OpenAIApiCLIPTextEncode:
@classmethod
def INPUT_TYPES(s):
@@ -445,10 +420,13 @@ class MZ_OpenAIApiCLIPTextEncode:
except Exception as e:
print(f"Failed to load openai_config.json: {e}")
default_api_key = default_config.get("api_key", "")
if default_api_key != "":
default_api_key = default_api_key[:4] + "******"
result = {
"required": {
"base_url": ("STRING", {"default": default_config.get("base_url", ""), "placeholder": ""}),
"api_key": ("STRING", {"default": default_config.get("api_key", ""), "placeholder": ""}),
"api_key": ("STRING", {"default": default_api_key, "placeholder": ""}),
"model_name": ("STRING", {"default": default_config.get("model_name", ""), }),
},
"optional": {
@@ -466,6 +444,7 @@ class MZ_OpenAIApiCLIPTextEncode:
return result
RETURN_TYPES = ("STRING", "CONDITIONING",)
RETURN_NAMES = ("text", "conditioning",)
OUTPUT_NODE = True
FUNCTION = "encode"
CATEGORY = CATEGORY_NAME
@@ -473,12 +452,24 @@ class MZ_OpenAIApiCLIPTextEncode:
import mz_openaiapi
importlib.reload(mz_openaiapi)
with open(self.openai_config_path, "w", encoding="utf-8") as f:
json.dump({
"base_url": kwargs.get("base_url", ""),
"api_key": kwargs.get("api_key", ""),
"model_name": kwargs.get("model_name", ""),
}, f, indent=4)
if kwargs.get("api_key", "").endswith("******"):
kwargs["api_key"] = ""
try:
with open(self.openai_config_path, "r", encoding="utf-8") as f:
config = json.load(f)
kwargs["api_key"] = config.get("api_key", "")
except Exception as e:
print(f"Failed to load openai_config.json: {e}")
if kwargs.get("api_key", "") != "":
with open(self.openai_config_path, "w", encoding="utf-8") as f:
json.dump({
"base_url": kwargs.get("base_url", ""),
"api_key": kwargs.get("api_key", ""),
"model_name": kwargs.get("model_name", ""),
}, f, indent=4)
else:
raise ValueError("api_key is required")
text = mz_openaiapi.query_beautify_prompt_text(kwargs)
conditionings = None
@@ -488,7 +479,7 @@ class MZ_OpenAIApiCLIPTextEncode:
cond, pooled = clip.encode_from_tokens(tokens, return_pooled=True,)
conditionings = [[cond, {"pooled_output": pooled}]]
return (text, conditionings)
return {"ui": {"string": [text,]}, "result": (text, conditionings)}
NODE_CLASS_MAPPINGS["MZ_OpenAIApiCLIPTextEncode"] = MZ_OpenAIApiCLIPTextEncode
web/prompt_mz.js
+91
View File
@@ -0,0 +1,91 @@
import { app } from "../../scripts/app.js";
import { api } from "../../scripts/api.js";
import { ComfyWidgets } from "/scripts/widgets.js";
async function sleep(ms) {
return new Promise((resolve) => setTimeout(resolve, ms));
}
/**
* @returns {import("./types/comfy").ComfyExtension} extension
*/
const my_ui = {
name: "prompt_mz.ui",
setup() {},
init: async () => {
console.log("prompt_mz Registering UI extension");
},
/**
* @param {import("./types/comfy").NodeType} nodeType
* @param {import("./types/comfy").NodeDef} nodeData
* @param {import("./types/comfy").App} app
*/
async beforeRegisterNodeDef(nodeType, nodeData, app) {
switch (nodeData.name) {
case "MZ_OpenAIApiCLIPTextEncode":
case "MZ_LLama3CLIPTextEncode":
case "MZ_Phi3CLIPTextEncode":
case "MZ_BaseLLamaCPPCLIPTextEncode":
case "MZ_LLavaImageInterrogator":
case "MZ_BaseLLavaImageInterrogator":
// Node Created
const onNodeCreated = nodeType.prototype.onNodeCreated;
nodeType.prototype.onNodeCreated = function () {
const ret = onNodeCreated
? onNodeCreated.apply(this, arguments)
: undefined;
const nodeName = this.name + "_" + "customtext";
const wi = ComfyWidgets.STRING(
this,
nodeName,
[
"STRING",
{
default: "",
placeholder: "Text message output...",
multiline: true,
},
],
app
);
wi.widget.inputEl.readOnly = true;
return ret;
};
const outSet = function (texts) {
if (texts.length > 0) {
let widget_id = this?.widgets.findIndex(
(w) => w.name === this.name + "_" + "customtext"
);
if (Array.isArray(texts))
texts = texts
.filter((word) => word.trim() !== "")
.map((word) => word.trim())
.join(" ");
this.widgets[widget_id].value = texts;
app.graph.setDirtyCanvas(true);
}
};
// onConfigure
const onConfigure = nodeType.prototype.onConfigure;
nodeType.prototype.onConfigure = function (w) {
onConfigure?.apply(this, arguments);
};
// onExecuted
const onExecuted = nodeType.prototype.onExecuted;
nodeType.prototype.onExecuted = function (a, b) {
console.log("onExecuted:", arguments);
onExecuted?.apply(this, arguments);
outSet.call(this, a?.string);
};
}
},
};
app.registerExtension(my_ui);