add case (#3150)

* add test base class

* fix codestyle

* fix codestyle

* add base chat

test/ce/server/test_base_chat.py

@@ -0,0 +1,146 @@
+#!/bin/env python3
+# -*- coding: utf-8 -*-
+# @author DDDivano
+# encoding=utf-8 vi:ts=4:sw=4:expandtab:ft=python
+
+import json
+
+from core import TEMPLATE, URL, build_request_payload, send_request
+
+
+def test_stream_response():
+    data = {
+        "stream": True,
+        "messages": [
+            {"role": "system", "content": "你是一个知识渊博的 AI 助手"},
+            {"role": "user", "content": "讲讲爱因斯坦的相对论"},
+        ],
+        "max_tokens": 10,
+    }
+    payload = build_request_payload(TEMPLATE, data)
+    resp = send_request(URL, payload, stream=True)
+
+    output = ""
+    for line in resp.iter_lines(decode_unicode=True):
+        if line.strip() == "" or not line.startswith("data: "):
+            continue
+        line = line[len("data: ") :]
+        if line.strip() == "[DONE]":
+            break
+        chunk = json.loads(line)
+        delta = chunk.get("choices", [{}])[0].get("delta", {})
+        output += delta.get("content", "")
+
+    print("Stream输出:", output)
+    assert "相对论" in output or len(output) > 0
+
+
+def test_system_prompt_effect():
+    data = {
+        "stream": False,
+        "messages": [
+            {"role": "system", "content": "请用一句话回答"},
+            {"role": "user", "content": "什么是人工智能？"},
+        ],
+        "max_tokens": 30,
+    }
+    payload = build_request_payload(TEMPLATE, data)
+    resp = send_request(URL, payload).json()
+    content = resp["choices"][0]["message"]["content"]
+    print("内容输出:", content)
+    assert len(content) < 50
+
+
+def test_logprobs_enabled():
+    data = {
+        "stream": False,
+        "logprobs": True,
+        "top_logprobs": 5,
+        "messages": [{"role": "user", "content": "非洲的首都是？"}],
+        "max_tokens": 3,
+    }
+    payload = build_request_payload(TEMPLATE, data)
+    resp = send_request(URL, payload).json()
+    logprob_data = resp["choices"][0].get("logprobs")
+    print("LogProbs:", logprob_data)
+    assert logprob_data is not None
+    content_logprobs = logprob_data.get("content", [])
+    assert isinstance(content_logprobs, list)
+    assert all("token" in item for item in content_logprobs)
+
+
+def test_stop_sequence():
+    data = {
+        "stream": False,
+        "stop": ["然后"],
+        "messages": [
+            {"role": "user", "content": "请输出：这是第一段。然后这是第二段。"},
+        ],
+        "max_tokens": 20,
+        "top_p": 0,
+    }
+    payload = build_request_payload(TEMPLATE, data)
+    resp = send_request(URL, payload).json()
+    content = resp["choices"][0]["message"]["content"]
+    print("截断输出:", content)
+    assert "第二段" not in content
+
+
+def test_sampling_parameters():
+    data = {
+        "stream": False,
+        "temperature": 0,
+        "top_p": 0,
+        "messages": [
+            {"role": "user", "content": "1+1=？,直接回答答案"},
+        ],
+        "max_tokens": 50,
+    }
+    payload = build_request_payload(TEMPLATE, data)
+    resp = send_request(URL, payload).json()
+    answer = resp["choices"][0]["message"]["content"]
+    print("Sampling输出:", answer)
+    assert any(ans in answer for ans in ["2", "二"])
+
+
+def test_multi_turn_conversation():
+    data = {
+        "stream": False,
+        "messages": [
+            {"role": "user", "content": "牛顿是谁？"},
+            {"role": "assistant", "content": "牛顿是一位物理学家。"},
+            {"role": "user", "content": "他提出了什么理论？"},
+        ],
+        "max_tokens": 30,
+    }
+    payload = build_request_payload(TEMPLATE, data)
+    resp = send_request(URL, payload).json()
+    content = resp["choices"][0]["message"]["content"]
+    print("多轮记忆:", content)
+    assert "三大运动定律" in content or "万有引力" in content
+
+
+def test_bad_words_filtering():
+    banned_tokens = ["你", "我", "年龄"]
+
+    data = {
+        "stream": False,
+        "messages": [
+            {"role": "system", "content": "你是一个助手，回答简洁清楚"},
+            {"role": "user", "content": "请输出我的年龄是10岁"},
+        ],
+        "top_p": 0,
+        "max_tokens": 69,
+        "bad_words": banned_tokens,
+    }
+
+    payload = build_request_payload(TEMPLATE, data)
+    response = send_request(URL, payload).json()
+
+    content = response["choices"][0]["message"]["content"]
+    print("生成内容:", content)
+
+    for word in banned_tokens:
+        assert word not in content, f"bad_word '{word}' 不应出现在生成结果中"
+
+    print("test_bad_words_filtering 通过：生成结果未包含被禁词")