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fix: prompts

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This commit is contained in:
Florian Hönicke
2023-03-18 01:30:50 +01:00
parent 06a0ecc6c1
commit d84cc8ee04
5 changed files with 71 additions and 49 deletions
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1
.gitignore vendored Normal file
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@@ -0,0 +1 @@
/executor/

19
README.md
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@@ -1,6 +1,21 @@
# vision
# 🔮 vision
create, deploy and update your microservice infrastructure
# frontend description
# 🏗 frontend description
The microchain-frontend is used to define the graph of microservice, their interfaces and their functionality.
Based on this definition, the backend will be generated automatically.
# 🏗 usage single microservice
## you provide
- input_modality
- output_modality
- description of the functionality of the transformation the microservice is handling
- examples of input and output pairs
## you get
- a microservice together with a playground
# 🤏 limitations for now
- stateless microservices only
- deterministic microservices only to make sure input and output pairs can be used

67
main.py
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@@ -6,77 +6,51 @@ from docarray import DocumentArray, Document
from jcloud.flow import CloudFlow
from jina import Client
from prompt_examples import executor_example, docarray_example
openai.api_key = os.environ['OPENAI_API_KEY']
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 " \
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 " \
"and returns the texts as output (as DocumentArray). "
test_description = 'The test downloads the image ' \
'https://double-rhyme.com/logo_en_white2.png ' \
input_test_description = 'The test downloads the image ' \
'https://upload.wikimedia.org/wikipedia/commons/thumb/a/aa/Onlineocr.png/640px-Onlineocr.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",
model="gpt-4",
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. 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, Deployment
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."
"Here is an example of how a DocumentArray can be defined:"
'''
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',
tags={'foo': 'bar'},
)
docs = DocumentArray([
d1, d2, d3, d4
])
'''
"these imports are needed:"
'''
from jina import DocumentArray, Document
'''
+ executor_example
+ docarray_example
},
{
"role": "user",
"content":
executor_description
input_executor_description
+ "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."
"First, write the executor name. (wrap the code in the string $$$start_executor_name$$$...$$$end_executor_name$$$) "
"The executor name only consists of lower case and upper case letters. "
"Then, write the executor code. (wrap the code in the string $$$start_executor$$$ ... $$$end_executor$$$)"
"Then, write the executor code. (executor.py) (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. Start the test with an extensive comment about the test case (wrap the code in the string $$$start_test_executor$$$ ... $$$end_test_executor$$$)"
"Then write a small unit test for the executor (test_executor.py). Start the test with an extensive comment about the test case. "
"Never do relative imports."
"(wrap the code in the string $$$start_test_executor$$$ ... $$$end_test_executor$$$)"
"Comments can only be written between tags."
# "the snipped should take the local file wolf.obj as input and save the output as png files. "
+ test_description
+ input_test_description
+ "Finally write the Dockerfile that defines the environment with all necessary dependencies that the executor uses. "
'First start with comments that give an executor-specific description the Dockerfile. '
"It is important to make sure that all libs are installed that are required by the python packages. "
"The base image of the Dockerfile is FROM jinaai/jina:3.14.2-dev18-py310-standard. "
'The entrypoint is ENTRYPOINT ["jina", "executor", "--uses", "config.yml"]'
# "The Dockerfile runs the test during the build process. "
'The entrypoint is ENTRYPOINT ["jina", "executor", "--uses", "config.yml"] '
"The Dockerfile runs the test during the build process. "
"(wrap the code in the string $$$start_dockerfile$$$ ... $$$end_dockerfile$$$)"
},
@@ -115,7 +89,7 @@ def recreate_folder(folder_path):
folder = 'executor'
recreate_folder(folder)
for tag, file_name in [['executor', f'{executor_name}.py'], ['requirements', 'requirements.txt'], ['test_executor', 'test_OCRDetectorExecutor.py'], ['dockerfile', 'Dockerfile']]:
for tag, file_name in [['executor', f'executor.py'], ['requirements', 'requirements.txt'], ['test_executor', 'test_executor.py'], ['dockerfile', 'Dockerfile']]:
content = find_between(plain_text, f'$$$start_{tag}$$$', f'$$$end_{tag}$$$')
clean = clean_content(content)
full_path = os.path.join(folder, file_name)
@@ -125,7 +99,7 @@ for tag, file_name in [['executor', f'{executor_name}.py'], ['requirements', 're
config_content = f'''
jtype: {executor_name}
py_modules:
- {executor_name}.py
- executor.py
metas:
name: {executor_name}
'''
@@ -164,7 +138,6 @@ full_flow_path = os.path.join('executor', 'flow.yml')
with open(full_flow_path, 'w') as f:
f.write(flow)
exit(0)
cloud_flow = CloudFlow(path=full_flow_path).__enter__()
host = cloud_flow.endpoints['gateway']
client = Client(host=host)

33
prompt_examples.py Normal file
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@@ -0,0 +1,33 @@
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, Deployment
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 = "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',
tags={'foo': 'bar'},
)
docs = DocumentArray([
d1, d2, d3, d4
])
'''

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prompt_tasks.py Normal file
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