Fix formatting again

This commit is contained in:
2025-11-16 00:42:05 +00:00
parent bf655edb1d
commit 82f634f249
2 changed files with 147 additions and 113 deletions
+53
View File
@@ -361,3 +361,56 @@ class LocalGraph:
cross_file_in.append(f"{rel_type}:{pred_type}:{pred_name}@{pred_file}")
return cross_file_out, cross_file_in
def get_node_by_id(self, node_id: str) -> Optional[dict]:
"""Get node data by ID for graph queries."""
if node_id in self.graph.nodes:
return dict(self.graph.nodes[node_id])
return None
def get_relationships_for_query(self, node_id: str, max_relationships: int = 10) -> dict:
"""Get relationships in a format suitable for graph queries."""
if node_id not in self.graph.nodes:
return {}
result = {
'node_id': node_id,
'outgoing': [],
'incoming': []
}
node_file = self.graph.nodes[node_id].get('file', '')
# Outgoing relationships
for neighbor_id in list(self.graph.successors(node_id))[:max_relationships]:
if neighbor_id in self.graph.nodes:
edge_data = self.graph.edges[node_id, neighbor_id]
neighbor_data = self.graph.nodes[neighbor_id]
rel_info = {
'type': edge_data.get('type', 'related'),
'target_id': neighbor_id,
'target_name': neighbor_data.get('name', ''),
'target_type': neighbor_data.get('type', ''),
'target_file': neighbor_data.get('file', ''),
'cross_file': neighbor_data.get('file', '') != node_file
}
result['outgoing'].append(rel_info)
# Incoming relationships
for predecessor_id in list(self.graph.predecessors(node_id))[:max_relationships]:
if predecessor_id in self.graph.nodes:
edge_data = self.graph.edges[predecessor_id, node_id]
predecessor_data = self.graph.nodes[predecessor_id]
rel_info = {
'type': edge_data.get('type', 'related'),
'source_id': predecessor_id,
'source_name': predecessor_data.get('name', ''),
'source_type': predecessor_data.get('type', ''),
'source_file': predecessor_data.get('file', ''),
'cross_file': predecessor_data.get('file', '') != node_file
}
result['incoming'].append(rel_info)
return result
+85 -104
View File
@@ -4995,7 +4995,7 @@ def _build_enhanced_result(chunk_text: str, meta: dict, score: float, graph: Opt
def _get_result_graph_context(meta: dict, graph: Optional[LocalGraph] = None) -> dict:
"""Fixed graph context using enhanced graph methods."""
"""Enhanced graph context that provides queryable node IDs and relationships."""
if graph is None or graph.graph.number_of_nodes() == 0:
return {}
@@ -5005,153 +5005,134 @@ def _get_result_graph_context(meta: dict, graph: Optional[LocalGraph] = None) ->
entity_type = meta.get('type', '')
language = meta.get('language', '')
# Try multiple node ID formats to find the right one
node_candidates = []
# Build node ID using the same logic as graph building
node_attrs = {
"lang": language,
"type": entity_type,
"file": file_path,
"name": entity_name
}
node_id = _build_node_id(node_attrs)
# Format 1: Standard node ID
if entity_name and file_path and language and entity_type:
node_candidates.append(f"{language}::{entity_type}::{file_path}::{entity_name}")
if node_id and node_id in graph.graph:
context['node_id'] = node_id
# Format 2: Method with class name
if entity_type in ['method', 'function'] and meta.get('class'):
class_name = meta.get('class')
node_candidates.append(f"{language}::{entity_type}::{file_path}::{class_name}.{entity_name}")
# Format 3: Svelte component
if entity_type == 'component' and language == 'svelte':
node_candidates.append(f"svelte::component::{file_path}::{entity_name}")
# Try to find the node using graph's enhanced search
target_node_id = None
for candidate in node_candidates:
if candidate in graph.graph.nodes:
target_node_id = candidate
break
# If still not found, try attribute-based search
if not target_node_id and entity_name and file_path:
matches = list(graph.find_nodes_by_attributes(
name=entity_name,
file=file_path,
type=entity_type if entity_type != 'code' else None
))
if matches:
target_node_id = matches[0][0] # Take first match
if not target_node_id:
return context
# Use the enhanced graph methods to get relationships
cross_file_out, cross_file_in = graph.get_cross_file_relationships(target_node_id, file_path)
# Get comprehensive relationships for graph queries
cross_file_out, cross_file_in = graph.get_cross_file_relationships(node_id, file_path)
# Format for graph queries: "node_id:relationship_type"
if cross_file_out:
context['cross_file'] = cross_file_out
if cross_file_in:
context['used_by'] = cross_file_in
context['cross_file'] = []
for rel in cross_file_out[:8]: # Limit to most important
# Extract target node info for graph queries
parts = rel.split('@')
relationship = parts[0]
target_file = parts[1] if len(parts) > 1 else ""
context['cross_file'].append(f"{relationship}->{target_file}")
# Get same-file relationships
if cross_file_in:
context['used_by'] = []
for rel in cross_file_in[:6]: # Limit to most important
parts = rel.split('@')
relationship = parts[0]
source_file = parts[1] if len(parts) > 1 else ""
context['used_by'].append(f"{relationship}<-{source_file}")
# Same-file relationships for local graph exploration
same_file_rels = []
for neighbor_id in graph.graph.successors(target_node_id):
for neighbor_id in graph.graph.successors(node_id):
if neighbor_id in graph.graph.nodes:
neighbor_file = graph.graph.nodes[neighbor_id].get('file', '')
if neighbor_file == file_path: # Same file
edge_data = graph.graph.edges[target_node_id, neighbor_id]
if neighbor_file == file_path:
edge_data = graph.graph.edges[node_id, neighbor_id]
rel_type = edge_data.get('type', 'related')
neighbor_name = graph.graph.nodes[neighbor_id].get('name', '')
neighbor_type = graph.graph.nodes[neighbor_id].get('type', '')
same_file_rels.append(f"{rel_type}:{neighbor_type}:{neighbor_name}")
if same_file_rels:
context['same_file'] = same_file_rels
# Get meaningful file entities (filter out noise)
meaningful_types = {'function', 'method', 'class', 'struct', 'interface', 'enum', 'module', 'component', 'trait', 'impl'}
file_entities = []
file_node_id = f"file::{file_path}"
if file_node_id in graph.graph.nodes:
for neighbor_id, neighbor_data in graph.neighbors(file_node_id):
neighbor_type = neighbor_data.get('type', '')
neighbor_name = neighbor_data.get('name', '')
# Filter criteria
if (neighbor_type in meaningful_types and
neighbor_name and
len(neighbor_name) > 1 and # No single letters
neighbor_name != entity_name and
not neighbor_name.startswith(('c:', 'b:', 'p:', 'r:', 't:', 'v:'))): # No import aliases
file_entities.append(f"{neighbor_type}:{neighbor_name}")
if file_entities:
context['file_entities'] = file_entities
context['same_file'] = same_file_rels[:10]
return context
def _build_node_id(attrs: dict) -> str:
"""Build node ID using the same logic as graph building."""
lang = attrs.get("lang", "unknown")
node_type = attrs.get("type", "Symbol")
name = attrs.get("name", "unknown")
fpath = attrs.get("file", "")
# Handle special cases
if node_type == "component" and lang == "svelte":
return f"svelte::component::{fpath}::{name}"
elif node_type in ["method", "function"] and attrs.get("class_name"):
return f"{lang}::{node_type}::{fpath}::{attrs['class_name']}.{name}"
else:
return f"{lang}::{node_type}::{fpath}::{name}"
def _format_enhanced_results(results: List[Dict], query: str, result_type: str) -> str:
"""Comprehensive format with ALL information preserved - optimized for LLM analysis."""
"""Format results in TOON (Token-Oriented Object Notation) for LLM consumption."""
if not results:
return f"# {result_type.title()}: {query}\nNo results found.\n"
lines = [
f"# {result_type.title()}: {query}",
f"results_count={len(results)}"
f"results[{len(results)}]{{file,line,type,name,language,score,content,graph_context}}:"
]
for i, result in enumerate(results, 1):
# Extract ALL metadata
for result in results:
# Extract all fields
file_path = result.get('file', '')
line_num = result.get('line', '')
entity_type = result.get('type', 'code')
entity_name = result.get('name', '')
language = result.get('language', '')
score = result.get('score', 0.0)
content = result.get('content', '') # NO TRUNCATION - let LLM handle it
docstring = result.get('docstring', '')
content = result.get('content', '')
graph_context = result.get('graph_context', {})
# Build comprehensive result block
lines.append(f"\n--- RESULT {i} ---")
lines.append(f"file:{file_path}:{line_num}")
lines.append(f"entity:{entity_type}:{entity_name}")
lines.append(f"language:{language}")
lines.append(f"score:{score:.3f}")
# Build compact graph context string
graph_parts = []
if graph_context.get('node_id'):
graph_parts.append(f"node:{graph_context['node_id']}")
# Content (FULL, no truncation)
if content:
lines.append(f"content: {content}")
# Docstring if available
if docstring:
lines.append(f"doc: {docstring}")
# Graph context - PRESERVE EVERYTHING
if graph_context:
lines.append("graph_context:")
# Cross-file dependencies (highest value)
if graph_context.get('cross_file'):
lines.append(f" cross_file: {' | '.join(graph_context['cross_file'])}")
graph_parts.append(f"xfile:{'|'.join(graph_context['cross_file'][:4])}")
# Reverse dependencies
if graph_context.get('used_by'):
lines.append(f" used_by: {' | '.join(graph_context['used_by'])}")
graph_parts.append(f"used:{'|'.join(graph_context['used_by'][:3])}")
# Same-file relationships
if graph_context.get('same_file'):
lines.append(f" same_file_rels: {' | '.join(graph_context['same_file'])}")
graph_parts.append(f"same:{'|'.join(graph_context['same_file'][:5])}")
# All relationships (comprehensive)
if graph_context.get('all_rels'):
lines.append(f" all_relationships: {' | '.join(graph_context['all_rels'][:15])}") # Reasonable limit
graph_str = ";".join(graph_parts)
# File contents
if graph_context.get('file_contents'):
lines.append(f" file_entities: {' | '.join(graph_context['file_contents'])}")
# Build TOON row
row = [
file_path,
str(line_num),
entity_type,
entity_name,
language,
f"{score:.2f}",
content, # No truncation - let LLM handle it
graph_str
]
# Escape fields according to TOON spec
escaped_row = []
for field in row:
field_str = str(field)
if any(char in field_str for char in [',', '"', '\n', '\r']):
escaped = field_str.replace('"', '\\"')
escaped_row.append(f'"{escaped}"')
else:
escaped_row.append(field_str)
lines.append(" " + ",".join(escaped_row))
return "\n".join(lines)
def _extract_clean_content(chunk_text: str) -> str:
"""Extract clean content WITHOUT truncation - preserve full context."""
lines = chunk_text.split('\n')