Model: Use true async jobs and add logprobs

The new async dynamic job allows for native async support without the
need of threading. Also add logprobs and metrics back to responses.

Signed-off-by: kingbri <bdashore3@proton.me>

common/gen_logging.py

@@ -70,29 +70,38 @@ def log_response(response: str):
 
 
 def log_metrics(
+    queue_time: float,
+    prompt_tokens: int,
+    prompt_time: float,
     generated_tokens: int,
-    elapsed_time: float,
+    generate_time: float,
     context_len: Optional[int],
     max_seq_len: int,
 ):
     initial_response = (
         f"Metrics: {generated_tokens} tokens generated in "
-        f"{round(elapsed_time, 2)} seconds"
+        f"{round(queue_time + prompt_time + generate_time, 2)} seconds"
     )
     itemization = []
     extra_parts = []
 
-    # Add tokens per second
-    tokens_per_second = (
-        "Indeterminate"
-        if elapsed_time == 0
-        else round(generated_tokens / elapsed_time, 2)
+    itemization.append(f"Queue: {round(queue_time, 2)} s")
+
+    prompt_ts = (
+        "Indeterminate" if prompt_time == 0 else round(prompt_tokens / prompt_time, 2)
     )
-    itemization.append(f"{tokens_per_second} T/s")
+    itemization.append(f"Process: {prompt_ts} T/s")
+
+    generate_ts = (
+        "Indeterminate"
+        if generate_time == 0
+        else round(generated_tokens / generate_time, 2)
+    )
+    itemization.append(f"Generate: {generate_ts} T/s")
 
     # Add context (original token count)
     if context_len:
-        itemization.append(f"context {context_len} tokens")
+        itemization.append(f"Context: {context_len} tokens")
 
         if context_len > max_seq_len:
             extra_parts.append("<-- Not accurate (truncated)")