feat: chain of thought

src/prompt_system.py

@@ -0,0 +1,104 @@
+from src.constants import FLOW_URL_PLACEHOLDER
+
+executor_example = "Here is an example of how an executor can be defined. It always starts with a comment:"
+'''
+
+# this executor takes ... as input and returns ... as output
+# it processes each document in the following way: ...
+from jina import Executor, requests, DocumentArray, Document
+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
+'''
+"An executor gets a DocumentArray as input and returns a DocumentArray as output. "
+
+docarray_example = (
+    "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 {
+  // A hexdigest that represents a unique document ID
+  string id = 1;
+
+  oneof content {
+    // the raw binary content of this document, which often represents the original document when comes into jina
+    bytes blob = 2;
+
+    // the ndarray of the image/audio/video document
+    NdArrayProto tensor = 3;
+
+    // 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;
+
+  // list of the sub-documents of this document (recursive structure)
+  repeated DocumentProto chunks = 6;
+
+  // the matched documents on the same level (recursive structure)
+  repeated DocumentProto matches = 7;
+
+  // 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: "
+'''
+
+from jina import DocumentArray, Document
+
+d1 = Document(text='hello')
+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...')
+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))
+d5.uri = 'https://audio.com/audio.mp3'
+d6 = Document()
+d6.blob = b'RIFF\\x00\\x00\\x00\\x00WAVEfmt \\x10\\x00...'
+docs = DocumentArray([
+   d1, d2, d3, d4
+])
+# 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... 
+'''
+)
+
+client_example = (
+"After the executor is deployed, it can be called via Jina Client. "
+"Here is an example of a client file: "
+f'''
+from jina import Client, Document, DocumentArray
+client = Client(host='{FLOW_URL_PLACEHOLDER}')
+d = Document(uri='data/img.png')
+d.load_uri_to_blob()
+response = client.post('/process', inputs=DocumentArray([d]))
+response[0].summary()
+''')
+
+
+system_base_definition = (
+        "You are a principal engineer working at Jina - an open source company."
+        "Using the Jina framework, users can define executors. "
+        + executor_example
+        + docarray_example
+        + client_example
+)