mirror of
https://github.com/aljazceru/dev-gpt.git
synced 2025-12-20 23:24:20 +01:00
Merge branch 'main' of https://github.com/jina-ai/gptdeploy into refactor-langchain
# Conflicts: # src/apis/gpt.py # src/cli.py # src/options/generate/generator.py # src/options/generate/prompt_system.py # src/options/generate/prompt_tasks.py
This commit is contained in:
43
README.md
43
README.md
@@ -100,54 +100,67 @@ jc delete <microservice id>
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<img src="res/teaser.png" alt="QR Code Generator" width="600" />
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### Chemical Formula Visualization
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```bash
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generate --description "Convert a chemical formula into a 2D chemical structure diagram" --test "C=C, CN=C=O, CCC(=O)O" --path microservice
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```
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<img src="res/chemical_formula_example.png" alt="Chemical Formula Visualization" width="600" />
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### Animal Detector
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```bash
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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" --model gpt-4
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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" --model gpt-4 --path microservice
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```
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<img src="res/animal_detector_example.png" alt="Animal Detector" width="600" />
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### Meme Generator
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```bash
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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" --model gpt-4
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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" --model gpt-4 --path microservice
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```
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<img src="res/meme_example.png" alt="Meme Generator" width="600" />
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### Rhyme Generator
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```bash
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gptdeploy generate --description "Given a word, return a list of rhyming words using the datamuse api" --test "hello" --model gpt-4
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gptdeploy generate --description "Given a word, return a list of rhyming words using the datamuse api" --test "hello" --model gpt-4 --path microservice
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```
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<img src="res/rhyme_generator_example.png" alt="Rhyme Generator" width="600" />
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### Word Cloud Generator
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```bash
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gptdeploy generate --description "Generate a word cloud from a given text" --test "Lorem ipsum dolor sit amet, consectetur adipiscing elit." --model gpt-4
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gptdeploy generate --description "Generate a word cloud from a given text" --test "Lorem ipsum dolor sit amet, consectetur adipiscing elit." --model gpt-4 --path microservice
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```
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<img src="res/word_cloud_example.png" alt="Word Cloud Generator" width="600" />
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### 3d model info
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```bash
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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" --model gpt-4
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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" --model gpt-4 --path microservice
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```
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<img src="res/obj_info_example.png" alt="3D Model Info" width="600" />
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### 2d rendering of 3d model
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```bash
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gptdeploy generate --description "create a 2d rendering of a whole 3d object and x,y,z object rotation using trimesh and pyrender.OffscreenRenderer with os.environ['PYOPENGL_PLATFORM'] = 'egl' and freeglut3-dev library" --test "input: https://graphics.stanford.edu/courses/cs148-10-summer/as3/code/as3/teapot.obj output: assert the image is not completely white or black" --model gpt-4 --path microservice
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```
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<img src="res/obj_render_example.gif" alt="2D Rendering of 3D Model" width="600" />
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### Table extraction
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```bash
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gptdeploy generate --description "Given a URL, extract all tables as csv" --test "http://www.ins.tn/statistiques/90" --model gpt-4
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gptdeploy generate --description "Given a URL, extract all tables as csv" --test "http://www.ins.tn/statistiques/90" --model gpt-4 --path microservice
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```
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<img src="res/table_extraction_example.png" alt="Table Extraction" width="600" />
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### Audio to mel spectrogram
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```bash
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gptdeploy generate --description "Create mel spectrograms from audio file" --test "https://cdn.pixabay.com/download/audio/2023/02/28/audio_550d815fa5.mp3" --model gpt-4
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gptdeploy generate --description "Create mel spectrograms from audio file" --test "https://cdn.pixabay.com/download/audio/2023/02/28/audio_550d815fa5.mp3" --model gpt-4 --path microservice
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```
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<img src="res/audio_to_mel_example.png" alt="Audio to Mel Spectrogram" width="600" />
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### Text to speech
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```bash
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gptdeploy generate --description "Convert text to speech" --test "Hello, welcome to GPT Deploy!" --model gpt-4
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gptdeploy generate --description "Convert text to speech" --test "Hello, welcome to GPT Deploy!" --model gpt-4 --path microservice
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```
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<a href=res/text_to_speech_example.wav><img src="res/text_to_speech_example.png" alt="Text to Speech" width="600" /></a>
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@@ -158,20 +171,20 @@ gptdeploy generate --description "Convert text to speech" --test "Hello, welcome
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### Heatmap Generator
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```bash
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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]]" --model gpt-4
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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]]" --model gpt-4 --path microservice
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```
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<img src="res/heatmap_example.png" alt="Heatmap Generator" width="600" />
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### QR Code Generator
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```bash
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gptdeploy generate --description "Generate QR code from URL" --test "https://www.example.com" --model gpt-4
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gptdeploy generate --description "Generate QR code from URL" --test "https://www.example.com" --model gpt-4 --path microservice
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```
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<img src="res/qr_example.png" alt="QR Code Generator" width="600" />
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### Mandelbrot Set Visualizer
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```bash
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gptdeploy generate --description "Visualize the Mandelbrot set with custom parameters" --test "center=-0+1i, zoom=1.0, size=800x800, iterations=1000" --model gpt-4
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gptdeploy generate --description "Visualize the Mandelbrot set with custom parameters" --test "center=-0+1i, zoom=1.0, size=800x800, iterations=1000" --model gpt-4 --path microservice
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```
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<img src="res/mandelbrot_example.png" alt="Mandelbrot Set Visualizer" width="600" />
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@@ -341,14 +354,6 @@ gptdeploy generate --description "Visualize the Mandelbrot set with custom param
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[//]: # (## Upcoming Challenges)
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[//]: # (### Chemical Structure Drawing)
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[//]: # (```bash)
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[//]: # (gptdeploy generate --description "Convert a chemical formula into a 2D chemical structure diagram" --test "C6H6")
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[//]: # (```)
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[//]: # (### Color Palette Generator)
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[//]: # (```bash)
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BIN
res/chemical_formula_example.png
Normal file
BIN
res/chemical_formula_example.png
Normal file
Binary file not shown.
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After Width: | Height: | Size: 110 KiB |
BIN
res/obj_render_example.gif
Normal file
BIN
res/obj_render_example.gif
Normal file
Binary file not shown.
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After Width: | Height: | Size: 898 KiB |
2
setup.py
2
setup.py
@@ -7,7 +7,7 @@ def read_requirements():
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setup(
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name='gptdeploy',
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version='0.18.16',
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version='0.18.18',
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description='Use natural language interface to generate, deploy and update your microservice infrastructure.',
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long_description=open('README.md', 'r', encoding='utf-8').read(),
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long_description_content_type='text/markdown',
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@@ -1,2 +1,2 @@
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__version__ = '0.18.16'
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__version__ = '0.18.18'
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from src.cli import main
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@@ -15,7 +15,9 @@ from src.utils.string_tools import print_colored
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class GPTSession:
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def __init__(self, model: str = 'gpt-4'):
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def __init__(self, task_description, test_description, model: str = 'gpt-4', ):
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self.task_description = task_description
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self.test_description = test_description
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self.configure_openai_api_key()
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self.model_name = 'gpt-4' if model == 'gpt-4' and self.is_gpt4_available() else 'gpt-3.5-turbo'
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@@ -51,7 +53,7 @@ If you have updated it already, please restart your terminal.
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return False
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def get_conversation(self, system_definition_examples: List[str] = ['executor', 'docarray', 'client']):
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return _GPTConversation(self.model_name, system_definition_examples)
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return _GPTConversation(self.model_name, self.task_description, self.test_description, system_definition_examples)
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class AssistantStreamingStdOutCallbackHandler(StreamingStdOutCallbackHandler):
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@@ -62,7 +64,7 @@ class AssistantStreamingStdOutCallbackHandler(StreamingStdOutCallbackHandler):
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class _GPTConversation:
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def __init__(self, model: str, system_definition_examples: List[str] = ['executor', 'docarray', 'client']):
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def __init__(self, model: str, task_description, test_description, system_definition_examples: List[str] = ['executor', 'docarray', 'client']):
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self.chat = ChatOpenAI(
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model_name=model,
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streaming=True,
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@@ -85,7 +87,7 @@ class _GPTConversation:
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return response
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@staticmethod
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def _create_system_message(system_definition_examples: List[str] = []) -> SystemMessage:
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def _create_system_message(task_description, test_description, system_definition_examples: List[str] = []) -> SystemMessage:
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system_message = system_message_base
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if 'executor' in system_definition_examples:
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system_message += f'\n{executor_example}'
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@@ -93,4 +95,5 @@ class _GPTConversation:
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system_message += f'\n{docarray_example}'
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if 'client' in system_definition_examples:
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system_message += f'\n{client_example}'
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# create from template
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return SystemMessage(content=system_message)
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@@ -248,10 +248,18 @@ def update_client_line_in_file(file_path, host):
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file.write(replaced_content)
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def remove_after_stderr(relevant_lines):
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def shorten_logs(relevant_lines):
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# handle duplicate error messages
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for index, line in enumerate(relevant_lines):
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if '--- Captured stderr call ----' in line:
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return relevant_lines[:index]
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relevant_lines = relevant_lines[:index]
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# filter pip install logs
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relevant_lines = [line for line in relevant_lines if ' Requirement already satisfied: ' not in line]
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# filter version not found logs
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for index, line in enumerate(relevant_lines):
|
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if 'ERROR: Could not find a version that satisfies the requirement ' in line:
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start_and_end = line[:150] + '...' + line[-150:]
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relevant_lines[index] = start_and_end
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return relevant_lines
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@@ -270,9 +278,9 @@ def process_error_message(error_message):
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if last_matching_line_index is not None:
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relevant_lines = lines[last_matching_line_index:]
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relevant_lines = remove_after_stderr(relevant_lines)
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relevant_lines = shorten_logs(relevant_lines)
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response = '\n'.join(relevant_lines[-25:]).strip()
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response = '\n'.join(relevant_lines[-100:]).strip()
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|
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# the following code tests the case that the docker file is corrupted and can not be parsed
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# the method above will not return a relevant error message in this case
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@@ -282,21 +290,3 @@ def process_error_message(error_message):
|
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if not response and last_line.startswith('error: '):
|
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return last_line
|
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return response
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||||
|
||||
|
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def build_docker(path):
|
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# The command to build the Docker image
|
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cmd = f"docker build -t micromagic {path}"
|
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|
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# Run the command and capture the output
|
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process = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, shell=True)
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stdout, stderr = process.communicate()
|
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|
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# Check if there was an error
|
||||
if process.returncode != 0:
|
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error_message = stderr.decode("utf-8")
|
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relevant_error_message = process_error_message(error_message)
|
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return relevant_error_message
|
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else:
|
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print("Docker build completed successfully.")
|
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return ''
|
||||
|
||||
@@ -64,13 +64,12 @@ def generate(
|
||||
return
|
||||
|
||||
from src.options.generate.generator import Generator
|
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generator = Generator(model=model)
|
||||
generator = Generator(description, test, model=model)
|
||||
with get_openai_callback() as cb:
|
||||
generator.generate(description, test, path)
|
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generator.generate(path)
|
||||
print(f"Prompt/Completion/Total Tokens: {cb.prompt_tokens}/{cb.completion_tokens}/{cb.total_tokens}")
|
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print(f"Total Cost on OpenAI (USD): ${cb.total_cost}")
|
||||
|
||||
|
||||
@main.command()
|
||||
@path_param
|
||||
def run(path):
|
||||
|
||||
@@ -30,5 +30,6 @@ MAX_DEBUGGING_ITERATIONS = 10
|
||||
DEMO_TOKEN = '45372338e04f5a41af949024db929d46'
|
||||
|
||||
PROBLEMATIC_PACKAGES = [
|
||||
'Pyrender', 'Trimesh', 'ModernGL', 'PyOpenGL', 'Pyglet', 'pythreejs', 'panda3d' # because they need a screen
|
||||
# 'Pyrender', 'Trimesh',
|
||||
'ModernGL', 'PyOpenGL', 'Pyglet', 'pythreejs', 'panda3d' # because they need a screen
|
||||
]
|
||||
@@ -1,13 +1,19 @@
|
||||
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_folder(path, max_fn=max):
|
||||
return max_fn([os.path.join(path, f) for f in os.listdir(path) if os.path.isdir(os.path.join(path, f))])
|
||||
|
||||
def version_max_fn(path_list):
|
||||
version_list = [int(path.split('/')[-1].replace('v', '')) for path in path_list]
|
||||
max_version = max(version_list)
|
||||
max_index = version_list.index(max_version)
|
||||
return path_list[max_index]
|
||||
|
||||
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)
|
||||
latest_version_path = get_latest_folder(latest_approach_path, max_fn=version_max_fn)
|
||||
return latest_version_path
|
||||
|
||||
def get_executor_name(microservice_path):
|
||||
|
||||
@@ -17,22 +17,23 @@ from src.utils.string_tools import print_colored
|
||||
|
||||
|
||||
class Generator:
|
||||
def __init__(self, model='gpt-4'):
|
||||
self.gpt_session = gpt.GPTSession(model=model)
|
||||
def __init__(self, task_description, test_description, model='gpt-4'):
|
||||
self.gpt_session = gpt.GPTSession(task_description, test_description, model=model)
|
||||
self.task_description = task_description
|
||||
self.test_description = test_description
|
||||
|
||||
def extract_content_from_result(self, plain_text, file_name, match_single_block=False):
|
||||
pattern = fr"^\*\*{file_name}\*\*\n```(?:\w+\n)?([\s\S]*?)```"
|
||||
match = re.search(pattern, plain_text, re.MULTILINE)
|
||||
if match:
|
||||
return match.group(1).strip()
|
||||
else:
|
||||
elif match_single_block:
|
||||
# Check for a single code block
|
||||
single_code_block_pattern = r"^```(?:\w+\n)?([\s\S]*?)```"
|
||||
single_code_block_match = re.findall(single_code_block_pattern, plain_text, re.MULTILINE)
|
||||
if match_single_block and len(single_code_block_match) == 1:
|
||||
if len(single_code_block_match) == 1:
|
||||
return single_code_block_match[0].strip()
|
||||
else:
|
||||
return ''
|
||||
return ''
|
||||
|
||||
def write_config_yml(self, microservice_name, dest_folder):
|
||||
config_content = f'''
|
||||
@@ -58,10 +59,10 @@ metas:
|
||||
test,
|
||||
path,
|
||||
microservice_name,
|
||||
package,
|
||||
packages,
|
||||
num_approach,
|
||||
):
|
||||
MICROSERVICE_FOLDER_v1 = get_microservice_path(path, microservice_name, package, num_approach, 1)
|
||||
MICROSERVICE_FOLDER_v1 = get_microservice_path(path, microservice_name, packages, num_approach, 1)
|
||||
os.makedirs(MICROSERVICE_FOLDER_v1)
|
||||
|
||||
print_colored('', '############# Microservice #############', 'blue')
|
||||
@@ -168,7 +169,6 @@ metas:
|
||||
persist_file(playground_content, os.path.join(microservice_path, 'app.py'))
|
||||
|
||||
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...')
|
||||
@@ -178,20 +178,22 @@ metas:
|
||||
error = process_error_message(log_hubble)
|
||||
if error:
|
||||
print('An error occurred during the build process. Feeding the error back to the assistent...')
|
||||
self.do_debug_iteration(description, error, error_before, next_microservice_path,
|
||||
self.do_debug_iteration(description, error, next_microservice_path,
|
||||
previous_microservice_path, test)
|
||||
error_before = error
|
||||
if i == MAX_DEBUGGING_ITERATIONS - 1:
|
||||
raise self.MaxDebugTimeReachedException('Could not debug the microservice.')
|
||||
else:
|
||||
print('Successfully build microservice.')
|
||||
break
|
||||
if i == MAX_DEBUGGING_ITERATIONS - 1:
|
||||
raise self.MaxDebugTimeReachedException('Could not debug the microservice.')
|
||||
|
||||
return get_microservice_path(path, microservice_name, packages, num_approach, i)
|
||||
|
||||
def do_debug_iteration(self, description, error, error_before, next_microservice_path, previous_microservice_path,
|
||||
def do_debug_iteration(self, description, error, next_microservice_path, previous_microservice_path,
|
||||
test):
|
||||
os.makedirs(next_microservice_path)
|
||||
file_name_to_content = get_all_microservice_files_with_content(previous_microservice_path)
|
||||
|
||||
summarized_error = self.summarize_error(error)
|
||||
is_dependency_issue = self.is_dependency_issue(error, file_name_to_content['Dockerfile'])
|
||||
if is_dependency_issue:
|
||||
all_files_string = self.files_to_string({
|
||||
@@ -199,11 +201,11 @@ metas:
|
||||
key in ['requirements.txt', 'Dockerfile']
|
||||
})
|
||||
user_query = template_solve_dependency_issue.format(
|
||||
description=description, error=error, all_files_string=all_files_string,
|
||||
description=description, summarized_error=summarized_error, all_files_string=all_files_string,
|
||||
)
|
||||
else:
|
||||
user_query = template_solve_code_issue.format(
|
||||
description=description, error=error, all_files_string=self.files_to_string(file_name_to_content),
|
||||
description=description, summarized_error=summarized_error, all_files_string=self.files_to_string(file_name_to_content),
|
||||
)
|
||||
conversation = self.gpt_session.get_conversation()
|
||||
returned_files_raw = conversation.chat(user_query)
|
||||
@@ -211,6 +213,7 @@ metas:
|
||||
updated_file = self.extract_content_from_result(returned_files_raw, file_name)
|
||||
if updated_file and (not is_dependency_issue or file_name in ['requirements.txt', 'Dockerfile']):
|
||||
file_name_to_content[file_name] = updated_file
|
||||
print(f'Updated {file_name}')
|
||||
for file_name, content in file_name_to_content.items():
|
||||
persist_file(content, os.path.join(next_microservice_path, file_name))
|
||||
|
||||
@@ -240,12 +243,12 @@ metas:
|
||||
template_generate_possible_packages.format(description=description)
|
||||
)
|
||||
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[:NUM_IMPLEMENTATION_STRATEGIES]
|
||||
return packages
|
||||
packages_list = [[pkg.strip() for pkg in packages_string.split(',')] for packages_string in packages_csv_string.split('\n')]
|
||||
packages_list = packages_list[:NUM_IMPLEMENTATION_STRATEGIES]
|
||||
return packages_list
|
||||
|
||||
def generate(self, description, test, microservice_path):
|
||||
generated_name = self.generate_microservice_name(description)
|
||||
def generate(self, microservice_path):
|
||||
generated_name = self.generate_microservice_name(self.task_description)
|
||||
microservice_name = f'{generated_name}{random.randint(0, 10_000_000)}'
|
||||
packages_list = self.get_possible_packages(description)
|
||||
packages_list = [
|
||||
@@ -254,7 +257,7 @@ metas:
|
||||
for num_approach, packages in enumerate(packages_list):
|
||||
try:
|
||||
self.generate_microservice(
|
||||
description, test, microservice_path, microservice_name, packages, num_approach
|
||||
self.task_description, self.test_description, microservice_path, microservice_name, packages, num_approach
|
||||
)
|
||||
final_version_path = self.debug_microservice(
|
||||
microservice_path, microservice_name, num_approach, packages, description, test
|
||||
@@ -274,3 +277,14 @@ gptdeploy deploy --path {microservice_path}
|
||||
'''
|
||||
)
|
||||
break
|
||||
|
||||
def summarize_error(self, error):
|
||||
conversation = self.gpt_session.get_conversation([])
|
||||
user_query = f'''
|
||||
Here is an error message I encountered during the docker build process:
|
||||
"{error}"
|
||||
Your task is to summarize the error message as compact and informative as possible while maintaining all information necessary to debug the core issue.
|
||||
Warnings are not worth mentioning.
|
||||
'''
|
||||
error_summary = conversation.query(user_query)
|
||||
return error_summary
|
||||
|
||||
@@ -16,7 +16,7 @@ class MyInfoExecutor(Executor):
|
||||
for d in docs:
|
||||
content = json.loads(d.text)
|
||||
...
|
||||
d.text = json.dumps(modified_content)
|
||||
d.text = json.dumps(modified_content) # serialized json
|
||||
return docs
|
||||
```
|
||||
|
||||
@@ -28,7 +28,7 @@ A Document is a python class that represents a single document.
|
||||
Here is the protobuf definition of a Document:
|
||||
```
|
||||
message DocumentProto {{
|
||||
// used to store json data the executor gets and returns
|
||||
// used to store serialized json data the executor gets and returns
|
||||
string text = 1;
|
||||
}}
|
||||
```
|
||||
@@ -71,7 +71,16 @@ print(response[0].text)
|
||||
```'''
|
||||
|
||||
|
||||
system_message_base = '''It is the year 2021.
|
||||
You are a principal engineer working at Jina - an open source company.
|
||||
system_base_definition = '''It is the year 2021.
|
||||
You are a principal engineer working at Jina - an open source company.
|
||||
You accurately satisfy all of the user's requirements.
|
||||
Your goal is to build a microservice that: {description}'''
|
||||
To be more specific, you help the user to build a microservice with the following requirements:
|
||||
```
|
||||
{task_description}
|
||||
```
|
||||
and the following test scenario:
|
||||
```
|
||||
{test_description}
|
||||
```
|
||||
|
||||
You must obey the following rules:''' + f'\n{not_allowed_executor}\n{not_allowed_docker}'
|
||||
|
||||
0
src/options/generate/prompt_tasks.py
Normal file
0
src/options/generate/prompt_tasks.py
Normal file
@@ -9,8 +9,8 @@ import docker
|
||||
from docker import APIClient
|
||||
|
||||
|
||||
def get_microservice_path(path, microservice_name, package, num_approach, version):
|
||||
package_path = '_'.join(package)
|
||||
def get_microservice_path(path, microservice_name, packages, num_approach, version):
|
||||
package_path = '_'.join(packages)
|
||||
return os.path.join(path, microservice_name, f'{num_approach}_{package_path}', f'v{version}')
|
||||
|
||||
def persist_file(file_content, file_path):
|
||||
|
||||
@@ -25,5 +25,5 @@ def test_generator(tmpdir):
|
||||
# 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))
|
||||
generator = Generator("my description", "my test")
|
||||
generator.generate(str(tmpdir))
|
||||
|
||||
Reference in New Issue
Block a user