Test case bugfix and add restful interface testcases.

.github/workflows/daily_ete_test.yml

@@ -34,7 +34,7 @@ env:
 jobs:
   test_functions:
     runs-on: [self-hosted, linux-a100]
-    timeout-minutes: 240
+    timeout-minutes: 300
     env:
       REPORT_DIR: /nvme/qa_test_models/test-reports
     container:
@@ -157,9 +157,9 @@ jobs:
       - name: Test lmdeploy - interface pipeline turbomind case
         continue-on-error: true
         if: github.event_name == 'schedule' || (contains(fromJSON(github.event.inputs.backend), 'turbomind') && contains(fromJSON(github.event.inputs.model), 'interface-pipeline'))
-        timeout-minutes: 20
+        timeout-minutes: 75
         run: |
-          pytest autotest/interface/pipeline/test_pipeline_turbomind_func.py -m 'not pr_test' --alluredir=allure-results
+          pytest autotest/interface/pipeline -m 'not pr_test' --alluredir=allure-results
       - name: Test lmdeploy - pipeline torch
         continue-on-error: true
         if: github.event_name == 'schedule' || (contains(fromJSON(github.event.inputs.backend), 'pytorch') && contains(fromJSON(github.event.inputs.model), 'pipeline'))
@@ -323,4 +323,8 @@ jobs:
       - name: fail notify
         if: contains(needs.*.result, 'failure')
         run: |
-          curl -X POST -H "Content-Type: application/json" -d '{"msg_type":"post","content":{"post":{"zh_cn":{"title":"Lmdeploy- daily test failed","content":[[{"tag":"text","text":"branch: ${{github.ref_name}}, run action: ${{github.workflow}} failed. "},{"tag":"a","text":"Please click here for details ","href":"https://github.com/'${{ github.repository }}'/actions/runs/'${GITHUB_RUN_ID}'"},{"tag":"at","user_id":"'${{ secrets.FEISHU_USER_ID }}'"}]]}}}}'  ${{ secrets.FEISHU_WEBHOOK_URL }}
+          curl -X POST -H "Content-Type: application/json" -d '{"msg_type":"post","content":{"post":{"zh_cn":{"title":"Lmdeploy- Daily test failed！！！","content":[[{"tag":"text","text":"branch: ${{github.ref_name}}, run action: ${{github.workflow}} failed. "},{"tag":"a","text":"Please click here for details ","href":"https://github.com/'${{ github.repository }}'/actions/runs/'${GITHUB_RUN_ID}'"},{"tag":"at","user_id":"'${{ secrets.FEISHU_USER_ID }}'"}]]}}}}'  ${{ secrets.FEISHU_WEBHOOK_URL }}
+      - name: success notify
+        if: needs.test_functions.result=='success' && needs.test_triton.result=='success'
+        run: |
+          curl -X POST -H "Content-Type: application/json" -d '{"msg_type":"post","content":{"post":{"zh_cn":{"title":"Lmdeploy- Daily test success","content":[[{"tag":"text","text":"branch: ${{github.ref_name}}, run action: ${{github.workflow}} failed. "},{"tag":"a","text":"Please click here for details ","href":"https://github.com/'${{ github.repository }}'/actions/runs/'${GITHUB_RUN_ID}'"}]]}}}}'  ${{ secrets.FEISHU_WEBHOOK_URL }}

.github/workflows/pr_ete_test.yml

@@ -15,6 +15,10 @@ on:
       - "setup.py"
   workflow_dispatch:
 
+concurrency:
+  group: ${{ github.workflow }}-${{ github.event.pull_request.number || github.ref }}
+  cancel-in-progress: true
+
 
