refactor: comprehensive audit — fix bugs, harden security, deduplicate providers, add CI/Docker

Phase 1: Fix compilation (config_path Option<PathBuf>, streaming test, stale test cleanup)
Phase 2: Fix critical bugs (remove block_on deadlocks in 4 providers, fix broken SQL query builder)
Phase 3: Security hardening (session manager, real auth, token masking, Gemini key to header, password policy)
Phase 4: Implement stubs (real provider test, /proc health metrics, client/provider/backup endpoints, has_images)
Phase 5: Code quality (shared provider helpers, explicit re-exports, all Clippy warnings fixed, unwrap removal, 6 unused deps removed, dashboard split into 7 sub-modules)
Phase 6: Infrastructure (GitHub Actions CI, multi-stage Dockerfile, rustfmt.toml, clippy.toml, script fixes)

src/utils/tokens.rs

@@ -1,27 +1,26 @@
-use tiktoken_rs::get_bpe_from_model;
 use crate::models::UnifiedRequest;
+use tiktoken_rs::get_bpe_from_model;
 
 /// Count tokens for a given model and text
 pub fn count_tokens(model: &str, text: &str) -> u32 {
     // If we can't get the bpe for the model, fallback to a safe default (cl100k_base for GPT-4/o1)
-    let bpe = get_bpe_from_model(model).unwrap_or_else(|_| {
-        tiktoken_rs::cl100k_base().expect("Failed to get cl100k_base encoding")
-    });
-    
+    let bpe = get_bpe_from_model(model)
+        .unwrap_or_else(|_| tiktoken_rs::cl100k_base().expect("Failed to get cl100k_base encoding"));
+
     bpe.encode_with_special_tokens(text).len() as u32
 }
 
 /// Estimate tokens for a unified request
 pub fn estimate_request_tokens(model: &str, request: &UnifiedRequest) -> u32 {
     let mut total_tokens = 0;
-    
+
     // Base tokens per message for OpenAI (approximate)
     let tokens_per_message = 3;
     let _tokens_per_name = 1;
-    
+
     for msg in &request.messages {
         total_tokens += tokens_per_message;
-        
+
         for part in &msg.content {
             match part {
                 crate::models::ContentPart::Text { text } => {
@@ -34,14 +33,14 @@ pub fn estimate_request_tokens(model: &str, request: &UnifiedRequest) -> u32 {
                 }
             }
         }
-        
+
         // Add name tokens if we had names (we don't in UnifiedMessage yet)
         // total_tokens += tokens_per_name;
     }
-    
+
     // Add 3 tokens for the assistant reply header
     total_tokens += 3;
-    
+
     total_tokens
 }