update

environment.yml

@@ -1,4 +1,4 @@
-name: db-pgt 
+name: db_pgt 
 channels:
   - pytorch
   - defaults

pilot/server/sqlgpt.py

@@ -12,18 +12,18 @@ from transformers import AutoTokenizer, AutoModelForCausalLM
 device = "cuda" if torch.cuda.is_available() else "cpu"
 BASE_MODE = "/home/magic/workspace/github/DB-GPT/models/vicuna-13b"
 
+tokenizer = AutoTokenizer.from_pretrained(BASE_MODE, use_fast=False)
+model = AutoModelForCausalLM.from_pretrained(
+    BASE_MODE, 
+    low_cpu_mem_usage=True, 
+    torch_dtype=torch.float16,
+    device_map="auto",
+)
+
 def generate(prompt):    
-    tokenizer = AutoTokenizer.from_pretrained(BASE_MODE, use_fast=False)
-    model = AutoModelForCausalLM.from_pretrained(
-        BASE_MODE, 
-        low_cpu_mem_usage=True, 
-        torch_dtype=torch.float16,
-        device_map="auto",
-    )
     # compress_module(model, device) 
     # model.to(device)
     print(model, tokenizer)
-
     params = {
         "model": "vicuna-13b",
         "prompt": prompt,
@@ -32,9 +32,12 @@ def generate(prompt):
         "stop": "###"
     }
     output = generate_stream(
-        model, tokenizer, params, device, context_len=2048, stream_interval=2)
+        model, tokenizer, params, device, context_len=2048, stream_interval=2): 
+        
 
-    yield output
+    for chunk in output.iter_lines(decode_unicode=False, delimiter=b"\0"):
+        if chunk:
+            yield chunk
 
 if __name__ == "__main__":
     with gr.Blocks() as demo: