feat: new structure

2025-12-19 06:34:21 +01:00 · 2023-04-14 16:07:05 +02:00
parent e5a9336619
commit a65b5ff9df
22 changed files with 436 additions and 247 deletions
--- a/README.md
+++ b/README.md
@@ -1,8 +1,7 @@
 <h1 align="center">
-GPT Deploy: One line to create them all 🧙🚀
+GPT Deploy: One line to generate them all 🧙🚀
 </h1>

-
 <p align="center">
 <img src="res/gpt-deploy-logo.png" alt="Jina NOW logo" width="150px">
 </p>
@@ -53,21 +52,35 @@ If you set the environment variable `OPENAI_API_KEY`, the configuration step can
 Your api key must have access to gpt-4 to use this tool. 
 We are working on a way to use gpt-3.5-turbo as well.

-### Create Microservice
+### Generate Microservice
 ```bash
-gptdeploy create --description "Given a PDF, return its text" --test "https://www.africau.edu/images/default/sample.pdf"
+gptdeploy generate --description "<description of the microservice>" --test "<specification of a test scenario>" --path .
 ```
-To create your personal microservice two things are required:
+To generate your personal microservice two things are required:
 - A `description` of the task you want to accomplish.
 - A `test` scenario that ensures the microservice works as expected.
+- A `path` on the local drive where the microservice will be generated.

 The creation process should take between 5 and 15 minutes.
 During this time, GPT iteratively builds your microservice until it finds a strategy that make your test scenario pass.
-Once the microservice is created and deployed, you can test it using the generated Streamlit playground.
-The deployment is made on the Jina`s infrastructure. 
-When creating a Jina account, you get some free credits, which you can use to deploy your microservice ($0.025/hour).
-Be aware that the costs you have to pay for openai vary between $0.50 and $3.00 per microservice.
-If you run out of credits, you can purchase more.
+
+
+### Run Microservice
+```bash
+gptdeploy run --path <path to microservice>
+```
+
+### Deploy Microservice
+It is required to have a [Jina account](https://cloud.jina.ai/) to deploy your microservice.
+
+```bash
+gptdeploy deploy --microservice_path <path to microservice>
+```
+[//]: # (Once the microservice is generated and deployed, you can test it using the generated Streamlit playground.)
+[//]: # (The deployment is made on the Jina`s infrastructure. )
+[//]: # (When creating a Jina account, you get some free credits, which you can use to deploy your microservice &#40;$0.025/hour&#41;.)
+[//]: # (Be aware that the costs you have to pay for openai vary between $0.50 and $3.00 per microservice.)
+[//]: # (If you run out of credits, you can purchase more.)

 ### Delete Microservice
 To save credits you can delete your microservice via the following commands:
@@ -84,51 +97,51 @@ jc delete <microservice id>
 ### Animal Detector
 ```bash

-gptdeploy create --description "Given an image, return the image with bounding boxes of all animals (https://pjreddie.com/media/files/yolov3.weights, https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolov3.cfg)" --test "https://images.unsplash.com/photo-1444212477490-ca407925329e contains animals"
+gptdeploy generate --description "Given an image, return the image with bounding boxes of all animals (https://pjreddie.com/media/files/yolov3.weights, https://raw.githubusercontent.com/pjreddie/darknet/master/cfg/yolov3.cfg)" --test "https://images.unsplash.com/photo-1444212477490-ca407925329e contains animals"
 ```

 <img src="res/animal_detector_example.png" alt="Animal Detector" width="600" />

 ### Meme Generator
 ```bash
-gptdeploy create --description "Generate a meme from an image and a caption" --test "Surprised Pikachu: https://media.wired.com/photos/5f87340d114b38fa1f8339f9/master/w_1600%2Cc_limit/Ideas_Surprised_Pikachu_HD.jpg, TOP:When you discovered GPTDeploy"
+gptdeploy generate --description "Generate a meme from an image and a caption" --test "Surprised Pikachu: https://media.wired.com/photos/5f87340d114b38fa1f8339f9/master/w_1600%2Cc_limit/Ideas_Surprised_Pikachu_HD.jpg, TOP:When you discovered GPTDeploy"
 ```

 <img src="res/meme_example.png" alt="Meme Generator" width="600" />

 ### Rhyme Generator
 ```bash
-gptdeploy create --description "Given a word, return a list of rhyming words using the datamuse api" --test "hello"
+gptdeploy generate --description "Given a word, return a list of rhyming words using the datamuse api" --test "hello"
 ```
 <img src="res/rhyme_generator_example.png" alt="Rhyme Generator" width="600" />

 ### Word Cloud Generator
 ```bash
-gptdeploy create --description "Generate a word cloud from a given text" --test "Lorem ipsum dolor sit amet, consectetur adipiscing elit."
+gptdeploy generate --description "Generate a word cloud from a given text" --test "Lorem ipsum dolor sit amet, consectetur adipiscing elit."
 ```
 <img src="res/word_cloud_example.png" alt="Word Cloud Generator" width="600" />

 ### 3d model info
 ```bash
-gptdeploy create --description "Given a 3d object, return vertex count and face count" --test "https://raw.githubusercontent.com/polygonjs/polygonjs-assets/master/models/wolf.obj"
+gptdeploy generate --description "Given a 3d object, return vertex count and face count" --test "https://raw.githubusercontent.com/polygonjs/polygonjs-assets/master/models/wolf.obj"
 ```
 <img src="res/obj_info_example.png" alt="3D Model Info" width="600" />

 ### Table extraction
 ```bash
-gptdeploy create --description "Given a URL, extract all tables as csv" --test "http://www.ins.tn/statistiques/90"
+gptdeploy generate --description "Given a URL, extract all tables as csv" --test "http://www.ins.tn/statistiques/90"
 ```
 <img src="res/table_extraction_example.png" alt="Table Extraction" width="600" />

 ### Audio to mel spectrogram
 ```bash
-gptdeploy create --description "Create mel spectrograms from audio file" --test "https://cdn.pixabay.com/download/audio/2023/02/28/audio_550d815fa5.mp3"
+gptdeploy generate --description "Create mel spectrograms from audio file" --test "https://cdn.pixabay.com/download/audio/2023/02/28/audio_550d815fa5.mp3"
 ```
 <img src="res/audio_to_mel_example.png" alt="Audio to Mel Spectrogram" width="600" />

 ### Text to speech
 ```bash
-gptdeploy create --description "Convert text to speech" --test "Hello, welcome to GPT Deploy!"
+gptdeploy generate --description "Convert text to speech" --test "Hello, welcome to GPT Deploy!"
 ```
 <a href=res/text_to_speech_example.wav><img src="res/text_to_speech_example.png" alt="Text to Speech" width="600" /></a>

