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akhaliq HF Staff commited on Jul 28

Commit

0182706

1 Parent(s): 6039a02

add new glm model

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app.py +374 -1

app.py CHANGED Viewed

@@ -18,6 +18,8 @@ import json
 import time
 import webbrowser
 import urllib.parse
 import gradio as gr
 from huggingface_hub import InferenceClient
@@ -359,6 +361,11 @@ AVAILABLE_MODELS = [
         "id": "HuggingFaceTB/SmolLM3-3B",
         "description": "SmolLM3-3B model for code generation and general tasks"
     },
     {
         "name": "GLM-4.1V-9B-Thinking",
         "id": "THUDM/GLM-4.1V-9B-Thinking",
@@ -1358,6 +1365,226 @@ The HTML code above contains the complete original website structure with all im
     except Exception as e:
         return f"Error extracting website content: {str(e)}"
 def generation_code(query: Optional[str], image: Optional[gr.Image], file: Optional[str], website_url: Optional[str], _setting: Dict[str, str], _history: Optional[History], _current_model: Dict, enable_search: bool = False, language: str = "html", provider: str = "auto"):
     if query is None:
         query = ''
@@ -1439,7 +1666,153 @@ This will help me create a better design for you."""
     # Enhance query with search if enabled
     enhanced_query = enhance_query_with_search(query, enable_search)
-    # Use dynamic client based on selected model
     client = get_inference_client(_current_model["id"], provider)
     if image is not None:

