fix: fix issue with same doc type in spawned processes

.github/workflows/cd.yml

@@ -147,6 +147,7 @@ jobs:
           pytest --suppress-no-test-exit-code --force-flaky --min-passes 1 --max-runs 5 --cov=jina --cov-report=xml --timeout=600 -v -s --ignore-glob='tests/integration/hub_usage/dummyhub*' tests/integration/docarray_v2/test_parameters_as_pydantic.py
           pytest --suppress-no-test-exit-code --force-flaky --min-passes 1 --max-runs 5 --cov=jina --cov-report=xml --timeout=600 -v -s --ignore-glob='tests/integration/hub_usage/dummyhub*' tests/integration/docarray_v2/test_streaming.py
           pytest --suppress-no-test-exit-code --force-flaky --min-passes 1 --max-runs 5 --cov=jina --cov-report=xml --timeout=600 -v -s --ignore-glob='tests/integration/hub_usage/dummyhub*' tests/integration/docarray_v2/sagemaker/test_sagemaker.py
+          pytest --suppress-no-test-exit-code --force-flaky --min-passes 1 --max-runs 5 --cov=jina --cov-report=xml --timeout=600 -v -s --ignore-glob='tests/integration/hub_usage/dummyhub*' tests/integration/docarray_v2/docker
           echo "flag it as jina for codeoverage"
           echo "codecov_flag=jina" >> $GITHUB_OUTPUT
         timeout-minutes: 45

.github/workflows/ci.yml

@@ -482,6 +482,7 @@ jobs:
           pytest --suppress-no-test-exit-code --force-flaky --min-passes 1 --max-runs 5 --cov=jina --cov-report=xml --timeout=600 -v -s --ignore-glob='tests/integration/hub_usage/dummyhub*' tests/integration/docarray_v2/test_parameters_as_pydantic.py
           pytest --suppress-no-test-exit-code --force-flaky --min-passes 1 --max-runs 5 --cov=jina --cov-report=xml --timeout=600 -v -s --ignore-glob='tests/integration/hub_usage/dummyhub*' tests/integration/docarray_v2/test_streaming.py
           pytest --suppress-no-test-exit-code --force-flaky --min-passes 1 --max-runs 5 --cov=jina --cov-report=xml --timeout=600 -v -s --ignore-glob='tests/integration/hub_usage/dummyhub*' tests/integration/docarray_v2/sagemaker/test_sagemaker.py
+          pytest --suppress-no-test-exit-code --force-flaky --min-passes 1 --max-runs 5 --cov=jina --cov-report=xml --timeout=600 -v -s --ignore-glob='tests/integration/hub_usage/dummyhub*' tests/integration/docarray_v2/docker
           echo "flag it as jina for codeoverage"
           echo "codecov_flag=jina" >> $GITHUB_OUTPUT
         timeout-minutes: 45

jina/serve/runtimes/gateway/http_fastapi_app_docarrayv2.py

@@ -200,7 +200,8 @@
             else:
                 docs = DocList[input_doc_list_model]([data])
                 if body.header is None:
-                    req_id = docs[0].id
+                    if hasattr(docs[0], 'id'):
+                        req_id = docs[0].id
 
             try:
                 async for resp in streamer.stream_docs(

jina/serve/stream/__init__.py

@@ -85,7 +85,6 @@
             connection_pool, retry_forever=True, is_cancel=is_cancel
         )
         self.logger.debug(f'Got all endpoints from TopologyGraph {endpoints}')
-
         if endpoints is not None:
             for endp in endpoints:
                 for origin_node in topology_graph.origin_nodes:
@@ -102,6 +101,16 @@
                         and len(leaf_input_output_model) > 0
                     ):
                         _endpoints_models_map[endp] = leaf_input_output_model[0]
+        cached_models = {}
+        for k, v in _endpoints_models_map.items():
+            if v['input'].__name__ not in cached_models:
+                cached_models[v['input'].__name__] = v['input']
+            else:
+                v['input'] = cached_models[v['input'].__name__]
+            if v['output'].__name__ not in cached_models:
+                cached_models[v['output'].__name__] = v['output']
+            else:
+                v['output'] = cached_models[v['output'].__name__]
         return _endpoints_models_map
 
     async def stream_doc(

tests/integration/docarray_v2/docker/executor1/Dockerfile

@@ -0,0 +1,7 @@
+FROM jinaai/jina:test-pip
+
+COPY . /executor_root/
+
+WORKDIR /executor_root
+
+ENTRYPOINT ["jina", "executor", "--uses", "config.yml"]

tests/integration/docarray_v2/docker/executor1/config.yml

@@ -0,0 +1,5 @@
+jtype: Encoder
+metas:
+  name: EncoderPrivate
+  py_modules:
+    - executor.py

