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import gradio as gr |
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from huggingface_hub import InferenceClient |
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from recursive_context import RecursiveContextManager |
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from pathlib import Path |
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import os |
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import json |
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import re |
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import time |
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import zipfile |
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import shutil |
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import traceback |
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import logging |
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logging.basicConfig( |
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level=logging.INFO, |
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format='%(asctime)s - %(levelname)s - %(message)s', |
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handlers=[ |
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logging.FileHandler("clawdbot_system.log"), |
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logging.StreamHandler() |
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] |
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) |
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logger = logging.getLogger("Clawdbot") |
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def log_action(action: str, details: str): |
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"""Records critical system events.""" |
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logger.info(f"ACTION: {action} | DETAILS: {details}") |
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""" |
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Clawdbot Unified Command Center |
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DIAMOND COPY [2026-02-03] |
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FIXED: Added missing retry logic. |
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FIXED: Increased Max Tokens to 8192 (Prevents truncation). |
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FIXED: Increased Loop Stamina to 15 (Prevents silence). |
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""" |
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AVAILABLE_TOOLS = { |
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"list_files", "read_file", "search_code", "write_file", |
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"create_shadow_branch", "shell_execute", "get_stats", |
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"search_conversations", "search_testament", "push_to_github", |
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"pull_from_github", "notebook_add", "notebook_delete", "notebook_read" |
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} |
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TEXT_EXTENSIONS = { |
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'.py', '.js', '.ts', '.jsx', '.tsx', '.json', '.yaml', '.yml', |
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'.md', '.txt', '.rst', '.html', '.css', '.scss', '.sh', '.bash', |
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'.sql', '.toml', '.cfg', '.ini', '.conf', '.xml', '.csv', |
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'.env', '.gitignore', '.dockerfile' |
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} |
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client = InferenceClient("https://router.huggingface.co/v1", token=os.getenv("HF_TOKEN")) |
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ET_SYSTEMS_SPACE = os.getenv("ET_SYSTEMS_SPACE", "") |
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REPO_PATH = os.getenv("REPO_PATH", "/workspace/e-t-systems") |
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MODEL_ID = "moonshotai/Kimi-K2.5" |
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def sync_from_space(space_id: str, local_path: Path): |
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token = os.getenv("HF_TOKEN") |
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if not token: return |
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try: |
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from huggingface_hub import HfFileSystem |
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fs = HfFileSystem(token=token) |
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space_path = f"spaces/{space_id}" |
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all_files = fs.glob(f"{space_path}/**") |
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local_path.mkdir(parents=True, exist_ok=True) |
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for file_path in all_files: |
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rel = file_path.replace(f"{space_path}/", "", 1) |
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if any(p.startswith('.') for p in rel.split('/')) or '__pycache__' in rel: continue |
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try: |
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if fs.info(file_path)['type'] == 'directory': continue |
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except: continue |
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dest = local_path / rel |
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dest.parent.mkdir(parents=True, exist_ok=True) |
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with fs.open(file_path, "rb") as f: dest.write_bytes(f.read()) |
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except Exception: pass |
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def _resolve_repo_path() -> str: |
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return os.path.dirname(os.path.abspath(__file__)) |
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ctx = RecursiveContextManager(_resolve_repo_path()) |
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def build_system_prompt() -> str: |
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stats = ctx.get_stats() |
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tools_doc = """ |
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## Available Tools |
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- **search_code(query, n=5)**: Semantic search codebase. |
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- **read_file(path, start_line, end_line)**: Read file content. |
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- **list_files(path, max_depth)**: Explore directory tree. |
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- **search_conversations(query, n=5)**: Search persistent memory. |
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- **search_testament(query, n=5)**: Search docs/plans. |
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- **write_file(path, content)**: Create/Update file (REQUIRES CHANGELOG). |
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- **shell_execute(command)**: Run shell command. |
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- **create_shadow_branch()**: Backup repository. |
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- **push_to_github(message)**: Save current state to GitHub. |
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- **pull_from_github(branch)**: Hard reset state from GitHub. |
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- **notebook_read()**: Read your working memory. |
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- **notebook_add(content)**: Add a note (max 25). |
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- **notebook_delete(index)**: Delete a note. |
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""" |
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return f"""You are Clawdbot π¦. ... {tools_doc} ... |
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System Stats: {stats.get('total_files', 0)} files, {stats.get('conversations', 0)} memories. |
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{tools_doc} |
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Output Format: Use [TOOL: tool_name(arg="value")] for tools. |
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## CRITICAL PROTOCOLS: |
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1. **RECURSIVE MEMORY FIRST**: If the user asks about past context (e.g., "the new UI"), you MUST use `search_conversations` BEFORE you answer. Do not ask the user for context you already have. |
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2. **THINK OUT LOUD**: When writing code, output the full code block in the chat BEFORE calling `write_file`. This ensures a backup exists in memory if the write fails. |
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3. **CHECK BEFORE WRITE**: Before writing code, use `read_file` or `list_files` to ensure you aren't overwriting good code with bad. |
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4. **NO SILENCE**: If you perform an action, report the result. |
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""" |
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def parse_tool_calls(text: str) -> list: |
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calls = [] |
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bracket_pattern = r"\[TOOL:\s*(\w+)\((.*?)\)\]" |
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for match in re.finditer(bracket_pattern, text, re.DOTALL): |
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tool_name = match.group(1) |
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args_str = match.group(2) |
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args = parse_tool_args(args_str) |
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calls.append((tool_name, args)) |
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if "<|tool_calls" in text: |
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clean_text = re.sub(r"<\|tool_calls_section_begin\|>", "", text) |
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clean_text = re.sub(r"<\|tool_calls_section_end\|>", "", clean_text) |
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clean_text = re.sub(r"<tool_code>", "", clean_text) |
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clean_text = re.sub(r"</tool_code>", "", clean_text) |
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xml_matches = re.finditer(r"(\w+)\s*\((.*?)\)", clean_text, re.DOTALL) |
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for match in xml_matches: |
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tool_name = match.group(1) |
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if tool_name in ["print", "range", "len", "str", "int"]: continue |
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if any(existing[0] == tool_name for existing in calls): continue |
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if tool_name in AVAILABLE_TOOLS: |
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calls.append((tool_name, parse_tool_args(match.group(2)))) |
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if not calls: |
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for match in re.finditer(r'<\|tool_call_begin\|>\s*functions\.(\w+):\d+\s*\n(.*?)<\|tool_call_end\|>', text, re.DOTALL): |
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try: calls.append((match.group(1), json.loads(match.group(2).strip()))) |
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except: pass |
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return calls |
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def parse_tool_args(args_str: str) -> dict: |
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args = {} |
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try: |
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if args_str.strip().startswith('{'): return json.loads(args_str) |
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pattern = r'(\w+)\s*=\s*(?:"([^"]*)"|\'([^\']*)\'|([^,\s]+))' |
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for match in re.finditer(pattern, args_str): |
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key = match.group(1) |
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val = match.group(2) or match.group(3) or match.group(4) |
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if val.isdigit(): val = int(val) |
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args[key] = val |
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except: pass |
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return args |
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def extract_conversational_text(content: str) -> str: |
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cleaned = re.sub(r'\[TOOL:.*?\]', '', content, flags=re.DOTALL) |
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cleaned = re.sub(r'<\|tool_calls.*?<\|tool_calls.*?\|>', '', cleaned, flags=re.DOTALL) |
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cleaned = re.sub(r'<\|tool_call_begin\|>.*?<\|tool_call_end\|>', '', cleaned, flags=re.DOTALL) |
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return cleaned.strip() |
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def execute_tool(tool_name: str, args: dict) -> dict: |
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try: |
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if tool_name == 'search_code': |
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res = ctx.search_code(args.get('query', ''), args.get('n', 5)) |
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return {"status": "executed", "tool": tool_name, "result": "\n".join([f"π {r['file']}\n```{r['snippet']}```" for r in res])} |
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elif tool_name == 'read_file': |
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return {"status": "executed", "tool": tool_name, "result": ctx.read_file(args.get('path', ''), args.get('start_line'), args.get('end_line'))} |
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elif tool_name == 'list_files': |
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return {"status": "executed", "tool": tool_name, "result": ctx.list_files(args.get('path', ''), args.get('max_depth', 3))} |
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elif tool_name == 'search_conversations': |
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res = ctx.search_conversations(args.get('query', ''), args.get('n', 5)) |
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formatted = "\n---\n".join([f"{r['content']}" for r in res]) if res else "No matches found." |
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return {"status": "executed", "tool": tool_name, "result": formatted} |
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elif tool_name == 'search_testament': |
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res = ctx.search_testament(args.get('query', ''), args.get('n', 5)) |
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formatted = "\n\n".join([f"π **{r['file']}**\n{r['snippet']}" for r in res]) if res else "No matches found." |
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return {"status": "executed", "tool": tool_name, "result": formatted} |
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elif tool_name == 'write_file': |
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result = ctx.write_file(args.get('path', ''), args.get('content', '')) |
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return {"status": "executed", "tool": tool_name, "result": result} |
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elif tool_name == 'write_file': |
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log_action("WRITE_ATTEMPT", f"Writing to {args.get('path')}") |
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elif tool_name == 'shell_execute': |
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result = ctx.shell_execute(args.get('command', '')) |
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return {"status": "executed", "tool": tool_name, "result": result} |
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elif tool_name == 'push_to_github': |
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result = ctx.push_to_github(args.get('message', 'Manual Backup')) |
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return {"status": "executed", "tool": tool_name, "result": result} |
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elif tool_name == 'pull_from_github': |
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result = ctx.pull_from_github(args.get('branch', 'main')) |
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return {"status": "executed", "tool": tool_name, "result": result} |
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elif tool_name == 'create_shadow_branch': |
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return {"status": "staged", "tool": tool_name, "args": args, "description": "π‘οΈ Create shadow branch"} |
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return {"status": "error", "result": f"Unknown tool: {tool_name}"} |
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except Exception as e: return {"status": "error", "result": str(e)} |
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def execute_staged_tool(tool_name: str, args: dict) -> str: |
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try: |
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if tool_name == 'write_file': return ctx.write_file(args.get('path', ''), args.get('content', '')) |
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if tool_name == 'shell_execute': return ctx.shell_execute(args.get('command', '')) |
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if tool_name == 'create_shadow_branch': return ctx.create_shadow_branch() |
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except Exception as e: return f"Error: {e}" |
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return "Unknown tool" |
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def process_uploaded_file(file) -> str: |
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if file is None: return "" |
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if isinstance(file, list): file = file[0] if len(file) > 0 else None |
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if file is None: return "" |
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file_path = file.name if hasattr(file, 'name') else str(file) |
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file_name = os.path.basename(file_path) |
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suffix = os.path.splitext(file_name)[1].lower() |
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if suffix == '.zip': |
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try: |
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extract_to = Path(REPO_PATH) / "uploaded_assets" / file_name.replace(".zip", "") |
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if extract_to.exists(): shutil.rmtree(extract_to) |
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extract_to.mkdir(parents=True, exist_ok=True) |
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with zipfile.ZipFile(file_path, 'r') as z: z.extractall(extract_to) |
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file_list = [f.name for f in extract_to.glob('*')] |
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preview = ", ".join(file_list[:10]) |
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return (f"π¦ **Unzipped: {file_name}**\nLocation: `{extract_to}`\nContents: {preview}\n" |
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f"SYSTEM NOTE: The files are extracted. Use list_files('{extract_to.name}') to explore them.") |
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except Exception as e: return f"β οΈ Failed to unzip {file_name}: {e}" |
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if suffix in TEXT_EXTENSIONS or suffix == '': |
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try: |
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with open(file_path, 'r', encoding='utf-8', errors='ignore') as f: |
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content = f.read() |
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if len(content) > 50000: content = content[:50000] + "\n...(truncated)" |
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return f"π **Uploaded: {file_name}**\n```\n{content}\n```" |
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except Exception as e: return f"π **Uploaded: {file_name}** (error reading: {e})" |
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return f"π **Uploaded: {file_name}** (binary file, {os.path.getsize(file_path):,} bytes)" |
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def call_model_with_retry(messages, model_id, max_retries=4): |
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for attempt in range(max_retries): |
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try: |
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return client.chat_completion(model=model_id, messages=messages, max_tokens=8192, temperature=0.7) |
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except Exception as e: |
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error_str = str(e) |
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if "504" in error_str or "503" in error_str or "timeout" in error_str.lower(): |
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if attempt == max_retries - 1: raise e |
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time.sleep(2 * (2 ** attempt)) |
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else: |
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raise e |
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def agent_loop(message: str, history: list, pending_proposals: list, uploaded_file) -> tuple: |
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safe_hist = history or [] |
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safe_props = pending_proposals or [] |
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try: |
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if not message.strip() and uploaded_file is None: |
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return (safe_hist, "", safe_props, _format_gate_choices(safe_props), _stats_label_files(), _stats_label_convos()) |
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full_message = message.strip() |
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if uploaded_file: |
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full_message = f"{process_uploaded_file(uploaded_file)}\n\n{full_message}" |
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safe_hist = safe_hist + [{"role": "user", "content": full_message}] |
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system_prompt = build_system_prompt() |
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api_messages = [{"role": "system", "content": system_prompt}] |
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for h in safe_hist[-40:]: |
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api_messages.append({"role": h["role"], "content": h["content"]}) |
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accumulated_text = "" |
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staged_this_turn = [] |
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MAX_ITERATIONS = 15 |
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for iteration in range(MAX_ITERATIONS): |
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try: |
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if iteration == MAX_ITERATIONS - 1: |
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api_messages.append({"role": "system", "content": "SYSTEM ALERT: Max steps reached. STOP using tools. Summarize findings immediately."}) |
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resp = call_model_with_retry(api_messages, MODEL_ID) |
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content = resp.choices[0].message.content or "" |
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except Exception as e: |
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safe_hist.append({"role": "assistant", "content": f"β οΈ API Error: {e}"}) |
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return (safe_hist, "", safe_props, _format_gate_choices(safe_props), _stats_label_files(), _stats_label_convos()) |
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calls = parse_tool_calls(content) |
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text = extract_conversational_text(content) |
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if text: accumulated_text += ("\n\n" if accumulated_text else "") + text |
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if not calls: break |
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results = [] |
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for name, args in calls: |
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res = execute_tool(name, args) |
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if res["status"] == "executed": |
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results.append(f"[Tool Result: {name}]\n{res['result']}") |
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elif res["status"] == "staged": |
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p_id = f"p_{int(time.time())}_{name}" |
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staged_this_turn.append({ |
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"id": p_id, "tool": name, "args": res["args"], |
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"description": res["description"], "timestamp": time.strftime("%H:%M:%S") |
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}) |
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results.append(f"[STAGED: {name}]") |
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if results: |
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api_messages += [{"role": "assistant", "content": content}, {"role": "user", "content": "\n".join(results)}] |
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else: |
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break |
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final = accumulated_text |
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if staged_this_turn: |
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final += "\n\nπ‘οΈ **Proposals Staged.** Check the Gate tab." |
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safe_props += staged_this_turn |
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if not final: final = "π€ I processed that but have no text response." |
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safe_hist.append({"role": "assistant", "content": final}) |
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try: ctx.save_conversation_turn(full_message, final, len(safe_hist)) |
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except: pass |
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return (safe_hist, "", safe_props, _format_gate_choices(safe_props), _stats_label_files(), _stats_label_convos()) |
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except Exception as e: |
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safe_hist.append({"role": "assistant", "content": f"π₯ Critical Error: {e}"}) |
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return (safe_hist, "", safe_props, _format_gate_choices(safe_props), _stats_label_files(), _stats_label_convos()) |
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def _format_gate_choices(proposals): |
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return gr.CheckboxGroup(choices=[(f"[{p['timestamp']}] {p['description']}", p['id']) for p in proposals], value=[]) |
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def execute_approved_proposals(ids, proposals, history): |
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if not ids: return "No selection.", proposals, _format_gate_choices(proposals), history |
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results, remaining = [], [] |
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for p in proposals: |
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if p['id'] in ids: |
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out = execute_staged_tool(p['tool'], p['args']) |
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results.append(f"**{p['tool']}**: {out}") |
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else: remaining.append(p) |
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if results: history.append({"role": "assistant", "content": "β
**Executed:**\n" + "\n".join(results)}) |
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return "Done.", remaining, _format_gate_choices(remaining), history |
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def auto_continue_after_approval(history, proposals): |
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last = history[-1].get("content", "") if history else "" |
|
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if "β
**Executed:**" in str(last): |
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return agent_loop("[System: Tools executed. Continue.]", history, proposals, None) |
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return history, "", proposals, _format_gate_choices(proposals), _stats_label_files(), _stats_label_convos() |
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def _stats_label_files(): return f"π Files: {ctx.get_stats().get('total_files', 0)}" |
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def _stats_label_convos(): return f"πΎ Convos: {ctx.get_stats().get('conversations', 0)}" |
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with gr.Blocks(title="π¦ Clawdbot") as demo: |
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state_proposals = gr.State([]) |
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gr.Markdown("# π¦ Clawdbot Command Center") |
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with gr.Tabs(): |
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with gr.Tab("π¬ Chat"): |
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with gr.Row(): |
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with gr.Column(scale=1): |
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stat_f = gr.Markdown(_stats_label_files()) |
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stat_c = gr.Markdown(_stats_label_convos()) |
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btn_ref = gr.Button("π") |
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file_in = gr.File(label="Upload", file_count="multiple") |
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with gr.Column(scale=4): |
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chat = gr.Chatbot(height=600, avatar_images=(None, "https://em-content.zobj.net/source/twitter/408/lobster_1f99e.png")) |
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with gr.Row(): |
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txt = gr.Textbox(scale=6, placeholder="Prompt...") |
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|
btn_send = gr.Button("Send", scale=1) |
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|
with gr.Tab("π‘οΈ Gate"): |
|
|
gate = gr.CheckboxGroup(label="Proposals", interactive=True) |
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|
with gr.Row(): |
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|
btn_exec = gr.Button("β
Execute", variant="primary") |
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|
btn_clear = gr.Button("ποΈ Clear") |
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|
res_md = gr.Markdown() |
|
|
|
|
|
inputs = [txt, chat, state_proposals, file_in] |
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outputs = [chat, txt, state_proposals, gate, stat_f, stat_c] |
|
|
|
|
|
txt.submit(agent_loop, inputs, outputs) |
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|
btn_send.click(agent_loop, inputs, outputs) |
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|
btn_ref.click(lambda: (_stats_label_files(), _stats_label_convos()), None, [stat_f, stat_c]) |
|
|
|
|
|
btn_exec.click(execute_approved_proposals, [gate, state_proposals, chat], [res_md, state_proposals, gate, chat]).then( |
|
|
auto_continue_after_approval, [chat, state_proposals], outputs |
|
|
) |
|
|
btn_clear.click(lambda p: ("Cleared.", [], _format_gate_choices([])), state_proposals, [res_md, state_proposals, gate]) |
|
|
|
|
|
if __name__ == "__main__": |
|
|
demo.launch(server_name="0.0.0.0", server_port=7860) |