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https://github.com/aljazceru/dev-gpt.git
synced 2025-12-23 00:24:20 +01:00
fix: prompts
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.gitignore
vendored
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.gitignore
vendored
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/executor/
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19
README.md
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README.md
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# vision
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# 🔮 vision
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create, deploy and update your microservice infrastructure
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create, deploy and update your microservice infrastructure
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# frontend description
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# 🏗 frontend description
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The microchain-frontend is used to define the graph of microservice, their interfaces and their functionality.
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The microchain-frontend is used to define the graph of microservice, their interfaces and their functionality.
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Based on this definition, the backend will be generated automatically.
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Based on this definition, the backend will be generated automatically.
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# 🏗 usage single microservice
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## you provide
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- input_modality
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- output_modality
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- description of the functionality of the transformation the microservice is handling
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- examples of input and output pairs
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## you get
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- a microservice together with a playground
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# 🤏 limitations for now
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- stateless microservices only
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- deterministic microservices only to make sure input and output pairs can be used
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67
main.py
67
main.py
@@ -6,77 +6,51 @@ from docarray import DocumentArray, Document
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from jcloud.flow import CloudFlow
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from jcloud.flow import CloudFlow
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from jina import Client
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from jina import Client
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from prompt_examples import executor_example, docarray_example
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openai.api_key = os.environ['OPENAI_API_KEY']
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openai.api_key = os.environ['OPENAI_API_KEY']
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executor_description = "Write an executor that takes image bytes as input (document.blob within a DocumentArray) and use BytesIO to convert it to PIL and detects ocr " \
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input_executor_description = "Write an executor that takes image bytes as input (document.blob within a DocumentArray) and use BytesIO to convert it to PIL and detects ocr " \
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"and returns the texts as output (as DocumentArray). "
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"and returns the texts as output (as DocumentArray). "
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test_description = 'The test downloads the image ' \
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input_test_description = 'The test downloads the image ' \
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'https://double-rhyme.com/logo_en_white2.png ' \
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'https://upload.wikimedia.org/wikipedia/commons/thumb/a/aa/Onlineocr.png/640px-Onlineocr.png ' \
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' loads it as bytes, takes it as input to the executor and asserts that the output is "Double Rhyme".'
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' loads it as bytes, takes it as input to the executor and asserts that the output is "Double Rhyme".'
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response = openai.ChatCompletion.create(
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response = openai.ChatCompletion.create(
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temperature=0,
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temperature=0,
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model="gpt-3.5-turbo",
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model="gpt-4",
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messages=[
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messages=[
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{
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{
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"role": "system",
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"role": "system",
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"content": "You are a principal engineer working at Jina - an open source company."
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"content": "You are a principal engineer working at Jina - an open source company."
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"Using the Jina framework, users can define executors."
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"Using the Jina framework, users can define executors."
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"Here is an example of how an executor can be defined. It always starts with a comment:"
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+ executor_example
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'''
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+ docarray_example
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# this executor takes ... as input and returns ... as output
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# it processes each document in the following way: ...
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from jina import Executor, requests, DocumentArray, Document, Deployment
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class MyExecutor(Executor):
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def __init__(self, **kwargs):
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super().__init__()
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@requests
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def foo(self, docs: DocumentArray, **kwargs) => DocumentArray:
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for d in docs:
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d.text = 'hello world'"
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return docs
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'''
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"An executor gets a DocumentArray as input and returns a DocumentArray as output."
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"Here is an example of how a DocumentArray can be defined:"
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'''
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d1 = Document(text='hello')
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d2 = Document(blob=b'\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR\x00\x00\x03L\x00\x00\x01\x18\x08\x06\x00\x00\x00o...')
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d3 = Document(tensor=numpy.array([1, 2, 3]), chunks=[Document(uri=/local/path/to/file)]
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d4 = Document(
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uri='https://docs.docarray.org',
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tags={'foo': 'bar'},
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)
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docs = DocumentArray([
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d1, d2, d3, d4
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])
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'''
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"these imports are needed:"
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'''
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from jina import DocumentArray, Document
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'''
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},
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},
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{
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{
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"role": "user",
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"role": "user",
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"content":
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"content":
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executor_description
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input_executor_description
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+ "The code you write is production ready. Every file starts with a 5 sentence comment of what the code is doing before the first import. Start from top-level and then fully implement all methods."
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+ "The code you write is production ready. Every file starts with a 5 sentence comment of what the code is doing before the first import. Start from top-level and then fully implement all methods."
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"First, write the executor name. (wrap the code in the string $$$start_executor_name$$$...$$$end_executor_name$$$) "
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"First, write the executor name. (wrap the code in the string $$$start_executor_name$$$...$$$end_executor_name$$$) "
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"The executor name only consists of lower case and upper case letters. "
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"The executor name only consists of lower case and upper case letters. "
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"Then, write the executor code. (wrap the code in the string $$$start_executor$$$ ... $$$end_executor$$$)"
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"Then, write the executor code. (executor.py) (wrap the code in the string $$$start_executor$$$ ... $$$end_executor$$$)"
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"In addition write the content of the requirements.txt file. Make sure to include pytest. (wrap the code in the string $$$start_requirements$$$ ... $$$end_requirements$$$)"
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"In addition write the content of the requirements.txt file. Make sure to include pytest. (wrap the code in the string $$$start_requirements$$$ ... $$$end_requirements$$$)"
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"Then write a small unit test for the executor. Start the test with an extensive comment about the test case (wrap the code in the string $$$start_test_executor$$$ ... $$$end_test_executor$$$)"
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"Then write a small unit test for the executor (test_executor.py). Start the test with an extensive comment about the test case. "
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"Never do relative imports."
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"(wrap the code in the string $$$start_test_executor$$$ ... $$$end_test_executor$$$)"
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"Comments can only be written between tags."
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"Comments can only be written between tags."
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# "the snipped should take the local file wolf.obj as input and save the output as png files. "
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# "the snipped should take the local file wolf.obj as input and save the output as png files. "
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+ test_description
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+ input_test_description
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+ "Finally write the Dockerfile that defines the environment with all necessary dependencies that the executor uses. "
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+ "Finally write the Dockerfile that defines the environment with all necessary dependencies that the executor uses. "
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'First start with comments that give an executor-specific description the Dockerfile. '
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"It is important to make sure that all libs are installed that are required by the python packages. "
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"It is important to make sure that all libs are installed that are required by the python packages. "
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"The base image of the Dockerfile is FROM jinaai/jina:3.14.2-dev18-py310-standard. "
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"The base image of the Dockerfile is FROM jinaai/jina:3.14.2-dev18-py310-standard. "
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'The entrypoint is ENTRYPOINT ["jina", "executor", "--uses", "config.yml"]'
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'The entrypoint is ENTRYPOINT ["jina", "executor", "--uses", "config.yml"] '
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# "The Dockerfile runs the test during the build process. "
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"The Dockerfile runs the test during the build process. "
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"(wrap the code in the string $$$start_dockerfile$$$ ... $$$end_dockerfile$$$)"
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"(wrap the code in the string $$$start_dockerfile$$$ ... $$$end_dockerfile$$$)"
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},
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},
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@@ -115,7 +89,7 @@ def recreate_folder(folder_path):
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folder = 'executor'
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folder = 'executor'
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recreate_folder(folder)
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recreate_folder(folder)
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for tag, file_name in [['executor', f'{executor_name}.py'], ['requirements', 'requirements.txt'], ['test_executor', 'test_OCRDetectorExecutor.py'], ['dockerfile', 'Dockerfile']]:
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for tag, file_name in [['executor', f'executor.py'], ['requirements', 'requirements.txt'], ['test_executor', 'test_executor.py'], ['dockerfile', 'Dockerfile']]:
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content = find_between(plain_text, f'$$$start_{tag}$$$', f'$$$end_{tag}$$$')
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content = find_between(plain_text, f'$$$start_{tag}$$$', f'$$$end_{tag}$$$')
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clean = clean_content(content)
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clean = clean_content(content)
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full_path = os.path.join(folder, file_name)
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full_path = os.path.join(folder, file_name)
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@@ -125,7 +99,7 @@ for tag, file_name in [['executor', f'{executor_name}.py'], ['requirements', 're
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config_content = f'''
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config_content = f'''
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jtype: {executor_name}
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jtype: {executor_name}
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py_modules:
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py_modules:
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- {executor_name}.py
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- executor.py
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metas:
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metas:
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name: {executor_name}
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name: {executor_name}
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'''
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'''
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@@ -164,7 +138,6 @@ full_flow_path = os.path.join('executor', 'flow.yml')
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with open(full_flow_path, 'w') as f:
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with open(full_flow_path, 'w') as f:
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f.write(flow)
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f.write(flow)
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exit(0)
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cloud_flow = CloudFlow(path=full_flow_path).__enter__()
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cloud_flow = CloudFlow(path=full_flow_path).__enter__()
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host = cloud_flow.endpoints['gateway']
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host = cloud_flow.endpoints['gateway']
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client = Client(host=host)
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client = Client(host=host)
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33
prompt_examples.py
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33
prompt_examples.py
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executor_example = "Here is an example of how an executor can be defined. It always starts with a comment:"
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'''
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# this executor takes ... as input and returns ... as output
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# it processes each document in the following way: ...
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from jina import Executor, requests, DocumentArray, Document, Deployment
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class MyExecutor(Executor):
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def __init__(self, **kwargs):
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super().__init__()
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@requests
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def foo(self, docs: DocumentArray, **kwargs) => DocumentArray:
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for d in docs:
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d.text = 'hello world'"
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return docs
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'''
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"An executor gets a DocumentArray as input and returns a DocumentArray as output."
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docarray_example = "Here is an example of how a DocumentArray can be defined:"
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'''
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from jina import DocumentArray, Document
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d1 = Document(text='hello')
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d2 = Document(blob=b'\x89PNG\r\n\x1a\n\x00\x00\x00\rIHDR\x00\x00\x03L\x00\x00\x01\x18\x08\x06\x00\x00\x00o...')
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d3 = Document(tensor=numpy.array([1, 2, 3]), chunks=[Document(uri=/local/path/to/file)]
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d4 = Document(
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uri='https://docs.docarray.org',
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tags={'foo': 'bar'},
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)
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docs = DocumentArray([
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d1, d2, d3, d4
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])
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'''
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0
prompt_tasks.py
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0
prompt_tasks.py
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