refactor: update code to use codegraph binary consistently and improve variable naming

Author: jruokola

CLAUDE.md

@@ -92,34 +92,28 @@ cargo doc --workspace --no-deps --open
 
 ### Running the MCP Server
 
-**Note:** The MCP server has two binaries:
-- `codegraph-official` (recommended): Uses official rmcp SDK, supports both STDIO and HTTP transports
-- `codegraph` (legacy): Original implementation, STDIO only
-
-All examples below use `codegraph-official` for consistency.
-
 ```bash
 # Build the MCP server binary (with AutoAgents experimental feature)
-cargo build --release -p codegraph-mcp --bin codegraph-official --features "ai-enhanced,autoagents-experimental,faiss,ollama"
+cargo build --release -p codegraph-mcp --bin codegraph --features "ai-enhanced,autoagents-experimental,faiss,ollama"
 
 # Or use Makefile target
 make build-mcp-autoagents
 
 # Or build without AutoAgents (uses legacy orchestrator)
-cargo build --release -p codegraph-mcp --bin codegraph-official --features "ai-enhanced,faiss,ollama"
+cargo build --release -p codegraph-mcp --bin codegraph --features "ai-enhanced,faiss,ollama"
 
 # Start MCP server (stdio mode - RECOMMENDED)
-./target/release/codegraph-official serve --transport stdio
+./target/release/codegraph start stdio
 
 # Check agentic tool configuration
-./target/release/codegraph-official config agent-status
+./target/release/codegraph config agent-status
 ```
 
 **HTTP Transport (Experimental):**
 - HTTP transport with SSE streaming is now available
 - Requires `server-http` feature flag
 - Build: `cargo build --release --features "ai-enhanced,autoagents-experimental,faiss,ollama,server-http"`
-- Start: `./target/release/codegraph-official serve --transport http --port 3000`
+- Start: `./target/release/codegraph start http --port 3000`
 - Endpoints:
   - `POST /mcp` - Send MCP requests (returns SSE stream)
   - `GET /sse` - Reconnect to existing session
@@ -134,10 +128,10 @@ cargo build --release -p codegraph-mcp --bin codegraph-official --features "ai-e
 cargo build --release -p codegraph-mcp --features "ai-enhanced,autoagents-experimental,faiss,ollama,server-http"
 
 # Start HTTP server (default: http://127.0.0.1:3000)
-./target/release/codegraph-official serve --transport http
+./target/release/codegraph start http
 
 # Custom host and port
-./target/release/codegraph-official serve --transport http --host 0.0.0.0 --port 8080
+./target/release/codegraph start http --host 0.0.0.0 --port 8080
 
 # Test with curl
 curl http://127.0.0.1:3000/health  # Should return "OK"
@@ -483,9 +477,9 @@ sudo apt-get install libfaiss-dev  # Ubuntu
 - Verify SurrealDB connection is working
 
 **MCP tests fail**
-- Check binary exists: `./target/release/codegraph-official` or `./target/debug/codegraph-official`
-- Try building with AutoAgents: `cargo build -p codegraph-mcp --bin codegraph-official --features "ai-enhanced,autoagents-experimental,faiss,ollama"`
-- Or without AutoAgents (legacy): `cargo build -p codegraph-mcp --bin codegraph-official --features "ai-enhanced,faiss,ollama"`
+- Check binary exists: `./target/release/codegraph` or `./target/debug/codegraph`
+- Try building with AutoAgents: `cargo build -p codegraph-mcp --bin codegraph --features "ai-enhanced,autoagents-experimental,faiss,ollama"`
+- Or without AutoAgents (legacy): `cargo build -p codegraph-mcp --bin codegraph --features "ai-enhanced,faiss,ollama"`
 
 ## Additional Resources
 

Cargo.lock

@@ -912,11 +912,11 @@ async fn handle_start(
                 .map_err(|e| anyhow::anyhow!("Server error: {}", e))?;
         }
         TransportType::Http {
-            host: _host,
-            port: _port,
-            tls: _tls,
-            cert: _cert,
-            key: _key,
+            host,
+            port,
+            tls,
+            cert,
+            key,
             cors: _,
         } => {
             #[cfg(not(feature = "server-http"))]

crates/codegraph-mcp/src/bin/codegraph.rs

@@ -44,7 +44,7 @@ impl GpuMemoryAllocation {
 
 #[derive(Debug)]
 pub struct GpuVectorData {
-    allocation: GpuMemoryAllocation,
+    _allocation: GpuMemoryAllocation,
     vector_count: usize,
     dimension: usize,
     uploaded: bool,
@@ -53,7 +53,7 @@ pub struct GpuVectorData {
 impl GpuVectorData {
     pub fn new(allocation: GpuMemoryAllocation, vector_count: usize, dimension: usize) -> Self {
         Self {
-            allocation,
+            _allocation: allocation,
             vector_count,
             dimension,
             uploaded: false,

crates/codegraph-vector/src/gpu.rs

@@ -50,7 +50,7 @@ struct MemoryBlock {
     ptr: *mut u8,
     size: usize,
     used: bool,
-    allocation_id: usize,
+    _allocation_id: usize,
 }
 
 unsafe impl Send for MemoryBlock {}
@@ -72,7 +72,7 @@ impl MemoryBlock {
             ptr,
             size,
             used: true,
-            allocation_id,
+            _allocation_id: allocation_id,
         })
     }
 

crates/codegraph-vector/src/memory.rs

@@ -188,14 +188,6 @@ impl ContextRetriever {
         Ok(results)
     }
 
-    #[cfg(not(feature = "faiss"))]
-    async fn semantic_similarity_search(
-        &self,
-        _query_embedding: &[f32],
-    ) -> Result<Vec<RetrievalResult>> {
-        Ok(Vec::new())
-    }
-
     async fn keyword_matching_search(&self, keywords: &[String]) -> Result<Vec<RetrievalResult>> {
         let mut results = Vec::new();
 
