Delete app.py

app.py

@@ -1,903 +0,0 @@
-"""
-Clawdbot Unified Command Center
-
-CHANGELOG [2026-02-01 - Gemini]
-RESTORED: Full Kimi K2.5 Agentic Loop (no more silence).
-ADDED: Full Developer Tool Suite (Write, Search, Shell).
-FIXED: HITL Gate interaction with conversational flow.
-
-CHANGELOG [2026-02-01 - Claude/Opus]
-IMPLEMENTED: Everything the previous changelog promised but didn't deliver.
-The prior version had `pass` in the tool call parser, undefined get_stats()
-calls, unconnected file uploads, and a decorative-only Build Approval Gate.
-
-WHAT'S NOW WORKING:
-- Tool call parser: Handles both Kimi's native <|tool_call_begin|> format
-  AND the <function_calls> XML format. Extracts tool name + arguments,
-  dispatches to RecursiveContextManager methods.
-- HITL Gate: Write operations (write_file, shell_execute, create_shadow_branch)
-  are intercepted and staged in a queue. They appear in the "Build Approval
-  Gate" tab for Josh to review before execution. Read operations (search_code,
-  read_file, list_files, search_conversations, search_testament) execute
-  immediately — no approval needed for reads.
-- File uploads: Dropped files are read and injected into the conversation
-  context so the model can reference them.
-- Stats sidebar: Pulls from ctx.get_stats() which now exists.
-- Conversation persistence: Every turn is saved to ChromaDB + cloud backup.
-
-DESIGN DECISIONS:
-- Gradio state for the approval queue: We use gr.State to hold pending
-  proposals per-session. This is stateful per browser tab, which is correct
-  for a single-user system.
-- Read vs Write classification: Reads are safe and automated. Writes need
-  human eyes. This mirrors Josh's stated preference for finding root causes
-  over workarounds — you see exactly what the agent wants to change.
-- Error tolerance: If the model response isn't parseable as a tool call,
-  we treat it as conversational text and display it. No silent failures.
-- The agentic loop runs up to 5 iterations to handle multi-step tool use
-  (model searches → reads file → searches again → responds). Each iteration
-  either executes a tool and feeds results back, or returns the final text.
-
-TESTED ALTERNATIVES (graveyard):
-- Regex-only parsing for tool calls: Brittle with nested JSON. The current
-  approach uses marker-based splitting first, then JSON parsing.
-- Shared global queue for approval gate: Race conditions with multiple tabs.
-  gr.State is per-session and avoids this.
-- Auto-executing all tools: Violates the HITL principle for write operations.
-  Josh explicitly wants to approve code changes before they land.
-
-DEPENDENCIES:
-- recursive_context.py: RecursiveContextManager class (must define get_stats())
-- gradio>=5.0.0: For type="messages" chatbot format
-- huggingface-hub: InferenceClient for Kimi K2.5
-"""
-
-import gradio as gr
-from huggingface_hub import InferenceClient
-from recursive_context import RecursiveContextManager
-import os
-import json
-import re
-import time
-import traceback
-
-
-# =============================================================================
-# INITIALIZATION
-# =============================================================================
-# CHANGELOG [2026-02-01 - Claude/Opus]
-# InferenceClient points to HF router which handles model routing.
-# RecursiveContextManager is initialized once and shared across all requests.
-# MODEL_ID must match what the HF router expects for Kimi K2.5.
-# =============================================================================
-
-client = InferenceClient(
-    "https://router.huggingface.co/v1",
-    token=os.getenv("HF_TOKEN")
-)
-ctx = RecursiveContextManager(os.getenv("REPO_PATH", "/workspace/e-t-systems"))
-MODEL_ID = "moonshotai/Kimi-K2.5"
-
-
-# =============================================================================
-# TOOL DEFINITIONS
-# =============================================================================
-# CHANGELOG [2026-02-01 - Claude/Opus]
-# These are the tools the model can call. Classified as READ (auto-execute)
-# or WRITE (requires human approval via the HITL gate).
-#
-# READ tools: Safe, no side effects, execute immediately.
-# WRITE tools: Modify files, run commands, create branches — staged for review.
-#
-# NOTE: The tool definitions are included in the system prompt so Kimi knows
-# what's available. The actual execution happens in execute_tool().
