add logprobs support for exl3

backends/exllamav3/model.py

@@ -2,6 +2,7 @@ import asyncio
 import gc
 import pathlib
 import re
+from itertools import zip_longest
 from typing import (
     Any,
     AsyncIterator,
@@ -608,6 +609,22 @@ class ExllamaV3Container(BaseModelContainer):
             "unk_token": self.tokenizer.unk_token,
         }
 
+    def get_logprobs(self, token_ids: torch.Tensor, token_probs: torch.Tensor):
+        top_tokens = [
+            self.tokenizer.get_id_to_piece_list(True)[index]
+            for index in token_ids.flatten().tolist()
+        ]
+
+        top_values = torch.log(token_probs).flatten().tolist()
+
+        # Cannot return -inf in JSON
+        cleaned_values = [
+            -1000 if value == float("-inf") else value for value in top_values
+        ]
+
+        return dict(zip_longest(top_tokens, cleaned_values))
+
+
     async def generate(
         self,
         request_id: str,
@@ -730,6 +747,26 @@ class ExllamaV3Container(BaseModelContainer):
             # Clean up and remove the job from active IDs
             del self.active_job_ids[request_id]
 
+    def handle_logprobs(self, result: dict, generation: dict):
+        top_tokens = unwrap(
+            result.get("top_k_tokens"),
+            torch.empty((1, 0, 1), dtype=torch.long),
+        )
+
+        top_probs = unwrap(
+            result.get("top_k_probs"),
+            torch.empty((1, 0, 1), dtype=torch.float),
+        )
+
+        if top_tokens.numel() > 0 and top_probs.numel() > 0:
+            logprobs = self.get_logprobs(top_tokens, top_probs)
+            generation["logprobs"] = logprobs
+
+            # The first logprob is the selected token prob
+            generation["token_probs"] = {
+                token: logprobs[token] for token in list(logprobs.keys())[:1]
+            }
+
     def handle_finish_chunk(self, result: dict, request_id: str, full_text: str):
         eos_reason = result.get("eos_reason")
 
@@ -915,6 +952,7 @@ class ExllamaV3Container(BaseModelContainer):
             stop_conditions=stop_conditions,
             banned_strings=params.banned_strings,
             embeddings=mm_embeddings_content,
+            return_top_tokens=params.logprobs,
         )
 
         generated_tokens = 0
@@ -948,6 +986,10 @@ class ExllamaV3Container(BaseModelContainer):
                         "generated_tokens": generated_tokens,
                         "offset": len(full_response),
                     }
+
+                    if params.logprobs > 0:
+                        self.handle_logprobs(result, generation)
+
                     yield generation
 
                 if result.get("eos"):