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feat: stable

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This commit is contained in:
Florian Hönicke
2023-03-28 14:53:05 +02:00
parent 50f47e91b2
commit 11dbc8b162
3 changed files with 166 additions and 82 deletions
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160
micro_chain.py
View File

@@ -1,10 +1,9 @@
import random
from main import extract_content_from_result, write_config_yml, get_all_executor_files_with_content, files_to_string
from src import gpt, jina_cloud
from src.constants import FILE_AND_TAG_PAIRS
from src.jina_cloud import build_docker
from src.jina_cloud import push_executor, process_error_message
from src.prompt_tasks import general_guidelines, executor_file_task, chain_of_thought_creation, test_executor_file_task, \
chain_of_thought_optimization, requirements_file_task, docker_file_task, not_allowed
from src.utils.io import recreate_folder, persist_file
@@ -15,35 +14,33 @@ def wrap_content_in_code_block(executor_content, file_name, tag):
return f'**{file_name}**\n```{tag}\n{executor_content}\n```\n\n'
def create_executor(
executor_description,
input_modality,
output_modality,
test_scenario,
executor_name
executor_name,
is_chain_of_thought=False,
):
input_doc_field = 'text' if input_modality == 'text' else 'blob'
output_doc_field = 'text' if output_modality == 'text' else 'blob'
# random integer at the end of the executor name to avoid name clashes
recreate_folder('executor')
EXECUTOR_FOLDER_v1 = 'executor/v1'
recreate_folder(EXECUTOR_FOLDER_v1)
recreate_folder('flow')
print_colored('', '############# Executor #############', 'red')
user_query = (
general_guidelines()
+ executor_file_task(executor_name, executor_description, input_modality, input_doc_field,
output_modality, output_doc_field)
+ executor_file_task(executor_name, executor_description, test_scenario)
+ chain_of_thought_creation()
)
conversation = gpt.Conversation()
conversation.query(user_query)
executor_content_raw = conversation.query(f"General rules: " + not_allowed() + chain_of_thought_optimization('python', 'executor.py'))
executor_content_raw = conversation.query(user_query)
if is_chain_of_thought:
executor_content_raw = conversation.query(
f"General rules: " + not_allowed() + chain_of_thought_optimization('python', 'executor.py'))
executor_content = extract_content_from_result(executor_content_raw, 'executor.py')
persist_file(executor_content, EXECUTOR_FOLDER_v1 + '/executor.py')
print_colored('', '############# Test Executor #############', 'red')
@@ -53,12 +50,13 @@ def create_executor(
+ test_executor_file_task(executor_name, test_scenario)
)
conversation = gpt.Conversation()
conversation.query(user_query)
test_executor_content_raw = conversation.query(
f"General rules: " + not_allowed() +
chain_of_thought_optimization('python', 'test_executor.py')
+ "Don't add any additional tests. "
)
test_executor_content_raw = conversation.query(user_query)
if is_chain_of_thought:
test_executor_content_raw = conversation.query(
f"General rules: " + not_allowed() +
chain_of_thought_optimization('python', 'test_executor.py')
+ "Don't add any additional tests. "
)
test_executor_content = extract_content_from_result(test_executor_content_raw, 'test_executor.py')
persist_file(test_executor_content, EXECUTOR_FOLDER_v1 + '/test_executor.py')
@@ -70,8 +68,10 @@ def create_executor(
+ requirements_file_task()
)
conversation = gpt.Conversation()
conversation.query(user_query)
requirements_content_raw = conversation.query(chain_of_thought_optimization('', 'requirements.txt') + "Keep the same version of jina ")
requirements_content_raw = conversation.query(user_query)
if is_chain_of_thought:
requirements_content_raw = conversation.query(
chain_of_thought_optimization('', 'requirements.txt') + "Keep the same version of jina ")
requirements_content = extract_content_from_result(requirements_content_raw, 'requirements.txt')
persist_file(requirements_content, EXECUTOR_FOLDER_v1 + '/requirements.txt')
@@ -85,13 +85,16 @@ def create_executor(
+ docker_file_task()
)
conversation = gpt.Conversation()
conversation.query(user_query)
dockerfile_content_raw = conversation.query(f"General rules: " + not_allowed() + chain_of_thought_optimization('dockerfile', 'Dockerfile'))
dockerfile_content_raw = conversation.query(user_query)
if is_chain_of_thought:
dockerfile_content_raw = conversation.query(
f"General rules: " + not_allowed() + chain_of_thought_optimization('dockerfile', 'Dockerfile'))
dockerfile_content = extract_content_from_result(dockerfile_content_raw, 'Dockerfile')
persist_file(dockerfile_content, EXECUTOR_FOLDER_v1 + '/Dockerfile')
write_config_yml(executor_name, EXECUTOR_FOLDER_v1)
def create_playground(executor_name, executor_path, host):
print_colored('', '############# Playground #############', 'red')
@@ -112,33 +115,40 @@ print(response[0].text) # can also be blob in case of image/audio..., this shoul
)
conversation = gpt.Conversation()
conversation.query(user_query)
playground_content_raw = conversation.query(f"General rules: " + not_allowed() + chain_of_thought_optimization('python', 'playground.py'))
playground_content_raw = conversation.query(
f"General rules: " + not_allowed() + chain_of_thought_optimization('python', 'playground.py'))
playground_content = extract_content_from_result(playground_content_raw, 'playground.py')
persist_file(playground_content, f'{executor_path}/playground.py')
def debug_executor():
for i in range(1, 20):
error = build_docker(f'executor/v{i}')
def debug_executor():
MAX_DEBUGGING_ITERATIONS = 20
error_before = ''
for i in range(1, MAX_DEBUGGING_ITERATIONS):
# error_docker = build_docker(f'executor/v{i}')
log_hubble = push_executor(f'executor/v{i}')
error = process_error_message(log_hubble)
if error:
recreate_folder(f'executor/v{i + 1}')
file_name_to_content = get_all_executor_files_with_content(f'executor/v{i}')
all_files_string = files_to_string(file_name_to_content)
user_query = (
f"General rules: " + not_allowed()
+ 'Here are all the files I use:\n'
+ all_files_string
+ 'I got the following error:\n'
+ error + '\n'
+ 'Think quickly about possible reasons. '
'Then output the files that need change. '
"Don't output files that don't need change. "
"If you output a file, then write the complete file. "
"Use the exact same syntax to wrap the code:\n"
f"**...**\n"
f"```...\n"
f"...code...\n"
f"```\n\n"
f"General rules: " + not_allowed()
+ 'Here are all the files I use:\n'
+ all_files_string
+ (('This is an error that is already fixed before:\n'
+ error_before) if error_before else '')
+ '\n\nNow, I get the following error:\n'
+ error + '\n'
+ 'Think quickly about possible reasons. '
'Then output the files that need change. '
"Don't output files that don't need change. "
"If you output a file, then write the complete file. "
"Use the exact same syntax to wrap the code:\n"
f"**...**\n"
f"```...\n"
f"...code...\n"
f"```\n\n"
)
conversation = gpt.Conversation()
returned_files_raw = conversation.query(user_query)
@@ -149,8 +159,12 @@ def debug_executor():
for file_name, content in file_name_to_content.items():
persist_file(content, f'executor/v{i + 1}/{file_name}')
error_before = error
else:
break
if i == MAX_DEBUGGING_ITERATIONS - 1:
raise Exception('Could not debug the executor.')
return f'executor/v{i}'
@@ -161,31 +175,48 @@ def main(
test_scenario,
):
executor_name = f'MicroChainExecutor{random.randint(0, 1000_000)}'
create_executor(executor_description, input_modality, output_modality, test_scenario, executor_name)
create_executor(executor_description, test_scenario, executor_name)
# executor_name = 'MicroChainExecutor790050'
executor_path = debug_executor()
print('Executor can be built locally, now we will push it to the cloud.')
jina_cloud.push_executor(executor_path)
# print('Executor can be built locally, now we will push it to the cloud.')
# jina_cloud.push_executor(executor_path)
print('Deploy a jina flow')
host = jina_cloud.deploy_flow(executor_name, 'flow')
print(f'Flow is deployed create the playground for {host}')
executor_name = 'MicroChainExecutor48442'
executor_path = 'executor/v2'
host = 'grpcs://mybelovedocrflow-24a412bc63.wolf.jina.ai'
create_playground(executor_name, executor_path, host)
print(
'Executor name:', executor_name, '\n',
'Executor path:', executor_path, '\n',
'Host:', host, '\n',
'Playground:', f'streamlit run {executor_path}/playground.py', '\n',
)
if __name__ == '__main__':
# ######## Level 1 task #########
main(
executor_description="The executor takes a pdf file as input, parses it and returns the text.",
input_modality='pdf',
output_modality='text',
test_scenario='Takes https://www2.deloitte.com/content/dam/Deloitte/de/Documents/about-deloitte/Deloitte-Unternehmensgeschichte.pdf and returns a string that is at least 100 characters long',
)
# money prompt: $0.56
# money generation: $0.22
# total money: $0.78
# main(
# executor_description="The executor takes a pdf file as input, parses it and returns the text.",
# input_modality='pdf',
# output_modality='text',
# test_scenario='Takes https://www2.deloitte.com/content/dam/Deloitte/de/Documents/about-deloitte/Deloitte-Unternehmensgeschichte.pdf and returns a string that is at least 100 characters long',
# )
main(
executor_description="The executor takes a url of a website as input and returns the logo of the website as an image.",
input_modality='url',
output_modality='image',
test_scenario='Takes https://jina.ai/ as input and returns an svg image of the logo.',
)
# # # ######## Level 1 task #########
# main(
# executor_description="The executor takes a pdf file as input, parses it and returns the text.",
# input_modality='pdf',
# output_modality='text',
# test_scenario='Takes https://www2.deloitte.com/content/dam/Deloitte/de/Documents/about-deloitte/Deloitte-Unternehmensgeschichte.pdf and returns a string that is at least 100 characters long',
# )
# ######## Level 2 task #########
# main(
# executor_description="OCR detector",
@@ -194,13 +225,12 @@ if __name__ == '__main__':
# test_scenario='Takes https://miro.medium.com/v2/resize:fit:1024/0*4ty0Adbdg4dsVBo3.png as input and returns a string that contains "Hello, world"',
# )
# ######## Level 3 task #########
# main(
# executor_description="The executor takes an mp3 file as input and returns bpm and pitch in the tags.",
# executor_description="The executor takes an mp3 file as input and returns bpm and pitch in a json.",
# input_modality='audio',
# output_modality='tags',
# test_scenario='Takes https://miro.medium.com/v2/resize:fit:1024/0*4ty0Adbdg4dsVBo3.png as input and returns a string that contains "Hello, world"',
# output_modality='json',
# test_scenario='Takes https://miro.medium.com/v2/resize:fit:1024/0*4ty0Adbdg4dsVBo3.png as input and returns a json with bpm and pitch',
# )
######### Level 4 task #########
@@ -212,3 +242,11 @@ if __name__ == '__main__':
# test_scenario='Test that 3d object from https://raw.githubusercontent.com/polygonjs/polygonjs-assets/master/models/wolf.obj '
# 'is put in and out comes a 2d rendering of it',
# )
# ######## Level 8 task #########
# main(
# executor_description="The executor takes an image as input and returns a list of bounding boxes of all animals in the image.",
# input_modality='blob',
# output_modality='json',
# test_scenario='Take the image from https://thumbs.dreamstime.com/b/dog-professor-red-bow-tie-glasses-white-background-isolated-dog-professor-glasses-197036807.jpg as input and assert that the list contains at least one bounding box. ',
# )

85
