feat: poc

main.py

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+import os
+
+import openai
+from docarray import DocumentArray, Document
+from jcloud.flow import CloudFlow
+from jina import Client
+
+openai.api_key = os.environ['OPENAI_API_KEY']
+
+executor_description = "Write an executor that takes an images as byte input (document.blob within a DocumentArray) saves it locally and detects ocr " \
+                       "and returns the texts as output (as DocumentArray). "
+
+test_description = 'The test downloads the image ' \
+                   'https://double-rhyme.com/logo_en_white2.png ' \
+                   ' loads it as bytes, takes it as input to the executor and asserts that the output is "Double Rhyme".'
+
+response = openai.ChatCompletion.create(
+    temperature=0,
+    model="gpt-3.5-turbo",
+    messages=[
+        {
+            "role": "system",
+            "content": "You are a principal engineer working at Jina - an open source company."
+                       "Using the Jina framework, users can define executors."
+                       "Here is an example of how an executor can be defined:"
+                       '''
+                       class MyExecutor(Executor):
+                           def __init__(self, **kwargs):
+                               super().__init__()
+                               
+                           @requests
+                           def foo(self, docs: DocumentArray, **kwargs) => DocumentArray:
+                               for d in docs:
+                                   d.text = 'hello world'"
+                               return docs
+                       '''
+                       "these imports are needed:"
+                       '''
+                       from jina import Executor, requests, DocumentArray, Document, Deployment
+                       '''
+                       "An executor gets a DocumentArray as input and returns a DocumentArray as output."
+                       "Here is an example of how a DocumentArray can be defined:"
+                       '''
+                       d1 = Document(text='hello')
+                       d2 = Document(blob=b'\f1')
+                       d3 = Document(tensor=numpy.array([1, 2, 3]), chunks=[Document(uri=/local/path/to/file)]
+                       d4 = Document(
+                           uri='https://docs.docarray.org',
+                           tags={'foo': 'bar'},
+                       )
+                       
+                       docs = DocumentArray([
+                           d1, d2, d3, d4
+                       ])
+                       '''
+                       "these imports are needed:"
+                       '''
+                       from jina import DocumentArray, Document
+                       '''
+
+        },
+        {
+            "role": "user",
+            "content":
+                executor_description
+                + "The code you write is production ready. Start from top-level and then fully implement all methods."
+                  "First, write the executor name. (wrap the code in the string $$$start_executor_name$$$ ... $$$end_executor_name$$$)"
+                  "Then, write the executor code. (wrap the code in the string $$$start_executor$$$ ... $$$end_executor$$$)"
+                  "In addition write the content of the requirements.txt file. Make sure to include pytest.  (wrap the code in the string $$$start_requirements$$$ ... $$$end_requirements$$$)"
+                  "Then write a small unit test for the executor. (wrap the code in the string $$$start_test_executor$$$ ... $$$end_test_executor$$$)"
+                # "the snipped should take the local file wolf.obj as input and save the output as png files. "
+                + test_description
+                + "Finally write the Dockerfile that defines the environment in which the executor runs. The dockerfile runs the test during the build process (wrap the code in the string $$$start_dockerfile$$$ ... $$$end_dockerfile$$$)"
+        },
+
+    ]
+)
+plain_text = response['choices'][0]['message']['content']
+print(plain_text)
+
+
+def find_between(input_string, start, end):
+    try:
+        start_index = input_string.index(start) + len(start)
+        end_index = input_string.index(end, start_index)
+        return input_string[start_index:end_index]
+    except ValueError:
+        raise ValueError(f'Could not find {start} and {end} in {input_string}')
+
+
+def clean_content(content):
+    return content.replace('```', '').strip()
+
+
+for tag, file_ending in [['executor', 'py'], ['requirements', 'txt'], ['test_executor', 'py'], ['dockerfile', '']]:
+    content = find_between(plain_text, f'$$$start_{tag}$$$', f'$$$end_{tag}$$$')
+    clean = clean_content(content)
+    file_name = f'{tag}.{file_ending}' if file_ending else tag
+    folder = 'executor'
+    full_path = os.path.join(folder, file_name)
+    os.makedirs(folder, exist_ok=True)
+    with open(full_path, 'w') as f:
+        f.write(clean)
+
+executor_name = find_between(plain_text, f'$$$start_executor_name$$$', f'$$$end_executor_name$$$').strip()
+config_content = f'''
+jtype: {executor_name}
+py_modules:
+  - executor.py
+metas:
+  name: {executor_name}
+'''
+with open('executor/config.yml', 'w') as f:
+    f.write(config_content)
+
+cmd = 'jina hub push executor/.'
+os.system(cmd)
+
+flow = f'''
+jtype: Flow
+with:
+  monitoring: true
+  env:
+    JINA_LOG_LEVEL: DEBUG
+jcloud:
+  version: '3.14.2.dev18'
+  labels:
+    team: now
+gateway:
+  jcloud:
+    expose: true
+executors:
+  - name: {executor_name.lower()}
+    uses: jinaai+docker://team-now-prod/{executor_name}
+    env:
+      JINA_LOG_LEVEL: DEBUG
+    jcloud:
+      expose: true
+      autoscale:
+        min: 4
+        max: 15
+        metric: concurrency
+        target: 1
+      resources:
+        instance: C4
+        capacity: spot
+'''
+full_flow_path = os.path.join('executor', 'flow.yml')
+with open(full_flow_path, 'w') as f:
+    f.write(flow)
+
+cloud_flow = CloudFlow(path=full_flow_path).__enter__()
+host = cloud_flow.endpoints['gateway']
+client = Client(host=host)
+
+response = client.post('/index', inputs=DocumentArray([Document(uri='https://double-rhyme.com/logo_en_white2.png')]))
+response[0].summary()
+
+# "Write an executor using open3d that takes 3d models in obj format (within a DocumentArray) as input and returns 3 2d renderings for each 3d model from unique random angles as output (as DocumentArray). Each document of the output DocumentArray has 3 chunks. Each chunk is one of the 2d renderings as png.  "
+

requirements.txt

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+jina[perf]==3.14.2.dev18