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