tests/integration/docarray_v2/docker/executor1/executor.py

@@ -0,0 +1,23 @@
+from typing import Optional
+from docarray import DocList, BaseDoc
+from docarray.typing import NdArray
+from jina import Executor, requests
+import numpy as np
+
+class MyDoc(BaseDoc):
+    text: str
+    embedding: Optional[NdArray] = None
+
+
+class Encoder(Executor):
+    def __init__(
+            self,
+            *args,
+            **kwargs,
+    ):
+        super().__init__(*args, **kwargs)
+
+    @requests
+    def encode(self, docs: DocList[MyDoc], **kwargs) -> DocList[MyDoc]:
+        for doc in docs:
+            doc.embedding = np.random.random(128)

tests/integration/docarray_v2/docker/executor2/Dockerfile

@@ -0,0 +1,7 @@
+FROM jinaai/jina:test-pip
+
+COPY . /executor_root/
+
+WORKDIR /executor_root
+
+ENTRYPOINT ["jina", "executor", "--uses", "config.yml"]

tests/integration/docarray_v2/docker/executor2/config.yml

@@ -0,0 +1,5 @@
+jtype: Indexer
+metas:
+  name: IndexerPrivate
+  py_modules:
+    - executor.py

tests/integration/docarray_v2/docker/executor2/executor.py

@@ -0,0 +1,39 @@
+from typing import Optional, List
+from docarray import DocList, BaseDoc
+from docarray.typing import NdArray
+from docarray.index import InMemoryExactNNIndex
+from jina import Executor, requests
+
+
+class MyDoc(BaseDoc):
+    text: str
+    embedding: Optional[NdArray] = None
+
+
+class MyDocWithMatches(MyDoc):
+    matches: DocList[MyDoc] = []
+    scores: List[float] = []
+
+
+class Indexer(Executor):
+    def __init__(self, *args, **kwargs):
+        super().__init__(*args, **kwargs)
+        self._indexer = InMemoryExactNNIndex[MyDoc]()
+
+    @requests(on='/index')
+    def index(self, docs: DocList[MyDoc], **kwargs) -> DocList[MyDoc]:
+        self._indexer.index(docs)
+        return docs
+
+    @requests(on='/search')
+    def search(self, docs: DocList[MyDoc], **kwargs) -> DocList[MyDocWithMatches]:
+        res = DocList[MyDocWithMatches]()
+        ret = self._indexer.find_batched(docs, search_field='embedding')
+        matched_documents = ret.documents
+        matched_scores = ret.scores
+        for query, matches, scores in zip(docs, matched_documents, matched_scores):
+            output_doc = MyDocWithMatches(**query.dict())
+            output_doc.matches = matches
+            output_doc.scores = scores.tolist()
+            res.append(output_doc)
+        return res

tests/integration/docarray_v2/docker/test_with_docker.py

@@ -0,0 +1,61 @@
+import os
+import time
+
+import pytest
+import requests as general_requests
+
+from jina import Flow
+
+cur_dir = os.path.dirname(os.path.abspath(__file__))
+
+
+@pytest.fixture
+def executor_images_built():
+    import docker
+
+    client = docker.from_env()
+    client.images.build(path=os.path.join(cur_dir, 'executor1'), tag='encoder-executor')
+    client.images.build(path=os.path.join(cur_dir, 'executor2'), tag='indexer-executor')
+    client.close()
+    yield
+    time.sleep(2)
+    client = docker.from_env()
+    client.containers.prune()
+
+
+@pytest.mark.parametrize('protocol', ['http', 'grpc'])
+def test_flow_with_docker(executor_images_built, protocol):
+    from docarray import BaseDoc, DocList
+    from typing import Optional, List
+    from docarray.typing import NdArray
+
+    class MyDoc(BaseDoc):
+        text: str
+        embedding: Optional[NdArray] = None
+
+    class MyDocWithMatches(MyDoc):
+        matches: DocList[MyDoc] = []
+        scores: List[float] = []
+
+    f = Flow(protocol=protocol).add(uses='docker://encoder-executor').add(uses='docker://indexer-executor')
+
+    with f:
+        if protocol == 'http':
+            resp = general_requests.get(f'http://localhost:{f.port}/openapi.json')
+            resp.json()
+
+        sentences = ['This framework generates embeddings for each input sentence',
+                     'Sentences are passed as a list of string.',
+                     'The quick brown fox jumps over the lazy dog.']
+
+        inputs = DocList[MyDoc]([MyDoc(text=sentence) for sentence in sentences])
+        f.post(on='/index', inputs=inputs)
+        queries = inputs[0:2]
+        search_results = f.post(on='/search', inputs=queries, return_type=DocList[MyDocWithMatches])
+
+        assert len(search_results) == len(queries)
+        for result in search_results:
+            assert result.text in sentences
+            assert len(result.matches) == len(sentences)
+            for m in result.matches:
+                assert m.text in sentences