 env:
   HOST_PIP_CACHE_DIR: /nvme/github-actions/pip-cache

autotest/interface/restful/test_restful_interface_func_pytorch.py

@@ -0,0 +1,286 @@
+import pytest
+from utils.restful_return_check import (assert_chat_completions_batch_return,
+                                        assert_chat_completions_stream_return,
+                                        assert_chat_interactive_batch_return,
+                                        assert_chat_interactive_stream_return)
+
+from lmdeploy.serve.openai.api_client import APIClient
+
+BASE_HTTP_URL = 'http://localhost'
+DEFAULT_PORT = 23333
+MODEL = 'internlm/internlm2-chat-20b'
+MODEL_NAME = 'internlm2-chat-20b'
+BASE_URL = ':'.join([BASE_HTTP_URL, str(DEFAULT_PORT)])
+
+
+@pytest.mark.order(8)
+@pytest.mark.pytorch
+@pytest.mark.flaky(reruns=2)
+class TestRestfulInterfaceChatCompletions:
+
+    def test_chat_completions_ignore_eos_batch(self):
+        api_client = APIClient(BASE_URL)
+        for output in api_client.chat_completions_v1(
+                model=MODEL_NAME,
+                messages='Hi, what is your name?',
+                ignore_eos=True,
+                max_tokens=100,
+                temperature=0.01):
+            continue
+        assert_chat_completions_batch_return(output, MODEL_NAME)
+        assert output.get('usage').get(
+            'completion_tokens') == 101 or output.get('usage').get(
+                'completion_tokens') == 100
+        assert output.get('choices')[0].get('finish_reason') == 'length'
+
+    def test_chat_completions_ignore_eos_stream(self):
+        api_client = APIClient(BASE_URL)
+        outputList = []
+        for output in api_client.chat_completions_v1(
+                model=MODEL_NAME,
+                messages='Hi, what is your name?',
+                ignore_eos=True,
+                stream=True,
+                max_tokens=100,
+                temperature=0.01):
+            outputList.append(output)
+
+        assert_chat_completions_stream_return(outputList[0], MODEL_NAME, True,
+                                              False)
+        assert_chat_completions_stream_return(outputList[-1], MODEL_NAME,
+                                              False, True)
+        for index in range(1, len(outputList) - 1):
+            assert_chat_completions_stream_return(outputList[index],
+                                                  MODEL_NAME)
+        assert outputList[-1].get('choices')[0].get(
+            'finish_reason') == 'length'
+        assert len(outputList) == 102
+
+    def test_chat_completions_max_tokens_batch(self):
+        api_client = APIClient(BASE_URL)
+        for output in api_client.chat_completions_v1(
+                model=MODEL_NAME,
+                messages='Hi, pls intro yourself',
+                max_tokens=5,
+                temperature=0.01):
+            continue
+        assert_chat_completions_batch_return(output, MODEL_NAME)
+        assert output.get('choices')[0].get('finish_reason') == 'length'
+        assert output.get('usage').get('completion_tokens') == 6 or output.get(
+            'usage').get('completion_tokens') == 5
+
+    def test_chat_completions_max_tokens_stream(self):
+        api_client = APIClient(BASE_URL)
+        outputList = []
+        for output in api_client.chat_completions_v1(
+                model=MODEL_NAME,
+                messages='Hi, pls intro yourself',
+                stream=True,
+                max_tokens=5,
+                temperature=0.01):
+            outputList.append(output)
+        assert_chat_completions_stream_return(outputList[0], MODEL_NAME, True,
+                                              False)
+        assert_chat_completions_stream_return(outputList[-1], MODEL_NAME,
+                                              False, True)
+        for index in range(1, len(outputList) - 1):
+            assert_chat_completions_stream_return(outputList[index],
+                                                  MODEL_NAME)
+        assert outputList[-1].get('choices')[0].get(
+            'finish_reason') == 'length'
+        assert len(outputList) == 7
+
+    def test_chat_completions_repetition_penalty_stream(self):
+        api_client = APIClient(BASE_URL)
+        outputList = []
+        response = ''
+        for output in api_client.chat_completions_v1(
+                model=MODEL_NAME,
+                messages='Hi, pls intro yourself',
+                stream=True,
+                repetition_penalty=0.1,
+                temperature=0.01,
+                max_tokens=200):
+            outputList.append(output)
+        assert_chat_completions_stream_return(outputList[0], MODEL_NAME, True,
+                                              False)
+        assert_chat_completions_stream_return(outputList[-1], MODEL_NAME,
+                                              False, True)
+        for index in range(1, len(outputList) - 1):
+            assert_chat_completions_stream_return(outputList[index],
+                                                  MODEL_NAME)
+            response += outputList[index].get('choices')[0].get('delta').get(
+                'content')
+        assert 'pls pls ' * 5 in response or \
+            'Hi, pls intro yourself\n' * 5 in response
+
+    def test_chat_completions_topp_min_batch(self):
+        api_client = APIClient(BASE_URL)
+        outputList = []
+        for i in range(3):
+            for output in api_client.chat_completions_v1(
+                    model=MODEL_NAME,
+                    messages='Shanghai is',
+                    top_p=0.1,
+                    temperature=0.01):
+                outputList.append(output)
+            assert_chat_completions_batch_return(output, MODEL_NAME)
+            print(output)
+        assert outputList[0].get('choices')[0].get('message').get(
+            'content') == outputList[1].get('choices')[0].get('message').get(
+                'content')
+        assert outputList[1].get('choices')[0].get('message').get(
+            'content') == outputList[2].get('choices')[0].get('message').get(
+                'content')
+
+    def test_chat_completions_topp_min_stream(self):
+        api_client = APIClient(BASE_URL)
+        responseList = []
+        for i in range(3):
+            outputList = []
+            response = ''
+            for output in api_client.chat_completions_v1(
+                    model=MODEL_NAME,
+                    messages='Hi, pls intro yourself',
