feat(transformers): support also text generation (#1630)

* feat(transformers): support also text generation

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

* embedded: set seed -1

---------

Signed-off-by: Ettore Di Giacinto <mudler@localai.io>

backend/python/transformers/transformers_server.py

@@ -15,7 +15,7 @@ import backend_pb2_grpc
 
 import grpc
 import torch
-
+import torch.cuda
 from transformers import AutoTokenizer, AutoModel
 
 _ONE_DAY_IN_SECONDS = 60 * 60 * 24
@@ -70,12 +70,8 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
         try:
             self.model = AutoModel.from_pretrained(model_name, trust_remote_code=True) # trust_remote_code is needed to use the encode method with embeddings models like jinai-v2
             self.tokenizer = AutoTokenizer.from_pretrained(model_name)
-
-            if request.CUDA:
+            if request.CUDA or torch.cuda.is_available():
                 try:
-                    # TODO: also tensorflow, make configurable
-                    import torch.cuda
-                    if torch.cuda.is_available():
                     print("Loading model", model_name, "to CUDA.", file=sys.stderr)
                     self.model = self.model.to("cuda")
                 except Exception as err:
@@ -113,6 +109,47 @@ class BackendServicer(backend_pb2_grpc.BackendServicer):
         print("Embeddings:", sentence_embeddings, file=sys.stderr)
         return backend_pb2.EmbeddingResult(embeddings=sentence_embeddings)
 
+    def Predict(self, request, context):
+        """
+        Generates text based on the given prompt and sampling parameters.
+
+        Args:
+            request: The predict request.
+            context: The gRPC context.
+
+        Returns:
+            backend_pb2.Reply: The predict result.
+        """
+        if request.TopP == 0:
+            request.TopP = 0.9
+
+        max_tokens = 200
+        if request.Tokens > 0:
+            max_tokens = request.Tokens
+
+        inputs = self.tokenizer.tokenizer(request.Prompt, return_tensors="pt").input_ids
+        outputs = self.model.generate(inputs,max_tokens=max_tokens, temperature=request.Temperature, top_p=request.TopP)
+
+        generated_text = self.tokenizer.tokenizer.batch_decode(outputs, skip_special_tokens=True)[0]
+        # Remove prompt from response if present
+        if request.Prompt in generated_text:
+            generated_text = generated_text.replace(request.Prompt, "")
+
+        return backend_pb2.Reply(message=bytes(generated_text, encoding='utf-8'))
+
+    def PredictStream(self, request, context):
+        """
+        Generates text based on the given prompt and sampling parameters, and streams the results.
+
+        Args:
+            request: The predict stream request.
+            context: The gRPC context.
+
+        Returns:
+            backend_pb2.Result: The predict stream result.
+        """
+        yield self.Predict(request, context)
+
 
 def serve(address):
     server = grpc.server(futures.ThreadPoolExecutor(max_workers=MAX_WORKERS))

embedded/models/dolphin-2.5-mixtral-8x7b.yaml

@@ -5,6 +5,7 @@ parameters:
   temperature: 0.2
   top_k: 40
   top_p: 0.95
+  seed: -1
 template:
   chat_message: |
     <|im_start|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "user"}}user{{end}}

embedded/models/llava.yaml

@@ -17,6 +17,7 @@ parameters:
   temperature: 0.2
   top_k: 40
   top_p: 0.95
+  seed: -1
 
 template:
   chat: |

embedded/models/mistral-openorca.yaml

@@ -5,6 +5,7 @@ parameters:
   temperature: 0.2
   top_k: 40
   top_p: 0.95
+  seed: -1
 template:
   chat_message: |
     <|im_start|>{{if eq .RoleName "assistant"}}assistant{{else if eq .RoleName "system"}}system{{else if eq .RoleName "user"}}user{{end}}

embedded/models/mixtral-instruct.yaml

@@ -4,6 +4,7 @@ parameters:
   model: huggingface://TheBloke/Mixtral-8x7B-Instruct-v0.1-GGUF/mixtral-8x7b-instruct-v0.1.Q2_K.gguf
   temperature: 0.2
   top_k: 40
+  seed: -1
   top_p: 0.95
 template:
   chat: &chat |

embedded/models/tinyllama-chat.yaml

@@ -4,6 +4,7 @@ parameters:
   model: huggingface://TheBloke/TinyLlama-1.1B-Chat-v0.3-GGUF/tinyllama-1.1b-chat-v0.3.Q8_0.gguf
   temperature: 0.2
   top_k: 40
+  seed: -1
   top_p: 0.95
 template:
   chat_message: |

examples/configurations/phi-2.yaml

@@ -10,6 +10,7 @@ parameters:
   temperature: 0.2
   top_k: 40
   top_p: 0.95
+  seed: -1
 template:
   chat: &template |
     Instruct: {{.Input}}