fix: rewind text if does not match pattern

Author: sangjanai

cpp/tensorrt_llm/cortex.tensorrt-llm/src/tensorrt-llm_engine.cc

@@ -79,30 +79,61 @@ void RemoveId(std::vector<int>& vec, int id) {
   vec.erase(std::remove(vec.begin(), vec.end(), id), vec.end());
 }
 
-bool HandleMatch(std::string const& rew_text, std::shared_ptr<InferenceState> infer_state, bool is_openhermes) {
+bool HandleMatch(std::string const& rew_text, 
+                std::shared_ptr<InferenceState> infer_state, 
+                std::function<void(Json::Value&&, Json::Value&&)> cb, 
+                bool is_openhermes) {
   if (infer_state->IsComplete(is_openhermes)) {
+    infer_state->rewind_strs.clear();
     return false;
   }
   if (infer_state->stop_word_match_len == 0) {
     if ((is_openhermes && rew_text.find('<') != std::string::npos) || 
         (!is_openhermes && rew_text.find('[') != std::string::npos)) {
       infer_state->stop_word_match_len++; // Move to next state
-      infer_state->prev_text = rew_text;
+      infer_state->rewind_strs.push_back(rew_text);
       return true;
     }
-  }
-  else if (rew_text == infer_state->GetSequence(is_openhermes, infer_state->stop_word_match_len)) {
+  } else if (rew_text == infer_state->GetSequence(is_openhermes, infer_state->stop_word_match_len)) {
     infer_state->stop_word_match_len++; // Move to next state
-    infer_state->prev_text = rew_text;
+    infer_state->rewind_strs.push_back(rew_text);
     return true;
-  }
-  else if (infer_state->stop_word_match_len > 0 && rew_text == infer_state->GetSequence(is_openhermes, 0u)) {
+  } else if (infer_state->stop_word_match_len > 0 && rew_text == infer_state->GetSequence(is_openhermes, 0u)) {
     infer_state->stop_word_match_len = 1; // Restart from first match if sequence breaks but matches start
-    infer_state->prev_text = rew_text;
+    // response cache data
+    for(auto const& s: infer_state->rewind_strs) {
+      // std::cout << s;
+      const std::string text_to_stream
+            = "data: " + tensorrtllm_utils::CreateReturnJson(tensorrtllm_utils::GenerateRandomString(20), "_", s) + "\n\n";
+        Json::Value resp_data;
+        resp_data["data"] = text_to_stream;
+        Json::Value status;
+        status["is_done"] = false;
+        status["has_error"] = false;
+        status["is_stream"] = true;
+        status["status_code"] = k200OK;
+        cb(std::move(status), std::move(resp_data));
+    }
+    infer_state->rewind_strs.clear();
+    infer_state->rewind_strs.push_back(rew_text);
     return true;
-  }
-  else {
+  } else {
     infer_state->Reset();
+    // response cache data
+    for(auto const& s: infer_state->rewind_strs) {
+      // std::cout << s;
+      const std::string text_to_stream
+            = "data: " + tensorrtllm_utils::CreateReturnJson(tensorrtllm_utils::GenerateRandomString(20), "_", s) + "\n\n";
+        Json::Value resp_data;
+        resp_data["data"] = text_to_stream;
+        Json::Value status;
+        status["is_done"] = false;
+        status["has_error"] = false;
+        status["is_stream"] = true;
+        status["status_code"] = k200OK;
+        cb(std::move(status), std::move(resp_data));
+    }
+    infer_state->rewind_strs.clear();
     return false; // Reset to start if sequence breaks
   }
   return false;
@@ -313,7 +344,7 @@ void TensorrtllmEngine::HandleChatCompletion(std::shared_ptr<Json::Value> json_b
         std::string rew_text = infer_state->texts_to_stream.front();
         // res_str += rew_text;
         infer_state->texts_to_stream.pop();
-        if (HandleMatch(rew_text, infer_state, is_openhermes_) && rew_text != "[DONE]") {
+        if (HandleMatch(rew_text, infer_state, cb, is_openhermes_) && rew_text != "[DONE]") {
             continue;
         };
 
@@ -338,7 +369,7 @@ void TensorrtllmEngine::HandleChatCompletion(std::shared_ptr<Json::Value> json_b
             = "data: " + tensorrtllm_utils::CreateReturnJson(tensorrtllm_utils::GenerateRandomString(20), model_id_, rew_text) + "\n\n";
 
         lock.unlock(); // Unlock as soon as possible
-        infer_state->prev_text = rew_text;
+        // std::cout << rew_text;
 
         Json::Value resp_data;
         resp_data["data"] = text_to_stream;

cpp/tensorrt_llm/cortex.tensorrt-llm/src/tensorrt-llm_engine.h

@@ -68,18 +68,17 @@ class Tokenizer {
 
 struct InferenceState {
   int prev_pos{0};
-  std::string prev_text;
   bool is_finished;
   std::queue<std::string> texts_to_stream;
   std::mutex queue_mutex; // Mutex to protect access to textsToStream
   size_t stop_word_match_len = 0;
   std::vector<std::string> sequence_openhermes = {"<", "|", "im", "_", "end", "|", ">"};
   std::vector<std::string> sequence_mistral = {"[", "INST", "]"};
   int token_gen_count = 0;
+  std::vector<std::string> rewind_strs;
 
   void Reset() {
-      stop_word_match_len = 0;
-      prev_text = "";
+    stop_word_match_len = 0;
   }
 
   bool IsComplete(bool is_openhermes) const {