finishinig the MVP and wow factor

app.py

@@ -12,6 +12,22 @@ from structured_experiment_chain import (
     wikipedia_chain as experiment_wikipedia_chain
 )
 
+from google_buckets import CloudStorageManager
+import dotenv
+import os
+
+from utils import (
+    change_file_extension, convert_obj_to_stl,
+    remove_files
+)
+
+from mesh_utils import generate_mesh_images
+
+from vision_model import analyze_images
+
+from gradio_client import Client as ShapEClient
+
+dotenv.load_dotenv()
 
 apparatus_retriever_options = {
     "Arxiv": apparatus_arxiv_chain,
@@ -32,7 +48,20 @@ def generate_apparatus(input_text, retriever_choice):
     app_components =  output_text["Material"]
     component_collection = weaviate_client.collections.get("Component")
     
+    bucket_name = os.getenv('GOOGLE_BUCKET_NAME')
+    manager = CloudStorageManager(bucket_name)
+    
     for i in app_components:
+        
+        client = ShapEClient("hysts/Shap-E")
+        client.hf_token = os.getenv("HUGGINGFACE_API_KEY")
+        result = client.predict(
+                i,	# str  in 'Prompt' Textbox component
+                1621396601,	# float (numeric value between 0 and 2147483647) in 'Seed' Slider component
+                15,	# float (numeric value between 1 and 20) in 'Guidance scale' Slider component
+                64,	# float (numeric value between 2 and 100) in 'Number of inference steps' Slider component
+                api_name="/text-to-3d"
+        )
 
         app_uuid = component_collection.data.insert({
             "Tags": output_text['Fields_of_study'],
@@ -40,6 +69,14 @@ def generate_apparatus(input_text, retriever_choice):
             "ToolName" : i,
             "UsedInComps" : [input_text]
         })
+        
+        
+        glb_file_name = app_uuid.hex + ".glb"
+        
+        manager.upload_file(
+            result,
+            glb_file_name,
+            )
     
     return output_text
 
@@ -91,6 +128,47 @@ def search_apparatus(input_text, number):
     
     return response_objects_string
 
+def review_3d_model(uuid:str) -> None:
+    """input the uuid of a 3d model"""
+    uuid = uuid.replace("-","")
+    bucket_name = os.getenv('GOOGLE_BUCKET_NAME')
+    manager = CloudStorageManager(bucket_name)
+    xx = manager.get_file_by_uuid(uuid)
+    manager.download_file(
+        xx,
+        xx
+    )
+    xx_as_stl = change_file_extension(xx,"stl")
+    convert_obj_to_stl(xx,xx_as_stl)
+    viewing_angles = [(30, 45), (60, 90), (45, 135)]
+    
+    prompt = "I am creating an 3d model of a Glass lenses for refracting light,\
+    using a text-to-3d model\
+    Do these images look correct?\
+    If not please make a suggesttion on how to improve the text input\
+    As this response will be used in a pipeline please only output a new \
+    potential prompt or output nothing, "
+    # Please keep the prompt to 5 25 words to not confuse the model"
+    
+    images = generate_mesh_images(
+        xx_as_stl,
+        viewing_angles,
+        
+        )
+    
+    response = analyze_images(
+        images, 
+        prompt, 
+        # api_key,
+        )
+    
+    #clean up
+    remove_files(images)
+    remove_files([xx,xx_as_stl])
+    return response
+    
+    
+
 generate_apparatus_interface = gr.Interface(
     fn=generate_apparatus,
     inputs=["text", gr.Radio(choices=list(apparatus_retriever_options.keys()), label="Select a retriever", value="Wikipedia")],
@@ -123,12 +201,27 @@ search_apparatus_interface = gr.Interface(
     description="If you would like an idea of the apparatuses in the vectorestore here is the place",
 )
 