@@ -139,20 +152,20 @@ gptdeploy create --description "Convert text to speech" --test "Hello, welcome t

 ### Heatmap Generator
 ```bash
-gptdeploy create --description "Create a heatmap from an image and a list of relative coordinates" --test "https://images.unsplash.com/photo-1574786198875-49f5d09fe2d2, [[0.1, 0.2], [0.3, 0.4], [0.5, 0.6], [0.2, 0.1], [0.7, 0.2], [0.4, 0.2]]"
+gptdeploy generate --description "Create a heatmap from an image and a list of relative coordinates" --test "https://images.unsplash.com/photo-1574786198875-49f5d09fe2d2, [[0.1, 0.2], [0.3, 0.4], [0.5, 0.6], [0.2, 0.1], [0.7, 0.2], [0.4, 0.2]]"
 ```
 <img src="res/heatmap_example.png" alt="Heatmap Generator" width="600" />

 ### QR Code Generator
 ```bash
-gptdeploy create --description "Generate QR code from URL" --test "https://www.example.com"
+gptdeploy generate --description "Generate QR code from URL" --test "https://www.example.com"
 ```
 <img src="res/qr_example.png" alt="QR Code Generator" width="600" />

 ### Mandelbrot Set Visualizer

 ```bash
-gptdeploy create --description "Visualize the Mandelbrot set with custom parameters" --test "center=-0+1i, zoom=1.0, size=800x800, iterations=1000"
+gptdeploy generate --description "Visualize the Mandelbrot set with custom parameters" --test "center=-0+1i, zoom=1.0, size=800x800, iterations=1000"
 ```
 <img src="res/mandelbrot_example.png" alt="Mandelbrot Set Visualizer" width="600" />

@@ -164,7 +177,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Given a password, return a score from 1 to 10 indicating the strength of the password" --test "Pa$$w0rd => 1/5, !Akfdh%.ytRadf => 5/5")
+[//]: # (gptdeploy generate --description "Given a password, return a score from 1 to 10 indicating the strength of the password" --test "Pa$$w0rd => 1/5, !Akfdh%.ytRadf => 5/5")

 [//]: # (```)

@@ -172,7 +185,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Convert text to morse code" --test "Hello, welcome to GPT Deploy!")
+[//]: # (gptdeploy generate --description "Convert text to morse code" --test "Hello, welcome to GPT Deploy!")

 [//]: # (```)

@@ -180,7 +193,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Given an IP address, return the geolocation information" --test "142.251.46.174")
+[//]: # (gptdeploy generate --description "Given an IP address, return the geolocation information" --test "142.251.46.174")

 [//]: # (```)

@@ -188,7 +201,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Converts any currency into any other" --test "1 usd to eur")
+[//]: # (gptdeploy generate --description "Converts any currency into any other" --test "1 usd to eur")

 [//]: # (```)

@@ -196,7 +209,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Given an image, resize it to a specified width and height" --test "https://images.unsplash.com/photo-1602738328654-51ab2ae6c4ff")
+[//]: # (gptdeploy generate --description "Given an image, resize it to a specified width and height" --test "https://images.unsplash.com/photo-1602738328654-51ab2ae6c4ff")

 [//]: # (```)

@@ -204,7 +217,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Given a city, return the current weather" --test "Berlin")
+[//]: # (gptdeploy generate --description "Given a city, return the current weather" --test "Berlin")

 [//]: # (```)

@@ -213,7 +226,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Given a sudoku puzzle, return the solution" --test "[[2, 5, 0, 0, 3, 0, 9, 0, 1], [0, 1, 0, 0, 0, 4, 0, 0, 0], [4, 0, 7, 0, 0, 0, 2, 0, 8], [0, 0, 5, 2, 0, 0, 0, 0, 0], [0, 0, 0, 0, 9, 8, 1, 0, 0], [0, 4, 0, 0, 0, 3, 0, 0, 0], [0, 0, 0, 3, 6, 0, 0, 7, 2], [0, 7, 0, 0, 0, 0, 0, 0, 3], [9, 0, 3, 0, 0, 0, 6, 0, 4]]")
+[//]: # (gptdeploy generate --description "Given a sudoku puzzle, return the solution" --test "[[2, 5, 0, 0, 3, 0, 9, 0, 1], [0, 1, 0, 0, 0, 4, 0, 0, 0], [4, 0, 7, 0, 0, 0, 2, 0, 8], [0, 0, 5, 2, 0, 0, 0, 0, 0], [0, 0, 0, 0, 9, 8, 1, 0, 0], [0, 4, 0, 0, 0, 3, 0, 0, 0], [0, 0, 0, 3, 6, 0, 0, 7, 2], [0, 7, 0, 0, 0, 0, 0, 0, 3], [9, 0, 3, 0, 0, 0, 6, 0, 4]]")

 [//]: # (```)

@@ -222,7 +235,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Estimate a company's carbon footprint based on factors like transportation, electricity usage, waste production etc..." --test "Jina AI")
+[//]: # (gptdeploy generate --description "Estimate a company's carbon footprint based on factors like transportation, electricity usage, waste production etc..." --test "Jina AI")

 [//]: # (```)

@@ -231,7 +244,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Create a microservice that estimates the value of a property based on factors like location, property type, age, and square footage." --test "Berlin Friedrichshain, Flat, 100m², 10 years old")
+[//]: # (gptdeploy generate --description "Create a microservice that estimates the value of a property based on factors like location, property type, age, and square footage." --test "Berlin Friedrichshain, Flat, 100m², 10 years old")

 [//]: # (```)

@@ -240,7 +253,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Align two DNA or RNA sequences using the Needleman-Wunsch algorithm" --test "AGTC, GTCA")
+[//]: # (gptdeploy generate --description "Align two DNA or RNA sequences using the Needleman-Wunsch algorithm" --test "AGTC, GTCA")

 [//]: # (```)

@@ -249,7 +262,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Convert markdown to HTML" --test "# Hello, welcome to GPT Deploy!")
+[//]: # (gptdeploy generate --description "Convert markdown to HTML" --test "# Hello, welcome to GPT Deploy!")

 [//]: # (```)

@@ -258,7 +271,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Generate a barcode from a string" --test "Hello, welcome to GPT Deploy!")
+[//]: # (gptdeploy generate --description "Generate a barcode from a string" --test "Hello, welcome to GPT Deploy!")

 [//]: # (```)

@@ -267,7 +280,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Compress a file using the gzip algorithm" --test "content of the file: Hello, welcome to GPT Deploy!")
+[//]: # (gptdeploy generate --description "Compress a file using the gzip algorithm" --test "content of the file: Hello, welcome to GPT Deploy!")

 [//]: # (```)

@@ -276,7 +289,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Add a watermark &#40;GPT Deploy&#41; to an image" --test "https://images.unsplash.com/photo-1602738328654-51ab2ae6c4ff")
+[//]: # (gptdeploy generate --description "Add a watermark &#40;GPT Deploy&#41; to an image" --test "https://images.unsplash.com/photo-1602738328654-51ab2ae6c4ff")

 [//]: # (```)

@@ -285,7 +298,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Extract metadata from a file" --test "https://images.unsplash.com/photo-1602738328654-51ab2ae6c4ff")
+[//]: # (gptdeploy generate --description "Extract metadata from a file" --test "https://images.unsplash.com/photo-1602738328654-51ab2ae6c4ff")

 [//]: # (```)

@@ -294,7 +307,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Extract a thumbnail from a video" --test "http://techslides.com/demos/sample-videos/small.mp4")
+[//]: # (gptdeploy generate --description "Extract a thumbnail from a video" --test "http://techslides.com/demos/sample-videos/small.mp4")

 [//]: # (```)

@@ -303,7 +316,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Create a gif from a list of images" --test "https://images.unsplash.com/photo-1564725075388-cc8338732289, https://images.unsplash.com/photo-1584555684040-bad07f46a21f, https://images.unsplash.com/photo-1584555613497-9ecf9dd06f68")
+[//]: # (gptdeploy generate --description "Create a gif from a list of images" --test "https://images.unsplash.com/photo-1564725075388-cc8338732289, https://images.unsplash.com/photo-1584555684040-bad07f46a21f, https://images.unsplash.com/photo-1584555613497-9ecf9dd06f68")

 [//]: # (```)

@@ -316,7 +329,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet
 [//]: # ()
 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Visualize a sound file and output the visualization as video combined with the sound" --test "some/mp3/file.mp3")
+[//]: # (gptdeploy generate --description "Visualize a sound file and output the visualization as video combined with the sound" --test "some/mp3/file.mp3")

 [//]: # (```)

@@ -326,7 +339,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Convert a chemical formula into a 2D chemical structure diagram" --test "C6H6")
+[//]: # (gptdeploy generate --description "Convert a chemical formula into a 2D chemical structure diagram" --test "C6H6")

 [//]: # (```)

@@ -334,7 +347,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "creates aesthetically pleasing color palettes based on a seed color, using color theory principles like complementary or analogous colors" --test "red")
+[//]: # (gptdeploy generate --description "creates aesthetically pleasing color palettes based on a seed color, using color theory principles like complementary or analogous colors" --test "red")

 [//]: # (```)

@@ -343,7 +356,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Generate a depth map from a 3d Object" --test "https://raw.githubusercontent.com/polygonjs/polygonjs-assets/master/models/wolf.obj")
+[//]: # (gptdeploy generate --description "Generate a depth map from a 3d Object" --test "https://raw.githubusercontent.com/polygonjs/polygonjs-assets/master/models/wolf.obj")

 [//]: # (```)

@@ -355,7 +368,7 @@ gptdeploy create --description "Visualize the Mandelbrot set with custom paramet

 [//]: # (```bash)

-[//]: # (gptdeploy create --description "Convert image to ASCII art" --test "https://images.unsplash.com/photo-1602738328654-51ab2ae6c4ff")
+[//]: # (gptdeploy generate --description "Convert image to ASCII art" --test "https://images.unsplash.com/photo-1602738328654-51ab2ae6c4ff")

 [//]: # (```)

@@ -390,7 +403,7 @@ graph TB

    registry --> deploy[deploy microservice]

-    deploy --> streamlit[create streamlit playground]
+    deploy --> streamlit[generate streamlit playground]

    streamlit --> user_run[user tests microservice]

@@ -398,21 +411,21 @@ graph TB

 1. GPT Deploy identifies several strategies to implement your task.
 2. It tests each strategy until it finds one that works.
-3. For each strategy, it creates the following files:
- executor.py: This is the main implementation of the microservice.
- test_executor.py: These are test cases to ensure the microservice works as expected.
+3. For each strategy, it generates the following files:
+- microservice.py: This is the main implementation of the microservice.
+- test_microservice.py: These are test cases to ensure the microservice works as expected.
 - requirements.txt: This file lists the packages needed by the microservice and its tests.
 - Dockerfile: This file is used to run the microservice in a container and also runs the tests when building the image.
 4. GPT Deploy attempts to build the image. If the build fails, it uses the error message to apply a fix and tries again to build the image.
 5. Once it finds a successful strategy, it:
 - Pushes the Docker image to the registry.
 - Deploys the microservice.
- Creates a Streamlit playground where you can test the microservice.
+- Generates a Streamlit playground where you can test the microservice.
 6. If it fails 10 times in a row, it moves on to the next approach.


 ## 🔮 vision
-Use natural language interface to create, deploy and update your microservice infrastructure.
+Use natural language interface to generate, deploy and update your microservice infrastructure.

 ## ✨ Contributers 
 If you want to contribute to this project, feel free to open a PR or an issue.
--- a/setup.py
+++ b/setup.py
@@ -8,7 +8,7 @@ def read_requirements():
 setup(
    name='gptdeploy',
    version='0.18.15',
-    description='Use natural language interface to create, deploy and update your microservice infrastructure.',
+    description='Use natural language interface to generate, deploy and update your microservice infrastructure.',
    long_description=open('README.md', 'r', encoding='utf-8').read(),
    long_description_content_type='text/markdown',
    author='Florian Hönicke',
--- a/src/apis/init.py
+++ b/src/apis/init.py
--- a/src/apis/gpt.py
+++ b/src/apis/gpt.py
@@ -7,13 +7,13 @@ from openai.error import RateLimitError, Timeout

 from src.constants import PRICING_GPT4_PROMPT, PRICING_GPT4_GENERATION, PRICING_GPT3_5_TURBO_PROMPT, \
    PRICING_GPT3_5_TURBO_GENERATION
-from src.prompt_system import system_base_definition
+from src.options.generate.prompt_system import system_base_definition
 from src.utils.io import timeout_generator_wrapper, GenerationTimeoutError
 from src.utils.string_tools import print_colored

 class GPTSession:
    def __init__(self):
-        self.get_openai_api_key()
+        self.configure_openai_api_key()
        if self.is_gpt4_available():
            self.supported_model = 'gpt-4'
            self.pricing_prompt = PRICING_GPT4_PROMPT
@@ -26,7 +26,7 @@ class GPTSession:
        self.chars_prompt_so_far = 0
        self.chars_generation_so_far = 0

-    def get_openai_api_key(self):
+    def configure_openai_api_key(self):
        if 'OPENAI_API_KEY' not in os.environ:
            raise Exception('''
 You need to set OPENAI_API_KEY in your environment.
--- a/src/apis/jina_cloud.py
+++ b/src/apis/jina_cloud.py
@@ -3,17 +3,41 @@ import json
 import os
 import re
 import subprocess
+import threading
 import webbrowser
 from pathlib import Path

+import click
 import hubble
 from hubble.executor.helper import upload_file, archive_package, get_request_header
 from jcloud.flow import CloudFlow
+from jina import Flow

-from src.utils.io import suppress_stdout
+from src.utils.io import suppress_stdout, is_docker_running
 from src.utils.string_tools import print_colored


+import requests
+import time
+
+def wait_until_app_is_ready(url):
+    is_app_ready = False
+    while not is_app_ready:
+        try:
+            response = requests.get(url)
+            print('waiting for app to be ready...')
+            if response.status_code == 200:
+                is_app_ready = True
+        except requests.exceptions.RequestException:
+            pass
+        time.sleep(0.5)
+
+def open_streamlit_app():
+    url = "http://localhost:8081/playground"
+    wait_until_app_is_ready(url)
+    webbrowser.open(url, new=2)
+
+
 def redirect_callback(href):
    print(
        f'You need login to Jina first to use GPTDeploy\n'
@@ -85,29 +109,89 @@ def get_user_name():
    return response['data']['name']


-def deploy_on_jcloud(flow_yaml):
+def _deploy_on_jcloud(flow_yaml):
    cloud_flow = CloudFlow(path=flow_yaml)
    return cloud_flow.__enter__().endpoints['gateway']


-def deploy_flow(executor_name, dest_folder):
+def deploy_on_jcloud(executor_name, microservice_path):
    print('Deploy a jina flow')
+    full_flow_path = create_flow_yaml(microservice_path, executor_name, use_docker=True)
+
+    for i in range(3):
+        try:
+            host = _deploy_on_jcloud(flow_yaml=full_flow_path)
+            break
+        except Exception as e:
+            print(f'Could not deploy on Jina Cloud. Trying again in 5 seconds. Error: {e}')
+            time.sleep(5)
+    if i == 2:
+        raise Exception('''
+            Could not deploy on Jina Cloud. 
+            This can happen when the microservice is buggy, if it requires too much memory or if the Jina Cloud is overloaded. 
+            Please try again later.
+'''
+        )
+
+    print(f'''
+Your Microservice is deployed.
+Run the following command to start the playground:
+
+streamlit run {os.path.join(microservice_path, "app.py")} --server.port 8081 --server.address 0.0.0.0 -- --host http://{host}
+'''
+          )
+    return host
+
+def run_streamlit_app(app_path):
+    subprocess.run(['streamlit', 'run', app_path, 'server.address', '0.0.0.0', '--server.port', '8081', '--', '--host', 'grpc://localhost:8080'])
+
+
+def run_locally(executor_name, microservice_version_path):
+    if is_docker_running():
+        use_docker = True
+    else:
+        click.echo('Docker daemon doesn\'t seem to be running. Trying to start it without docker')
+        use_docker = False
+    print('Run a jina flow locally')
+    full_flow_path = create_flow_yaml(microservice_version_path, executor_name, use_docker)
+    flow = Flow.load_config(full_flow_path)
+    with flow:
+        print(f'''
+Your microservice started locally.
+We now start the playground for you.
+''')
+
+        app_path = os.path.join(microservice_version_path, "app.py")
+
+        # Run the Streamlit app in a separate thread
+        streamlit_thread = threading.Thread(target=run_streamlit_app, args=(app_path,))
+        streamlit_thread.start()
+
+        # Open the Streamlit app in the user's default web browser
+        open_streamlit_app()
+
+        flow.block()
+
+def create_flow_yaml(dest_folder, executor_name, use_docker):
+    if use_docker:
+        prefix = 'jinaai+docker'
+    else:
+        prefix = 'jinaai'
    flow = f'''
 jtype: Flow
 with:
  name: nowapi
-  env:
-    JINA_LOG_LEVEL: DEBUG
+  port: 8080
 jcloud:
  version: 3.14.2.dev18
  labels:
    creator: microchain
  name: gptdeploy
+
 executors:
  - name: {executor_name.lower()}
-    uses: jinaai+docker://{get_user_name()}/{executor_name}:latest
-    env:
-      JINA_LOG_LEVEL: DEBUG
+    uses: {prefix   }://{get_user_name()}/{executor_name}:latest
+    {"" if use_docker else "install-requirements: True"}
    jcloud:
      resources:
        instance: C2
@@ -117,16 +201,7 @@ executors:
                                  'flow.yml')
    with open(full_flow_path, 'w') as f:
        f.write(flow)
-
-    for i in range(3):
-        try:
-            host = deploy_on_jcloud(flow_yaml=full_flow_path)
-            break
-        except Exception as e:
-            raise e
-
-    print(f'Flow is deployed create the playground for {host}')
-    return host
+    return full_flow_path


 def replace_client_line(file_content: str, replacement: str) -> str:
--- a/src/cli.py
+++ b/src/cli.py
@@ -1,30 +1,80 @@
+import functools
+import os
+
 import click

-from src.executor_factory import ExecutorFactory
-from src.jina_cloud import jina_auth_login
-from src.key_handling import set_api_key
+from src.apis.jina_cloud import jina_auth_login
+from src.options.configure.key_handling import set_api_key
+
+
+def exception_interceptor(func):
+    @functools.wraps(func)
+    def wrapper(*args, **kwargs):
+        try:
+            return func(*args, **kwargs)
+        except Exception as e:
+            raise type(e)(f'''
+{str(e)}
+
+😱😱😱 Sorry for this experience. Could you please report an issue about this on our github repo? We'll try to fix it asap.
+''') from e
+    return wrapper
+
+def path_param(func):
+    @click.option('--path', required=True, help='Path to the generated microservice.')
+    @functools.wraps(func)
+    def wrapper(*args, **kwargs):
+        path = os.path.expanduser(kwargs['path'])
+        path = os.path.abspath(path)
+        kwargs['path'] = path
+        return func(*args, **kwargs)
+    return wrapper


@click.group(invoke_without_command=True)
-def main():
+@click.pass_context
+@exception_interceptor
+def main(ctx):
+    if ctx.invoked_subcommand is None:
+        click.echo(ctx.get_help())
    jina_auth_login()


@main.command()
-@click.option('--description', required=True, help='Description of the executor.')
-@click.option('--test', required=True, help='Test scenario for the executor.')
-@click.option('--num_approaches', default=3, type=int,
-              help='Number of num_approaches to use to fulfill the task (default: 3).')
-@click.option('--output_path', default='executor', help='Path to the output folder (must be empty). ')
-def create(
+@click.option('--description', required=True, help='Description of the microservice.')
+@click.option('--test', required=True, help='Test scenario for the microservice.')
+@path_param
+def generate(
        description,
        test,
-        num_approaches=3,
-        output_path='executor',
+        path,
 ):
-    executor_factory = ExecutorFactory()
-    executor_factory.create(description, num_approaches, output_path, test)
+    from src.options.generate.generator import Generator
+    path = os.path.expanduser(path)
+    path = os.path.abspath(path)
+    if os.path.exists(path):
+        if os.listdir(path):
+            click.echo(f"Error: The path {path} you provided via --path is not empty. Please choose a directory that does not exist or is empty.")
+            return
+    generator = Generator()
+    generator.generate(description, test, path)

+@main.command()
+@path_param
+def run(path):
+    from src.options.run import Runner
+    path = os.path.expanduser(path)
+    path = os.path.abspath(path)
+    Runner().run(path)
+
+
+@main.command()
+@path_param
+def deploy(path):
+    from src.options.deploy.deployer import Deployer
+    path = os.path.expanduser(path)
+    path = os.path.abspath(path)
+    Deployer().deploy(path)

@main.command()
@click.option('--key', required=True, help='Your OpenAI API key.')
--- a/src/constants.py
+++ b/src/constants.py
@@ -1,5 +1,5 @@
-EXECUTOR_FILE_NAME = 'executor.py'
-TEST_EXECUTOR_FILE_NAME = 'test_executor.py'
+EXECUTOR_FILE_NAME = 'microservice.py'
+TEST_EXECUTOR_FILE_NAME = 'test_microservice.py'
 REQUIREMENTS_FILE_NAME = 'requirements.txt'
 DOCKER_FILE_NAME = 'Dockerfile'
 CLIENT_FILE_NAME = 'client.py'
@@ -21,12 +21,12 @@ FILE_AND_TAG_PAIRS = [
    (STREAMLIT_FILE_NAME, STREAMLIT_FILE_TAG)
 ]

-EXECUTOR_FOLDER_v1 = 'executor_v1'
-EXECUTOR_FOLDER_v2 = 'executor_v2'
-
 FLOW_URL_PLACEHOLDER = 'jcloud.jina.ai'

 PRICING_GPT4_PROMPT = 0.03
 PRICING_GPT4_GENERATION = 0.06
 PRICING_GPT3_5_TURBO_PROMPT = 0.002
-PRICING_GPT3_5_TURBO_GENERATION = 0.002
+PRICING_GPT3_5_TURBO_GENERATION = 0.002
+
+NUM_IMPLEMENTATION_STRATEGIES = 3
+MAX_DEBUGGING_ITERATIONS = 10
--- a/src/options/init.py
+++ b/src/options/init.py
@@ -0,0 +1,37 @@
+import os
+
+
+def get_latest_folder(path):
+    return max([os.path.join(path, f) for f in os.listdir(path) if os.path.isdir(os.path.join(path, f))])
+
+def get_latest_version_path(microservice_path):
+    executor_name_path = get_latest_folder(microservice_path)
+    latest_approach_path = get_latest_folder(executor_name_path)
+    latest_version_path = get_latest_folder(latest_approach_path)
+    return latest_version_path
+
+def get_executor_name(microservice_path):
+    return get_latest_folder(microservice_path).split('/')[-1]
+
+
+def validate_folder_is_correct(microservice_path):
+    if not os.path.exists(microservice_path):
+        raise ValueError(f'Path {microservice_path} does not exist')
+    if not os.path.isdir(microservice_path):
+        raise ValueError(f'Path {microservice_path} is not a directory')
+    if len(os.listdir(microservice_path)) == 0:
+        raise ValueError(f'Path {microservice_path} is empty. Please generate a microservice first. Type `gptdeploy generate` for further instructions.')
+    if len(os.listdir(microservice_path)) > 1:
+        raise ValueError(f'Path {microservice_path} needs to contain only one folder. Please make sure that you only have one microservice in this folder.')
+    latest_version_path = get_latest_version_path(microservice_path)
+    required_files = [
+        'app.py',
+        'requirements.txt',
+        'Dockerfile',
+        'config.yml',
+        'microservice.py',
+        'test_microservice.py',
+    ]
+    for file_name in required_files:
+        if not os.path.exists(os.path.join(latest_version_path, file_name)):
+            raise ValueError(f'Path {latest_version_path} needs to contain a file named {file_name}')
--- a/src/options/configure/init.py
+++ b/src/options/configure/init.py
--- a/src/options/configure/key_handling.py
+++ b/src/options/configure/key_handling.py
--- a/src/options/deploy/init.py
+++ b/src/options/deploy/init.py
--- a/src/options/deploy/deployer.py
+++ b/src/options/deploy/deployer.py
@@ -0,0 +1,10 @@
+from src.apis.jina_cloud import deploy_on_jcloud
+from src.options import validate_folder_is_correct, get_executor_name, get_latest_version_path
+
+
+class Deployer:
+    def deploy(self, microservice_path):
+        validate_folder_is_correct(microservice_path)
+        executor_name = get_executor_name(microservice_path)
+        latest_version_path = get_latest_version_path(microservice_path)
+        deploy_on_jcloud(executor_name, latest_version_path)
--- a/src/options/generate/init.py
+++ b/src/options/generate/init.py
--- a/src/options/generate/generator.py
+++ b/src/options/generate/generator.py
@@ -2,16 +2,16 @@ import os
 import random
 import re

-from src import gpt, jina_cloud
-from src.constants import FILE_AND_TAG_PAIRS
-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 persist_file
+from src.apis import gpt
+from src.constants import FILE_AND_TAG_PAIRS, NUM_IMPLEMENTATION_STRATEGIES, MAX_DEBUGGING_ITERATIONS
+from src.apis.jina_cloud import process_error_message, push_executor
+from src.options.generate.prompt_tasks import general_guidelines, chain_of_thought_creation, executor_file_task, \
+    not_allowed, chain_of_thought_optimization, test_executor_file_task, requirements_file_task, docker_file_task
+from src.utils.io import persist_file, get_all_microservice_files_with_content, get_microservice_path
 from src.utils.string_tools import print_colored


-class ExecutorFactory:
+class Generator:
    def __init__(self):
        self.gpt_session = gpt.GPTSession()

@@ -23,93 +23,81 @@ class ExecutorFactory:
        else:
            return ''

-    def write_config_yml(self, executor_name, dest_folder):
+    def write_config_yml(self, microservice_name, dest_folder):
        config_content = f'''
-    jtype: {executor_name}
+    jtype: {microservice_name}
    py_modules:
-      - executor.py
+      - microservice.py
    metas:
-      name: {executor_name}
+      name: {microservice_name}
        '''
        with open(os.path.join(dest_folder, 'config.yml'), 'w') as f:
            f.write(config_content)

-    def get_all_executor_files_with_content(self, folder_path):
-        file_name_to_content = {}
-        for filename in os.listdir(folder_path):
-            file_path = os.path.join(folder_path, filename)
-
-            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 files_to_string(self, file_name_to_content):
-        all_executor_files_string = ''
+        all_microservice_files_string = ''
        for file_name, tag in FILE_AND_TAG_PAIRS:
            if file_name in file_name_to_content:
-                all_executor_files_string += f'**{file_name}**\n'
-                all_executor_files_string += f'```{tag}\n'
-                all_executor_files_string += file_name_to_content[file_name]
-                all_executor_files_string += '\n```\n\n'
-        return all_executor_files_string
+                all_microservice_files_string += f'**{file_name}**\n'
+                all_microservice_files_string += f'```{tag}\n'
+                all_microservice_files_string += file_name_to_content[file_name]
+                all_microservice_files_string += '\n```\n\n'
+        return all_microservice_files_string

-    def wrap_content_in_code_block(self, executor_content, file_name, tag):
-        return f'**{file_name}**\n```{tag}\n{executor_content}\n```\n\n'
+    def wrap_content_in_code_block(self, microservice_content, file_name, tag):
+        return f'**{file_name}**\n```{tag}\n{microservice_content}\n```\n\n'

-    def create_executor(
+    def generate_microservice(
            self,
            description,
            test,
-            output_path,
-            executor_name,
+            path,
+            microservice_name,
            package,
            num_approach,
            is_chain_of_thought=False,
    ):
-        EXECUTOR_FOLDER_v1 = self.get_executor_path(output_path, executor_name, package, num_approach, 1)
-        os.makedirs(EXECUTOR_FOLDER_v1)
+        MICROSERVICE_FOLDER_v1 = get_microservice_path(path, microservice_name, package, num_approach, 1)
+        os.makedirs(MICROSERVICE_FOLDER_v1)

-        print_colored('', '############# Executor #############', 'red')
+        print_colored('', '############# Microservice #############', 'red')
        user_query = (
                general_guidelines()
-                + executor_file_task(executor_name, description, test, package)
+                + executor_file_task(microservice_name, description, test, package)
                + chain_of_thought_creation()
        )
        conversation = self.gpt_session.get_conversation()
-        executor_content_raw = conversation.query(user_query)
+        microservice_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 = self.extract_content_from_result(executor_content_raw, 'executor.py')
+            microservice_content_raw = conversation.query(
+                f"General rules: " + not_allowed() + chain_of_thought_optimization('python', 'microservice.py'))
+        microservice_content = self.extract_content_from_result(microservice_content_raw, 'microservice.py')

-        persist_file(executor_content, os.path.join(EXECUTOR_FOLDER_v1, 'executor.py'))
+        persist_file(microservice_content, os.path.join(MICROSERVICE_FOLDER_v1, 'microservice.py'))

-        print_colored('', '############# Test Executor #############', 'red')
+        print_colored('', '############# Test Microservice #############', 'red')
        user_query = (
                general_guidelines()
-                + self.wrap_content_in_code_block(executor_content, 'executor.py', 'python')
-                + test_executor_file_task(executor_name, test)
+                + self.wrap_content_in_code_block(microservice_content, 'microservice.py', 'python')
+                + test_executor_file_task(microservice_name, test)
        )
        conversation = self.gpt_session.get_conversation()
-        test_executor_content_raw = conversation.query(user_query)
+        test_microservice_content_raw = conversation.query(user_query)
        if is_chain_of_thought:
-            test_executor_content_raw = conversation.query(
+            test_microservice_content_raw = conversation.query(
                f"General rules: " + not_allowed() +
-                chain_of_thought_optimization('python', 'test_executor.py')
+                chain_of_thought_optimization('python', 'test_microservice.py')
                + "Don't add any additional tests. "
            )
-        test_executor_content = self.extract_content_from_result(test_executor_content_raw, 'test_executor.py')
-        persist_file(test_executor_content, os.path.join(EXECUTOR_FOLDER_v1, 'test_executor.py'))
+        test_microservice_content = self.extract_content_from_result(test_microservice_content_raw, 'test_microservice.py')
+        persist_file(test_microservice_content, os.path.join(MICROSERVICE_FOLDER_v1, 'test_microservice.py'))

        print_colored('', '############# Requirements #############', 'red')
-        requirements_path = os.path.join(EXECUTOR_FOLDER_v1, 'requirements.txt')
+        requirements_path = os.path.join(MICROSERVICE_FOLDER_v1, 'requirements.txt')
        user_query = (
                general_guidelines()
-                + self.wrap_content_in_code_block(executor_content, 'executor.py', 'python')
-                + self.wrap_content_in_code_block(test_executor_content, 'test_executor.py', 'python')
+                + self.wrap_content_in_code_block(microservice_content, 'microservice.py', 'python')
+                + self.wrap_content_in_code_block(test_microservice_content, 'test_microservice.py', 'python')
                + requirements_file_task()
        )
        conversation = self.gpt_session.get_conversation()
@@ -124,8 +112,8 @@ class ExecutorFactory:
        print_colored('', '############# Dockerfile #############', 'red')
        user_query = (
                general_guidelines()
-                + self.wrap_content_in_code_block(executor_content, 'executor.py', 'python')
-                + self.wrap_content_in_code_block(test_executor_content, 'test_executor.py', 'python')
+                + self.wrap_content_in_code_block(microservice_content, 'microservice.py', 'python')
+                + self.wrap_content_in_code_block(test_microservice_content, 'test_microservice.py', 'python')
                + self.wrap_content_in_code_block(requirements_content, 'requirements.txt', '')
                + docker_file_task()
        )
@@ -135,28 +123,29 @@ class ExecutorFactory:
            dockerfile_content_raw = conversation.query(
                f"General rules: " + not_allowed() + chain_of_thought_optimization('dockerfile', 'Dockerfile'))
        dockerfile_content = self.extract_content_from_result(dockerfile_content_raw, 'Dockerfile')
-        persist_file(dockerfile_content, os.path.join(EXECUTOR_FOLDER_v1, 'Dockerfile'))
+        persist_file(dockerfile_content, os.path.join(MICROSERVICE_FOLDER_v1, 'Dockerfile'))

-        self.write_config_yml(executor_name, EXECUTOR_FOLDER_v1)
-        print('First version of the executor created. Start iterating on it to make the tests pass...')
+        self.write_config_yml(microservice_name, MICROSERVICE_FOLDER_v1)
+        print('First version of the microservice generated. Start iterating on it to make the tests pass...')

-    def create_playground(self, executor_name, executor_path, host):
+    def generate_playground(self, microservice_name, microservice_path):
        print_colored('', '############# Playground #############', 'red')

-        file_name_to_content = self.get_all_executor_files_with_content(executor_path)
+        file_name_to_content = get_all_microservice_files_with_content(microservice_path)
        user_query = (
                general_guidelines()
-                + self.wrap_content_in_code_block(file_name_to_content['executor.py'], 'executor.py', 'python')
-                + self.wrap_content_in_code_block(file_name_to_content['test_executor.py'], 'test_executor.py',
+                + self.wrap_content_in_code_block(file_name_to_content['microservice.py'], 'microservice.py', 'python')
+                + self.wrap_content_in_code_block(file_name_to_content['test_microservice.py'], 'test_microservice.py',
                                                  'python')
                + f'''
-Create a playground for the executor {executor_name} using streamlit.
+Create a playground for the executor {microservice_name} using streamlit.
 The playground must look like it was made by a professional designer.
 All the ui elements are well thought out to make them visually appealing and easy to use.
-The executor is hosted on {host}. 
+The playground must be started with a custom host: streamlit run app.py -- --host grpc://...
+The playground must not let the user configure the --host grpc://... on the ui.
 This is an example how you can connect to the executor assuming the document (d) is already defined:
 from jina import Client, Document, DocumentArray
-client = Client(host='{host}')
+client = Client(host=host)
 response = client.post('/', inputs=DocumentArray([d])) # always use '/'
 print(response[0].text) # can also be blob in case of image/audio..., this should be visualized in the streamlit app
 '''
@@ -166,25 +155,21 @@ print(response[0].text) # can also be blob in case of image/audio..., this shoul
        playground_content_raw = conversation.query(
            f"General rules: " + not_allowed() + chain_of_thought_optimization('python', 'app.py'))
        playground_content = self.extract_content_from_result(playground_content_raw, 'app.py')
-        persist_file(playground_content, os.path.join(executor_path, 'app.py'))
+        persist_file(playground_content, os.path.join(microservice_path, 'app.py'))

-    def get_executor_path(self, output_path, executor_name, package, num_approach, version):
-        package_path = '_'.join(package)
-        return os.path.join(output_path, executor_name, f'{num_approach}_{package_path}', f'v{version}')

-    def debug_executor(self, output_path, executor_name, num_approach, packages, description, test):
-        MAX_DEBUGGING_ITERATIONS = 10
+    def debug_microservice(self, path, microservice_name, num_approach, packages, description, test):
        error_before = ''
        for i in range(1, MAX_DEBUGGING_ITERATIONS):
            print('Debugging iteration', i)
            print('Trying to build the microservice. Might take a while...')
-            previous_executor_path = self.get_executor_path(output_path, executor_name, packages, num_approach, i)
-            next_executor_path = self.get_executor_path(output_path, executor_name, packages, num_approach, i + 1)
-            log_hubble = push_executor(previous_executor_path)
+            previous_microservice_path = get_microservice_path(path, microservice_name, packages, num_approach, i)
+            next_microservice_path = get_microservice_path(path, microservice_name, packages, num_approach, i + 1)
+            log_hubble = push_executor(previous_microservice_path)
            error = process_error_message(log_hubble)
            if error:
-                os.makedirs(next_executor_path)
-                file_name_to_content = self.get_all_executor_files_with_content(previous_executor_path)
+                os.makedirs(next_microservice_path)
+                file_name_to_content = get_all_microservice_files_with_content(previous_microservice_path)
                all_files_string = self.files_to_string(file_name_to_content)
                user_query = (
                        f"General rules: " + not_allowed()
@@ -217,19 +202,19 @@ print(response[0].text) # can also be blob in case of image/audio..., this shoul
                        file_name_to_content[file_name] = updated_file

                for file_name, content in file_name_to_content.items():
-                    persist_file(content, os.path.join(next_executor_path, file_name))
+                    persist_file(content, os.path.join(next_microservice_path, file_name))
                error_before = error

            else:
                break
            if i == MAX_DEBUGGING_ITERATIONS - 1:
-                raise self.MaxDebugTimeReachedException('Could not debug the executor.')
-        return self.get_executor_path(output_path, executor_name, packages, num_approach, i)
+                raise self.MaxDebugTimeReachedException('Could not debug the microservice.')
+        return get_microservice_path(path, microservice_name, packages, num_approach, i)

    class MaxDebugTimeReachedException(BaseException):
        pass

-    def generate_executor_name(self, description):
+    def generate_microservice_name(self, description):
        conversation = self.gpt_session.get_conversation()
        user_query = f'''
 Generate a name for the executor matching the description:
@@ -250,7 +235,7 @@ PDFParserExecutor
        name = self.extract_content_from_result(name_raw, 'name.txt')
        return name

-    def get_possible_packages(self, description, threads):
+    def get_possible_packages(self, description):
        print_colored('', '############# What package to use? #############', 'red')
        user_query = f'''
 Here is the task description of the problme you need to solve:
@@ -279,29 +264,26 @@ package2,package3,...
        packages_raw = conversation.query(user_query)
        packages_csv_string = self.extract_content_from_result(packages_raw, 'packages.csv')
        packages = [package.split(',') for package in packages_csv_string.split('\n')]
-        packages = packages[:threads]
+        packages = packages[:NUM_IMPLEMENTATION_STRATEGIES]
        return packages