 import time
 import webbrowser
 import urllib.parse
+import copy
+import html
 import gradio as gr
 from huggingface_hub import InferenceClient
         "id": "HuggingFaceTB/SmolLM3-3B",
         "description": "SmolLM3-3B model for code generation and general tasks"
     },
+    {
+        "name": "GLM-4.5",
+        "id": "GLM-4.5",
+        "description": "GLM-4.5 model with thinking capabilities for advanced code generation"
+    },
     {
         "name": "GLM-4.1V-9B-Thinking",
         "id": "THUDM/GLM-4.1V-9B-Thinking",
     except Exception as e:
         return f"Error extracting website content: {str(e)}"
+# GLM-4.5 Model Implementation
+stop_generation = False
+def stream_from_vllm(messages, thinking_enabled=True, temperature=1.0):
+    global stop_generation
+    # Get GLM API configuration from environment variables
+    glm_api_key = os.getenv('OPENAI_API_KEY')
+    glm_base_url = os.getenv('GLM_BASE_URL', 'https://open.bigmodel.cn/api/paas/v4/')
+    if not glm_api_key:
+        # Return configuration error if no API key
+        error_msg = """
+GLM-4.5 API Key Not Configured
+To use GLM-4.5, please:
+1. Get your API key from: https://open.bigmodel.cn/
+2. Set environment variable: OPENAI_API_KEY=your_api_key_here
+3. Optionally set GLM_BASE_URL if using different endpoint
+Example HTML code generation with Gradio:
+```html
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Sample App</title>
+    <style>
+        body { font-family: Arial, sans-serif; margin: 40px; }
+        .container { max-width: 600px; margin: 0 auto; }
+        h1 { color: #333; }
+        .button {
+            background: #007acc;
+            color: white;
+            padding: 10px 20px;
+            border: none;
+            border-radius: 5px;
+            cursor: pointer;
+        }
+    </style>
+</head>
+<body>
+    <div class="container">
+        <h1>GLM-4.5 Configuration Required</h1>
+        <p>Please configure your GLM-4.5 API key to use this model.</p>
+        <button class="button" onclick="alert('Configure OPENAI_API_KEY environment variable')">Get Started</button>
+    </div>
+</body>
+</html>
+```
+"""
+        yield type('Delta', (), {'content': error_msg, 'reasoning_content': None})()
+        return
+    # Configure OpenAI client for GLM-4.5
+    try:
+        client = OpenAI(
+            base_url=glm_base_url,
+            api_key=glm_api_key,
+        )
+        response = client.chat.completions.create(
+            model="GLM-4.5",
+            messages=messages,
+            temperature=temperature,
+            stream=True,
+            max_tokens=65536,
+            extra_body={
+                "thinking": {
+                    "type": "enabled" if thinking_enabled else "disabled",
+                }
+            }
+        )
+        for chunk in response:
+            if stop_generation:
+                break
+            if chunk.choices and chunk.choices[0].delta:
+                yield chunk.choices[0].delta
+    except Exception as e:
+        # Fallback: if GLM-4.5 API fails, yield error with sample code
+        error_msg = f"""Error connecting to GLM-4.5: {str(e)}
+Please check:
+1. OPENAI_API_KEY environment variable is set correctly
+2. API key is valid and has credits
+3. Network connection is working
+4. GLM_BASE_URL is correct (current: {glm_base_url})
+Here's a sample HTML code to test the UI:
+```html
+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>GLM-4.5 Error - Sample Output</title>
+    <style>
+        body {{
+            font-family: Arial, sans-serif;
+            margin: 40px;
+            background: linear-gradient(135deg, #667eea 0%, #764ba2 100%);
+            color: white;
+        }}
+        .container {{
+            max-width: 600px;
+            margin: 0 auto;
+            background: rgba(255,255,255,0.1);
+            padding: 30px;
+            border-radius: 15px;
+            backdrop-filter: blur(10px);
+        }}
+        h1 {{ color: #fff; text-align: center; }}
+        .error {{ background: rgba(255,0,0,0.2); padding: 15px; border-radius: 8px; margin: 20px 0; }}
+        .button {{
+            background: rgba(255,255,255,0.2);
+            color: white;
+            padding: 12px 24px;
+            border: 1px solid rgba(255,255,255,0.3);
+            border-radius: 8px;
+            cursor: pointer;
+            display: block;
+            margin: 20px auto;
+        }}
+        .button:hover {{ background: rgba(255,255,255,0.3); }}
+    </style>
+</head>
+<body>
+    <div class="container">
+        <h1>🤖 GLM-4.5 Configuration Error</h1>
+        <div class="error">
+            <strong>Error:</strong> {str(e)}
+        </div>
+        <p>This is a sample HTML output to demonstrate the UI while you configure GLM-4.5.</p>
+        <button class="button" onclick="window.open('https://open.bigmodel.cn/', '_blank')">Configure GLM-4.5 API</button>
+    </div>
+    <script>
+        console.log('GLM-4.5 API Error: {str(e)}');
+    </script>
+</body>
+</html>
+```"""
+        print(f"GLM-4.5 API Error: {e}")
+        yield type('Delta', (), {'content': error_msg, 'reasoning_content': None})()
+class GLM45Model:
+    def __init__(self):
+        self.accumulated_content = ""
+        self.accumulated_reasoning = ""
+    def reset_state(self):
+        self.accumulated_content = ""
+        self.accumulated_reasoning = ""
+    def _render_response(self, reasoning_content, regular_content, skip_think=False):
+        html_parts = []
+        if reasoning_content and not skip_think:
+            reasoning_escaped = html.escape(reasoning_content).replace("\n", "<br>")
+            think_html = (
+                    "<details open><summary style='cursor:pointer;font-weight:bold;color:#007acc;'>Thinking</summary>"
