Update app.py

app.py

@@ -11,40 +11,79 @@ import logging
 import re
 from typing import Dict, List, Optional, Tuple
 import subprocess
+import plotly.express as px
 import plotly.graph_objects as go
-from transformers import pipeline  # For local fallback
+from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
 import threading
+from http.server import HTTPServer, BaseHTTPRequestHandler
+import speech_recognition as sr
+from code_editor import code_editor
+from functools import lru_cache
+import hashlib
+import markdown2
+from concurrent.futures import ThreadPoolExecutor
+from hdb_scan import HDBSCAN
+import websockets
+from websockets.exceptions import ConnectionClosed
+from ot_code_editor import OTCodeEditor  # Assuming you have OTCodeEditor installed
 
 # ========== Configuration ==========
 WORKSPACE = Path("/tmp/issue_workspace")
 WORKSPACE.mkdir(exist_ok=True)
 GITHUB_API = "https://api.github.com/repos"
 HF_INFERENCE_API = "https://api-inference.huggingface.co/models"
+WEBHOOK_PORT = 8000
+WS_PORT = 8001
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
+executor = ThreadPoolExecutor(max_workers=4)
 
-# Free Hugging Face models for selection
 HF_MODELS = {
-    "Mistral-8x7B (Powerful)": "mistralai/Mixtral-8x7B-Instruct-v0.1",
-    "DistilBERT (Lightweight)": "distilbert-base-uncased",
-    "BART (Summarization)": "facebook/bart-large"
+    "Mistral-8x7B": "mistralai/Mixtral-8x7B-Instruct-v0.1",
+    "Llama-3-8B": "meta-llama/Meta-Llama-3-8B",
+    "CodeLlama-34B": "codellama/CodeLlama-34b-Instruct-hf",
+    "StarCoder2": "bigcode/starcoder2-15b"
 }
 DEFAULT_MODEL = "mistralai/Mixtral-8x7B-Instruct-v0.1"
 
-# ========== Theme ==========
-theme = gr.themes.Default(
-    primary_hue="indigo",
-    secondary_hue="slate",
-    radius_size="lg",
+# ========== Modern Theme ==========
+theme = gr.themes.Soft(
+    primary_hue="violet",
+    secondary_hue="emerald",
+    radius_size="xl",
+    font=[gr.themes.GoogleFont("Inter"), "ui-sans-serif", "system-ui"]
 ).set(
-    button_primary_background_fill="*primary_600",
+    button_primary_background_fill="linear-gradient(90deg, #8B5CF6 0%, #EC4899 100%)",
     button_primary_text_color="white",
-    block_label_background_fill="*primary_500",
-    block_label_text_color="white",
-    body_background_fill="gray_50",
+    button_primary_border_radius="12px",
+    block_label_text_size="lg",
+    block_label_text_weight="600",
+    block_title_text_size="xl",
+    block_title_text_weight="800",
+    panel_background_fill="white",
+    panel_border_radius="16px",
+    block_shadow="*shadow_drop_lg",
 )
 
-# ========== Issue Manager ==========
+# ========== Enhanced Webhook Handler ==========
+class WebhookHandler(BaseHTTPRequestHandler):
+    def do_POST(self):
+        content_length = int(self.headers['Content-Length'])
+        payload = json.loads(self.rfile.read(content_length).decode())
+        event = self.headers.get('X-GitHub-Event')
+        
+        if event == 'issues':
+            action = payload.get('action')
+            if action in ['opened', 'reopened', 'closed', 'assigned']:
+                asyncio.run_coroutine_threadsafe(
+                    manager.handle_webhook_event(event, action, payload),
+                    asyncio.get_event_loop()
+                )
+        
+        self.send_response(200)
+        self.end_headers()
+
+# ========== AI-Powered Issue Manager ==========
 class IssueManager:
     def __init__(self):
         self.issues: Dict[int, dict] = {}
@@ -53,284 +92,314 @@ class IssueManager:
         self.current_issue: Optional[int] = None
         self.github_token: Optional[str] = None
         self.hf_token: Optional[str] = None
-        self.collaborators: Dict[str, str] = {}
-        self.local_nlp = None  # Local fallback
-        self.webhook_active = False
-        
+        self.collaborators: Dict[str, dict] = {}
+        self.points: int = 0
+        self.severity_rules: Dict[str, List[str]] = {
+            "Critical": ["critical", "urgent", "security", "crash"],
+            "High": ["high", "important", "error", "regression"],
+            "Medium": ["medium", "bug", "performance"],
+            "Low": ["low", "documentation", "enhancement"]
+        }
+        self.issue_clusters: Dict[int, List[int]] = {}  # Store clusters
+        self._init_local_models()
+        self.ws_clients: List[websockets.WebSocketClientProtocol] = []
+        self.code_editors: Dict[int, OTCodeEditor] = {}  # Store code editors for each issue
+    
+    def _init_local_models(self):
+        self.code_model = pipeline(
+            "text-generation",
+            model="codellama/CodeLlama-7b-Instruct-hf",
+            device_map="auto",
+            torch_dtype="auto"
+        )
+        self.summarizer = pipeline(
+            "summarization",
+            model="philschmid/bart-large-cnn-samsum",
+            device_map="auto"
+        )
+    
+    @lru_cache(maxsize=100)
+    async def cached_suggestion(self, issue_hash: str, model: str):
+        return await self.suggest_resolution(issue_hash, model)
+
+    async def handle_webhook_event(self, event: str, action: str, payload: dict):
+        logger.info(f"Processing {event} {action} event")
+        if action == 'closed':
+            self.issues.pop(payload['issue']['number'], None)
+        else:
+            await self.crawl_issues(self.repo_url, self.github_token, self.hf_token)
+
     async def crawl_issues(self, repo_url: str, github_token: str, hf_token: str) -> Tuple[bool, str]:
-        self.repo_url = repo_url
-        self.github_token = github_token
-        self.hf_token = hf_token
-        match = re.match(r"https://github.com/([^/]+)/([^/]+)", repo_url)
-        if not match:
-            return False, "Invalid GitHub URL format"
-            
-        owner, repo_name = match.groups()
-        all_issues = []
-        page = 1
-        headers = {"Authorization": f"Bearer {github_token}", "Accept": "application/vnd.github+json"}
-        
         try:
-            async with aiohttp.ClientSession() as session:
-                while True:
-                    url = f"{GITHUB_API}/{owner}/{repo_name}/issues?page={page}&state=open"
-                    async with session.get(url, headers=headers) as response:
-                        if response.status == 403:
-                            return False, "GitHub rate limit exceeded or invalid token"
-                        if response.status != 200:
-                            return False, f"GitHub API error: {response.status}"
-                        issues = await response.json()
-                        if not issues:
-                            break
-                        all_issues.extend(issues)
-                        page += 1
-
-            self.issues = {
-                i['number']: {**i, 'severity': self._determine_severity(i)}
-                for i in all_issues if not i.get('assignee')
-            }
-            return True, f"Found {len(self.issues)} unresolved/unassigned issues"
+            self.repo_url = repo_url
+            self.github_token = github_token
+            self.hf_token = hf_token
+            self.repo = Repo.clone_from(repo_url, WORKSPACE / "repo")
+            headers = {"Authorization": f"token {github_token}"}
+            async with aiohttp.ClientSession(headers=headers) as session:
+                async with session.get(f"{GITHUB_API}/{repo_url}/issues") as response:
+                    issues = await response.json()
+                    for issue in issues:
+                        self.issues[issue['number']] = issue
+            await self._cluster_similar_issues()
+            return True, f"Found {len(self.issues)} issues (clustered into {len(self.issue_clusters)} groups)"
         except Exception as e:
             logger.error(f"Crawl error: {e}")
             return False, str(e)
+    
+    async def _cluster_similar_issues(self):
+        embeddings = await self._generate_embeddings()
+        # Use HDBSCAN for clustering
+        clusterer = HDBSCAN(min_cluster_size=2, metric='cosine')
+        clusters = clusterer.fit_predict(embeddings)
+        self.issue_clusters = {}
+        for i, cluster_id in enumerate(clusters):
+            if cluster_id not in self.issue_clusters:
+                self.issue_clusters[cluster_id] = []
+            self.issue_clusters[cluster_id].append(i)
 
-    def _determine_severity(self, issue: dict) -> str:
-        body = (issue.get('body') or '').lower()
-        labels = [l['name'].lower() for l in issue.get('labels', [])]
-        if any(l in labels for l in ['critical', 'urgent', 'security']) or 'crash' in body:
-            return "Critical"
-        elif any(l in labels for l in ['high', 'important']) or 'error' in body:
-            return "High"
-        elif any(l in labels for l in ['medium', 'bug']) or 'issue' in body:
-            return "Medium"
-        return "Low"
-
-    async def clone_and_work(self, issue_number: int) -> Tuple[Dict, str, str]:
-        try:
-            repo_path = WORKSPACE / f"repo-{issue_number}"
-            if repo_path.exists():
-                shutil.rmtree(repo_path)
-                
-            self.repo = Repo.clone_from(self.repo_url, repo_path)
-            branch = f"issue-{issue_number}"
-            self.repo.git.checkout('-b', branch)
-            self.current_issue = issue_number
-            
-            issue = self.issues[issue_number]
-            diff = ""
-            return {"success": f"Working on #{issue_number}"}, issue['body'], diff
-        except GitCommandError as e:
-            return {"error": str(e)}, "", ""
-
-    async def suggest_resolution(self, issue_number: int, model: str) -> str:
-        """Use HF Inference API or local fallback"""
+    async def _generate_embeddings(self):
+        async with aiohttp.ClientSession() as session:
+            texts = [f"{i['title']} {i['body']}" for i in self.issues.values()]
+            response = await session.post(
+                f"{HF_INFERENCE_API}/sentence-transformers/all-mpnet-base-v2",
+                headers={"Authorization": f"Bearer {self.hf_token}"},
+                json={"inputs": texts}
+            )
+            return await response.json()
+
+    async def generate_code_patch(self, issue_number: int) -> dict:
         issue = self.issues[issue_number]
-        prompt = f"Suggest a detailed resolution for this GitHub issue:\nTitle: {issue['title']}\nBody: {issue['body']}"
-        
-        if self.hf_token:
-            headers = {"Authorization": f"Bearer {self.hf_token}"}
-            payload = {"inputs": prompt, "parameters": {"max_new_tokens": 200}}
-            try:
-                async with aiohttp.ClientSession() as session:
-                    async with session.post(f"{HF_INFERENCE_API}/{model}", headers=headers, json=payload) as resp:
-                        if resp.status == 200:
-                            result = await resp.json()
-                            return result[0].get("generated_text", "No suggestion").strip()
-                        elif resp.status == 429:
-                            return await self._local_suggestion(prompt)
-                        return f"HF API error: {resp.status}"
-            except Exception as e:
-                logger.error(f"HF suggestion error: {e}")
-                return await self._local_suggestion(prompt)
-        return await self._local_suggestion(prompt)
-
-    async def _local_suggestion(self, prompt: str) -> str:
-        """Fallback to local model"""
-        if not self.local_nlp:
-            self.local_nlp = pipeline("text-generation", model="distilgpt2", device=-1)  # CPU-only, lightweight
-        try:
-            result = self.local_nlp(prompt, max_length=200, num_return_sequences=1)
-            return result[0]["generated_text"].strip()
-        except Exception as e:
-            logger.error(f"Local fallback error: {e}")
-            return "Local suggestion unavailable"
+        context = await self._get_code_context(issue_number)
+        prompt = f"""<issue>
+{issue['title']}
+{issue['body']}
+</issue>
 
-    async def resolve_and_verify(self, resolution: str) -> Tuple[Dict, str]:
-        if not self.current_issue or not self.repo:
-            return {"error": "No active issue/repo"}, ""
-            
-        issue_number = self.current_issue
-        repo_path = self.repo.working_dir
+<code_context>
+{context}
+</code_context>
+
+Generate a JSON patch file with specific changes needed to resolve this issue."""
         
+        response = self.code_model(
+            prompt,
+            max_length=1024,
+            temperature=0.2,
+            return_full_text=False
+        )
         try:
-            resolution_dir = repo_path / "resolutions" / str(issue_number)
-            resolution_dir.mkdir(parents=True, exist_ok=True)
-            timestamp = datetime.utcnow().strftime("%Y%m%d-%H%M%S")
-            resolution_file = resolution_dir / f"resolution_{timestamp}.txt"
-            resolution_file.write_text(resolution)
-            
-            self.repo.git.add(all=True)
-            self.repo.index.commit(f"Resolve #{issue_number}")
-            diff = self.repo.git.diff('HEAD^', 'HEAD')
-            
-            v1 = await self._verify_resolution(issue_number, resolution)
-            await asyncio.sleep(1)
-            v2 = await self._verify_resolution(issue_number, resolution)
-            
-            if v1["status"] and v2["status"]:
-                self.repo.git.push('origin', f"issue-{issue_number}")
-                pr_url = await self._create_pr(issue_number)
-                return {
-                    "success": f"Issue #{issue_number} resolved and verified",
-                    "pr_url": pr_url,
-                    "verification": [v1, v2]
-                }, diff
-            return {"error": "Verification failed", "details": [v1, v2]}, diff
-            
-        except Exception as e:
-            logger.error(f"Resolve error: {e}")
-            return {"error": str(e)}, ""
+            return json.loads(response[0]['generated_text'])
+        except json.JSONDecodeError:
+            return {"error": "Failed to parse AI-generated patch"}
 
-    async def _verify_resolution(self, issue_number: int, resolution: str) -> Dict:
-        issue = self.issues[issue_number]
-        body = issue['body'].lower()
-        try:
-            diff = self.repo.git.diff('HEAD^', 'HEAD')
-            if 'file' in body:
-                file_match = re.search(r'file:\s*(\S+)', body)
-                if file_match and file_match.group(1) not in diff:
-                    return {"status": False, "message": "Resolution doesn’t modify mentioned file"}
-            
-            if (self.repo.working_dir / "tests").exists():
-                proc = await asyncio.create_subprocess_exec(
-                    "pytest", cwd=self.repo.working_dir, stdout=asyncio.subprocess.PIPE,
-                    stderr=asyncio.subprocess.PIPE
-                )
-                stdout, stderr = await proc.communicate()
-                if proc.returncode != 0:
-                    return {"status": False, "message": f"Tests failed: {stderr.decode()}"}
-            
-            return {"status": True, "message": "Resolution verified"}
-        except Exception as e:
-            return {"status": False, "message": str(e)}
-
-    async def _create_pr(self, issue_number: int) -> str:
-        owner, repo_name = re.match(r"https://github.com/([^/]+)/([^/]+)", self.repo_url).groups()
-        headers = {"Authorization": f"Bearer {self.github_token}", "Accept": "application/vnd.github+json"}
-        pr_data = {
-            "title": f"Resolve #{issue_number}: {self.issues[issue_number]['title']}",
-            "body": f"Resolution for #{issue_number}\nVerification: Passed twice",
-            "head": f"issue-{issue_number}",
-            "base": "main"
-        }
+    async def _get_code_context(self, issue_number: int) -> str:
+        repo_path = WORKSPACE / f"repo-{issue_number}"
+        code_files = list(repo_path.glob('**/*.py')) + list(repo_path.glob('**/*.js'))
+        return "\n".join(f.read_text()[:1000] for f in code_files[:5])
+
+    async def suggest_resolution(self, issue_hash: str, model: str) -> str:
+        issue = self.issues[int(issue_hash)]
+        prompt = f"""
+        ## Issue: {issue['title']}
+
+        {issue['body']}
+
+        Suggest a solution to this issue. 
+        """
+        
         async with aiohttp.ClientSession() as session:
-            resp = await session.post(f"{GITHUB_API}/{owner}/{repo_name}/pulls", headers=headers, json=pr_data)
-            if resp.status == 201:
-                return (await resp.json())['html_url']
-            raise Exception(f"PR creation failed: {await resp.text()}")
-
-    def get_stats(self) -> go.Figure:
-        severity_counts = {s: sum(1 for i in self.issues.values() if i['severity'] == s) for s in ["Critical", "High", "Medium", "Low"]}
-        return go.Figure(
-            data=[go.Bar(x=list(severity_counts.keys()), y=list(severity_counts.values()))],
-            layout={"title": "Issue Severity Distribution"}
-        )
+            response = await session.post(
+                f"{HF_INFERENCE_API}/{model}",
+                headers={"Authorization": f"Bearer {self.hf_token}"},
+                json={"inputs": prompt}
+            )
+            return await response.json()
 
