feat: modify embedding method to use embedding class

pyproject.toml

@@ -40,11 +40,11 @@ build-backend = "poetry.core.masonry.api"
 codegate = "codegate.cli:main"
 
 [tool.black]
-line-length = 88
+line-length = 127
 target-version = ["py310"]
 
 [tool.ruff]
-line-length = 88
+line-length = 127
 target-version = "py310"
 fix = true
 

scripts/import_packages.py

@@ -1,129 +1,117 @@
 import json
-
 import weaviate
+import asyncio
+
 from weaviate.classes.config import DataType, Property
 from weaviate.embedded import EmbeddedOptions
-
-from utils.embedding_util import generate_embeddings
-
-json_files = [
-    "data/archived.jsonl",
-    "data/deprecated.jsonl",
-    "data/malicious.jsonl",
-]
+from weaviate.util import generate_uuid5
+from codegate.inference.inference_engine import LlamaCppInferenceEngine
 
 
-def setup_schema(client):
-    if not client.collections.exists("Package"):
-        client.collections.create(
-            "Package",
-            properties=[
-                Property(name="name", data_type=DataType.TEXT),
-                Property(name="type", data_type=DataType.TEXT),
-                Property(name="status", data_type=DataType.TEXT),
-                Property(name="description", data_type=DataType.TEXT),
-            ],
+class PackageImporter:
+    def __init__(self):
+        self.client = weaviate.WeaviateClient(
+            embedded_options=EmbeddedOptions(
+                persistence_data_path="./weaviate_data",
+                grpc_port=50052
+            )
         )
-
-
-def generate_vector_string(package):
-    vector_str = f"{package['name']}"
-    # add description
-    package_url = ""
-    if package["type"] == "pypi":
-        vector_str += " is a Python package available on PyPI"
-        package_url = f"https://trustypkg.dev/pypi/{package['name']}"
-    elif package["type"] == "npm":
-        vector_str += " is a JavaScript package available on NPM"
-        package_url = f"https://trustypkg.dev/npm/{package['name']}"
-    elif package["type"] == "go":
-        vector_str += " is a Go package. "
-        package_url = f"https://trustypkg.dev/go/{package['name']}"
-    elif package["type"] == "crates":
-        vector_str += " is a Rust package available on Crates. "
-        package_url = f"https://trustypkg.dev/crates/{package['name']}"
-    elif package["type"] == "java":
-        vector_str += " is a Java package. "
-        package_url = f"https://trustypkg.dev/java/{package['name']}"
-
-    # add extra status
-    if package["status"] == "archived":
-        vector_str += f". However, this package is found to be archived and no longer \
-maintained. For additional information refer to {package_url}"
-    elif package["status"] == "deprecated":
-        vector_str += f". However, this package is found to be deprecated and no \
-longer recommended for use. For additional information refer to {package_url}"
-    elif package["status"] == "malicious":
-        vector_str += f". However, this package is found to be malicious. For \
-additional information refer to {package_url}"
-    return vector_str
-
-
-def add_data(client):
-    collection = client.collections.get("Package")
-
-    # read all the data from db, we will only add if there is no data, or is different
-    existing_packages = list(collection.iterator())
-    packages_dict = {}
-    for package in existing_packages:
-        key = package.properties["name"] + "/" + package.properties["type"]
-        value = {
-            "status": package.properties["status"],
-            "description": package.properties["description"],
+        self.json_files = [
+            "data/archived.jsonl",
+            "data/deprecated.jsonl",
+            "data/malicious.jsonl",
+        ]
+        self.client.connect()
+        self.inference_engine = LlamaCppInferenceEngine()
+        self.model_path = "./models/all-minilm-L6-v2-q5_k_m.gguf"
+
+    def setup_schema(self):
+        if not self.client.collections.exists("Package"):
+            self.client.collections.create(
+                "Package",
+                properties=[
+                    Property(name="name", data_type=DataType.TEXT),
+                    Property(name="type", data_type=DataType.TEXT),
+                    Property(name="status", data_type=DataType.TEXT),
+                    Property(name="description", data_type=DataType.TEXT),
+                ],
+            )
+
+    def generate_vector_string(self, package):
+        vector_str = f"{package['name']}"
+        package_url = ""
+        type_map = {
+            "pypi": "Python package available on PyPI",
+            "npm": "JavaScript package available on NPM",
+            "go": "Go package",
+            "crates": "Rust package available on Crates",
+            "java": "Java package"
+        }
+        status_messages = {
+            "archived": "However, this package is found to be archived and no longer maintained.",
+            "deprecated": "However, this package is found to be deprecated and no longer recommended for use.",
+            "malicious": "However, this package is found to be malicious."
+        }
+        vector_str += f" is a {type_map.get(package['type'], 'unknown type')} "
+        package_url = f"https://trustypkg.dev/{package['type']}/{package['name']}"
+
+        # Add extra status
+        status_suffix = status_messages.get(package["status"], "")
+        if status_suffix:
+            vector_str += f"{status_suffix} For additional information refer to {package_url}"
+        return vector_str
+
+    async def process_package(self, batch, package):
+        vector_str = self.generate_vector_string(package)
+        vector = await self.inference_engine.embed(self.model_path, [vector_str])
+        # This is where the synchronous call is made
+        batch.add_object(properties=package, vector=vector[0])
+
+    async def add_data(self):
+        collection = self.client.collections.get("Package")
+        existing_packages = list(collection.iterator())
+        packages_dict = {
+            f"{package.properties['name']}/{package.properties['type']}": {
+                "status": package.properties["status"],
+                "description": package.properties["description"]
+            } for package in existing_packages
         }
-        packages_dict[key] = value
-
-    for json_file in json_files:
-        with open(json_file, "r") as f:
-            print("Adding data from", json_file)
 
-            # temporary, just for testing
-            with collection.batch.dynamic() as batch:
+        for json_file in self.json_files:
+            with open(json_file, "r") as f:
+                print("Adding data from", json_file)
+                packages_to_insert = []
                 for line in f:
                     package = json.loads(line)
+                    package["status"] = json_file.split('/')[-1].split('.')[0]
+                    key = f"{package['name']}/{package['type']}"
 
-                    # now add the status column
-                    if "archived" in json_file:
-                        package["status"] = "archived"
-                    elif "deprecated" in json_file:
-                        package["status"] = "deprecated"
-                    elif "malicious" in json_file:
-                        package["status"] = "malicious"
-                    else:
-                        package["status"] = "unknown"
-
-                    # check for the existing package and only add if different
-                    key = package["name"] + "/" + package["type"]
-                    if key in packages_dict:
-                        if (
-                            packages_dict[key]["status"] == package["status"]
-                            and packages_dict[key]["description"]
-                            == package["description"]
-                        ):
-                            print("Package already exists", key)
-                            continue
-
-                    # prepare the object for embedding
-                    print("Generating data for", key)
-                    vector_str = generate_vector_string(package)
-                    vector = generate_embeddings(vector_str)
-
-                    batch.add_object(properties=package, vector=vector)
+                    if key in packages_dict and packages_dict[key] == {
+                        "status": package["status"],
+                        "description": package["description"]
+                    }:
+                        print("Package already exists", key)
+                        continue
 
+                    vector_str = self.generate_vector_string(package)
+                    vector = await self.inference_engine.embed(self.model_path, [vector_str])
+                    packages_to_insert.append((package, vector[0]))
 
-def run_import():
-    client = weaviate.WeaviateClient(
-        embedded_options=EmbeddedOptions(
-            persistence_data_path="./weaviate_data", grpc_port=50052
-        ),
-    )
-    with client:
-        client.connect()
-        print("is_ready:", client.is_ready())
+                # Synchronous batch insert after preparing all data
+                with collection.batch.dynamic() as batch:
+                    for package, vector in packages_to_insert:
+                        batch.add_object(properties=package, vector=vector, uuid=generate_uuid5(package))
 
-        setup_schema(client)
-        add_data(client)
+    async def run_import(self):
+        self.setup_schema()
+        await self.add_data()
 
 
 if __name__ == "__main__":
-    run_import()
+    importer = PackageImporter()
+    asyncio.run(importer.run_import())
+    try:
+        assert importer.client.is_live()
+        pass
+    finally:
+        importer.client.close()