+                    "<div style='color:#555555;line-height:1.6;padding:15px;border-left:4px solid #007acc;margin:10px 0;background-color:#f0f7ff;border-radius:4px;'>"
+                    + reasoning_escaped +
+                    "</div></details>"
+            )
+            html_parts.append(think_html)
+        if regular_content:
+            content_escaped = html.escape(regular_content).replace("\n", "<br>")
+            content_html = f"<div style='margin:0.5em 0; white-space: pre-wrap; line-height:1.6;'>{content_escaped}</div>"
+            html_parts.append(content_html)
+        return "".join(html_parts)
+    def _build_messages(self, raw_hist, sys_prompt):
+        msgs = []
+        if sys_prompt.strip():
+            msgs.append({"role": "system", "content": sys_prompt.strip()})
+        for h in raw_hist:
+            if h["role"] == "user":
+                msgs.append({"role": "user", "content": h["content"]})
+            else:
+                msg = {"role": "assistant", "content": h.get("content", "")}
+                if h.get("reasoning_content"):
+                    msg["reasoning_content"] = h.get("reasoning_content")
+                msgs.append(msg)
+        return msgs
+    def stream_generate(self, raw_hist, sys_prompt, thinking_enabled=True, temperature=1.0):
+        global stop_generation
+        stop_generation = False
+        msgs = self._build_messages(raw_hist, sys_prompt)
+        self.reset_state()
+        try:
+            for delta in stream_from_vllm(msgs, thinking_enabled, temperature):
+                if stop_generation:
+                    break
+                if hasattr(delta, 'content') and delta.content:
+                    self.accumulated_content += delta.content
+                if hasattr(delta, 'reasoning_content') and delta.reasoning_content:
+                    self.accumulated_reasoning += delta.reasoning_content
+                yield self._render_response(self.accumulated_reasoning, self.accumulated_content, not thinking_enabled)
+        except Exception as e:
+            yield self._render_response("", f"Error: {str(e)}")
+# Global GLM-4.5 instance
+glm45 = GLM45Model()
 def generation_code(query: Optional[str], image: Optional[gr.Image], file: Optional[str], website_url: Optional[str], _setting: Dict[str, str], _history: Optional[History], _current_model: Dict, enable_search: bool = False, language: str = "html", provider: str = "auto"):
     if query is None:
         query = ''
     # Enhance query with search if enabled
     enhanced_query = enhance_query_with_search(query, enable_search)
+    # Check if this is GLM-4.5 model and handle differently
+    if _current_model["id"] == "GLM-4.5":
+        # For GLM-4.5, use the specialized implementation with simpler streaming
+        if image is not None:
+            messages.append(create_multimodal_message(enhanced_query, image))
+        else:
+            messages.append({'role': 'user', 'content': enhanced_query})
+        content = ""
+        reasoning_content = ""
+        try:
+            # Use GLM-4.5 streaming directly
+            for delta in stream_from_vllm(messages, True, 1.0):
+                if stop_generation:
+                    break
+                if hasattr(delta, 'content') and delta.content:
+                    content += delta.content
+                if hasattr(delta, 'reasoning_content') and delta.reasoning_content:
+                    reasoning_content += delta.reasoning_content
+                # Show streaming content (extract just the code part)
+                clean_code = remove_code_block(content)
+                search_status = " (with web search)" if enable_search and tavily_client else ""
+                # Handle different language outputs for GLM-4.5 during streaming
+                if language == "transformers.js":
+                    files = parse_transformers_js_output(clean_code)
+                    if files['index.html'] and files['index.js'] and files['style.css']:
+                        formatted_output = format_transformers_js_output(files)
+                        yield {
+                            code_output: gr.update(value=formatted_output, language="html"),
+                            history_output: history_to_chatbot_messages(_history),
+                            sandbox: send_to_sandbox(files['index.html']) if files['index.html'] else "<div style='padding:1em;color:#888;text-align:center;'>Preview is only available for HTML. Please download your code using the download button above.</div>",
+                        }
+                    else:
+                        yield {
+                            code_output: gr.update(value=clean_code, language="html"),
+                            history_output: history_to_chatbot_messages(_history),
+                            sandbox: "<div style='padding:1em;color:#888;text-align:center;'>Generating transformers.js app...</div>",
+                        }
+                elif language == "svelte":
+                    yield {
+                        code_output: gr.update(value=clean_code, language="html"),
+                        history_output: history_to_chatbot_messages(_history),
+                        sandbox: "<div style='padding:1em;color:#888;text-align:center;'>Generating Svelte app...</div>",
+                    }
+                else:
+                    if has_existing_content:
+                        if clean_code.strip().startswith("<!DOCTYPE html>") or clean_code.strip().startswith("<html"):
+                            yield {
+                                code_output: gr.update(value=clean_code, language=get_gradio_language(language)),
+                                history_output: history_to_chatbot_messages(_history),