@@ -397,6 +389,7 @@ impl ContextRetriever {
         }
     }
 
+    #[cfg(feature = "faiss")]
     async fn get_node(&self, node_id: NodeId) -> Result<Option<CodeNode>> {
         Ok(self.node_cache.get(&node_id).cloned())
     }
@@ -464,14 +457,6 @@ fn cosine_similarity(a: &[f32], b: &[f32]) -> f32 {
     }
 }
 
-fn simple_hash(text: &str) -> u32 {
-    let mut hash = 5381u32;
-    for byte in text.bytes() {
-        hash = hash.wrapping_mul(33).wrapping_add(byte as u32);
-    }
-    hash
-}
-
 #[cfg(test)]
 mod tests {
     use super::*;

crates/codegraph-vector/src/rag/context_retriever.rs

@@ -2,6 +2,7 @@ use crate::rag::{
     ContextRetriever, GeneratedResponse, GenerationConfig, ProcessedQuery, QueryProcessor,
     RankedResult, RankingConfig, ResponseGenerator, ResultRanker, RetrievalConfig,
 };
+#[cfg(feature = "faiss")]
 use crate::EmbeddingGenerator;
 #[cfg(feature = "faiss")]
 use crate::{FaissVectorStore, SemanticSearch};
@@ -71,6 +72,7 @@ pub struct RAGSystem {
     response_generator: ResponseGenerator,
     #[cfg(feature = "faiss")]
     semantic_search: Option<Arc<SemanticSearch>>,
+    #[cfg(feature = "faiss")]
     embedding_generator: Arc<EmbeddingGenerator>,
     query_cache: Arc<RwLock<HashMap<String, QueryResult>>>,
     #[cfg(feature = "cache")]
@@ -99,6 +101,7 @@ impl RAGSystem {
             config.ranking.clone(),
         )));
         let response_generator = ResponseGenerator::with_config(config.generation.clone());
+        #[cfg(feature = "faiss")]
         let embedding_generator = Arc::new(EmbeddingGenerator::default());
 
         #[cfg(feature = "cache")]
@@ -126,6 +129,7 @@ impl RAGSystem {
             response_generator,
             #[cfg(feature = "faiss")]
             semantic_search: None,
+            #[cfg(feature = "faiss")]
             embedding_generator,
             query_cache: Arc::new(RwLock::new(HashMap::new())),
             #[cfg(feature = "cache")]

crates/codegraph-vector/src/rag/rag_system.rs

@@ -62,7 +62,6 @@ pub struct ResponseGenerator {
 struct ResponseTemplate {
     pattern: String,
     template: String,
-    confidence_boost: f32,
 }
 
 impl ResponseGenerator {
@@ -687,22 +686,18 @@ impl ResponseGenerator {
             ResponseTemplate {
                 pattern: "how".to_string(),
                 template: "To accomplish this, you can use {node_name} which is a {node_type}:\n\n{content}".to_string(),
-                confidence_boost: 0.2,
             },
             ResponseTemplate {
                 pattern: "what".to_string(),
                 template: "{node_name} is a {node_type} that provides the following functionality:\n\n{content}".to_string(),
-                confidence_boost: 0.1,
             },
             ResponseTemplate {
                 pattern: "find".to_string(),
                 template: "I found {node_name} ({node_type}) which matches your criteria:\n\n{content}".to_string(),
-                confidence_boost: 0.1,
             },
             ResponseTemplate {
                 pattern: "error".to_string(),
                 template: "For error handling, consider using {node_name}:\n\n{content}".to_string(),
-                confidence_boost: 0.3,
             },
         ]
     }

crates/codegraph-vector/src/rag/response_generator.rs

@@ -524,6 +524,7 @@ impl SemanticSearch {
     }
 }
 
+#[cfg(feature = "faiss")]
 fn cosine_similarity(a: &[f32], b: &[f32]) -> f32 {
     if a.len() != b.len() {
         return 0.0;
@@ -540,6 +541,7 @@ fn cosine_similarity(a: &[f32], b: &[f32]) -> f32 {
     }
 }
 
+#[cfg(feature = "faiss")]
 fn simple_hash(text: &str) -> u32 {
     let mut hash = 5381u32;
     for byte in text.bytes() {
@@ -548,6 +550,7 @@ fn simple_hash(text: &str) -> u32 {
     hash
 }
 
+#[cfg(feature = "faiss")]
 fn build_filter_signature(filters: Option<&SearchFilters>) -> String {
     if let Some(f) = filters {
         let mut langs: Vec<String> = f
@@ -579,6 +582,7 @@ fn build_filter_signature(filters: Option<&SearchFilters>) -> String {
     }
 }
 
+#[cfg(feature = "faiss")]
 fn normalize_scores(results: &mut [SearchResult]) {
     if results.is_empty() {
         return;