chore: import upstream snapshot with attribution

2026-07-13 13:34:58 +08:00
commit a203934033
1368 changed files with 175001 additions and 0 deletions
@@ -0,0 +1,44 @@
+# Copyright (c) ModelScope Contributors. All rights reserved.
+import os
+from openai import OpenAI
+
+os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+
+
+def infer(client, model: str, messages):
+    query = messages[0]['content']
+    print(f'query: {query}')
+    resp = client.completions.create(model=model, prompt=query, max_tokens=64, temperature=0)
+    response = resp.choices[0].text
+    print(f'response: {response}')
+    # or (The two calling methods are equivalent.)
+    resp = client.chat.completions.create(model=model, messages=messages, max_tokens=64, temperature=0)
+    response = resp.choices[0].message.content
+    print(f'response: {response}')
+    return response
+
+
+def run_client(host: str = '127.0.0.1', port: int = 8000):
+    client = OpenAI(
+        api_key='EMPTY',
+        base_url=f'http://{host}:{port}/v1',
+    )
+    model = client.models.list().data[0].id
+    print(f'model: {model}')
+
+    messages = [{'role': 'user', 'content': '浙江 -> 杭州\n安徽 -> 合肥\n四川 ->'}]
+    infer(client, model, messages)
+
+
+if __name__ == '__main__':
+    from swift import DeployArguments, run_deploy
+
+    # NOTE: In a real deployment scenario, please comment out the context of run_deploy.
+    with run_deploy(
+            DeployArguments(
+                model='Qwen/Qwen2.5-1.5B',
+                verbose=False,
+                log_interval=-1,
+                infer_backend='transformers',
+                use_chat_template=False)) as port:
+        run_client(port=port)
@@ -0,0 +1,37 @@
+# Copyright (c) ModelScope Contributors. All rights reserved.
+import os
+from typing import List
+
+os.environ['CUDA_VISIBLE_DEVICES'] = '0'
+
+
+def infer_batch(engine: 'InferEngine', infer_requests: List['InferRequest']):
+    request_config = RequestConfig(max_tokens=64, temperature=0)
+
+    resp_list = engine.infer(infer_requests, request_config)
+
+    query0 = infer_requests[0].messages[0]['content']
+    print(f'query0: {query0}')
+    print(f'response0: {resp_list[0].choices[0].message.content}')
+
+
+def run_client(host: str = '127.0.0.1', port: int = 8000):
+    engine = InferClient(host=host, port=port)
+    print(f'models: {engine.models}')
+
+    infer_requests = [InferRequest(messages=[{'role': 'user', 'content': '浙江 -> 杭州\n安徽 -> 合肥\n四川 ->'}])]
+    infer_batch(engine, infer_requests)
+
+
+if __name__ == '__main__':
+    from swift import DeployArguments, InferClient, InferEngine, InferRequest, RequestConfig, run_deploy
+
+    # NOTE: In a real deployment scenario, please comment out the context of run_deploy.
+    with run_deploy(
+            DeployArguments(
+                model='Qwen/Qwen2.5-1.5B',
+                verbose=False,
+                log_interval=-1,
+                infer_backend='transformers',
+                use_chat_template=False)) as port:
+        run_client(port=port)