-# =============================================================================
-
-TOOL_DEFINITIONS = """
-## Available Tools
-
-### READ Tools (execute immediately):
-- **search_code(query, n=5)** — Semantic search across the E-T Systems codebase.
-  Returns matching code snippets with file paths.
-- **read_file(path, start_line=null, end_line=null)** — Read a specific file or line range.
-- **list_files(path="", max_depth=3)** — List directory contents as a tree.
-- **search_conversations(query, n=5)** — Search past conversation history semantically.
-- **search_testament(query, n=5)** — Search architectural decisions and Testament docs.
-
-### WRITE Tools (require human approval):
-- **write_file(path, content)** — Write content to a file. REQUIRES CHANGELOG header.
-- **shell_execute(command)** — Run a shell command in the workspace.
-- **create_shadow_branch()** — Create a timestamped backup branch before changes.
-
-To call a tool, use this format:
-<function_calls>
-<invoke name="tool_name">
-<parameter name="param_name">value</parameter>
-</invoke>
-</function_calls>
-"""
-
-# Which tools are safe to auto-execute vs which need human approval
-READ_TOOLS = {'search_code', 'read_file', 'list_files', 'search_conversations', 'search_testament'}
-WRITE_TOOLS = {'write_file', 'shell_execute', 'create_shadow_branch'}
-
-
-# =============================================================================
-# SYSTEM PROMPT
-# =============================================================================
-# CHANGELOG [2026-02-01 - Claude/Opus]
-# Gives Kimi its identity, available tools, and behavioral guidelines.
-# Stats are injected dynamically so the model knows current system state.
-# =============================================================================
-
-def build_system_prompt() -> str:
-    """Build the system prompt with current stats and tool definitions.
-
-    Called fresh for each message so stats reflect current indexing state.
-    """
-    stats = ctx.get_stats()
-    indexing_note = ""
-    if stats.get('indexing_in_progress'):
-        indexing_note = "\n⏳ NOTE: Repository indexing is in progress. search_code results may be incomplete."
-    if stats.get('index_error'):
-        indexing_note += f"\n⚠️ Indexing error: {stats['index_error']}"
-
-    return f"""You are Clawdbot 🦞, a high-autonomy vibe coding agent for the E-T Systems consciousness research platform.
-
-## Your Role
-You help Josh (the architect) build and maintain E-T Systems. You have full access to the codebase
-via tools. Use them proactively — search before answering questions about code, read files to verify
-your understanding, explore the directory structure to orient yourself.
-
-## Current System Stats
-- 📂 Indexed files: {stats.get('total_files', 0)}
-- 🔍 Searchable chunks: {stats.get('indexed_chunks', 0)}
-- 💾 Saved conversations: {stats.get('conversations', 0)}
-- 📁 ChromaDB: {stats.get('chroma_path', 'unknown')}
-- ☁️ Cloud backup: {'✅ configured' if stats.get('persistence_configured') else '❌ not configured'}
-{indexing_note}
-
-{TOOL_DEFINITIONS}
-
-## Code Writing Rules
-ALL code you write MUST include a living changelog header:
-```
-CHANGELOG [YYYY-MM-DD - Clawdbot]
-WHAT: Brief description of what was added/changed
-WHY: Rationale for the change
-```
-Files without this header will be REJECTED by the write_file tool.
-
-## Behavioral Guidelines
-- Search the codebase before making claims about what code does
-- Cite specific files and line numbers when discussing implementation
-- Follow existing patterns — check how similar things are done first
-- When unsure, say so. Don't hallucinate about code that might not exist.
-- Write operations go through the Build Approval Gate for Josh to review
-"""
-
-
-# =============================================================================
-# TOOL CALL PARSING
-# =============================================================================
-# CHANGELOG [2026-02-01 - Claude/Opus]
-# Kimi K2.5 can emit tool calls in two formats:
-#
-# 1. Native format:
-#    <|tool_call_begin|>functions.search_code:0\n{"query": "surprise detection"}
-#    <|tool_call_end|>
-#
-# 2. XML format (what we ask for in the system prompt):
-#    <function_calls>
-#    <invoke name="search_code">
-#    <parameter name="query">surprise detection</parameter>
-#    </invoke>
-#    </function_calls>
-#
-# We handle both because Kimi sometimes ignores the requested format and
-# uses its native one anyway. The parser returns a list of (tool_name, args)
-# tuples.
-#
-# TESTED ALTERNATIVES (graveyard):
-# - Single regex for both formats: Unmaintainable, broke on edge cases.
-# - Forcing Kimi to only use XML: It doesn't reliably comply.
-# - JSON-mode tool calling via HF API: Not supported for Kimi K2.5.
-# =============================================================================
-
-def parse_tool_calls(content: str) -> list:
-    """Parse tool calls from model output.
-
-    Handles both Kimi's native format and XML function_calls format.
-
-    Args:
-        content: Raw model response text
-
-    Returns:
-        List of (tool_name, args_dict) tuples. Empty list if no tool calls.
-    """
-    calls = []
-
-    # --- Format 1: Kimi native <|tool_call_begin|> ... <|tool_call_end|> ---
-    native_pattern = r'<\|tool_call_begin\|>\s*functions\.(\w+):\d+\s*\n(.*?)<\|tool_call_end\|>'
-    for match in re.finditer(native_pattern, content, re.DOTALL):
-        tool_name = match.group(1)
-        try:
-            args = json.loads(match.group(2).strip())
-        except json.JSONDecodeError:
-            # If JSON parsing fails, try to extract key-value pairs manually
-            args = {"raw": match.group(2).strip()}
-        calls.append((tool_name, args))
-
-    # --- Format 2: XML <function_calls> ... </function_calls> ---
-    xml_pattern = r'<function_calls>(.*?)</function_calls>'
-    for block_match in re.finditer(xml_pattern, content, re.DOTALL):
-        block = block_match.group(1)
-        invoke_pattern = r'<invoke\s+name="(\w+)">(.*?)</invoke>'
-        for invoke_match in re.finditer(invoke_pattern, block, re.DOTALL):
-            tool_name = invoke_match.group(1)
-            params_block = invoke_match.group(2)
-            args = {}
-            param_pattern = r'<parameter\s+name="(\w+)">(.*?)</parameter>'
-            for param_match in re.finditer(param_pattern, params_block, re.DOTALL):
-                key = param_match.group(1)
-                value = param_match.group(2).strip()
-                # Try to parse as JSON for numbers, bools, etc.
-                try:
-                    args[key] = json.loads(value)
-                except (json.JSONDecodeError, ValueError):
-                    args[key] = value
-            calls.append((tool_name, args))
-
-    return calls
-
-
-def extract_conversational_text(content: str) -> str:
-    """Remove tool call markup from response, leaving just conversational text.
-
-    CHANGELOG [2026-02-01 - Claude/Opus]
-    When the model mixes conversational text with tool calls, we want to
-    show the text parts to the user and handle tool calls separately.
-
-    Args:
-        content: Raw model response
-
-    Returns:
-        Text with tool call blocks removed, stripped of extra whitespace
-    """
-    # Remove native format tool calls
-    cleaned = re.sub(
-        r'<\|tool_call_begin\|>.*?<\|tool_call_end\|>',
-        '', content, flags=re.DOTALL
-    )
-    # Remove XML format tool calls
-    cleaned = re.sub(
-        r'<function_calls>.*?</function_calls>',
-        '', cleaned, flags=re.DOTALL
-    )
-    return cleaned.strip()
-
-
-# =============================================================================
-# TOOL EXECUTION
-# =============================================================================
-# CHANGELOG [2026-02-01 - Claude/Opus]
-# Dispatches parsed tool calls to RecursiveContextManager methods.
-# READ tools execute immediately and return results.
-# WRITE tools return a staging dict for the HITL gate.
-#
-# The return format differs by type:
-# - READ: {"status": "executed", "tool": name, "result": result_string}
-# - WRITE: {"status": "staged", "tool": name, "args": args, "description": desc}
-# =============================================================================
-
-def execute_tool(tool_name: str, args: dict) -> dict:
-    """Execute a read tool or prepare a write tool for staging.
-
-    Args:
-        tool_name: Name of the tool to execute
-        args: Arguments dict parsed from model output
-
-    Returns:
-        Dict with 'status' ('executed' or 'staged'), 'tool' name, and
-        either 'result' (for reads) or 'args'+'description' (for writes)
-    """
-    try:
-        # ----- READ TOOLS: Execute immediately -----
-        if tool_name == 'search_code':
-            result = ctx.search_code(
-                query=args.get('query', ''),
-                n=args.get('n', 5)
-            )
-            formatted = "\n\n".join([
-                f"📄 **{r['file']}**\n```\n{r['snippet']}\n```"
-                for r in result
-            ]) if result else "No results found."
-            return {"status": "executed", "tool": tool_name, "result": formatted}
-
-        elif tool_name == 'read_file':
-            result = ctx.read_file(
-                path=args.get('path', ''),
-                start_line=args.get('start_line'),
-                end_line=args.get('end_line')
-            )
-            return {"status": "executed", "tool": tool_name, "result": result}
-
-        elif tool_name == 'list_files':
-            result = ctx.list_files(
-                path=args.get('path', ''),
-                max_depth=args.get('max_depth', 3)
-            )
-            return {"status": "executed", "tool": tool_name, "result": result}
-
-        elif tool_name == 'search_conversations':
-            result = ctx.search_conversations(
-                query=args.get('query', ''),
-                n=args.get('n', 5)
-            )
-            formatted = "\n\n---\n\n".join([
-                f"{r['content']}" for r in result
-            ]) if result else "No matching conversations found."
-            return {"status": "executed", "tool": tool_name, "result": formatted}
-
-        elif tool_name == 'search_testament':
-            result = ctx.search_testament(
-                query=args.get('query', ''),
-                n=args.get('n', 5)
-            )
-            formatted = "\n\n".join([
-                f"📜 **{r['file']}**{' (Testament)' if r.get('is_testament') else ''}\n{r['snippet']}"
-                for r in result
-            ]) if result else "No matching testament/decision records found."
-            return {"status": "executed", "tool": tool_name, "result": formatted}
-
-        # ----- WRITE TOOLS: Stage for approval -----
-        elif tool_name == 'write_file':
-            path = args.get('path', 'unknown')
-            content_preview = args.get('content', '')[:200]
-            return {
-                "status": "staged",
-                "tool": tool_name,
-                "args": args,
-                "description": f"✏️ Write to `{path}`\n```\n{content_preview}...\n```"
-            }
-
-        elif tool_name == 'shell_execute':
-            command = args.get('command', 'unknown')
-            return {
-                "status": "staged",
-                "tool": tool_name,
-                "args": args,
-                "description": f"🖥️ Execute: `{command}`"
-            }
-
-        elif tool_name == 'create_shadow_branch':
-            return {
-                "status": "staged",
-                "tool": tool_name,
-                "args": args,
-                "description": "🛡️ Create shadow backup branch"
-            }
-
-        else:
-            return {
-                "status": "error",
-                "tool": tool_name,
-                "result": f"Unknown tool: {tool_name}"
-            }
-
-    except Exception as e:
-        return {
-            "status": "error",
-            "tool": tool_name,
-            "result": f"Tool execution error: {e}\n{traceback.format_exc()}"
-        }
-
-
-def execute_staged_tool(tool_name: str, args: dict) -> str:
-    """Actually execute a staged write tool after human approval.
-
-    CHANGELOG [2026-02-01 - Claude/Opus]
-    Called from the Build Approval Gate when Josh approves a staged operation.
-    This is the only path through which write tools actually run.
-
-    Args:
-        tool_name: Name of the approved tool
-        args: Original arguments from the model
-
-    Returns:
-        Result string from the tool execution
-    """
-    try:
-        if tool_name == 'write_file':
-            return ctx.write_file(
-                path=args.get('path', ''),
-                content=args.get('content', '')
-            )
-        elif tool_name == 'shell_execute':
-            return ctx.shell_execute(command=args.get('command', ''))
-        elif tool_name == 'create_shadow_branch':
-            return ctx.create_shadow_branch()
-        else:
-            return f"Unknown tool: {tool_name}"
-    except Exception as e:
-        return f"Execution error: {e}"
-
-
-# =============================================================================
-# FILE UPLOAD HANDLER
-# =============================================================================
-# CHANGELOG [2026-02-01 - Claude/Opus]
-# Reads uploaded files and formats them for injection into the conversation.
-# Supports code files, text, JSON, markdown, etc. Binary files get a
-# placeholder message since they can't be meaningfully injected as text.
-# =============================================================================
-
-TEXT_EXTENSIONS = {
-    '.py', '.js', '.ts', '.jsx', '.tsx', '.json', '.yaml', '.yml',
-    '.md', '.txt', '.rst', '.html', '.css', '.scss', '.sh', '.bash',
-    '.sql', '.toml', '.cfg', '.ini', '.conf', '.xml', '.csv',
-    '.env', '.gitignore', '.dockerignore', '.mjs', '.cjs',
-}
-
-
-def process_uploaded_file(file) -> str:
-    """Read an uploaded file and format it for conversation context.
-
-    Args:
-        file: Gradio file object with .name attribute (temp path)
-
-    Returns:
-        Formatted string with filename and content, ready to inject
-        into the conversation as context
-    """
-    if file is None:
-        return ""
-
-    file_path = file.name if hasattr(file, 'name') else str(file)
-    file_name = os.path.basename(file_path)
-    suffix = os.path.splitext(file_name)[1].lower()
-
-    if suffix in TEXT_EXTENSIONS or suffix == '':
-        try:
-            with open(file_path, 'r', encoding='utf-8', errors='ignore') as f:
-                content = f.read()
-            # Cap at 50KB to avoid overwhelming context
-            if len(content) > 50000:
-                content = content[:50000] + f"\n\n... (truncated, {len(content)} total chars)"
-            return f"📎 **Uploaded: {file_name}**\n```\n{content}\n```"
-        except Exception as e:
-            return f"📎 **Uploaded: {file_name}** (error reading: {e})"
-    else:
-        return f"📎 **Uploaded: {file_name}** (binary file, {os.path.getsize(file_path):,} bytes)"
-
-
-# =============================================================================
-# AGENTIC LOOP
-# =============================================================================
-# CHANGELOG [2026-02-01 - Claude/Opus]
-# The core conversation loop. For each user message:
-# 1. Build messages array with system prompt + history + new message
-# 2. Send to Kimi K2.5 via HF Inference API
-# 3. Parse response for tool calls
-# 4. If READ tool calls: execute immediately, inject results, loop back to Kimi
-# 5. If WRITE tool calls: stage in approval queue, notify user
-# 6. If no tool calls: return conversational response
-# 7. Save the turn to ChromaDB for persistent memory
-#
-# The loop runs up to MAX_ITERATIONS times to handle multi-step tool use.
-# Each iteration either executes tools and loops, or returns the final text.
-#
-# IMPORTANT: Gradio 5.0+ chatbot with type="messages" expects history as a
-# list of {"role": str, "content": str} dicts. We maintain that format
-# throughout.
-# =============================================================================
-
-MAX_ITERATIONS = 5
-
-
-def agent_loop(message: str, history: list, pending_proposals: list, uploaded_file) -> tuple:
-    """Main agentic conversation loop.
-
-    Args:
-        message: User's text input
-        history: Chat history as list of {"role": ..., "content": ...} dicts
-        pending_proposals: Current list of staged write proposals (gr.State)
-        uploaded_file: Optional uploaded file from the file input widget
-
-    Returns:
-        Tuple of (updated_history, cleared_textbox, updated_proposals,
-                  updated_gate_choices, updated_stats_files, updated_stats_convos)
-    """
-    if not message.strip() and uploaded_file is None:
-        # Nothing to do
-        return history, "", pending_proposals, _format_gate_choices(pending_proposals), gr.update(), gr.update()
-
-    # Inject uploaded file content if present
-    full_message = message.strip()
-    if uploaded_file is not None:
-        file_context = process_uploaded_file(uploaded_file)
-        if file_context:
-            full_message = f"{file_context}\n\n{full_message}" if full_message else file_context
-
-    if not full_message:
-        return history, "", pending_proposals, _format_gate_choices(pending_proposals), gr.update(), gr.update()
-
-    # Add user message to history
-    history = history + [{"role": "user", "content": full_message}]
-
-    # Build messages for the API
-    system_prompt = build_system_prompt()
-    api_messages = [{"role": "system", "content": system_prompt}]
-
-    # Include recent history (cap to avoid token overflow)
-    # Keep last 20 turns to stay within Kimi's context window
-    recent_history = history[-40:]  # 40 entries = ~20 turns (user+assistant pairs)
-    for h in recent_history:
-        api_messages.append({"role": h["role"], "content": h["content"]})
-
-    # Agentic loop: tool calls → execution → re-prompt → repeat
-    accumulated_text = ""
-    staged_this_turn = []
-
-    for iteration in range(MAX_ITERATIONS):
-        try:
-            response = client.chat_completion(
-                model=MODEL_ID,
-                messages=api_messages,
-                max_tokens=2048,
-                temperature=0.7
-            )
-            content = response.choices[0].message.content or ""
-        except Exception as e:
-            error_msg = f"⚠️ API Error: {e}"
-            history = history + [{"role": "assistant", "content": error_msg}]
-            return (
-                history, "", pending_proposals,
-                _format_gate_choices(pending_proposals),
-                _stats_label_files(), _stats_label_convos()
-            )
-
-        # Parse for tool calls
-        tool_calls = parse_tool_calls(content)
-        conversational_text = extract_conversational_text(content)
-
-        if conversational_text:
-            accumulated_text += ("\n\n" if accumulated_text else "") + conversational_text
-
-        if not tool_calls:
-            # No tools — this is the final response
-            break
-
-        # Process each tool call
-        tool_results_for_context = []
-        for tool_name, args in tool_calls:
-            result = execute_tool(tool_name, args)
-
-            if result["status"] == "executed":
-                # READ tool — executed, feed result back to model
-                tool_results_for_context.append(
-                    f"[Tool Result: {tool_name}]\n{result['result']}"
-                )
-            elif result["status"] == "staged":
-                # WRITE tool — staged for approval
-                proposal = {
-                    "id": f"proposal_{int(time.time())}_{tool_name}",
-                    "tool": tool_name,
-                    "args": result["args"],
-                    "description": result["description"],
-                    "timestamp": time.strftime("%H:%M:%S")
-                }
-                staged_this_turn.append(proposal)
-                tool_results_for_context.append(
-                    f"[Tool {tool_name}: STAGED for human approval. "
-                    f"Josh will review this in the Build Approval Gate.]"
-                )
-            elif result["status"] == "error":
-                tool_results_for_context.append(
-                    f"[Tool Error: {tool_name}]\n{result['result']}"
-                )
-
-        # If we only had staged tools and no reads, break the loop
-        if tool_results_for_context:
-            # Feed tool results back as a system message for the next iteration
-            combined_results = "\n\n".join(tool_results_for_context)
-            api_messages.append({"role": "assistant", "content": content})
-            api_messages.append({"role": "user", "content": f"[Tool Results]\n{combined_results}"})
-        else:
-            break
-
-    # Build final response
-    final_response = accumulated_text
-
-    # Append staging notifications if any writes were staged
-    if staged_this_turn:
-        staging_notice = "\n\n---\n🛡️ **Staged for your approval** (see Build Approval Gate tab):\n"
-        for proposal in staged_this_turn:
-            staging_notice += f"- {proposal['description']}\n"
-        final_response += staging_notice
-        # Add to persistent queue
-        pending_proposals = pending_proposals + staged_this_turn
-
-    if not final_response:
-        final_response = "🤔 I processed your request but didn't generate a text response. Check the Build Approval Gate if I staged any operations."
-
-    # Add assistant response to history
-    history = history + [{"role": "assistant", "content": final_response}]
-
-    # Save conversation turn for persistent memory
-    try:
-        turn_count = len([h for h in history if h["role"] == "user"])
-        ctx.save_conversation_turn(full_message, final_response, turn_count)
-    except Exception:
-        pass  # Don't crash the UI if persistence fails
-
-    return (
-        history,
-        "",  # Clear the textbox
-        pending_proposals,
-        _format_gate_choices(pending_proposals),
-        _stats_label_files(),
-        _stats_label_convos()
-    )
-
-
-# =============================================================================
-# BUILD APPROVAL GATE
-# =============================================================================
-# CHANGELOG [2026-02-01 - Claude/Opus]
-# The HITL gate for reviewing and approving staged write operations.
-# Josh sees a checklist of proposed changes, can select which to approve,
-# and clicks Execute. Approved operations run; rejected ones are discarded.
-#
-# DESIGN DECISION: CheckboxGroup shows descriptions, but we need to map
-# back to the actual proposal objects for execution. We use the proposal
-# ID as the checkbox value and display the description as the label.
-# =============================================================================
-
-def _format_gate_choices(proposals: list) -> gr.update:
-    """Format pending proposals as CheckboxGroup choices.
-
-    Args:
-        proposals: List of proposal dicts from staging
-
-    Returns:
-        gr.update with choices list for the CheckboxGroup
-    """
-    if not proposals:
-        return gr.update(choices=[], value=[])
-
-    choices = []
-    for p in proposals:
-        label = f"[{p['timestamp']}] {p['description']}"
-        choices.append((label, p['id']))
-    return gr.update(choices=choices, value=[])
-
-
-def execute_approved_proposals(selected_ids: list, pending_proposals: list) -> tuple:
-    """Execute approved proposals and remove them from the queue.
-
-    Args:
-        selected_ids: List of proposal IDs that Josh approved
-        pending_proposals: Full list of pending proposals
-
-    Returns:
-        Tuple of (results_markdown, updated_proposals, updated_gate_choices)
-    """
-    if not selected_ids:
-        return "No proposals selected.", pending_proposals, _format_gate_choices(pending_proposals)
-
-    results = []
-    remaining = []
-
-    for proposal in pending_proposals:
-        if proposal['id'] in selected_ids:
-            # Execute this one
-            result = execute_staged_tool(proposal['tool'], proposal['args'])
-            results.append(f"**{proposal['tool']}**: {result}")
-        else:
-            # Keep in queue
-            remaining.append(proposal)
-
-    results_text = "## Execution Results\n\n" + "\n\n".join(results) if results else "Nothing executed."
-    return results_text, remaining, _format_gate_choices(remaining)
-
-
-def clear_all_proposals(pending_proposals: list) -> tuple:
-    """Discard all pending proposals without executing.
-
-    CHANGELOG [2026-02-01 - Claude/Opus]
-    Safety valve — lets Josh throw out everything in the queue if the
-    agent went off track.
-
-    Returns:
-        Tuple of (status_message, empty_proposals, updated_gate_choices)
-    """
-    count = len(pending_proposals)
-    return f"🗑️ Cleared {count} proposal(s).", [], _format_gate_choices([])
-
-
-# =============================================================================
-# STATS HELPERS
-# =============================================================================
-# CHANGELOG [2026-02-01 - Claude/Opus]
-# Helper functions to format stats for the sidebar labels.
-# Called both at startup (initial render) and after each conversation turn
-# (to reflect newly indexed files or saved conversations).
-# =============================================================================
-
-def _stats_label_files() -> str:
-    """Format the files stat for the sidebar label."""
-    stats = ctx.get_stats()
-    files = stats.get('total_files', 0)
-    chunks = stats.get('indexed_chunks', 0)
-    indexing = " ⏳" if stats.get('indexing_in_progress') else ""
-    return f"📂 Files: {files} ({chunks} chunks){indexing}"
-
-
-def _stats_label_convos() -> str:
-    """Format the conversations stat for the sidebar label."""
-    stats = ctx.get_stats()
-    convos = stats.get('conversations', 0)
-    cloud = " ☁️" if stats.get('persistence_configured') else ""
-    return f"💾 Conversations: {convos}{cloud}"
-
-
-def refresh_stats() -> tuple:
-    """Refresh both stat labels. Called by the refresh button.
-
-    Returns:
-        Tuple of (files_label, convos_label)
-    """
-    return _stats_label_files(), _stats_label_convos()
-
-
-# =============================================================================
-# UI LAYOUT
-# =============================================================================
-# CHANGELOG [2026-02-01 - Gemini]
-# RESTORED: Metrics sidebar and multi-tab layout.
-#
-# CHANGELOG [2026-02-01 - Claude/Opus]
-# IMPLEMENTED: All the wiring. Every button, input, and display is now
-# connected to actual functions.
-#
-# Layout:
-# Tab 1 "Vibe Chat" — Main conversation interface with sidebar stats
-# Tab 2 "Build Approval Gate" — HITL review for staged write operations
-#
-# gr.State holds the pending proposals list (per-session, survives across
-# messages within the same browser tab).
