fix: pass correct type to chat handlers for chat completion logprobs

Author: abetlen

llama_cpp/llama.py

@@ -1664,7 +1664,8 @@ def create_chat_completion(
             top_k=top_k,
             min_p=min_p,
             typical_p=typical_p,
-            logprobs=top_logprobs if logprobs else None,
+            logprobs=logprobs,
+            top_logprobs=top_logprobs,
             stream=stream,
             stop=stop,
             seed=seed,

llama_cpp/llama_chat_format.py

@@ -77,6 +77,8 @@ def __call__(
         mirostat_eta: float = 0.1,
         logits_processor: Optional[llama.LogitsProcessorList] = None,
         grammar: Optional[llama.LlamaGrammar] = None,
+        logprobs: Optional[bool] = None,
+        top_logprobs: Optional[int] = None,
         **kwargs,  # type: ignore
     ) -> Union[
         llama_types.CreateChatCompletionResponse,
@@ -338,7 +340,7 @@ def _convert_completion_to_chat_function(
                             }
                         ],
                     },
-                    "logprobs": None,
+                    "logprobs": completion["choices"][0]["logprobs"],
                     "finish_reason": "tool_calls",
                 }
             ],
@@ -391,7 +393,7 @@ def _stream_response_to_function_stream(
                             {
                                 "index": 0,
                                 "finish_reason": None,
-                                "logprobs": None,
+                                "logprobs": chunk["choices"][0]["logprobs"],
                                 "delta": {
                                     "role": None,
                                     "content": None,
@@ -426,7 +428,7 @@ def _stream_response_to_function_stream(
                         {
                             "index": 0,
                             "finish_reason": None,
-                            "logprobs": None,
+                            "logprobs": chunk["choices"][0]["logprobs"],
                             "delta": {
                                 "role": None,
                                 "content": None,
@@ -491,7 +493,6 @@ def chat_completion_handler(
         temperature: float = 0.2,
         top_p: float = 0.95,
         top_k: int = 40,
-        logprobs: int = 0,
         min_p: float = 0.05,
         typical_p: float = 1.0,
         stream: bool = False,
@@ -512,6 +513,8 @@ def chat_completion_handler(
         logits_processor: Optional[llama.LogitsProcessorList] = None,
         grammar: Optional[llama.LlamaGrammar] = None,
         logit_bias: Optional[Dict[str, float]] = None,
+        logprobs: Optional[bool] = None,
+        top_logprobs: Optional[int] = None,
         **kwargs,  # type: ignore
     ) -> Union[
         llama_types.CreateChatCompletionResponse,
@@ -581,7 +584,7 @@ def chat_completion_handler(
             top_k=top_k,
             min_p=min_p,
             typical_p=typical_p,
-            logprobs=logprobs,
+            logprobs=top_logprobs if logprobs else None,
             stream=stream,
             stop=stop,
             seed=seed,
@@ -1628,7 +1631,7 @@ def message_to_str(msg: llama_types.ChatCompletionRequestMessage):
                         }
                     ],
                 },
-                "logprobs": None,
+                "logprobs": completion["choices"][0]["logprobs"],
                 "finish_reason": "tool_calls",
             }
         ],
@@ -2085,7 +2088,7 @@ def create_completion(stop):
         choices=[
             {
                 "index": 0,
-                "logprobs": None,
+                "logprobs": completion["choices"][0]["logprobs"],
                 "message": {
                     "role": "assistant",
                     "content": None if content == "" else content,
@@ -2311,11 +2314,14 @@ def chatml_function_calling(
     model: Optional[str] = None,
     logits_processor: Optional[llama.LogitsProcessorList] = None,
     grammar: Optional[llama.LlamaGrammar] = None,
+    logprobs: Optional[bool] = None,
+    top_logprobs: Optional[int] = None,
     **kwargs,  # type: ignore
 ) -> Union[
     llama_types.CreateChatCompletionResponse,
     Iterator[llama_types.CreateChatCompletionStreamResponse],
 ]:
+    print(logprobs)
     function_calling_template = (
         "{% for message in messages %}"
         "<|im_start|>{{ message.role }}\n"
@@ -2437,6 +2443,7 @@ def chatml_function_calling(
                 model=model,
                 logits_processor=logits_processor,
                 grammar=grammar,
+                logprobs=top_logprobs if logprobs else None,
             ),
             stream=stream,
         )
@@ -2549,6 +2556,7 @@ def chatml_function_calling(
                 typical_p=typical_p,
                 stream=stream,
                 stop=["<|im_end|>"],
+                logprobs=top_logprobs if logprobs else None,
                 max_tokens=None,
                 presence_penalty=presence_penalty,
                 frequency_penalty=frequency_penalty,
@@ -2660,7 +2668,7 @@ def chatml_function_calling(
                 {
                     "finish_reason": "tool_calls",
                     "index": 0,
-                    "logprobs": None,
+                    "logprobs": completion["choices"][0]["logprobs"],
                     "message": {
                         "role": "assistant",
                         "content": None,