mirror of
https://github.com/aljazceru/dev-gpt.git
synced 2025-12-21 15:44:19 +01:00
feat: server
This commit is contained in:
72
main.py
72
main.py
@@ -1,13 +1,11 @@
|
||||
import os
|
||||
|
||||
from docarray import DocumentArray, Document
|
||||
from jina import Client
|
||||
|
||||
from src import gpt, jina_cloud
|
||||
from src.constants import TAG_TO_FILE_NAME, EXECUTOR_FOLDER
|
||||
from src.prompt_examples import executor_example, docarray_example
|
||||
from src.constants import TAG_TO_FILE_NAME, EXECUTOR_FOLDER, CLIENT_FILE_NAME
|
||||
from src.jina_cloud import run_client_file
|
||||
from src.prompt_examples import executor_example, docarray_example, client_example
|
||||
from src.prompt_tasks import general_guidelines, executor_file_task, requirements_file_task, \
|
||||
test_executor_file_task, docker_file_task
|
||||
test_executor_file_task, docker_file_task, client_file_task
|
||||
from src.utils.io import recreate_folder
|
||||
from src.utils.string import find_between, clean_content
|
||||
|
||||
@@ -37,27 +35,50 @@ metas:
|
||||
with open('executor/config.yml', 'w') as f:
|
||||
f.write(config_content)
|
||||
|
||||
def get_all_executor_files_with_content():
|
||||
folder_path = 'executor'
|
||||
file_name_to_content = {}
|
||||
for filename in os.listdir(folder_path):
|
||||
file_path = os.path.join(folder_path, filename)
|
||||
|
||||
def main(executor_name, input_executor_description, input_test_description):
|
||||
if os.path.isfile(file_path):
|
||||
with open(file_path, 'r', encoding='utf-8') as file:
|
||||
content = file.read()
|
||||
file_name_to_content[filename] = content
|
||||
|
||||
return file_name_to_content
|
||||
|
||||
def main(
|
||||
executor_name,
|
||||
input_executor_description,
|
||||
input_modality,
|
||||
input_doc_field,
|
||||
output_modality,
|
||||
output_doc_field,
|
||||
input_test_in,
|
||||
input_test_out
|
||||
):
|
||||
recreate_folder(EXECUTOR_FOLDER)
|
||||
system_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
|
||||
)
|
||||
|
||||
user_query = (
|
||||
input_executor_description
|
||||
+ general_guidelines
|
||||
+ executor_file_task()
|
||||
+ test_executor_file_task(executor_name)
|
||||
general_guidelines()
|
||||
+ executor_file_task(executor_name, input_executor_description, input_modality, input_doc_field,
|
||||
output_modality, output_doc_field)
|
||||
+ test_executor_file_task(executor_name, input_test_in, input_test_out)
|
||||
+ requirements_file_task()
|
||||
+ docker_file_task()
|
||||
+ input_test_description
|
||||
+ client_file_task()
|
||||
)
|
||||
|
||||
plain_text = gpt.get_response(system_definition, user_query)
|
||||
|
||||
extract_and_write(plain_text)
|
||||
|
||||
write_config_yml(executor_name)
|
||||
@@ -66,26 +87,19 @@ def main(executor_name, input_executor_description, input_test_description):
|
||||
|
||||
host = jina_cloud.deploy_flow(executor_name)
|
||||
|
||||
client = Client(host=host)
|
||||
run_client_file(f'executor/{CLIENT_FILE_NAME}', host)
|
||||
|
||||
d = Document(uri='data/txt.png')
|
||||
d.load_uri_to_blob()
|
||||
response = client.post('/index', inputs=DocumentArray([d]))
|
||||
response[0].summary()
|
||||
return get_all_executor_files_with_content()
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
main(
|
||||
executor_name='MyBelovedOcrExecutor',
|
||||
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). "
|
||||
),
|
||||
|
||||
input_test_description='The test downloads the image ' \
|
||||
'https://miro.medium.com/v2/resize:fit:1024/0*4ty0Adbdg4dsVBo3.png ' \
|
||||
' loads it as bytes, takes it as input to the executor and asserts that the output is "> Hello, world!_".',
|
||||
|
||||
executor_name='MyCoolOcrExecutor',
|
||||
input_executor_description="OCR detector",
|
||||
input_modality='image',
|
||||
input_doc_field='uri',
|
||||
output_modality='text',
|
||||
output_doc_field='text',
|
||||
input_test_in='https://miro.medium.com/v2/resize:fit:1024/0*4ty0Adbdg4dsVBo3.png',
|
||||
input_test_out='> Hello, world!_',
|
||||
)
|
||||
|
||||
41
server.py
Normal file
41
server.py
Normal file
@@ -0,0 +1,41 @@
|
||||
from fastapi import FastAPI
|
||||
from pydantic import BaseModel, HttpUrl
|
||||
from typing import Optional, Dict
|
||||
|
||||
from main import main
|
||||
|
||||
app = FastAPI()
|
||||
|
||||
# Define the request model
|
||||
class CreateRequest(BaseModel):
|
||||
executor_name: str
|
||||
input_executor_description: str
|
||||
input_modality: str
|
||||
input_doc_field: str
|
||||
output_modality: str
|
||||
output_doc_field: str
|
||||
input_test_in: HttpUrl
|
||||
input_test_out: str
|
||||
|
||||
# Define the response model
|
||||
class CreateResponse(BaseModel):
|
||||
result: Dict[str, str]
|
||||
success: bool
|
||||
message: Optional[str]
|
||||
|
||||
@app.post("/create", response_model=CreateResponse)
|
||||
async def create_endpoint(request: CreateRequest):
|
||||
try:
|
||||
result = main(
|
||||
executor_name=request.executor_name,
|
||||
input_executor_description=request.input_executor_description,
|
||||
input_modality=request.input_modality,
|
||||
input_doc_field=request.input_doc_field,
|
||||
output_modality=request.output_modality,
|
||||
output_doc_field=request.output_doc_field,
|
||||
input_test_in=request.input_test_in,
|
||||
input_test_out=request.input_test_out,
|
||||
)
|
||||
return CreateResponse(result=result, success=True, message=None)
|
||||
except Exception as e:
|
||||
return CreateResponse(result=None, success=False, message=str(e))
|
||||
@@ -2,17 +2,21 @@ EXECUTOR_FILE_NAME = 'executor.py'
|
||||
TEST_EXECUTOR_FILE_NAME = 'test_executor.py'
|
||||
REQUIREMENTS_FILE_NAME = 'requirements.txt'
|
||||
DOCKER_FILE_NAME = 'Dockerfile'
|
||||
CLIENT_FILE_NAME = 'client.py'
|
||||
|
||||
EXECUTOR_FILE_TAG = 'executor'
|
||||
TEST_EXECUTOR_FILE_TAG = 'test_executor'
|
||||
REQUIREMENTS_FILE_TAG = 'requirements'
|
||||
DOCKER_FILE_TAG = 'dockerfile'
|
||||
CLIENT_FILE_TAG = 'client'
|
||||
|
||||
TAG_TO_FILE_NAME = {
|
||||
EXECUTOR_FILE_TAG: EXECUTOR_FILE_NAME,
|
||||
TEST_EXECUTOR_FILE_TAG: TEST_EXECUTOR_FILE_NAME,
|
||||
REQUIREMENTS_FILE_TAG: REQUIREMENTS_FILE_NAME,
|
||||
DOCKER_FILE_TAG: DOCKER_FILE_NAME
|
||||
DOCKER_FILE_TAG: DOCKER_FILE_NAME,
|
||||
CLIENT_FILE_TAG: CLIENT_FILE_NAME
|
||||
}
|
||||
|
||||
EXECUTOR_FOLDER = 'executor'
|
||||
FLOW_URL_PLACEHOLDER = 'jcloud.jina.ai'
|
||||
@@ -2,9 +2,13 @@ import os
|
||||
|
||||
import openai
|
||||
|
||||
from src.utils.string import print_colored
|
||||
|
||||
openai.api_key = os.environ['OPENAI_API_KEY']
|
||||
|
||||
def get_response(system_definition, user_query):
|
||||
print_colored('system_definition', system_definition, 'magenta')
|
||||
print_colored('user_query', user_query, 'blue')
|
||||
response = openai.ChatCompletion.create(
|
||||
temperature=0,
|
||||
model="gpt-4",
|
||||
@@ -23,5 +27,5 @@ def get_response(system_definition, user_query):
|
||||
]
|
||||
)
|
||||
content = response['choices'][0]['message']['content']
|
||||
print(content)
|
||||
print_colored('agent response', content, 'green')
|
||||
return content
|
||||
@@ -1,9 +1,12 @@
|
||||
import os
|
||||
from multiprocessing.connection import Client
|
||||
|
||||
import hubble
|
||||
from jcloud.flow import CloudFlow
|
||||
from jina import Flow
|
||||
|
||||
from src.constants import FLOW_URL_PLACEHOLDER
|
||||
|
||||
|
||||
def push_executor():
|
||||
cmd = 'jina hub push executor/. --verbose'
|
||||
@@ -46,4 +49,24 @@ executors:
|
||||
with flow:
|
||||
pass
|
||||
|
||||
return CloudFlow(path=full_flow_path).__enter__().endpoints['gateway']
|
||||
return CloudFlow(path=full_flow_path).__enter__().endpoints['gateway']
|
||||
|
||||
def replace_client_line(file_content: str, replacement: str) -> str:
|
||||
lines = file_content.split('\n')
|
||||
for index, line in enumerate(lines):
|
||||
if 'Client(' in line:
|
||||
lines[index] = replacement
|
||||
break
|
||||
return '\n'.join(lines)
|
||||
|
||||
def run_client_file(file_path, host):
|
||||
with open(file_path, 'r') as file:
|
||||
content = file.read()
|
||||
|
||||
replaced_content = replace_client_line(content, f"client = Client(host='{host}')")
|
||||
|
||||
|
||||
with open(file_path, 'w') as file:
|
||||
file.write(replaced_content)
|
||||
|
||||
import executor.client # runs the client script for validation
|
||||
|
||||
@@ -1,3 +1,5 @@
|
||||
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:"
|
||||
'''
|
||||
|
||||
@@ -14,7 +16,7 @@ class MyExecutor(Executor):
|
||||
d.text = 'hello world'"
|
||||
return docs
|
||||
'''
|
||||
"An executor gets a DocumentArray as input and returns a DocumentArray as output."
|
||||
"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. "
|
||||
@@ -60,7 +62,7 @@ message DocumentProto {
|
||||
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...')
|
||||
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',
|
||||
@@ -69,9 +71,24 @@ d4 = Document(
|
||||
d5 = Document()
|
||||
d5.tensor = np.ones((2,4))
|
||||
d6 = Document()
|
||||
d6.blob = b'RIFF\x00\x00\x00\x00WAVEfmt \x10\x00...'
|
||||
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()
|
||||
''')
|
||||
@@ -1,36 +1,51 @@
|
||||
from src.constants import EXECUTOR_FILE_NAME, REQUIREMENTS_FILE_NAME, TEST_EXECUTOR_FILE_NAME, DOCKER_FILE_NAME, \
|
||||
DOCKER_FILE_TAG
|
||||
DOCKER_FILE_TAG, CLIENT_FILE_TAG, CLIENT_FILE_NAME
|
||||
|
||||
general_guidelines = (
|
||||
"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. "
|
||||
"Start from top-level and then fully implement all methods."
|
||||
)
|
||||
|
||||
def general_guidelines():
|
||||
return (
|
||||
"General guidelines: "
|
||||
"The code you write is production ready. "
|
||||
"Every file starts with comments describing what the code is doing before the first import. "
|
||||
"Then all imports are listed. It is important to import all modules that could be needed in the executor code."
|
||||
"Comments can only be written between tags. "
|
||||
"Start from top-level and then fully implement all methods. "
|
||||
"\n"
|
||||
)
|
||||
|
||||
|
||||
def _task(task, tag_name, file_name):
|
||||
return task + f"The code will go into {file_name}. Wrap the code in the string $$$start_{tag_name}$$$...$$$end_{tag_name}$$$ "
|
||||
return task + f"The code will go into {file_name}. Wrap the code in the string $$$start_{tag_name}$$$...$$$end_{tag_name}$$$ \n\n"
|
||||
|
||||
|
||||
|
||||
def executor_file_task():
|
||||
return _task("Write the executor code. ", 'executor', EXECUTOR_FILE_NAME)
|
||||
def executor_file_task(executor_name, input_executor_description, input_modality, input_doc_field,
|
||||
output_modality, output_doc_field):
|
||||
return _task(
|
||||
f"Write the executor called '{executor_name}'. "
|
||||
f"It matches the following description: '{input_executor_description}'. "
|
||||
f"It gets a DocumentArray as input where each document has the input modality '{input_modality}' that is stored in document.{input_doc_field}. "
|
||||
f"It returns a DocumentArray as output where each document has the output modality '{output_modality}' that is stored in document.{output_doc_field}. ",
|
||||
'executor',
|
||||
EXECUTOR_FILE_NAME
|
||||
)
|
||||
|
||||
|
||||
def requirements_file_task():
|
||||
return _task("Write the content of the requirements.txt file. "
|
||||
"Make sure to include pytest. "
|
||||
"All versions are fixed. " , 'requirements',
|
||||
"All versions are fixed. ", 'requirements',
|
||||
REQUIREMENTS_FILE_NAME)
|
||||
|
||||
|
||||
def test_executor_file_task(executor_name):
|
||||
def test_executor_file_task(executor_name, input_test_in, input_test_out):
|
||||
return _task(
|
||||
"Write a small unit test for the executor. "
|
||||
"Start the test with an extensive comment about the test case. "
|
||||
"Use the following import to import the executor: "
|
||||
f"from executor import {executor_name}",
|
||||
+ (
|
||||
"Test that the executor converts the input '" + input_test_in + "' to the output '" + input_test_out + "'. "
|
||||
) if input_test_in and input_test_out else ""
|
||||
"Use the following import to import the executor: "
|
||||
f"from executor import {executor_name} ",
|
||||
'test_executor',
|
||||
TEST_EXECUTOR_FILE_NAME
|
||||
)
|
||||
@@ -48,3 +63,9 @@ def docker_file_task():
|
||||
"The Dockerfile runs the test during the build process. "
|
||||
, DOCKER_FILE_TAG, DOCKER_FILE_NAME)
|
||||
|
||||
|
||||
def client_file_task():
|
||||
return _task(
|
||||
"Write the client file. "
|
||||
, CLIENT_FILE_TAG, CLIENT_FILE_NAME
|
||||
)
|
||||
|
||||
@@ -9,3 +9,26 @@ def find_between(input_string, start, end):
|
||||
|
||||
def clean_content(content):
|
||||
return content.replace('```', '').strip()
|
||||
|
||||
def print_colored(headline, text, color_code):
|
||||
if color_code == 'black':
|
||||
color_code = '30'
|
||||
elif color_code == 'red':
|
||||
color_code = '31'
|
||||
elif color_code == 'green':
|
||||
color_code = '32'
|
||||
elif color_code == 'yellow':
|
||||
color_code = '33'
|
||||
elif color_code == 'blue':
|
||||
color_code = '34'
|
||||
elif color_code == 'magenta':
|
||||
color_code = '35'
|
||||
elif color_code == 'cyan':
|
||||
color_code = '36'
|
||||
elif color_code == 'white':
|
||||
color_code = '37'
|
||||
color_start = f"\033[{color_code}m"
|
||||
reset = "\033[0m"
|
||||
bold_start = "\033[1m"
|
||||
print(f"{bold_start}{color_start}{headline}{reset}")
|
||||
print(f"{color_start}{text}{reset}")
|
||||
|
||||
Reference in New Issue
Block a user