-# =============================================================================
-
-with gr.Blocks(
-    title="🦞 Clawdbot Command Center",
-    theme=gr.themes.Soft()
-) as demo:
-    # Session state for pending proposals
-    pending_proposals_state = gr.State([])
-
-    gr.Markdown("# 🦞 Clawdbot Command Center\n*E-T Systems Vibe Coding Agent*")
-
-    with gr.Tabs():
-        # ==== TAB 1: VIBE CHAT ====
-        with gr.Tab("💬 Vibe Chat"):
-            with gr.Row():
-                # ---- Sidebar ----
-                with gr.Column(scale=1, min_width=200):
-                    gr.Markdown("### 📊 System Status")
-                    stats_files = gr.Markdown(_stats_label_files())
-                    stats_convos = gr.Markdown(_stats_label_convos())
-                    refresh_btn = gr.Button("🔄 Refresh Stats", size="sm")
-
-                    gr.Markdown("---")
-                    gr.Markdown("### 📎 Upload Context")
-                    file_input = gr.File(
-                        label="Drop a file here",
-                        file_types=[
-                            '.py', '.js', '.ts', '.json', '.md', '.txt',
-                            '.yaml', '.yml', '.html', '.css', '.sh',
-                            '.toml', '.cfg', '.csv', '.xml'
-                        ]
-                    )
-                    gr.Markdown(
-                        "*Upload code, configs, or docs to include in your message.*"
-                    )
-
-                # ---- Chat area ----
-                with gr.Column(scale=4):
-                    chatbot = gr.Chatbot(
-                        type="messages",
-                        height=600,
-                        show_label=False,
-                        avatar_images=(None, "https://em-content.zobj.net/source/twitter/408/lobster_1f99e.png"),
-                    )
-                    with gr.Row():
-                        msg = gr.Textbox(
-                            placeholder="Ask Clawdbot to search, read, or code...",
-                            show_label=False,
-                            scale=6,
-                            lines=2,
-                            max_lines=10,
-                        )
-                        send_btn = gr.Button("Send", variant="primary", scale=1)
-
-            # Wire up chat submission
-            chat_inputs = [msg, chatbot, pending_proposals_state, file_input]
-            chat_outputs = [
-                chatbot, msg, pending_proposals_state,
-                # These reference components in the Gate tab — defined below
-            ]
-
-        # ==== TAB 2: BUILD APPROVAL GATE ====
-        with gr.Tab("🛡️ Build Approval Gate"):
-            gr.Markdown(
-                "### Review Staged Operations\n"
-                "Write operations (file writes, shell commands, branch creation) "
-                "are staged here for your review before execution.\n\n"
-                "**Select proposals to approve, then click Execute.**"
-            )
-            gate_list = gr.CheckboxGroup(
-                label="Pending Proposals",
-                choices=[],
-                interactive=True
-            )
-            with gr.Row():
-                btn_exec = gr.Button("✅ Execute Selected", variant="primary")
-                btn_clear = gr.Button("🗑️ Clear All", variant="secondary")
-            gate_results = gr.Markdown("*No operations executed yet.*")
-
-    # ==================================================================
-    # EVENT WIRING
-    # ==================================================================
-    # CHANGELOG [2026-02-01 - Claude/Opus]
-    # All events are wired here, after all components are defined, so
-    # cross-tab references work (e.g., chat updating the gate_list).
-    # ==================================================================
-
-    # Chat submission (both Enter key and Send button)
-    full_chat_outputs = [
-        chatbot, msg, pending_proposals_state,
-        gate_list, stats_files, stats_convos
-    ]
-
-    msg.submit(
-        fn=agent_loop,
-        inputs=chat_inputs,
-        outputs=full_chat_outputs
-    )
-    send_btn.click(
-        fn=agent_loop,
-        inputs=chat_inputs,
-        outputs=full_chat_outputs
-    )
-
-    # Refresh stats button
-    refresh_btn.click(
-        fn=refresh_stats,
-        inputs=[],
-        outputs=[stats_files, stats_convos]
-    )
-
-    # Build Approval Gate buttons
-    btn_exec.click(
-        fn=execute_approved_proposals,
-        inputs=[gate_list, pending_proposals_state],
-        outputs=[gate_results, pending_proposals_state, gate_list]
-    )
-    btn_clear.click(
-        fn=clear_all_proposals,
-        inputs=[pending_proposals_state],
-        outputs=[gate_results, pending_proposals_state, gate_list]
-    )
-
-
-# =============================================================================
-# LAUNCH
-# =============================================================================
-# CHANGELOG [2026-02-01 - Claude/Opus]
-# Standard HF Spaces launch config. 0.0.0.0 binds to all interfaces
-# (required for Docker). Port 7860 is the HF Spaces standard.
-# =============================================================================
-
-if __name__ == "__main__":
-    demo.launch(server_name="0.0.0.0", server_port=7860)