Automated snippet conversion by scripts

These changes are purely mechanical to differentiate them from manual
fixes/adjustments made in the next commit.
This results in broken code as some snippets contain errors.

Made in four steps:
1. Run ./migrate-snippet.py that converts `.md` files to code files
   and perhaps adds missing lines under `// @hide` comments.
2. Sort Java imports.
3. Remove old `.md` files.
4. Run ./generate.md to produce `*/generated/*.md` files.

qdrant-landing/content/documentation/headless/snippets/fastembed/minicoil/create-collection/generated/python.md

@@ -7,4 +7,4 @@ client.create_collection(
         )
     }
 )
-```
+```

qdrant-landing/content/documentation/headless/snippets/fastembed/minicoil/create-collection/python.py

@@ -0,0 +1,12 @@
+from qdrant_client import QdrantClient, models  # @hide
+
+client = QdrantClient(url="http://localhost:6333")  # @hide
+
+client.create_collection(
+    collection_name="{minicoil_collection_name}",
+    sparse_vectors_config={
+        "minicoil": models.SparseVectorParams(
+            modifier=models.Modifier.IDF #Inverse Document Frequency
+        )
+    }
+)

qdrant-landing/content/documentation/headless/snippets/fastembed/minicoil/query-points/generated/python.md

@@ -10,4 +10,4 @@ client.query_points(
     using="minicoil",
     limit=1
 )
-```
+```

qdrant-landing/content/documentation/headless/snippets/fastembed/minicoil/query-points/python.py

@@ -0,0 +1,15 @@
+from qdrant_client import QdrantClient, models  # @hide
+
+client = QdrantClient(url="http://localhost:6333")  # @hide
+
+query = "Vectors in Medicine"
+
+client.query_points(
+    collection_name="{minicoil_collection_name}",
+    query=models.Document(
+        text=query, 
+        model="Qdrant/minicoil-v1"
+    ), 
+    using="minicoil",
+    limit=1
+)

qdrant-landing/content/documentation/headless/snippets/fastembed/minicoil/upsert-points/generated/python.md

@@ -24,4 +24,4 @@ client.upsert(
         for i in range(len(documents))
     ],
 )
-```
+```

qdrant-landing/content/documentation/headless/snippets/fastembed/minicoil/upsert-points/python.py

@@ -0,0 +1,29 @@
+from qdrant_client import QdrantClient, models  # @hide
+
+client = QdrantClient(url="http://localhost:6333")  # @hide
+
+#Estimating the average length of the documents in the corpus
+avg_documents_length = sum(len(document.split()) for document in documents) / len(documents)
+
+client.upsert(
+    collection_name="{minicoil_collection_name}",
+    points=[
+        models.PointStruct(
+            id=i,
+            payload={
+                "text": documents[i]
+            },
+            vector={
+                # Sparse miniCOIL vectors
+                "minicoil": models.Document(
+                    text=documents[i],
+                    model="Qdrant/minicoil-v1",
+                    options={"avg_len": avg_documents_length}   
+                    #Average length of documents in the corpus 
+                     # (a part of the BM25 formula on which miniCOIL is built)
+                )
+            },
+        )
+        for i in range(len(documents))
+    ],
+)