+                                sandbox: send_to_sandbox(clean_code) if language == "html" else "<div style='padding:1em;color:#888;text-align:center;'>Preview is only available for HTML. Please download your code using the download button above.</div>",
+                            }
+                        else:
+                            last_content = _history[-1][1] if _history and len(_history[-1]) > 1 else ""
+                            modified_content = apply_search_replace_changes(last_content, clean_code)
+                            clean_content = remove_code_block(modified_content)
+                            yield {
+                                code_output: gr.update(value=clean_content, language=get_gradio_language(language)),
+                                history_output: history_to_chatbot_messages(_history),
+                                sandbox: send_to_sandbox(clean_content) if language == "html" else "<div style='padding:1em;color:#888;text-align:center;'>Preview is only available for HTML. Please download your code using the download button above.</div>",
+                            }
+                    else:
+                        yield {
+                            code_output: gr.update(value=clean_code, language=get_gradio_language(language)),
+                            history_output: history_to_chatbot_messages(_history),
+                            sandbox: send_to_sandbox(clean_code) if language == "html" else "<div style='padding:1em;color:#888;text-align:center;'>Preview is only available for HTML. Please download your code using the download button above.</div>",
+                        }
+        except Exception as e:
+            content = f"Error: {str(e)}"
+            print(f"GLM-4.5 Error: {e}")
+        # Final processing for GLM-4.5
+        clean_code = remove_code_block(content)
+        # Store content with thinking information if available
+        if reasoning_content:
+            full_response = f"**Thinking:**\n{reasoning_content}\n\n**Code:**\n{content}"
+        else:
+            full_response = content
+        if language == "transformers.js":
+            files = parse_transformers_js_output(clean_code)
+            if files['index.html'] and files['index.js'] and files['style.css']:
+                formatted_output = format_transformers_js_output(files)
+                _history.append([query, full_response])
+                yield {
+                    code_output: formatted_output,
+                    history: _history,
+                    sandbox: send_to_sandbox(files['index.html']),
+                    history_output: history_to_chatbot_messages(_history),
+                }
+            else:
+                _history.append([query, full_response])
+                yield {
+                    code_output: clean_code,
+                    history: _history,
+                    sandbox: "<div style='padding:1em;color:#888;text-align:center;'>Error parsing transformers.js output. Please try again.</div>",
+                    history_output: history_to_chatbot_messages(_history),
+                }
+        elif language == "svelte":
+            files = parse_svelte_output(clean_code)
+            if files['src/App.svelte'] and files['src/app.css']:
+                formatted_output = format_svelte_output(files)
+                _history.append([query, full_response])
+                yield {
+                    code_output: formatted_output,
+                    history: _history,
+                    sandbox: "<div style='padding:1em;color:#888;text-align:center;'>Preview is only available for HTML. Please download your Svelte code using the download button above.</div>",
+                    history_output: history_to_chatbot_messages(_history),
+                }
+            else:
+                _history.append([query, full_response])
+                yield {
+                    code_output: clean_code,
+                    history: _history,
+                    sandbox: "<div style='padding:1em;color:#888;text-align:center;'>Preview is only available for HTML. Please download your Svelte code using the download button above.</div>",
+                    history_output: history_to_chatbot_messages(_history),
+                }
+        else:
+            if has_existing_content and not (clean_code.strip().startswith("<!DOCTYPE html>") or clean_code.strip().startswith("<html")):
+                last_content = _history[-1][1] if _history and len(_history[-1]) > 1 else ""
+                modified_content = apply_search_replace_changes(last_content, clean_code)
+                clean_content = remove_code_block(modified_content)
+                _history.append([query, full_response])
+                yield {
+                    code_output: clean_content,
+                    history: _history,
+                    sandbox: send_to_sandbox(clean_content) if language == "html" else "<div style='padding:1em;color:#888;text-align:center;'>Preview is only available for HTML. Please download your code using the download button above.</div>",
+                    history_output: history_to_chatbot_messages(_history),
+                }
+            else:
+                _history.append([query, full_response])
+                yield {
+                    code_output: clean_code,
+                    history: _history,
+                    sandbox: send_to_sandbox(clean_code) if language == "html" else "<div style='padding:1em;color:#888;text-align:center;'>Preview is only available for HTML. Please download your code using the download button above.</div>",
+                    history_output: history_to_chatbot_messages(_history),
+                }
+        return
+    # Use dynamic client based on selected model (for non-GLM-4.5 models)
     client = get_inference_client(_current_model["id"], provider)
     if image is not None: