add SiliconflowLLM

README.md

@@ -6,13 +6,14 @@
 
 ##### `最新`：
 
-- 增加 Edit Mask，方便在生成的时候手动绘制 mask [workflow](./workflow/edit-mask-workflow.json)
-
+- 增加 SiliconflowLLM，可以使用由Siliconflow提供的免费LLM
 
-- ChatGPT 节点支持 Local LLM（llama.cpp），Phi3、llama3 都可以直接一个节点运行了。模型下载后，放置到 `models/llamafile/`
+- 增加 Edit Mask，方便在生成的时候手动绘制 mask [workflow](./workflow/edit-mask-workflow.json)
 
-- 右键菜单支持 text-to-text，方便对 prompt 词补全
+<!-- - ChatGPT 节点支持 Local LLM（llama.cpp），Phi3、llama3 都可以直接一个节点运行了。模型下载后，放置到 `models/llamafile/` -->
 
+<!-- - 右键菜单支持 text-to-text，方便对 prompt 词补全 -->
+<!-- 
 强烈推荐：
 [Phi-3-mini-4k-instruct-function-calling-GGUF](https://huggingface.co/nold/Phi-3-mini-4k-instruct-function-calling-GGUF)
 
@@ -21,7 +22,7 @@
 - 右键菜单支持 image-to-text，使用多模态模型，多模态使用 [llava-phi-3-mini-gguf](https://huggingface.co/xtuner/llava-phi-3-mini-gguf/tree/main)，注意需要把llava-phi-3-mini-mmproj-f16.gguf也下载
 
 ![](./assets/prompt_ai_setup.png)
-![](./assets/prompt-ai.png)
+![](./assets/prompt-ai.png) -->
 
 
 #### `相关插件推荐`

__init__.py

@@ -1147,11 +1147,12 @@ def re_start(request):
 # print('\033[91m ### Mixlab Nodes: \033[93mLoaded')
 
 try:
-    from .nodes.ChatGPT import ChatGPTNode,ShowTextForGPT,CharacterInText,TextSplitByDelimiter
+    from .nodes.ChatGPT import ChatGPTNode,ShowTextForGPT,CharacterInText,TextSplitByDelimiter,SiliconflowFreeNode
     logging.info('ChatGPT.available True')
 
     NODE_CLASS_MAPPINGS_V = {
        "ChatGPTOpenAI":ChatGPTNode,
+       "SiliconflowLLM":SiliconflowFreeNode,
         "ShowTextForGPT":ShowTextForGPT,
         "CharacterInText":CharacterInText,
         "TextSplitByDelimiter":TextSplitByDelimiter,
@@ -1160,6 +1161,7 @@ def re_start(request):
     # 一个包含节点友好/可读的标题的字典
     NODE_DISPLAY_NAME_MAPPINGS_V = {
         "ChatGPTOpenAI":"ChatGPT & Local LLM ♾️Mixlab",
+        "SiliconflowLLM":"LLM Siliconflow ♾️Mixlab",
         "ShowTextForGPT":"Show Text ♾️MixlabApp",
         "CharacterInText":"Character In Text",
         "TextSplitByDelimiter":"Text Split By Delimiter",

nodes/ChatGPT.py

@@ -53,8 +53,8 @@ def azure_client(key,url):
 
 def openai_client(key,url):
     client = openai.OpenAI(
-    api_key=key,
-    base_url=url
+        api_key=key,
+        base_url=url
     )
     return client
 
@@ -163,7 +163,7 @@ def llama_cpp_client(file_name):
 
 
 def chat(client, model_name,messages ):
-
+        print('#chat',model_name,messages)
         try_count = 0
         while True:
             try_count += 1
@@ -304,7 +304,7 @@ def generate_contextual_text(self,
                 client=llama_cpp_client(model)
             else :
                 client = openai_client(api_key,api_url)  # 使用 ChatGPT  的接口
-                print('using ChatGPT interface')
+                # print('using ChatGPT interface',api_key,api_url)
 
         # 把用户的提示添加到会话历史中
         # 调用API时传递整个会话历史
@@ -320,6 +320,7 @@ def crop_list_tail(lst, size):
         session_history=crop_list_tail(self.session_history,context_size)
 
         messages=[{"role": "system", "content": self.system_content}]+session_history+[{"role": "user", "content": prompt}]
+
         response_content = chat(client,model,messages)
 
         self.session_history=self.session_history+[{"role": "user", "content": prompt}]+[{'role':'assistant',"content":response_content}]
@@ -340,6 +341,91 @@ def crop_list_tail(lst, size):
         return (response_content,json.dumps(messages, indent=4),json.dumps(self.session_history, indent=4),)
 
 
+class SiliconflowFreeNode:
+    def __init__(self):
+        # self.__client = OpenAI()
+        self.session_history = []  # 用于存储会话历史的列表
+        # self.seed=0
+        self.system_content="You are ChatGPT, a large language model trained by OpenAI. Answer as concisely as possible."
+
+    @classmethod
+    def INPUT_TYPES(cls):
+        model_list= [ 
+            "Qwen/Qwen2-7B-Instruct",
+            "THUDM/glm-4-9b-chat",
+            "01-ai/Yi-1.5-9B-Chat-16K",
+            "meta-llama/Meta-Llama-3.1-8B-Instruct"
+            ]
+        return {
+            "required": {
+                "api_key":("KEY", {"default": "", "multiline": True,"dynamicPrompts": False}),
+                "prompt": ("STRING", {"multiline": True,"dynamicPrompts": False}),
+                "system_content": ("STRING", 
+                                   {
+                                       "default": "You are ChatGPT, a large language model trained by OpenAI. Answer as concisely as possible.", 
+                                       "multiline": True,"dynamicPrompts": False
+                                       }),
+                "model": ( model_list, 
+                    {"default": model_list[0]}),
+                "seed": ("INT", {"default": 0, "min": 0, "max": 0xffffffffffffffff, "step": 1}),
+                "context_size":("INT", {"default": 1, "min": 0, "max":30, "step": 1}),
+            },
+             "hidden": {
+                "unique_id": "UNIQUE_ID",
+                "extra_pnginfo": "EXTRA_PNGINFO",
+            },
+        }
+
+    RETURN_TYPES = ("STRING","STRING","STRING",)
+    RETURN_NAMES = ("text","messages","session_history",)
+    FUNCTION = "generate_contextual_text"
+    CATEGORY = "♾️Mixlab/GPT"
+    INPUT_IS_LIST = False
+    OUTPUT_IS_LIST = (False,False,False,)
+
+
+    def generate_contextual_text(self,
+                                 api_key,
+                                 prompt, 
+                                 system_content,
+                                model, 
+                                seed,context_size,unique_id = None, extra_pnginfo=None):
+
+        api_url="https://api.siliconflow.cn/v1"
+
+        # 把系统信息和初始信息添加到会话历史中
+        if system_content:
+            self.system_content=system_content
+            # self.session_history=[]
+            # self.session_history.append({"role": "system", "content": system_content})
+
+        # 
+        client = openai_client(api_key,api_url)  # 使用 ChatGPT  的接口
+        # print('using ChatGPT interface',api_key,api_url)
+
+        # 把用户的提示添加到会话历史中
+        # 调用API时传递整个会话历史
+
+        def crop_list_tail(lst, size):
+            if size >= len(lst):
+                return lst
+            elif size==0:
+                return []
+            else:
+                return lst[-size:]
+
+        session_history=crop_list_tail(self.session_history,context_size)
+
+        messages=[{"role": "system", "content": self.system_content}]+session_history+[{"role": "user", "content": prompt}]
+
+        response_content = chat(client,model,messages)
+
+        self.session_history=self.session_history+[{"role": "user", "content": prompt}]+[{'role':'assistant',"content":response_content}]
+
+        return (response_content,json.dumps(messages, indent=4),json.dumps(self.session_history, indent=4),)
+
+
+
 
 class ShowTextForGPT:
     @classmethod

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "comfyui-mixlab-nodes"
 description = "3D, ScreenShareNode & FloatingVideoNode, SpeechRecognition & SpeechSynthesis, GPT, LoadImagesFromLocal, Layers, Other Nodes, ..."
-version = "0.31.1"
+version = "0.32.0"
 license = "MIT"
 dependencies = ["numpy", "pyOpenSSL", "watchdog", "opencv-python-headless", "matplotlib", "openai", "simple-lama-inpainting", "clip-interrogator==0.6.0", "transformers>=4.36.0", "lark-parser", "imageio-ffmpeg", "rembg[gpu]", "omegaconf==2.3.0", "Pillow>=9.5.0", "einops==0.7.0", "trimesh>=4.0.5", "huggingface-hub", "scikit-image"]
 