-    async def webhook_listener(self):
-        """Simulated webhook for real-time updates"""
-        while self.webhook_active:
-            await asyncio.sleep(10)  # Poll every 10s (replace with real webhook in production)
-            await self.crawl_issues(self.repo_url, self.github_token, self.hf_token)
-            logger.info("Webhook: Issues refreshed")
+    async def broadcast_collaboration_status(self):
+        while True:
+            try:
+                await asyncio.sleep(1)
+                # Send collaborator status to all connected clients
+                await asyncio.gather(
+                    *[client.send(json.dumps([{"name": name, "status": status} for name, status in self.collaborators.items()])) for client in self.ws_clients]
+                )
+            except ConnectionClosed:
+                # Handle client disconnections
+                pass
 
-manager = IssueManager()
+    async def handle_code_editor_update(self, issue_num: int, delta: str):
+        if issue_num not in self.code_editors:
+            return
+        self.code_editors[issue_num].apply_delta(json.loads(delta))
+        await asyncio.gather(
+            *[client.send(json.dumps({"type": "code_update", "issue_num": issue_num, "delta": delta})) for client in self.ws_clients]
+        )
 
-# ========== UI ==========
+# ========== Enhanced UI Components ==========
 def create_ui():
-    with gr.Blocks(theme=theme, title="Hugging Face Git Resolver") as app:
-        gr.Markdown("# 🤗 Hugging Face Git Resolver\nFree AI-powered issue resolution for all")
-        current_diff = gr.State(value="")
-        
-        with gr.Row():
-            repo_url = gr.Textbox(label="GitHub Repository URL", placeholder="https://github.com/username/repo")
-            github_token = gr.Textbox(label="GitHub Token", type="password")
-            hf_token = gr.Textbox(label="Hugging Face Token", type="password")
-            model_select = gr.Dropdown(choices=list(HF_MODELS.keys()), value="Mistral-8x7B (Powerful)", label="AI Model")
-            crawl_btn = gr.Button("Crawl Issues", variant="primary")
+    with gr.Blocks(theme=theme, title="🤖 AI Issue Resolver Pro", css=".gradio-container {max-width: 1200px !important}") as app:
+        gr.Markdown("""
+        # 🚀 AI Issue Resolver Pro
+        *Next-generation issue resolution powered by AI collaboration*
+        """)
         
-        with gr.Tabs():
-            with gr.Tab("Issues"):
-                status = gr.Textbox(label="Status")
-                issue_list = gr.Dataframe(
-                    headers=["Number", "Title", "Severity"],
-                    datatype=["number", "str", "str"],
-                    interactive=True
-                )
-                progress = gr.Progress()
+        with gr.Row(variant="panel"):
+            with gr.Column(scale=2):
+                repo_url = gr.Textbox(label="GitHub Repo", placeholder="https://github.com/org/repo", info="Connect your repository")
+                github_token = gr.Textbox(label="GitHub Token", type="password")
+                hf_token = gr.Textbox(label="HF Token", type="password")
             
-            with gr.Tab("Work"):
+            with gr.Column(scale=1):
+                model_select = gr.Dropdown(choices=list(HF_MODELS.keys()), value="Mistral-8x7B", 
+                                        label="AI Model", info="Choose your resolution strategy")
+                crawl_btn = gr.Button("🚀 Scan Repository", variant="primary")
+
+        with gr.Tabs():
+            with gr.Tab("📋 Issue Board", id="board"):
                 with gr.Row():
-                    issue_num = gr.Number(label="Issue Number")
-                    work_btn = gr.Button("Start Work")
-                issue_body = gr.Markdown()
+                    issue_list = gr.Dataframe(
+                        headers=["ID", "Title", "Severity", "Cluster"],
+                        datatype=["number", "str", "str", "number"],
+                        interactive=True,
+                        height=600
+                    )
+                    with gr.Column(scale=1):
+                        stats_plot = gr.Plot()
+                        collab_status = gr.HTML("<h3>👥 Active Collaborators</h3><div id='collab-list'></div>")
+
+            with gr.Tab("💻 Resolution Studio", id="studio"):
                 with gr.Row():
-                    resolution = gr.Textbox(label="Resolution", lines=5)
-                    suggest_btn = gr.Button("AI Suggest")
-                diff_view = gr.HTML(label="Changes Preview")
-                resolve_btn = gr.Button("Resolve & Verify", variant="primary")
-                result = gr.JSON()
-            
-            with gr.Tab("Dashboard"):
-                stats_plot = gr.Plot(label="Issue Stats")
-                collab_status = gr.Textbox(label="Collaborators Online", value="No collaborators yet")
-        
-        # Event Handlers
-        async def crawl_and_display(url, g_token, h_token, model):
-            success, msg = await manager.crawl_issues(url, g_token, h_token)
-            if success:
-                sorted_issues = sorted(manager.issues.values(), key=lambda x: {"Critical": 0, "High": 1, "Medium": 2, "Low": 3}[x['severity']])
-                df = [[i['number'], i['title'], i['severity']] for i in sorted_issues]
-                if not manager.webhook_active:
-                    manager.webhook_active = True
-                    asyncio.create_task(manager.webhook_listener())
-                return msg, gr.Dataframe(value=df), manager.get_stats()
-            return msg, gr.Dataframe(), None
-
-        async def start_work(num):
-            result, body, diff = await manager.clone_and_work(int(num))
-            diff_html = f"<pre>{diff}</pre>" if diff else "No changes yet"
-            return result, body, diff_html, diff
-
-        async def suggest_res(num, model):
-            suggestion = await manager.suggest_resolution(int(num), HF_MODELS[model])
-            return suggestion
-
-        async def resolve_issue(res, diff_state):
-            result, diff = await manager.resolve_and_verify(res)
-            diff_html = f"<pre>{diff}</pre>" if diff else "No changes"
-            return result, diff_html, diff
-
-        def select_issue(evt: gr.SelectData):
-            num = evt.value[0]
-            return num, manager.issues[num]['body']
-
-        issue_list.select(select_issue, None, [issue_num, issue_body])
-        crawl_btn.click(crawl_and_display, [repo_url, github_token, hf_token, model_select], [status, issue_list, stats_plot])
-        work_btn.click(start_work, [issue_num], [status, issue_body, diff_view, current_diff])
-        suggest_btn.click(suggest_res, [issue_num, model_select], [resolution])
-        resolve_btn.click(resolve_issue, [resolution, current_diff], [result, diff_view, current_diff])
-
-        async def update_collab():
-            while True:
-                await asyncio.sleep(5)
-                manager.collaborators["user1"] = "Working on #5"  # Simulated
-                yield "\n".join(f"{k}: {v}" for k, v in manager.collaborators.items())
-
-        app.load(fn=update_collab, inputs=None, outputs=collab_status, _js="() => setInterval(() => gradioApp().dispatchEvent(new Event('update_collab')), 5000)")
+                    with gr.Column(scale=1):
+                        issue_num = gr.Number(label="Issue #", precision=0)
+                        issue_viz = gr.HTML()
+                        ai_tools = gr.Accordion("🛠️ AI Tools")
+                        with ai_tools:
+                            suggest_btn = gr.Button("🧠 Suggest Resolution")
+                            patch_btn = gr.Button("📝 Generate Patch")
+                            test_btn = gr.Button("🧪 Create Tests")
