toon-er
This commit is contained in:
+109
@@ -414,3 +414,112 @@ class LocalGraph:
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result['incoming'].append(rel_info)
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return result
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def get_queryable_relationships(self, node_id: str) -> dict:
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"""Get relationships in a format optimized for graph queries."""
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if node_id not in self.graph.nodes:
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return {}
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node_data = self.graph.nodes[node_id]
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result = {
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'node_id': node_id,
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'node_type': node_data.get('type', ''),
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'node_name': node_data.get('name', ''),
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'file': node_data.get('file', ''),
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'outgoing': [],
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'incoming': [],
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'cross_file': [],
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'same_file': []
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}
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node_file = node_data.get('file', '')
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# Process all relationships
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for neighbor_id in self.graph.successors(node_id):
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if neighbor_id in self.graph.nodes:
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edge_data = self.graph.edges[node_id, neighbor_id]
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neighbor_data = self.graph.nodes[neighbor_id]
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rel_info = {
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'type': edge_data.get('type', 'related'),
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'target_id': neighbor_id,
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'target_name': neighbor_data.get('name', ''),
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'target_type': neighbor_data.get('type', ''),
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'target_file': neighbor_data.get('file', '')
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}
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result['outgoing'].append(rel_info)
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# Classify by file relationship
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if neighbor_data.get('file') and neighbor_data.get('file') != node_file:
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result['cross_file'].append(rel_info)
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else:
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result['same_file'].append(rel_info)
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# Reverse relationships
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for predecessor_id in self.graph.predecessors(node_id):
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if predecessor_id in self.graph.nodes:
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edge_data = self.graph.edges[predecessor_id, node_id]
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predecessor_data = self.graph.nodes[predecessor_id]
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rel_info = {
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'type': edge_data.get('type', 'related'),
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'source_id': predecessor_id,
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'source_name': predecessor_data.get('name', ''),
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'source_type': predecessor_data.get('type', ''),
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'source_file': predecessor_data.get('file', '')
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}
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result['incoming'].append(rel_info)
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return result
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def classify_relationships(self, node_id):
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node_data = self.graph.nodes[node_id]
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node_file = node_data.get('file', '')
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result = {
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'outgoing': [],
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'incoming': [],
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'same_file': [],
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'cross_file': []
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}
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for neighbor_id in self.graph.successors(node_id):
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if neighbor_id in self.graph.nodes:
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edge_data = self.graph.edges[node_id, neighbor_id]
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neighbor_data = self.graph.nodes[neighbor_id]
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rel_info = {
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'type': edge_data.get('type', 'related'),
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'target_id': neighbor_id,
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'target_name': neighbor_data.get('name', ''),
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'target_type': neighbor_data.get('type', ''),
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'target_file': neighbor_data.get('file', '')
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}
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result['outgoing'].append(rel_info)
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# Classify by file relationship
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if neighbor_data.get('file') and neighbor_data.get('file') != node_file:
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result['cross_file'].append(rel_info)
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else:
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result['same_file'].append(rel_info)
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# Reverse relationships
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for predecessor_id in self.graph.predecessors(node_id):
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if predecessor_id in self.graph.nodes:
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edge_data = self.graph.edges[predecessor_id, node_id]
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predecessor_data = self.graph.nodes[predecessor_id]
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rel_info = {
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'type': edge_data.get('type', 'related'),
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'source_id': predecessor_id,
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'source_name': predecessor_data.get('name', ''),
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'source_type': predecessor_data.get('type', ''),
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'source_file': predecessor_data.get('file', '')
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}
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result['incoming'].append(rel_info)
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return result
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+60
-52
@@ -4999,76 +4999,79 @@ def _get_result_graph_context(meta: dict, graph: Optional[LocalGraph] = None) ->
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if graph is None or graph.graph.number_of_nodes() == 0:
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return {}
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context = {}
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_format_enhanced_results = {}
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file_path = meta.get('file', '')
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entity_name = meta.get('name', '')
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entity_type = meta.get('type', '')
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language = meta.get('language', '')
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# Build node ID using the same logic as graph building
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node_attrs = {
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"lang": language,
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"type": entity_type,
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"file": file_path,
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"name": entity_name
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}
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node_id = _build_node_id(node_attrs)
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node_id = _build_node_id(language, entity_type, file_path, entity_name, meta)
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if node_id and node_id in graph.graph:
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context['node_id'] = node_id
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# Get comprehensive relationships for graph queries
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cross_file_out, cross_file_in = graph.get_cross_file_relationships(node_id, file_path)
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# Format for graph queries: "node_id:relationship_type"
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if cross_file_out:
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context['cross_file'] = []
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for rel in cross_file_out[:8]: # Limit to most important
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# Extract target node info for graph queries
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parts = rel.split('@')
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relationship = parts[0]
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target_file = parts[1] if len(parts) > 1 else ""
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context['cross_file'].append(f"{relationship}->{target_file}")
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if cross_file_in:
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context['used_by'] = []
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for rel in cross_file_in[:6]: # Limit to most important
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parts = rel.split('@')
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relationship = parts[0]
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source_file = parts[1] if len(parts) > 1 else ""
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context['used_by'].append(f"{relationship}<-{source_file}")
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# Same-file relationships for local graph exploration
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# Get ALL relationships for comprehensive graph queries
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cross_file_out = []
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cross_file_in = []
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same_file_rels = []
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# Outgoing relationships
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for neighbor_id in graph.graph.successors(node_id):
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if neighbor_id in graph.graph.nodes:
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neighbor_file = graph.graph.nodes[neighbor_id].get('file', '')
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if neighbor_file == file_path:
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edge_data = graph.graph.edges[node_id, neighbor_id]
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rel_type = edge_data.get('type', 'related')
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neighbor_name = graph.graph.nodes[neighbor_id].get('name', '')
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neighbor_type = graph.graph.nodes[neighbor_id].get('type', '')
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same_file_rels.append(f"{rel_type}:{neighbor_type}:{neighbor_name}")
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edge_data = graph.graph.edges[node_id, neighbor_id]
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neighbor_data = graph.graph.nodes[neighbor_id]
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rel_type = edge_data.get('type', 'related')
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neighbor_name = neighbor_data.get('name', '')
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neighbor_type = neighbor_data.get('type', '')
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neighbor_file = neighbor_data.get('file', '')
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rel_info = f"{rel_type}:{neighbor_type}:{neighbor_name}"
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# Cross-file relationships (most valuable for queries)
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if neighbor_file and neighbor_file != file_path:
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cross_file_out.append(f"{rel_info}@{neighbor_file}")
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else:
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same_file_rels.append(rel_info)
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# Incoming relationships (reverse dependencies)
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for predecessor_id in graph.graph.predecessors(node_id):
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if predecessor_id in graph.graph.nodes:
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edge_data = graph.graph.edges[predecessor_id, node_id]
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predecessor_data = graph.graph.nodes[predecessor_id]
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rel_type = edge_data.get('type', 'related')
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pred_name = predecessor_data.get('name', '')
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pred_type = predecessor_data.get('type', '')
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pred_file = predecessor_data.get('file', '')
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if pred_file and pred_file != file_path:
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cross_file_in.append(f"{rel_type}:{pred_type}:{pred_name}@{pred_file}")
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# Store in context for TOON format
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if cross_file_out:
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context['cross_file'] = cross_file_out[:6] # Top 6 cross-file deps
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if cross_file_in:
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context['used_by'] = cross_file_in[:4] # Top 4 reverse deps
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if same_file_rels:
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context['same_file'] = same_file_rels[:10]
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context['same_file'] = same_file_rels[:8] # Top 8 same-file rels
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return context
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def _build_node_id(attrs: dict) -> str:
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def _build_node_id(lang: str, entity_type: str, file_path: str, entity_name: str, meta: dict) -> str:
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"""Build node ID using the same logic as graph building."""
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lang = attrs.get("lang", "unknown")
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node_type = attrs.get("type", "Symbol")
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name = attrs.get("name", "unknown")
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fpath = attrs.get("file", "")
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if not entity_name or not file_path or not lang:
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return None
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# Handle special cases
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if node_type == "component" and lang == "svelte":
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return f"svelte::component::{fpath}::{name}"
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elif node_type in ["method", "function"] and attrs.get("class_name"):
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return f"{lang}::{node_type}::{fpath}::{attrs['class_name']}.{name}"
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# Handle special cases to match graph building logic
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if entity_type in ["method", "function"] and meta.get("class"):
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class_name = meta.get("class")
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return f"{lang}::{entity_type}::{file_path}::{class_name}.{entity_name}"
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elif entity_type == "component" and lang == "svelte":
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return f"svelte::component::{file_path}::{entity_name}"
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else:
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return f"{lang}::{node_type}::{fpath}::{name}"
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return f"{lang}::{entity_type}::{file_path}::{entity_name}"
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def _format_enhanced_results(results: List[Dict], query: str, result_type: str) -> str:
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"""Format results in TOON (Token-Oriented Object Notation) for LLM consumption."""
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@@ -5091,23 +5094,28 @@ def _format_enhanced_results(results: List[Dict], query: str, result_type: str)
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content = result.get('content', '')
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graph_context = result.get('graph_context', {})
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# Build compact graph context string
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# Build compact graph context string for queries
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graph_parts = []
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# Node ID for direct graph queries
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if graph_context.get('node_id'):
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graph_parts.append(f"node:{graph_context['node_id']}")
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# Cross-file dependencies for import/call queries
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if graph_context.get('cross_file'):
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graph_parts.append(f"xfile:{'|'.join(graph_context['cross_file'][:4])}")
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# Reverse dependencies for "used by" queries
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if graph_context.get('used_by'):
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graph_parts.append(f"used:{'|'.join(graph_context['used_by'][:3])}")
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# Same-file relationships for file context queries
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if graph_context.get('same_file'):
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graph_parts.append(f"same:{'|'.join(graph_context['same_file'][:5])}")
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graph_str = ";".join(graph_parts)
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# Build TOON row
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# Build TOON row - compact format for LLM parsing
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row = [
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file_path,
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str(line_num),
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@@ -5115,7 +5123,7 @@ def _format_enhanced_results(results: List[Dict], query: str, result_type: str)
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entity_name,
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language,
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f"{score:.2f}",
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content, # No truncation - let LLM handle it
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content, # Full content - LLM can handle truncation if needed
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graph_str
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]
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