add support for precompiled binaries, used as a fallback

.gitignore

@@ -1,6 +1,5 @@
 *.o
 *.a
-*.so
 *.bin
 .DS_Store
 .build/
@@ -80,16 +79,17 @@ tests/test-quantize-perf
 tests/test-sampling
 tests/test-tokenizer-0
 
-koboldcpp_default.so
+/koboldcpp_default.so
-koboldcpp_failsafe.so
+/koboldcpp_failsafe.so
-koboldcpp_openblas.so
+/koboldcpp_openblas.so
-koboldcpp_noavx2.so
+/koboldcpp_noavx2.so
-koboldcpp_clblast.so
+/koboldcpp_clblast.so
-koboldcpp_default.dll
+/koboldcpp_cublas.so
-koboldcpp_failsafe.dll
+/koboldcpp_default.dll
-koboldcpp_openblas.dll
+/koboldcpp_failsafe.dll
-koboldcpp_noavx2.dll
+/koboldcpp_openblas.dll
-koboldcpp_clblast.dll
+/koboldcpp_noavx2.dll
-koboldcpp_cublas.dll
+/koboldcpp_clblast.dll
-cublas64_11.dll
+/koboldcpp_cublas.dll
-cublasLt64_11.dll
+/cublas64_11.dll
+/cublasLt64_11.dll

class.py

@@ -0,0 +1,104 @@
+## KoboldCpp based GGML Backend by Concedo
+## For use as a custom backend in KoboldAI United
+## Not intended for general use.
+
+from __future__ import annotations
+
+import time, json
+import torch
+import requests
+import numpy as np
+from typing import List, Optional, Union
+import os
+from . import koboldcpp
+
+import utils
+from logger import logger
+from modeling.inference_model import (
+    GenerationResult,
+    GenerationSettings,
+    InferenceModel,
+)
+
+model_backend_name = "koboldcpp" #specific instead of ggml
+model_backend_type = "ggml" #This should be a generic name in case multiple model backends are compatible (think Hugging Face Custom and Basic Hugging Face)
+
+kcpp_backend_loaded = False
+
+class KoboldCppException(Exception):
+    """To be used for errors on cpp side of KoboldCpp."""
+
+class KcppArgsObject:
+    def __init__(self, **kwargs):
+        self.__dict__.update(kwargs)
+
+class model_backend(InferenceModel):
+    def __init__(self) -> None:
+        super().__init__()
+
+    def is_valid(self, model_name, model_path, menu_path):
+        return "ggml" in model_name.lower()
+
+    def get_requested_parameters(self, model_name, model_path, menu_path, parameters = {}):
+        self.filename = model_name #model_path is null, name is path for some reason
+        self.model_name = "GGML_Model"
+        try:
+            from pathlib import Path
+            self.model_name = Path(model_name).name
+        except:
+            pass
+        requested_parameters = []
+        return requested_parameters
+
+    def set_input_parameters(self, parameters):
+        pass
+
+    def _load(self, save_model: bool, initial_load: bool) -> None:
+        global kcpp_backend_loaded
+        self.tokenizer = self._get_tokenizer("gpt2")
+        if not kcpp_backend_loaded:
+            kcppargs = KcppArgsObject(model=self.filename, model_param=self.filename,
+            port=5001, port_param=5001, host='', launch=False, lora=None, threads=5, blasthreads=5,
+            psutil_set_threads=False, highpriority=False, contextsize=2048,
+            blasbatchsize=512, ropeconfig=[0.0, 10000.0], stream=False, smartcontext=False,
+            unbantokens=False, bantokens=None, usemirostat=None, forceversion=0, nommap=False,
+            usemlock=False, noavx2=False, debugmode=0, skiplauncher=False, hordeconfig=None, noblas=False,
+            useclblast=None, usecublas=None, gpulayers=0, tensor_split=None)
+
+            koboldcpp.main(kcppargs,False) #initialize library without enabling Lite http server
+            kcpp_backend_loaded = True
+        pass
+
+    def _save_settings(self):
+        pass
+
+    def _raw_generate(
+        self,
+        prompt_tokens: Union[List[int], torch.Tensor],
+        max_new: int,
+        gen_settings: GenerationSettings,
+        single_line: bool = False,
+        batch_count: int = 1,
+        seed: Optional[int] = None,
+        **kwargs,
+    ) -> GenerationResult:
+
+        decoded_prompt = utils.decodenewlines(self.tokenizer.decode(prompt_tokens))
+
+        # Store context in memory to use it for comparison with generated content
+        utils.koboldai_vars.lastctx = decoded_prompt
+
+        genresult = koboldcpp.generate(decoded_prompt,max_new,utils.koboldai_vars.max_length,
+        gen_settings.temp,int(gen_settings.top_k),gen_settings.top_a,gen_settings.top_p,
+        gen_settings.typical,gen_settings.tfs,gen_settings.rep_pen,gen_settings.rep_pen_range)
+
+        outputs = [genresult]
+        return GenerationResult(
+            model=self,
+            out_batches=np.array(
+                [self.tokenizer.encode(x) for x in outputs]
+            ),
+            prompt=prompt_tokens,
+            is_whole_generation=True,
+            single_line=single_line,
+        )

koboldcpp.py

@@ -76,13 +76,20 @@ def file_exists(filename):
     return os.path.exists(os.path.join(getdirpath(), filename))
 
 def pick_existant_file(ntoption,nonntoption):
+    precompiled_prefix = "precompiled_"
     ntexist = file_exists(ntoption)
     nonntexist = file_exists(nonntoption)
+    precompiled_ntexist = file_exists(precompiled_prefix+ntoption)
+    precompiled_nonntexist = file_exists(precompiled_prefix+nonntoption)
     if os.name == 'nt':
+        if not ntexist and precompiled_ntexist:
+            return (precompiled_prefix+ntoption)
         if nonntexist and not ntexist:
             return nonntoption
         return ntoption
     else:
+        if not nonntexist and precompiled_nonntexist:
+            return (precompiled_prefix+nonntoption)
         if ntexist and not nonntexist:
             return ntoption
         return nonntoption