+review_3d_model_interface = gr.Interface(
+    fn=review_3d_model,
+    inputs=["text"],
+    outputs="text",
+    title="Review 3D Model",
+    description="Input the UUID of a 3D model to review its images and provide feedback.",
+)
+
 demo = gr.TabbedInterface([
     generate_apparatus_interface, 
     generate_experiment_interface,
     search_experiments_interface,
     search_apparatus_interface,
-], ["Generate Apparatus", "Generate Experiment", "Search Existing Experiments","Search Existing Apparatuses"])
+    review_3d_model_interface,
+], [
+    "Generate Apparatus",
+    "Generate Experiment", 
+    "Search Existing Experiments",
+    "Search Existing Apparatuses",
+    "review_3d_model_interface"
+    ])
 
 if __name__ == "__main__":
     demo.launch()

chain_apparatarus_weaviate.py

@@ -11,12 +11,19 @@ from structured_experiment_chain import (
     wikipedia_chain as experiment_wikipedia_chain
 )
 
+
+# from google_buckets import upload_file, man
+
 from weaviate_utils import init_client
 
 from datetime import datetime, timezone
 
+from gradio_client import Client as ShapEClient
+import os
 
+from google_buckets import CloudStorageManager
 
+from utils import copy_file_to_location
 
 def main():
     # exp_qury = "fabricating cellolouse based electronics"
@@ -33,9 +40,26 @@ def main():
     component_image_collection = weaviate_client.collections.get("ComponentImage")
     science_experiment_collection = weaviate_client.collections.get("ScienceEperiment")
     
+    
+    bucket_name = os.getenv('GOOGLE_BUCKET_NAME')
+    manager = CloudStorageManager(bucket_name)
+    
+    
+    
     app_components =  app_data["Material"]
     
     for i in app_components:
+        
+        client = ShapEClient("hysts/Shap-E")
+        client.hf_token = os.getenv("HUGGINGFACE_API_KEY")
+        result = client.predict(
+                i,	# str  in 'Prompt' Textbox component
+                1621396601,	# float (numeric value between 0 and 2147483647) in 'Seed' Slider component
+                15,	# float (numeric value between 1 and 20) in 'Guidance scale' Slider component
+                64,	# float (numeric value between 2 and 100) in 'Number of inference steps' Slider component
+                api_name="/text-to-3d"
+        )
+        
     
         app_uuid = component_collection.data.insert({
             "Tags": app_data['Fields_of_study'],
@@ -43,6 +67,18 @@ def main():
             "ToolName" : i,
             "UsedInComps" : [app_query]
         })
+        
+        glb_file_name = app_uuid.hex + ".glb"
+        
+        manager.upload_file(
+            result,
+            glb_file_name,
+            )
+        # copy_file_to_location(result,glb_file_name)
+        # upload_file(glb_file_name)
+        # os.remove(glb_file_name)
+        
+        x = 0
     
     response = component_collection.query.bm25(
             query="something that goes in a microscope",

google_buckets.py

@@ -2,58 +2,81 @@ from google.cloud import storage
 import os
 import json
 
-SERVICE_ACOUNT_STUFF = os.getenv('GOOGLE_APPLICATION_CREDENTIALS_JSON')
 
-# https://stackoverflow.com/questions/71878229/initializing-firebase-admin-via-environment-variables-without-storing-serviceacc
-key_dict = json.loads(
-    os.environ["GOOGLE_APPLICATION_CREDENTIALS_JSON"]
-)
 
-SERVICE_ACOUNT_STUFF = os.getenv('GOOGLE_APPLICATION_CREDENTIALS_JSON')
+from google.cloud import storage
+
+class CloudStorageManager:
+    def __init__(self, bucket_name):
+        self.client = storage.Client()
+        self.bucket_name = bucket_name
 
+    def upload_file(self, file_path, destination_file_name):
+        bucket = self.client.bucket(self.bucket_name)
+        blob = bucket.blob(destination_file_name)
+        blob.upload_from_filename(file_path)
+        print(f'File {destination_file_name} uploaded to {self.bucket_name}.')
 
-# fire_app = firebase_admin.initialize_app(Certificate(key_dict))
+    def download_file(self, source_file_name, destination_path):
+        bucket = self.client.bucket(self.bucket_name)
+        blob = bucket.blob(source_file_name)
+        blob.download_to_filename(destination_path)
+        print(f'File {source_file_name} downloaded to {destination_path}.')
 
+    def delete_file(self, file_name):
+        bucket = self.client.bucket(self.bucket_name)
+        blob = bucket.blob(file_name)
+        blob.delete()
+        print(f'File {file_name} deleted from {self.bucket_name}.')
+        
+    def get_file_by_uuid(self, uuid):
+        bucket = self.client.bucket(self.bucket_name)
+        blobs = bucket.list_blobs(prefix=uuid)
+        for blob in blobs:
+            if blob.name.endswith('.glb'):
+                return blob.name
+        return None
 
-# db = client = firestore.client(app=fire_app)
-# Initialize Google Cloud Storage client
-client = storage.Client()
+def main():
+    SERVICE_ACOUNT_STUFF = os.getenv('GOOGLE_APPLICATION_CREDENTIALS_JSON')
 
-# Define bucket and file name
-# bucket_name = os.getenv('GOOGLE_PROJECT_ID')
-bucket_name = "production-blender-platform-bucket"
-# file_name = 'your-file.glb'
-file_name = "tmpcpd7o7v0.glb"
+    # https://stackoverflow.com/questions/71878229/initializing-firebase-admin-via-environment-variables-without-storing-serviceacc
+    key_dict = json.loads(
+        os.environ["GOOGLE_APPLICATION_CREDENTIALS_JSON"]
+    )
 
+    SERVICE_ACOUNT_STUFF = os.getenv('GOOGLE_APPLICATION_CREDENTIALS_JSON')
 
 
-# Function to upload a .glb file to the bucket
-def upload_file(file_path):
-    bucket = client.get_bucket(bucket_name)
-    blob = bucket.blob(file_name)
-    blob.upload_from_filename(file_path)
-    print(f'File {file_name} uploaded to {bucket_name}.')
+    # fire_app = firebase_admin.initialize_app(Certificate(key_dict))
 
-# Function to download a .glb file from the bucket
-def download_file(destination_path):
-    bucket = client.get_bucket(bucket_name)
-    blob = bucket.blob(file_name)
-    blob.download_to_filename(destination_path)
-    print(f'File {file_name} downloaded to {destination_path}.')
 
-# Function to delete a .glb file from the bucket
-def delete_file():
-    bucket = client.get_bucket(bucket_name)
-    blob = bucket.blob(file_name)
-    blob.delete()
-    print(f'File {file_name} deleted from {bucket_name}.')
+    # Initialize Google Cloud Storage client
+    client = storage.Client()
+    bucket_name = os.getenv('GOOGLE_BUCKET_NAME')
+    manager = CloudStorageManager(bucket_name)
+    
+    
+    # uuid = '9ca1555c-e8ca-4111-a084-1a2374b2e6bd'
+    # uuid = '9ca1555c-e8ca-4111-a084-1a2374b2e6bd'.replace("-","")
+    uuid = "506bb34a122a4bea86a64f96933f6bbd"
+    xx = manager.get_file_by_uuid(uuid)
+    
+    # manager.upload_file(
+    #     "506bb34a122a4bea86a64f96933f6bbd.glb",
+    #     "506bb34a122a4bea86a64f96933f6bbd.glb"
+    # )
+    
+    manager.download_file(
+        xx,
+        xx
+    )
+    x = 0
 
-def main():
     # Example usage
-    file_name = "tmpcpd7o7v0.glb"
-    upload_file(file_name)
-    download_file('path/to/save/your/file.glb')
-    delete_file()
+    # manager.upload_file("/home/isayahc/projects/Hackathon-Projects/Maker-Tech-Tree/7698996e43bf4aa1ba98f5dd0bf77000.glb", "7698996e43bf4aa1ba98f5dd0bf77000.glb")
+    # manager.download_file('your-file.glb', 'path/to/save/your/file.glb')
+    # manager.delete_file('your-file.glb')
 
 if __name__ == "__main__":
     main()

multi_angle_stl.py

@@ -1,39 +1,39 @@
 from stl import mesh
+import matplotlib.pyplot as plt
 from mpl_toolkits import mplot3d
-from matplotlib import pyplot as plt
 
-# Load the STL file
-your_mesh = mesh.Mesh.from_file('sample_data.stl')
-
-# Define three different viewing angles
-viewing_angles = [(30, 45), (60, 90), (45, 135)]
-
-# Iterate over each viewing angle and generate an image
-for i, (elev, azim) in enumerate(viewing_angles, start=1):
-    # Create a new plot with a larger figure size
-    fig = plt.figure(figsize=(10, 10))
-    ax = fig.add_subplot(111, projection='3d')
-
-    # Add the STL file to the plot
-    ax.add_collection3d(mplot3d.art3d.Poly3DCollection(your_mesh.vectors))
-
-    # Calculate the limits of the mesh
-    max_dim = max(your_mesh.points.flatten())
-    min_dim = min(your_mesh.points.flatten())
-
-    # Set the limits of the plot
-    ax.set_xlim([min_dim, max_dim])
-    ax.set_ylim([min_dim, max_dim])
-    ax.set_zlim([min_dim, max_dim])
-
-    # Set the viewing angle
-    ax.view_init(elev=elev, azim=azim)
-
-    # Save the plot as an image
-    plt.savefig(f'mesh_{i}.png')
-
-    # Close the plot to avoid memory leaks
-    plt.close()
-
-# Optional: Show the last generated plot
-# plt.show()
+def load_stl(file_path):
+    """Load the STL file."""
+    return mesh.Mesh.from_file(file_path)
+
+def generate_images(mesh, viewing_angles, figsize=(10, 10)):
+    """Generate images from different viewing angles."""
+    for i, (elev, azim) in enumerate(viewing_angles, start=1):
+        fig = plt.figure(figsize=figsize)
+        ax = fig.add_subplot(111, projection='3d')
+        ax.add_collection3d(mplot3d.art3d.Poly3DCollection(mesh.vectors))
+        max_dim = max(mesh.points.flatten())
+        min_dim = min(mesh.points.flatten())
+        ax.set_xlim([min_dim, max_dim])
+        ax.set_ylim([min_dim, max_dim])
+        ax.set_zlim([min_dim, max_dim])
+        ax.view_init(elev=elev, azim=azim)
+        plt.savefig(f'mesh_{i}.png')
+        plt.close()
+
+def main():
+    # Load the STL file
+    # stl_file_path = 'sample_data.stl'
+    # your_mesh = load_stl(stl_file_path)
+
+    # Define three different viewing angles
+    viewing_angles = [(30, 45), (60, 90), (45, 135)]
+
+    # Generate images from different viewing angles
+    # generate_images(your_mesh, viewing_angles)
+
+    # Optional: Show the last generated plot
+    # plt.show()
+
+if __name__ == "__main__":
+    main()

utils.py

@@ -73,3 +73,22 @@ def base64_to_file(base64_string: str, output_file_location: str) -> None:
     binary_data = base64.b64decode(base64_string)
     with open(output_file_location, "wb") as output_file:
         output_file.write(binary_data)
+
+def copy_file_to_location(file_path: str, destination_path: str) -> None:
+    """
+    Copy a file to a new location with the same name.
+
+    Args:
+        file_path: The path of the file to be copied.
+        destination_path: The path of the destination directory.
+    """
+    shutil.copy(file_path, destination_path)
+    
+def remove_files(file_paths):
+    """Remove files given a list of file paths."""
+    for file_path in file_paths:
+        try:
+            os.remove(file_path)
+            print(f"File '{file_path}' removed successfully.")
+        except OSError as e:
+            print(f"Error removing file '{file_path}': {e}")