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Merge pull request #2005 from qdrant/essentials-course-fix-remove-dotenv

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removed all python-dotenv snippets
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Kirstin
2025-11-25 19:35:45 +01:00
committed by GitHub
parent 92a27ddd9c 3a473827fc
commit e0b9e1ac3c
18 changed files with 7 additions and 46 deletions
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qdrant-landing/content/course/essentials/day-1/embedding-models.md
-2
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@@ -122,9 +122,7 @@ To create a collection with Named Vectors, you need to specify a configuration f
```python
from qdrant_client import QdrantClient, models
import os
from dotenv import load_dotenv
load_dotenv()
client = QdrantClient(url=os.getenv("QDRANT_URL"), api_key=os.getenv("QDRANT_API_KEY"))
# For Colab:
qdrant-landing/content/course/essentials/day-1/pitstop-project.md
+1 -3
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@@ -31,7 +31,7 @@ A working semantic search engine that demonstrates:
### Prerequisites
- Qdrant Cloud cluster (URL + API key)
- Python 3.9+ (or Colab)
- Packages: `qdrant-client`, `sentence-transformers`, `python-dotenv` (optional), `google.colab` (if using Colab)
- Packages: `qdrant-client`, `sentence-transformers`, `google.colab` (if using Colab)
### Models
- SentenceTransformer: `all-MiniLM-L6-v2` (384-dim)
@@ -62,9 +62,7 @@ Pick something with rich, descriptive text where semantic search adds value:
from sentence_transformers import SentenceTransformer
from qdrant_client import QdrantClient, models
import os
from dotenv import load_dotenv
load_dotenv()
client = QdrantClient(url=os.getenv("QDRANT_URL"), api_key=os.getenv("QDRANT_API_KEY"))
# For Colab: