Implement core agent tooling infrastructure (chat, knowledge search) and update tool registration

2026-06-15 15:03:22 +02:00
parent 0c04d5bf7d
commit 97366bb8e0
4 changed files with 378 additions and 0 deletions
--- a/backend/agent/tools/knowledge.py
+++ b/backend/agent/tools/knowledge.py
@@ -0,0 +1,74 @@
+from __future__ import annotations
+
+import asyncio
+from typing import Any, Dict
+
+from ...local_rag import LibraryContextRequest, library_context
+from ..registry import NativeToolProvider, ToolDefinition, ToolExecutionContext
+
+
+def _knowledge_source(source: Dict[str, Any], library_slug: str) -> Dict[str, Any]:
+    return {
+        "type": "knowledge",
+        "library_slug": library_slug,
+        "doc_id": source.get("doc_id"),
+        "title": source.get("title"),
+        "url": source.get("url"),
+        "record_type": source.get("record_type"),
+        "mime": source.get("mime"),
+        "lang": source.get("lang"),
+        "snippet": source.get("snippet"),
+        "scores": source.get("scores") or {},
+    }
+
+
+async def knowledge_search_handler(arguments: Dict[str, Any], _context: ToolExecutionContext) -> Dict[str, Any]:
+    request = LibraryContextRequest(
+        prompt=arguments["prompt"],
+        top_k=arguments.get("top_k", 5),
+        embed_model=arguments.get("embedding_model"),
+    )
+    payload = await asyncio.to_thread(library_context, arguments["library_slug"], request)
+    raw_hits = (payload.get("result") or {}).get("sources") or []
+    budget = int(arguments.get("context_character_budget") or 12_000)
+    context_block = str(payload.get("context_block") or "")[:budget]
+    sources = [_knowledge_source(item, arguments["library_slug"]) for item in raw_hits]
+    return {
+        "hits": sources,
+        "context_block": context_block,
+        "sources": sources,
+        "scores": [item.get("scores") or {} for item in sources],
+    }
+
+
+def register_knowledge_tools(registry: NativeToolProvider) -> None:
+    registry.register(ToolDefinition(
+        name="heimgeist.knowledge_search",
+        description="Retrieve structured evidence from an indexed Heimgeist knowledge library.",
+        input_schema={
+            "type": "object",
+            "properties": {
+                "prompt": {"type": "string", "minLength": 1},
+                "library_slug": {"type": "string", "minLength": 1},
+                "top_k": {"type": "integer", "minimum": 1, "maximum": 20},
+                "context_character_budget": {"type": "integer", "minimum": 500, "maximum": 60000},
+                "embedding_model": {"type": ["string", "null"]},
+            },
+            "required": ["prompt", "library_slug"],
+            "additionalProperties": False,
+        },
+        output_schema={
+            "type": "object",
+            "properties": {
+                "hits": {"type": "array"},
+                "context_block": {"type": "string"},
+                "sources": {"type": "array"},
+                "scores": {"type": "array"},
+            },
+            "required": ["hits", "context_block", "sources", "scores"],
+            "additionalProperties": False,
+        },
+        handler=knowledge_search_handler,
+        timeout_seconds=180,
+        result_size_limit=100_000,
+    ))