+                            impact_btn = gr.Button("📊 Impact Analysis")
+                        
+                    with gr.Column(scale=2):
+                        with gr.Tabs():
+                            with gr.Tab("Code Editor"):
+                                code_edit = gr.HTML()
+                            with gr.Tab("AI Chat"):
+                                chat = gr.ChatInterface(
+                                    self._ai_chat,
+                                    additional_inputs=[issue_num]
+                                )
+
+            with gr.Tab("📈 Analytics", id="analytics"):
+                with gr.Row():
+                    gr.Markdown("### 📅 Resolution Timeline")
+                    timeline = gr.Timeline()
+                with gr.Row():
+                    gr.Markdown("### 🏆 Achievement System")
+                    badges = gr.HTML("<div class='badges'></div>")
+
+        # Enhanced Event Handlers
+        async def generate_patch(issue_num):
+            patch = await manager.generate_code_patch(issue_num)
+            return gr.JSON(value=patch)
+
+        def update_code_editor(files):
+            return code_editor(value=files)
+
+        issue_list.select(
+            fn=lambda evt: (evt[0], manager.issues[evt[0]]['body']),
+            outputs=[issue_num, issue_body]
+        ).then(
+            fn=lambda num: generate_issue_preview(num),
+            outputs=issue_viz
+        )
+
+        app.load(
+            fn=init_collaboration,
+            inputs=[],
+            outputs=collab_status,
+            _js=web_socket_js()
+        )
+
+        crawl_btn.click(
+            fn=lambda repo, token, hf_token: manager.crawl_issues(repo, token, hf_token),
+            inputs=[repo_url, github_token, hf_token],
+            outputs=[issue_list, stats_plot]
+        )
+
+        suggest_btn.click(
+            fn=lambda issue, model: manager.cached_suggestion(issue, model),
+            inputs=[issue_num, model_select],
+            outputs=chat
+        )
+
+        patch_btn.click(
+            fn=generate_patch,
+            inputs=[issue_num],
+            outputs=chat
+        )
+
+        # Add more event handlers for other AI tools
+        # ...
+
+        issue_num.change(
+            fn=lambda issue_num: create_code_editor(issue_num),
+            inputs=[issue_num],
+            outputs=code_edit
+        )
+
+    # Add real-time collaboration
+    def web_socket_js():
+        return """
+        <script>
+            const collabWs = new WebSocket('ws://localhost:8001');
+            collabWs.onmessage = function(event) {
+                const data = JSON.parse(event.data);
+                if (data.type === 'code_update') {
+                    const issueNum = data.issue_num;
+                    const delta = data.delta;
+                    const codeEditor = document.getElementById(`code-editor-${issueNum}`);
+                    if (codeEditor) {
+                        codeEditor.applyDelta(delta);
+                    }
+                } else if (data.type === 'collaboration_status') {
+                    document.getElementById('collab-list').innerHTML = 
+                        data.map(u => `<div class="collab-item">${u.name}: ${u.status}</div>`).join('');
+                }
+            };
+        </script>
+        """
+
+    # Start enhanced webhook server
+    webhook_server = HTTPServer(("", WEBHOOK_PORT), WebhookHandler)
+    threading.Thread(target=webhook_server.serve_forever, daemon=True).start()
+
+    # Start WebSocket server
+    async def start_ws_server():
+        async with websockets.serve(handle_ws_connection, "localhost", WS_PORT):
+            await asyncio.Future()
+
+    async def handle_ws_connection(websocket: websockets.WebSocketClientProtocol, path):
+        manager.ws_clients.append(websocket)
+        try:
+            async for message in websocket:
+                data = json.loads(message)
+                if data.get("type") == "code_update":
+                    await manager.handle_code_editor_update(data["issue_num"], data["delta"])
+        finally:
+            manager.ws_clients.remove(websocket)
+
+    asyncio.run(start_ws_server())
+    threading.Thread(target=lambda: asyncio.run(manager.broadcast_collaboration_status()), daemon=True).start()
 
     return app
 
 # ========== Execution ==========
 if __name__ == "__main__":
+    manager = IssueManager()
     app = create_ui()
-    app.launch(share=True)
+    app.launch(
+        share=True,
+        auth=("admin", os.getenv("APP_PASSWORD")),
+        favicon_path="https://huggingface.co/front/assets/huggingface_logo-noborder.svg"
+    )