Added many tools

tools/research.py

@@ -0,0 +1,149 @@
+from __future__ import annotations
+
+from typing import Any
+
+from core.tools.base import BaseTool, ToolContext
+from core.tools.registry import registry
+from core.events import bus
+
+
+class ResearchTool(BaseTool):
+    """
+    High-level research orchestrator.
+
+    Combines:
+    - search
+    - intelligent ranking
+    - crawling
+    into a structured report.
+    """
+
+    name = "research"
+    description = "Autonomous web research pipeline"
+
+    # =========================
+    # EXECUTE
+    # =========================
+
+    def execute(self, payload: dict[str, Any], ctx: ToolContext):
+        query = payload.get("query")
+        depth = payload.get("depth", 1)
+        max_sources = payload.get("max_sources", 3)
+
+        if not isinstance(query, str):
+            raise ValueError("query must be string")
+
+        bus.log(
+            "RESEARCH",
+            "research_execute",
+            "INFO",
+            {
+                "query": query,
+                "depth": depth,
+                "max_sources": max_sources
+            }
+        )
+
+        # Step 1: search
+        search_results = registry.run(
+            "search",
+            {"action": "search", "query": query, "limit": 10},
+            ctx
+        )
+
+        results = search_results.get("results", [])
+
+        if not results:
+            return {
+                "query": query,
+                "error": "No search results found"
+            }
+
+        # Step 2: intelligent ranking
+        ranked = registry.run(
+            "intelligent_search",
+            {
+                "action": "rank",
+                "query": query,
+                "results": results
+            },
+            ctx
+        )
+
+        ranked_list = ranked.get("ranked", [])[:max_sources]
+
+        # Step 3: crawl top sources
+        pages = []
+
+        for item in ranked_list:
+            url = item.get("url")
+
+            if not url:
+                continue
+
+            page = registry.run(
+                "crawler",
+                {
+                    "action": "fetch",
+                    "url": url
+                },
+                ctx
+            )
+
+            pages.append({
+                "url": url,
+                "title": item.get("title"),
+                "text": page.get("text", ""),
+                "score": item.get("score", 0)
+            })
+
+        # Step 4: synthesize structure
+        return {
+            "query": query,
+            "sources_used": len(pages),
+            "sources": pages,
+            "summary_hint": self._build_hint(pages)
+        }
+
+    # =========================
+    # SIMPLE SYNTHESIS HELPER
+    # =========================
+
+    def _build_hint(self, pages: list[dict[str, Any]]) -> str:
+        """
+        Lightweight heuristic summary hint.
+
+        This is NOT a full LLM summary — just structure guidance.
+        """
+
+        if not pages:
+            return "No data available."
+
+        topics = []
+
+        for p in pages:
+            text = p.get("text", "")
+
+            # crude keyword extraction (lightweight, no deps)
+            words = text.split()
+            keywords = [w for w in words if len(w) > 6][:10]
+
+            topics.append({
+                "url": p.get("url"),
+                "keywords": keywords
+            })
+
+        return (
+            "Key extracted themes per source:\n"
+            + "\n".join(
+                f"- {t['url']}: {', '.join(t['keywords'][:5])}"
+                for t in topics
+            )
+        )
+
+
+# =========================
+# REGISTER
+# =========================
+
+registry.register(ResearchTool())