refactor: docs refactor fixes

src/prompt_system.py

@@ -16,8 +16,6 @@ class MyInfoExecutor(Executor):
     def foo(self, docs: DocumentArray, **kwargs) => DocumentArray:
         for d in docs:
             d.load_uri_to_blob()
-            d.tags['byte_length'] = len(d.blob) # tags must be a flat dictionary where keys are strings and values are strings, ints, floats, or bools
-            d.tags['radius'] = 'large'
             d.blob = None
         return docs
 ```
@@ -25,16 +23,16 @@ class MyInfoExecutor(Executor):
 An executor gets a DocumentArray as input and returns a DocumentArray as output. 
 '''
 
-docarray_example = '''
+docarray_example = f'''
 A DocumentArray is a python class that can be seen as a list of Documents.
 A Document is a python class that represents a single document.
 Here is the protobuf definition of a Document:
 
-message DocumentProto {
+message DocumentProto {{
   // A hexdigest that represents a unique document ID
   string id = 1;
 
-  oneof content {
+  oneof content {{
     // the raw binary content of this document, which often represents the original document when comes into jina
     bytes blob = 2;
 
@@ -43,7 +41,7 @@ message DocumentProto {
 
     // a text document
     string text = 4;
-  }
+  }}
 
   // a uri of the document is a remote url starts with http or https or data URI scheme
   string uri = 5;
@@ -56,11 +54,7 @@ message DocumentProto {
 
   // the embedding of this document
   NdArrayProto embedding = 8;
-
-  // a structured data value, consisting of field which map to dynamically typed values.
-  google.protobuf.Struct tags = 9;
-
-}
+}}
 
 Here is an example of how a DocumentArray can be defined:
 
@@ -77,7 +71,6 @@ d2 = Document(blob=obj_data) # blob is bytes like b'\\x89PNG\\r\\n\\x1a\\n\
 d3 = Document(tensor=numpy.array([1, 2, 3]), chunks=[Document(uri=/local/path/to/file)]
 d4 = Document(
    uri='https://docs.docarray.org/img/logo.png',
-   tags={'foo': 'bar'},
 )
 d5 = Document()
 d5.tensor = np.ones((2,4))
@@ -87,6 +80,10 @@ d6.blob # like b'RIFF\\x00\\x00\\x00\\x00WAVEfmt \\x10\\x00...'
 docs = DocumentArray([
    d1, d2, d3, d4
 ])
+d7 = Document()
+d7.text = 'test string'
+d8 = Document()
+d8.text = json.dumps([{{"id": "1", "text": ["hello", 'test']}}, {{"id": "2", "text": "world"}}])
 # the document has a helper function load_uri_to_blob:
 # For instance, d4.load_uri_to_blob() downloads the file from d4.uri and stores it in d4.blob. 
 # If d4.uri was something like 'https://website.web/img.jpg', then d4.blob would be something like  b'\\xff\\xd8\\xff\\xe0\\x00\\x10JFIF\\x00\\x01\\x01... 
@@ -103,7 +100,6 @@ from jina import Client, Document, DocumentArray
 client = Client(host='{FLOW_URL_PLACEHOLDER}')
 d = Document(uri='...')
 d.load_uri_to_blob()
-d.tags['style'] = 'abstract' # tags must be a flat dictionary where keys are strings and values are strings, ints, floats, or bools
 response = client.post('/', inputs=DocumentArray([d])) # the client must be called on '/'
 print(response[0].text)
 ```

src/prompt_tasks.py

@@ -7,7 +7,7 @@ def general_guidelines():
     return (
         "The code you write is production ready. "
         "Every file starts with comments describing what the code is doing before the first import. "
-        "Comments can only be written between tags. "
+        "Comments can only be written within code blocks. "
         "Then all imports are listed. "
         "It is important to import all modules that could be needed in the executor code. "
         "Always import: "
@@ -130,8 +130,9 @@ def not_allowed():
 The executor must not use the GPU.
 The executor must not access a database.
 The executor must not access a display.
-The executor must not access external apis except unless it is explicitly mentioned in the description. 
+The executor must not access external apis except unless it is explicitly mentioned in the description or test case (e.g. by mentioning the api that should be used or by providing a URL to access the data). 
 The executor must not load data from the local file system unless it was created by the executor itself.
-The executor is not allowed to use a pre-trained model unless it is explicitly mentioned in the description.
-The executor is not allowed to train a model.
+The executor must not use a pre-trained model unless it is explicitly mentioned in the description.
+The executor must not train a model.
+The executor must not use Document.tags.
 '''