src/jina_cloud.py
View File

@@ -1,16 +1,59 @@
import hashlib
import json
import os
import subprocess
import re
from argparse import Namespace
from pathlib import Path
import hubble
from hubble.executor.helper import upload_file, archive_package, get_request_header
from jcloud.flow import CloudFlow
from jina import Flow
def push_executor(dir_path):
cmd = f'jina hub push {dir_path}/. --verbose --replay'
os.system(cmd)
dir_path = Path(dir_path)
md5_hash = hashlib.md5()
bytesio = archive_package(dir_path)
content = bytesio.getvalue()
md5_hash.update(content)
md5_digest = md5_hash.hexdigest()
form_data = {
'public': 'True',
'private': 'False',
'verbose': 'True',
'md5sum': md5_digest,
}
req_header = get_request_header()
resp = upload_file(
'https://api.hubble.jina.ai/v2/rpc/executor.push',
'filename',
content,
dict_data=form_data,
headers=req_header,
stream=False,
method='post',
)
json_lines_str = resp.content.decode('utf-8')
if 'exited on non-zero code' not in json_lines_str:
return ''
responses = []
for json_line in json_lines_str.splitlines():
if 'exit code:' in json_line:
break
d = json.loads(json_line)
if 'payload' in d and type(d['payload']) == str:
responses.append(d['payload'])
elif type(d) == str:
responses.append(d)
return '\n'.join(responses)
def get_user_name():
client = hubble.Client(max_retries=None, jsonify=True)
@@ -51,10 +94,10 @@ executors:
with open(full_flow_path, 'w') as f:
f.write(flow)
print('try local execution')
flow = Flow.load_config(full_flow_path)
with flow:
pass
# print('try local execution')
# flow = Flow.load_config(full_flow_path)
# with flow:
# pass
print('deploy flow on jcloud')
return deploy_on_jcloud(flow_yaml=full_flow_path)
@@ -78,22 +121,24 @@ def update_client_line_in_file(file_path, host):
file.write(replaced_content)
def process_error_message(error_message):
lines = error_message.split('\n')
relevant_lines = []
pattern = re.compile(r"^#\d+ \[[ \d]+/[ \d]+\]") # Pattern to match lines like "#11 [7/8]"
last_matching_line_index = None
for index, line in enumerate(lines):
if pattern.match(line):
last_matching_line_index = index
if last_matching_line_index is not None:
relevant_lines = lines[last_matching_line_index:]
return '\n'.join(relevant_lines[-25:])
def build_docker(path):
def process_error_message(error_message):
lines = error_message.split('\n')
relevant_lines = []
pattern = re.compile(r"^#\d+ \[[ \d]+/[ \d]+\]") # Pattern to match lines like "#11 [7/8]"
last_matching_line_index = None
for index, line in enumerate(lines):
if pattern.match(line):
last_matching_line_index = index
if last_matching_line_index is not None:
relevant_lines = lines[last_matching_line_index:]
return '\n'.join(relevant_lines)
# The command to build the Docker image
cmd = f"docker build -t micromagic {path}"

3
src/prompt_tasks.py
View File

@@ -27,11 +27,12 @@ def _task(task, tag_name, file_name):
)
def executor_file_task(executor_name, executor_description, input_modality, input_doc_field,
def executor_file_task(executor_name, executor_description, test_scenario, input_modality, input_doc_field,
output_modality, output_doc_field):
return _task(f'''
Write the executor called '{executor_name}'.
It matches the following description: '{executor_description}'.
It will be tested with the following scenario: '{test_scenario}'.
It gets a DocumentArray as input where each document has the input modality '{input_modality}' and can be accessed via document.{input_doc_field}.
It returns a DocumentArray as output where each document has the output modality '{output_modality}' that is stored in document.{output_doc_field}.
Have in mind that d.uri is never a path to a local file. It is always a url.