Simplify generate(string) to always delegate to generate(vector)

generate(string) is now a pure wrapper — empty string passes an
empty vector, non-empty wraps as MultimodalInput. The "decode from
prior prefill" logic moves to generate(vector) when inputs is empty,
giving both overloads consistent semantics.

This PR was authored with the assistance of Claude.

Author: kirklandsign

extension/llm/runner/multimodal_runner.cpp

@@ -221,52 +221,18 @@ Error MultimodalRunner::generate(
     const GenerationConfig& config,
     std::function<void(const std::string&)> token_callback,
     std::function<void(const Stats&)> stats_callback) {
+  std::vector<MultimodalInput> inputs;
   if (!prompt.empty()) {
-    std::vector<MultimodalInput> inputs;
     inputs.emplace_back(MultimodalInput(prompt));
-    return generate(inputs, config, token_callback, stats_callback);
   }
-
-  // Empty prompt: consume prefill_next_token_ and go straight to decode
-  ET_CHECK_OR_RETURN_ERROR(
-      prefill_next_token_.has_value(),
-      InvalidState,
-      "Empty prompt requires a prior prefill() call");
-
-  if (!is_loaded()) {
-    ET_CHECK_OK_OR_RETURN_ERROR(load());
-  }
-
-  // Wrap the token_callback with print function
-  std::function<void(const std::string&)> wrapped_callback =
-      [token_callback, config](const std::string& piece) {
-        if (!config.warming) {
-          safe_printf(piece.c_str());
-          fflush(stdout);
-        }
-        if (token_callback) {
-          token_callback(piece);
-        }
-      };
-
-  stats_->inference_start_ms = time_in_ms();
-
-  uint64_t cur_token = prefill_next_token_.value();
-  prefill_next_token_.reset();
-
-  return decode_from_token(cur_token, config, wrapped_callback, stats_callback);
+  return generate(inputs, config, token_callback, stats_callback);
 }
 
 Error MultimodalRunner::generate(
     const std::vector<MultimodalInput>& inputs,
     const GenerationConfig& config,
     std::function<void(const std::string&)> token_callback,
     std::function<void(const Stats&)> stats_callback) {
-  if (inputs.empty()) {
-    ET_LOG(Error, "MultimodalInput vector cannot be empty");
-    return Error::InvalidArgument;
-  }
-
   if (!is_loaded()) {
     ET_CHECK_OK_OR_RETURN_ERROR(load());
   }
@@ -295,16 +261,27 @@ Error MultimodalRunner::generate(
   // Reset internal state and start inference
   stats_->inference_start_ms = time_in_ms();
 
-  // Echo the last text input if enabled
-  if (config.echo && inputs.back().is_text()) {
-    wrapped_callback(inputs.back().get_text());
-  }
+  uint64_t cur_token;
+  if (!inputs.empty()) {
+    // Echo the last text input if enabled
+    if (config.echo && inputs.back().is_text()) {
+      wrapped_callback(inputs.back().get_text());
+    }
 
-  // Prefill all inputs and get the first decode token
-  auto prefill_result = prefill(inputs, config.num_bos, config.num_eos);
-  ET_CHECK_OK_OR_RETURN_ERROR(prefill_result.error());
-  uint64_t cur_token = prefill_result.get();
-  prefill_next_token_.reset();
+    // Prefill all inputs and get the first decode token
+    auto prefill_result = prefill(inputs, config.num_bos, config.num_eos);
+    ET_CHECK_OK_OR_RETURN_ERROR(prefill_result.error());
+    cur_token = prefill_result.get();
+    prefill_next_token_.reset();
+  } else {
+    // Empty inputs: consume token from a prior prefill() call
+    ET_CHECK_OR_RETURN_ERROR(
+        prefill_next_token_.has_value(),
+        InvalidState,
+        "Empty inputs requires a prior prefill() call");
+    cur_token = prefill_next_token_.value();
+    prefill_next_token_.reset();
+  }
 
   return decode_from_token(cur_token, config, wrapped_callback, stats_callback);
 }