wehub-resource-sync
219 lines
7.4 KiB
Python
219 lines
7.4 KiB
Python
#!/usr/bin/env python3
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"""
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s10: System Prompt — Runtime prompt assembly with caching.
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Run: python s10_system_prompt/code.py
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Need: pip install anthropic python-dotenv + .env with ANTHROPIC_API_KEY
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Changes from s09:
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- PROMPT_SECTIONS: topic-keyed dict of prompt fragments
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- assemble_system_prompt(context): select + join sections by real state
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- get_system_prompt(context): deterministic cache via json.dumps
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- agent_loop uses get_system_prompt(context) instead of hardcoded SYSTEM
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Memory section loads when .memory/MEMORY.md exists (real state, not keywords).
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"""
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import os, subprocess, json
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from pathlib import Path
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try:
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import readline
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readline.parse_and_bind('set bind-tty-special-chars off')
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except ImportError:
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pass
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from anthropic import Anthropic
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from dotenv import load_dotenv
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load_dotenv(override=True)
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if os.getenv("ANTHROPIC_BASE_URL"):
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os.environ.pop("ANTHROPIC_AUTH_TOKEN", None)
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WORKDIR = Path.cwd()
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MEMORY_DIR = WORKDIR / ".memory"
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MEMORY_INDEX = MEMORY_DIR / "MEMORY.md"
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client = Anthropic(base_url=os.getenv("ANTHROPIC_BASE_URL"))
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MODEL = os.environ["MODEL_ID"]
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# ── Prompt Sections ──
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PROMPT_SECTIONS = {
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"identity": "You are a coding agent. Act, don't explain.",
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"tools": "Available tools: bash, read_file, write_file.",
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"workspace": f"Working directory: {WORKDIR}",
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"memory": "Relevant memories are injected below when available.",
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}
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def assemble_system_prompt(context: dict) -> str:
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"""Select and join prompt sections based on current context."""
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sections = []
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# Always loaded — identity, tools, workspace
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sections.append(PROMPT_SECTIONS["identity"])
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sections.append(PROMPT_SECTIONS["tools"])
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sections.append(PROMPT_SECTIONS["workspace"])
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# Conditional — memory loaded when MEMORY.md exists and has content
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memories = context.get("memories", "")
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if memories:
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sections.append(f"Relevant memories:\n{memories}")
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return "\n\n".join(sections)
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_last_context_key = None
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_last_prompt = None
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def get_system_prompt(context: dict) -> str:
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"""Cache wrapper — reassemble only when context changes.
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Uses json.dumps for deterministic serialization, not Python's hash()
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which has process randomization and fails on nested dicts/lists.
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This cache only avoids redundant string assembly within a process.
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Real Claude Code additionally protects API-level prompt cache via
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stable section ordering and SYSTEM_PROMPT_DYNAMIC_BOUNDARY.
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"""
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global _last_context_key, _last_prompt
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key = json.dumps(context, sort_keys=True, ensure_ascii=False, default=str)
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if key == _last_context_key and _last_prompt:
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print(" \033[90m[cache hit] system prompt unchanged\033[0m")
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return _last_prompt
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_last_context_key = key
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_last_prompt = assemble_system_prompt(context)
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loaded = ["identity", "tools", "workspace"]
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if context.get("memories"):
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loaded.append("memory")
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print(f" \033[32m[assembled] sections: {', '.join(loaded)}\033[0m")
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return _last_prompt
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# ── Tools ──
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def safe_path(p: str) -> Path:
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path = (WORKDIR / p).resolve()
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if not path.is_relative_to(WORKDIR):
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raise ValueError(f"Path escapes workspace: {p}")
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return path
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def run_bash(command: str) -> str:
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try:
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r = subprocess.run(command, shell=True, cwd=WORKDIR,
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capture_output=True, text=True, timeout=120)
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out = (r.stdout + r.stderr).strip()
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return out[:50000] if out else "(no output)"
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except subprocess.TimeoutExpired:
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return "Error: Timeout (120s)"
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def run_read(path: str, limit: int | None = None) -> str:
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try:
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lines = safe_path(path).read_text().splitlines()
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if limit and limit < len(lines):
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lines = lines[:limit] + [f"... ({len(lines) - limit} more lines)"]
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return "\n".join(lines)
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except Exception as e:
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return f"Error: {e}"
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def run_write(path: str, content: str) -> str:
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try:
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file_path = safe_path(path)
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file_path.parent.mkdir(parents=True, exist_ok=True)
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file_path.write_text(content)
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return f"Wrote {len(content)} bytes to {path}"
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except Exception as e:
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return f"Error: {e}"
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TOOLS = [
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{"name": "bash", "description": "Run a shell command.",
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"input_schema": {"type": "object",
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"properties": {"command": {"type": "string"}},
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"required": ["command"]}},
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{"name": "read_file", "description": "Read file contents.",
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"input_schema": {"type": "object",
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"properties": {"path": {"type": "string"},
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"limit": {"type": "integer"}},
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"required": ["path"]}},
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{"name": "write_file", "description": "Write content to a file.",
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"input_schema": {"type": "object",
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"properties": {"path": {"type": "string"},
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"content": {"type": "string"}},
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"required": ["path", "content"]}},
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]
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TOOL_HANDLERS = {"bash": run_bash, "read_file": run_read, "write_file": run_write}
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# ── Context ──
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def update_context(context: dict, messages: list) -> dict:
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"""Derive context from real state: which tools exist, whether memory files exist."""
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memories = ""
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if MEMORY_INDEX.exists():
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content = MEMORY_INDEX.read_text().strip()
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if content:
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memories = content
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return {
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"enabled_tools": list(TOOL_HANDLERS.keys()),
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"workspace": str(WORKDIR),
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"memories": memories,
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}
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# ── Agent Loop ──
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def agent_loop(messages: list, context: dict):
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"""Main loop — uses assembled system prompt instead of hardcoded SYSTEM."""
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system = get_system_prompt(context)
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while True:
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response = client.messages.create(
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model=MODEL, system=system, messages=messages,
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tools=TOOLS, max_tokens=8000)
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messages.append({"role": "assistant", "content": response.content})
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if response.stop_reason != "tool_use":
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return
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results = []
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for block in response.content:
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if block.type != "tool_use":
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continue
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print(f"\033[36m> {block.name}\033[0m")
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handler = TOOL_HANDLERS.get(block.name)
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output = handler(**block.input) if handler else f"Unknown: {block.name}"
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print(str(output)[:200])
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results.append({"type": "tool_result",
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"tool_use_id": block.id, "content": output})
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messages.append({"role": "user", "content": results})
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# Re-evaluate context and prompt after each tool round
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context = update_context(context, messages)
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system = get_system_prompt(context)
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if __name__ == "__main__":
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print("s10: system prompt — runtime assembly")
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print("Enter a question, press Enter to send. Type q to quit.\n")
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history = []
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context = update_context({}, [])
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while True:
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try:
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query = input("\033[36ms10 >> \033[0m")
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except (EOFError, KeyboardInterrupt):
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break
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if query.strip().lower() in ("q", "exit", ""):
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break
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history.append({"role": "user", "content": query})
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agent_loop(history, context)
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context = update_context(context, history)
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for block in history[-1]["content"]:
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if getattr(block, "type", None) == "text":
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print(block.text)
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print()
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