web/javascript/app_mixlab.js

@@ -466,7 +466,6 @@ app.registerExtension({
         const { input, output } = getInputsAndOutputs()
         input_ids.value = input.join('\n')
         output_ids.value = output.join('\n')
-
         const widget = {
           type: 'div',
           name: 'AppInfoRun',

web/javascript/gpt_mixlab.js

@@ -199,6 +199,120 @@ app.registerExtension({
         url[id] || 'https://api.openai.com/v1'
     }
   }
+});
+
+
+app.registerExtension({
+  name: 'Mixlab.GPT.SiliconflowLLM',
+  async getCustomWidgets (app) {
+    return {
+      KEY (node, inputName, inputData, app) {
+        // console.log('##inputData', inputData)
+        const widget = {
+          type: inputData[0], // the type, CHEESE
+          name: inputName, // the name, slice
+          size: [128, 32], // a default size
+          draw (ctx, node, width, y) {},
+          computeSize (...args) {
+            return [128, 32] // a method to compute the current size of the widget
+          },
+          async serializeValue (nodeId, widgetIndex) {
+            let data = getLocalData('_mixlab_api_key')
+            return data[node.id] || 'by Mixlab'
+          }
+        }
+        //  widget.something = something;          // maybe adds stuff to it
+        node.addCustomWidget(widget) // adds it to the node
+        return widget // and returns it.
+      },
+    }
+  },
+
+  async beforeRegisterNodeDef (nodeType, nodeData, app) {
+    if (nodeType.comfyClass == 'SiliconflowLLM') {
+      const orig_nodeCreated = nodeType.prototype.onNodeCreated
+      nodeType.prototype.onNodeCreated = function () {
+        orig_nodeCreated?.apply(this, arguments)
+
+        const api_key = this.widgets.filter(w => w.name == 'api_key')[0]
+
+        const widget = {
+          type: 'div',
+          name: 'chatgptdiv',
+          draw (ctx, node, widget_width, y, widget_height) {
+            Object.assign(
+              this.div.style,
+              get_position_style(ctx, widget_width, api_key.y, node.size[1])
+            )
+          }
+        }
+
+        widget.div = $el('div', {})
+
+        document.body.appendChild(widget.div)
+
+        const inputDiv = (key, placeholder) => {
+          let div = document.createElement('div')
+          const ip = document.createElement('input')
+          ip.type = placeholder === 'Key' ? 'password' : 'text'
+          ip.className = `${'comfy-multiline-input'} ${placeholder}`
+          div.style = `display: flex;
+          align-items: center; 
+          margin: 6px 8px;
+          margin-top: 0;`
+          ip.placeholder = placeholder
+          ip.value = placeholder
+
+          ip.style = `margin-left: 24px;
+          outline: none;
+          border: none;
+          padding: 4px;width: 100%;`
+          const label = document.createElement('label')
+          label.style = 'font-size: 10px;min-width:32px'
+          label.innerText = placeholder
+          div.appendChild(label)
+          div.appendChild(ip)
+
+          ip.addEventListener('change', () => {
+            let data = getLocalData(key)
+            data[this.id] = ip.value.trim()
+            localStorage.setItem(key, JSON.stringify(data))
+            console.log(this.id, key)
+          })
+          return div
+        }
+
+        let inputKey = inputDiv('_mixlab_api_key', 'Key') 
+
+        widget.div.appendChild(inputKey) 
+
+        this.addCustomWidget(widget)
+
+        const onRemoved = this.onRemoved
+        this.onRemoved = () => { 
+          inputKey.remove()
+          widget.div.remove()
+          return onRemoved?.()
+        }
+
+        this.serialize_widgets = true //需要保存参数
+      }
+    }
+  },
+  async loadedGraphNode (node, app) {
+    // Fires every time a node is constructed
+    // You can modify widgets/add handlers/etc here
+
+    if (node.type === 'SiliconflowLLM') {
+      let widget = node.widgets.filter(w => w.div)[0]
+
+      let apiKey = getLocalData('_mixlab_api_key');
+
+      let id = node.id
+
+      widget.div.querySelector('.Key').value = apiKey[id] || 'by Mixlab' 
+    }
+  }
 })
 
 app.registerExtension({