-    def create(self, description, num_approaches, output_path, test):
-        generated_name = self.generate_executor_name(description)
-        executor_name = f'{generated_name}{random.randint(0, 1000_000)}'
-        packages_list = self.get_possible_packages(description, num_approaches)
+    def generate(self, description, test, microservice_path):
+        generated_name = self.generate_microservice_name(description)
+        microservice_name = f'{generated_name}{random.randint(0, 10_000_000)}'
+        packages_list = self.get_possible_packages(description)
        for num_approach, packages in enumerate(packages_list):
            try:
-                self.create_executor(description, test, output_path, executor_name, packages, num_approach)
-                executor_path = self.debug_executor(output_path, executor_name, num_approach, packages, description, test)
-                host = jina_cloud.deploy_flow(executor_name, executor_path)
-                self.create_playground(executor_name, executor_path, host)
+                self.generate_microservice(description, test, microservice_path, microservice_name, packages, num_approach)
+                final_version_path = self.debug_microservice(microservice_path, microservice_name, num_approach, packages, description, test)
+                self.generate_playground(microservice_name, final_version_path)
            except self.MaxDebugTimeReachedException:
-                print('Could not debug the Executor.')
+                print('Could not debug the Microservice.')
                continue
            print(f'''
-Executor name: {executor_name}
-Executor path: {executor_path}
-Host: {host}
-
-Run the following command to start the playground:
-streamlit run {os.path.join(executor_path, "app.py")}
+You can now run or deploy your microservice:
+gptdeploy run --path {microservice_path}
+gptdeploy deploy --path {microservice_path}
 '''
                  )
            break
+
--- a/src/options/generate/prompt_system.py
+++ b/src/options/generate/prompt_system.py
@@ -4,9 +4,8 @@ executor_example = '''
 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:

-**executor.py**
+**microservice.py**
 ```python
-# this executor binary files as input and returns the length of each binary file as output
 from jina import Executor, requests, DocumentArray, Document
 import json
 class MyInfoExecutor(Executor):
--- a/src/options/generate/prompt_tasks.py
+++ b/src/options/generate/prompt_tasks.py
@@ -50,7 +50,7 @@ def test_executor_file_task(executor_name, test_scenario):
            if test_scenario else ""
        )
        + "Use the following import to import the executor: "
-          f"from executor import {executor_name} "
+          f"from microservice import {executor_name} "
        + not_allowed()
        + "The test must not open local files. "
        + "The test must not mock a function of the executor. "
--- a/src/options/run/init.py
+++ b/src/options/run/init.py
@@ -0,0 +1 @@
+from src.options.run.runner import Runner
--- a/src/options/run/runner.py
+++ b/src/options/run/runner.py
@@ -0,0 +1,11 @@
+from src.apis.jina_cloud import run_locally
+from src.options import validate_folder_is_correct, get_executor_name, get_latest_version_path
+
+
+class Runner():
+    def run(self, microservice_path):
+        validate_folder_is_correct(microservice_path)
+        executor_name = get_executor_name(microservice_path)
+        latest_version_path = get_latest_version_path(microservice_path)
+        run_locally(executor_name, latest_version_path)
+
--- a/src/server.py
+++ b/src/server.py
@@ -1,53 +0,0 @@
-# from fastapi import FastAPI
-# from fastapi.exceptions import RequestValidationError
-# from pydantic import BaseModel
-# from typing import Optional, Dict
-#
-# from starlette.middleware.cors import CORSMiddleware
-# from starlette.requests import Request
-# from starlette.responses import JSONResponse
-# from main import main
-#
-# app = FastAPI()
-#
-# # Define the request model
-# class CreateRequest(BaseModel):
-#     test_scenario: str
-#     executor_description: str
-#
-# # Define the response model
-# class CreateResponse(BaseModel):
-#     result: Dict[str, str]
-#     success: bool
-#     message: Optional[str]
-#
-# @app.post("/create", response_model=CreateResponse)
-# def create_endpoint(request: CreateRequest):
-#
-#     result = main(
-#         executor_description=request.executor_description,
-#         test_scenario=request.test_scenario,
-#     )
-#     return CreateResponse(result=result, success=True, message=None)
-#
-#
-# app.add_middleware(
-#     CORSMiddleware,
-#     allow_origins=["*"],
-#     allow_credentials=True,
-#     allow_methods=["*"],
-#     allow_headers=["*"],
-# )
-#
-# # Add a custom exception handler for RequestValidationError
-# @app.exception_handler(RequestValidationError)
-# def validation_exception_handler(request: Request, exc: RequestValidationError):
-#     return JSONResponse(
-#         status_code=422,
-#         content={"detail": exc.errors()},
-#     )
-#
-#
-# if __name__ == "__main__":
-#     import uvicorn
-#     uvicorn.run("server:app", host="0.0.0.0", port=8000, log_level="info")
--- a/src/utils/io.py
+++ b/src/utils/io.py
@@ -1,17 +1,37 @@
 import os
-import shutil
+
 import concurrent.futures
 import concurrent.futures
 from typing import Generator
 import sys
 from contextlib import contextmanager

+import docker
+from docker import APIClient
+
+
+def get_microservice_path(path, microservice_name, package, num_approach, version):
+    package_path = '_'.join(package)
+    return os.path.join(path, microservice_name, f'{num_approach}_{package_path}', f'v{version}')

 def persist_file(file_content, file_path):
    with open(file_path, 'w') as f:
        f.write(file_content)


+def get_all_microservice_files_with_content(folder_path):
+    file_name_to_content = {}
+    for filename in os.listdir(folder_path):
+        file_path = os.path.join(folder_path, filename)
+
+        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
+
+
 class GenerationTimeoutError(Exception):
    pass

@@ -42,4 +62,19 @@ def suppress_stdout():
        yield
    finally:
        sys.stdout.close()
-        sys.stdout = original_stdout
+        sys.stdout = original_stdout
+
+
+def is_docker_running():
+    try:
+        from hubble import __windows__
+        _client = docker.from_env()
+        # low-level client
+        _raw_client = APIClient(
+            base_url=docker.constants.DEFAULT_NPIPE
+            if __windows__
+            else docker.constants.DEFAULT_UNIX_SOCKET
+        )
+    except Exception:
+        return False
+    return True
--- a/test/init.py
+++ b/test/init.py
--- a/test/test_generator.py
+++ b/test/test_generator.py
@@ -0,0 +1,29 @@
+import unittest.mock as mock
+from src.options.generate.generator import Generator
+from src.apis.gpt import GPTSession
+
+def test_generator(tmpdir):
+    # Define a mock response
+    mock_response = {
+        "choices": [
+            {
+                "delta": {
+                    "content": "This is a mock response."
+                }
+            }
+        ]
+    }
+
+    # Define a function to replace openai.ChatCompletion.create
+    def mock_create(*args, **kwargs):
+        return [mock_response] * kwargs.get("stream", 1)
+
+    # Define a function to replace get_openai_api_key
+    def mock_get_openai_api_key(*args, **kwargs):
+        pass
+
+    # Use mock.patch as a context manager to replace the original methods with the mocks
+    with mock.patch("openai.ChatCompletion.create", side_effect=mock_create), \
+            mock.patch.object(GPTSession, "configure_openai_api_key", side_effect=mock_get_openai_api_key):
+        generator = Generator()
+        generator.generate("my description", "my test", str(tmpdir))