+                    stream=True,
+                    top_p=0.1,
+                    temperature=0.01):
+                outputList.append(output)
+            assert_chat_completions_stream_return(outputList[0], MODEL_NAME,
+                                                  True, False)
+            assert_chat_completions_stream_return(outputList[-1], MODEL_NAME,
+                                                  False, True)
+            for index in range(1, len(outputList) - 1):
+                assert_chat_completions_stream_return(outputList[index],
+                                                      MODEL_NAME)
+                response += outputList[index].get('choices')[0].get(
+                    'delta').get('content')
+            responseList.append(response)
+        assert responseList[0] == responseList[1]
+        assert responseList[1] == responseList[2]
+
+    def test_chat_completions_longinput_stream(self):
+        api_client = APIClient(BASE_URL)
+        outputList = []
+        for output in api_client.chat_completions_v1(
+                model=MODEL_NAME,
+                messages='Hi, pls intro yourself' * 10000,
+                stream=True,
+                temperature=0.01):
+            outputList.append(output)
+        assert_chat_completions_stream_return(outputList[0], MODEL_NAME, True,
+                                              False)
+        assert_chat_completions_stream_return(outputList[0], MODEL_NAME, True,
+                                              False)
+        for index in range(1, len(outputList) - 1):
+            assert_chat_completions_stream_return(outputList[index],
+                                                  MODEL_NAME)
+        assert outputList[1].get('choices')[0].get('finish_reason') == 'length'
+        assert outputList[1].get('choices')[0].get('delta').get(
+            'content') == ''
+        assert len(outputList) == 2
+
+
+@pytest.mark.order(8)
+@pytest.mark.pytorch
+@pytest.mark.flaky(reruns=2)
+class TestRestfulInterfaceChatInteractive:
+
+    def test_chat_interactive_ignore_eos_batch(self):
+        api_client = APIClient(BASE_URL)
+        for output in api_client.chat_interactive_v1(
+                prompt='Hi, what is your name?',
+                ignore_eos=True,
+                request_output_len=100,
+                temperature=0.01):
+            continue
+        assert_chat_interactive_batch_return(output)
+        assert output.get('tokens') == 100
+        assert output.get('finish_reason') == 'length'
+
+    def test_chat_interactive_ignore_eos_stream(self):
+        api_client = APIClient(BASE_URL)
+        outputList = []
+        for output in api_client.chat_interactive_v1(
+                prompt='Hi, what is your name?',
+                ignore_eos=True,
+                stream=True,
+                request_output_len=100,
+                temperature=0.01):
+            outputList.append(output)
+            print(output)
+        assert_chat_interactive_stream_return(outputList[-1],
+                                              True,
+                                              index=len(outputList) - 2)
+        for index in range(0, len(outputList) - 1):
+            assert_chat_interactive_stream_return(outputList[index],
+                                                  index=index)
+        assert output.get('finish_reason') == 'length'
+        assert len(outputList) == 101
+
+    def test_chat_interactive_max_tokens_batch(self):
+        api_client = APIClient(BASE_URL)
+        for output in api_client.chat_interactive_v1(
+                prompt='Hi, pls intro yourself',
+                request_output_len=5,
+                temperature=0.01):
+            continue
+        assert_chat_interactive_batch_return(output)
+        assert output.get('finish_reason') == 'length'
+        assert output.get('tokens') == 5
+
+    def test_chat_interactive_max_tokens_stream(self):
+        api_client = APIClient(BASE_URL)
+        outputList = []
+        for output in api_client.chat_interactive_v1(
+                prompt='Hi, pls intro yourself',
+                stream=True,
+                request_output_len=5,
+                temperature=0.01):
+            outputList.append(output)
+        assert_chat_interactive_stream_return(outputList[-1],
+                                              True,
+                                              index=len(outputList) - 2)
+        for index in range(0, len(outputList) - 1):
+            assert_chat_interactive_stream_return(outputList[index],
+                                                  index=index)
+        assert output.get('finish_reason') == 'length'
+        assert len(outputList) == 6
+
+    def test_chat_interactive_topp_min_batch(self):
+        api_client = APIClient(BASE_URL)
+        outputList = []
+        for i in range(3):
+            for output in api_client.chat_interactive_v1(prompt='Shanghai is',
+                                                         top_p=0.01,
+                                                         temperature=0.01):
+                continue
+            assert_chat_interactive_batch_return(output)
+            outputList.append(output)
+            print(output)
+        assert outputList[0] == outputList[1]
+        assert outputList[1] == outputList[2]
+
+    def test_chat_interactive_topp_min_stream(self):
+        api_client = APIClient(BASE_URL)
+        responseList = []
+        for i in range(3):
+            outputList = []
+            response = ''
+            for output in api_client.chat_interactive_v1(
+                    model=MODEL_NAME,
+                    prompt='Hi, pls intro yourself',
+                    stream=True,
+                    top_p=0.01,
+                    temperature=0.01):
+                outputList.append(output)
+            assert_chat_interactive_stream_return(outputList[-1],
+                                                  True,
+                                                  index=len(outputList) - 2)
+            for index in range(0, len(outputList) - 1):
+                assert_chat_interactive_stream_return(outputList[index],
+                                                      index=index)
+                response += outputList[index].get('text')
+            responseList.append(response)
+        assert responseList[0] == responseList[1]
+        assert responseList[1] == responseList[2]