Fix typos in python code

README.md

@@ -2609,7 +2609,9 @@ library_name: transformers
 
 Sionic AI delivers more accessible and cost-effective AI technology addressing the various needs to boost productivity and drive innovation.
 
-The Large Language Model (LLM) is not for research and experimentation. We offer solutions that leverage LLM to add value to your business. Anyone can easily train and control AI.
+The Large Language Model (LLM) is not for research and experimentation. 
+We offer solutions that leverage LLM to add value to your business. 
+Anyone can easily train and control AI.
 
 ## How to get embeddings
 
@@ -2664,7 +2666,12 @@ Response:
 
 ### Python code Example
 Get embeddings by directly calling Sionic's embedding API.
+
 ```python
+from typing import List
+import numpy as np
+import requests
+
 def get_embedding(queries: List[str], url):
     response = requests.post(url=url, json={'inputs': queries})
     return np.asarray(response.json()['embedding'], dtype=np.float32)
@@ -2685,7 +2692,7 @@ from model_api import SionicEmbeddingModel
 
 inputs1 = ["first query", "second query"]
 inputs2 = ["third query", "fourth query"]
-model - SionicEmbeddingModel(url="https://api.sionic.ai/v1/embedding",
+model = SionicEmbeddingModel(url="https://api.sionic.ai/v1/embedding",
                              dimension=2048)
 embedding1 = model.encode(inputs1)
 embedding2 = model.encode(inputs2)
@@ -2701,7 +2708,7 @@ from model_api import SionicEmbeddingModel
 
 query = ["first query", "second query"]
 passage = ["This is a passage related to the first query", "This is a passage related to the second query"]
-model - SionicEmbeddingModel(url="https://api.sionic.ai/v1/embedding",
+model = SionicEmbeddingModel(url="https://api.sionic.ai/v1/embedding",
                              instruction="query: ",
                              dimension=2048)
 query_embedding = model.encode_queries(query)