Claude Code Memory Compiler

scripts/query.py

@@ -0,0 +1,138 @@
+"""
+Query the knowledge base using index-guided retrieval (no RAG).
+
+The LLM reads the index, picks relevant articles, and synthesizes an answer.
+No vector database, no embeddings, no chunking - just structured markdown
+and an index the LLM can reason over.
+
+Usage:
+    uv run python query.py "How should I handle auth redirects?"
+    uv run python query.py "What patterns do I use for API design?" --file-back
+"""
+
+from __future__ import annotations
+
+import argparse
+import asyncio
+from pathlib import Path
+
+from config import KNOWLEDGE_DIR, QA_DIR, now_iso
+from utils import load_state, read_all_wiki_content, save_state
+
+ROOT_DIR = Path(__file__).resolve().parent.parent
+
+
+async def run_query(question: str, file_back: bool = False) -> str:
+    """Query the knowledge base and optionally file the answer back."""
+    from claude_agent_sdk import (
+        AssistantMessage,
+        ClaudeAgentOptions,
+        ResultMessage,
+        TextBlock,
+        query,
+    )
+
+    wiki_content = read_all_wiki_content()
+
+    tools = ["Read", "Glob", "Grep"]
+    if file_back:
+        tools.extend(["Write", "Edit"])
+
+    file_back_instructions = ""
+    if file_back:
+        timestamp = now_iso()
+        file_back_instructions = f"""
+
+## File Back Instructions
+
+After answering, do the following:
+1. Create a Q&A article at {QA_DIR}/ with the filename being a slugified version
+   of the question (e.g., knowledge/qa/how-to-handle-auth-redirects.md)
+2. Use the Q&A article format from the schema (frontmatter with title, question,
+   consulted articles, filed date)
+3. Update {KNOWLEDGE_DIR / 'index.md'} with a new row for this Q&A article
+4. Append to {KNOWLEDGE_DIR / 'log.md'}:
+   ## [{timestamp}] query (filed) | question summary
+   - Question: {question}
+   - Consulted: [[list of articles read]]
+   - Filed to: [[qa/article-name]]
+"""
+
+    prompt = f"""You are a knowledge base query engine. Answer the user's question by
+consulting the knowledge base below.
+
+## How to Answer
+
+1. Read the INDEX section first - it lists every article with a one-line summary
+2. Identify 3-10 articles that are relevant to the question
+3. Read those articles carefully (they're included below)
+4. Synthesize a clear, thorough answer
+5. Cite your sources using [[wikilinks]] (e.g., [[concepts/supabase-auth]])
+6. If the knowledge base doesn't contain relevant information, say so honestly
+
+## Knowledge Base
+
+{wiki_content}
+
+## Question
+
+{question}
+{file_back_instructions}"""
+
+    answer = ""
+    cost = 0.0
+
+    try:
+        async for message in query(
+            prompt=prompt,
+            options=ClaudeAgentOptions(
+                cwd=str(ROOT_DIR),
+                system_prompt={"type": "preset", "preset": "claude_code"},
+                allowed_tools=tools,
+                permission_mode="acceptEdits",
+                max_turns=15,
+            ),
+        ):
+            if isinstance(message, AssistantMessage):
+                for block in message.content:
+                    if isinstance(block, TextBlock):
+                        answer += block.text
+            elif isinstance(message, ResultMessage):
+                cost = message.total_cost_usd or 0.0
+    except Exception as e:
+        answer = f"Error querying knowledge base: {e}"
+
+    # Update state
+    state = load_state()
+    state["query_count"] = state.get("query_count", 0) + 1
+    state["total_cost"] = state.get("total_cost", 0.0) + cost
+    save_state(state)
+
+    return answer
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Query the personal knowledge base")
+    parser.add_argument("question", help="The question to ask")
+    parser.add_argument(
+        "--file-back",
+        action="store_true",
+        help="File the answer back into the knowledge base as a Q&A article",
+    )
+    args = parser.parse_args()
+
+    print(f"Question: {args.question}")
+    print(f"File back: {'yes' if args.file_back else 'no'}")
+    print("-" * 60)
+
+    answer = asyncio.run(run_query(args.question, file_back=args.file_back))
+    print(answer)
+
+    if args.file_back:
+        print("\n" + "-" * 60)
+        qa_count = len(list(QA_DIR.glob("*.md"))) if QA_DIR.exists() else 0
+        print(f"Answer filed to knowledge/qa/ ({qa_count} Q&A articles total)")
+
+
+if __name__ == "__main__":
+    main()