diff --git a/src/content/notebooks/impresso-py-maps.mdx b/src/content/notebooks/impresso-py-maps.mdx
index af3332b..5523c11 100644
--- a/src/content/notebooks/impresso-py-maps.mdx
+++ b/src/content/notebooks/impresso-py-maps.mdx
@@ -2,6 +2,7 @@
 title: Exploring impresso with maps
 githubUrl: https://github.com/impresso/impresso-datalab-notebooks/blob/main/4-impresso-py/maps_explore.ipynb
 authors:
+  - impresso-team
   - RomanKalyakin
 sha: 168c669246385a2ec6c3e088b0081364f129d11c
 date: 2024-09-27T12:54:12Z
@@ -9,22 +10,26 @@ googleColabUrl: https://colab.research.google.com/github/impresso/impresso-datal
 ---
 
 {/* cell:0 cell_type:markdown */}
+
 ## Install dependencies
 
 We need the following packages:
 
- * [impresso-py](https://impresso-project.ch/)
- * [ipyleaflet](https://ipyleaflet.readthedocs.io/en/latest/index.html)
+- [impresso-py](https://impresso-project.ch/)
+- [ipyleaflet](https://ipyleaflet.readthedocs.io/en/latest/index.html)
 
 {/* cell:1 cell_type:code */}
+
 ```python
 %pip install git+https://github.com/impresso/impresso-py.git ipyleaflet
 ```
 
 {/* cell:2 cell_type:markdown */}
+
 ## Connect to Impresso
 
 {/* cell:3 cell_type:code */}
+
 ```python
 from impresso import connect, OR, DateRange
 
@@ -32,11 +37,13 @@ impresso = connect(public_api_url="https://dev.impresso-project.ch/public-api")
 ```
 
 {/* cell:4 cell_type:markdown */}
+
 ## Search and collect entities
 
 Find top 100 location entities mentioned in articles that talk about nuclear power plants in the first three decades following the second world war.
 
 {/* cell:5 cell_type:code */}
+
 ```python
 locations = impresso.search.facet(
     "location",
@@ -52,6 +59,7 @@ locations
 Get entities details, including wikidata details
 
 {/* cell:7 cell_type:code */}
+
 ```python
 entities_ids = locations.df.index.tolist()
 entities = impresso.entities.find(entity_id=OR(*entities_ids), load_wikidata=True, limit=len(entities_ids))
@@ -62,6 +70,7 @@ entities
 Filter out entities that have no coordinates and add a country tag.
 
 {/* cell:9 cell_type:code */}
+
 ```python
 df = entities.df
 entities_with_coordinates = df[df['wikidata.coordinates.latitude'].notna() & df['wikidata.coordinates.longitude'].notna()]
@@ -74,6 +83,7 @@ entities_with_coordinates
 Add counts of mentions to the entities dataframe.
 
 {/* cell:11 cell_type:code */}
+
 ```python
 entities_with_coordinates['mentions_count'] = entities_with_coordinates.index.map(locations.df['count'])
 ```
@@ -82,6 +92,7 @@ entities_with_coordinates['mentions_count'] = entities_with_coordinates.index.ma
 Plot entities on the map.
 
 {/* cell:13 cell_type:markdown */}
+
 ### Utility methods
 
 Functions used to calculate extra details needed to plot data on a map.
@@ -90,6 +101,7 @@ Functions used to calculate extra details needed to plot data on a map.
 Find geo bounds of a group of items.
 
 {/* cell:15 cell_type:code */}
+
 ```python
 def find_bounds(coordinates):
   """
@@ -124,6 +136,7 @@ def find_bounds(coordinates):
 Create an HTML used for rendering the hover pop-up.
 
 {/* cell:17 cell_type:code */}
+
 ```python
 from ipywidgets import HTML
 from ipyleaflet import Popup
@@ -150,9 +163,11 @@ def build_hover_popup(title: str, subtitle: str, mentions: int) -> Popup:
 ```
 
 {/* cell:18 cell_type:markdown */}
+
 ### Plot
 
 {/* cell:19 cell_type:code */}
+
 ```python
 from ipyleaflet import Map, Marker, AwesomeIcon, CircleMarker
 
diff --git a/src/content/notebooks/impresso-py-network.mdx b/src/content/notebooks/impresso-py-network.mdx
index 2b9696c..b56ce8f 100644
--- a/src/content/notebooks/impresso-py-network.mdx
+++ b/src/content/notebooks/impresso-py-network.mdx
@@ -2,6 +2,7 @@
 title: Network graph with Impresso Py
 githubUrl: https://github.com/impresso/impresso-datalab-notebooks/blob/main/4-impresso-py/network_graph.ipynb
 authors:
+  - impresso-team
   - RomanKalyakin
 sha: 168c669246385a2ec6c3e088b0081364f129d11c
 date: 2024-09-27T12:54:12Z
@@ -9,17 +10,21 @@ googleColabUrl: https://colab.research.google.com/github/impresso/impresso-datal
 ---
 
 {/* cell:0 cell_type:markdown */}
+
 ## Install dependencies
 
 {/* cell:1 cell_type:code */}
+
 ```python
 %pip install git+https://github.com/impresso/impresso-py.git ipysigma
 ```
 
 {/* cell:2 cell_type:markdown */}
+
 ## Connect to Impresso
 
 {/* cell:3 cell_type:code */}
+
 ```python
 from impresso import connect, OR, AND
 
@@ -27,16 +32,19 @@ impresso = connect(public_api_url="https://dev.impresso-project.ch/public-api")
 ```
 
 {/* cell:4 cell_type:markdown */}
+
 ## Part 1: Get entities and their co-occurrences
 
 Find all persons mentioned in all articles that talk about the [Prague Spring](https://en.wikipedia.org/wiki/Prague_Spring).
 
 {/* cell:5 cell_type:code */}
+
 ```python
 query = OR("Prague Spring", "Prager Frühling", "Printemps de Prague")
 ```
 
 {/* cell:6 cell_type:code */}
+
 ```python
 persons = impresso.search.facet(
   facet="person",
@@ -51,6 +59,7 @@ persons
 Get all combinations of all entities with a mention count higher than `N`.
 
 {/* cell:8 cell_type:code */}
+
 ```python
 import itertools
 
@@ -66,6 +75,7 @@ print(f"Total combinations: {len(persons_ids_combinations)}")
 ```
 
 {/* cell:9 cell_type:code */}
+
 ```python
 if len(persons_ids_combinations) > 500:
   msg = (
@@ -81,6 +91,7 @@ if len(persons_ids_combinations) > 500:
 Get timestamps and counts of all articles where persons pairs appear.
 
 {/* cell:11 cell_type:code */}
+
 ```python
 from impresso.util.error import ImpressoError
 from time import sleep
@@ -115,6 +126,7 @@ for idx, combo in enumerate(persons_ids_combinations):
 Put them all into a dataframe
 
 {/* cell:13 cell_type:code */}
+
 ```python
 import pandas as pd
 
@@ -132,14 +144,17 @@ connections_df
 ```
 
 {/* cell:14 cell_type:code */}
+
 ```python
 connections_df.to_csv("connections.csv")
 ```
 
 {/* cell:15 cell_type:markdown */}
+
 ## Part 2: visualise
 
 {/* cell:16 cell_type:code */}
+
 ```python
 import pandas as pd
 
@@ -148,6 +163,7 @@ connections_df
 ```
 
 {/* cell:17 cell_type:code */}
+
 ```python
 grouped_connections_df = connections_df.groupby(['node_a', 'node_b']) \
     .agg({'timestamp': lambda x: ', '.join(list(x)), 'count': 'sum', 'url': lambda x: list(set(x))[0]}) \
@@ -156,6 +172,7 @@ grouped_connections_df
 ```
 
 {/* cell:18 cell_type:code */}
+
 ```python
 import networkx as nx
 
@@ -172,12 +189,14 @@ G.nodes
 ```
 
 {/* cell:19 cell_type:code */}
+
 ```python
 filename = input("Enter the filename: ")
 filename = f"{filename.replace(' ', '_')}.gefx"
 ```
 
 {/* cell:20 cell_type:code */}
+
 ```python
 nx.write_gexf(G, filename)
 ```
@@ -186,6 +205,7 @@ nx.write_gexf(G, filename)
 If running in Colab - activate custom widgets to allow Sigma to render the graph.
 
 {/* cell:22 cell_type:code */}
+
 ```python
 try:
     from google.colab import output
@@ -198,6 +218,7 @@ except:
 Render the graph.
 
 {/* cell:24 cell_type:code */}
+
 ```python
 import networkx as nx
 from ipysigma import Sigma
diff --git a/src/content/notebooks/impresso-py-search.mdx b/src/content/notebooks/impresso-py-search.mdx
index e4fe012..6229d52 100644
--- a/src/content/notebooks/impresso-py-search.mdx
+++ b/src/content/notebooks/impresso-py-search.mdx
@@ -1,6 +1,7 @@
 ---
 githubUrl: https://github.com/impresso/impresso-py/blob/main/examples/notebooks/search.ipynb
 authors:
+  - impresso-team
   - RomanKalyakin
 seealso:
   - impresso-py-collections
@@ -11,6 +12,7 @@ googleColabUrl: https://colab.research.google.com/github/impresso/impresso-py/bl
 ---
 
 {/* cell:0 cell_type:code */}
+
 ```python
 from impresso import connect
 
@@ -18,39 +20,49 @@ impresso = connect()
 ```
 
 {/* cell:1 cell_type:markdown */}
+
 ## Term
 
 Find all items containing "impresso" keyword.
 
 {/* cell:2 cell_type:code */}
+
 ```python
 impresso.search.find(q="impresso")
 ```
 
 {/* cell:3 cell_type:markdown */}
+
 ## With text content only
 
 Limit to articles that have text.
 
 {/* cell:4 cell_type:code */}
+
 ```python
 impresso.search.find(q="impresso", with_text_contents=True)
 ```
 
 {/* cell:5 cell_type:markdown */}
+
 ## Title
+
 Find items that have the keyword "impresso" in their title.
 
 {/* cell:6 cell_type:code */}
+
 ```python
 impresso.search.find(title="impresso")
 ```
 
 {/* cell:7 cell_type:markdown */}
+
 ### Complex term requests
+
 Find items that have both terms.
 
 {/* cell:8 cell_type:code */}
+
 ```python
 from impresso import AND
 
@@ -63,6 +75,7 @@ Find items that have either one term or the other.
 Here we find all articles that contain either "homme" or "femme" in the title.
 
 {/* cell:10 cell_type:code */}
+
 ```python
 from impresso import OR
 
@@ -70,11 +83,13 @@ impresso.search.find(title=OR("homme", "femme"))
 ```
 
 {/* cell:11 cell_type:markdown */}
-## Inverted search (everything excluding term A __OR__ term B).
+
+## Inverted search (everything excluding term A **OR** term B).
 
 We want to find all articles with the word "luddite" in the title that do not mention neither "textile" nor "machine"
 
 {/* cell:12 cell_type:code */}
+
 ```python
 from impresso import OR
 
@@ -82,15 +97,17 @@ impresso.search.find(title="luddite", q=~OR("textile", "machine"))
 ```
 
 {/* cell:13 cell_type:markdown */}
+
 ### Complex combintation of terms
 
 The following cell searches all articles with all of the the following condition:
 
-* mentioning "hitler" and "stalin"
-* also mentioning one of: "molotow" or "ribbentrop"
-* and not mentioning "churchill"
+- mentioning "hitler" and "stalin"
+- also mentioning one of: "molotow" or "ribbentrop"
+- and not mentioning "churchill"
 
 {/* cell:14 cell_type:code */}
+
 ```python
 from impresso import AND, OR
 
@@ -98,21 +115,25 @@ impresso.search.find(q=AND("hitler", "stalin") & OR("molotow", "ribbentrop") & ~
 ```
 
 {/* cell:15 cell_type:markdown */}
+
 ## Front page
 
 Find articles published on the front page only
 
 {/* cell:16 cell_type:code */}
+
 ```python
 impresso.search.find(q="impresso", front_page=True)
 ```
 
 {/* cell:17 cell_type:markdown */}
+
 ## Entity ID
 
 Search by entity ID
 
 {/* cell:18 cell_type:code */}
+
 ```python
 impresso.search.find(entity_id="aida-0001-54-Switzerland")
 ```
@@ -121,6 +142,7 @@ impresso.search.find(entity_id="aida-0001-54-Switzerland")
 Find all articles that mention Switzerland and Albert Einstein.
 
 {/* cell:20 cell_type:code */}
+
 ```python
 impresso.search.find(entity_id=AND("aida-0001-54-Switzerland", "aida-0001-50-Albert_Einstein"))
 ```
@@ -129,26 +151,31 @@ impresso.search.find(entity_id=AND("aida-0001-54-Switzerland", "aida-0001-50-Alb
 Find all articles that mention either Switzerland or Albert Einstein.
 
 {/* cell:22 cell_type:code */}
+
 ```python
 impresso.search.find(entity_id=OR("aida-0001-54-Switzerland", "aida-0001-50-Albert_Einstein"))
 ```
 
 {/* cell:23 cell_type:markdown */}
+
 ## Newspaper
 
 Limit search to two newspapers
 
 {/* cell:24 cell_type:code */}
+
 ```python
 impresso.search.find(q="independence", newspaper_id=OR("EXP", "GDL"))
 ```
 
 {/* cell:25 cell_type:markdown */}
+
 ## Date range
 
 Items published between dates
 
 {/* cell:26 cell_type:code */}
+
 ```python
 from impresso import DateRange
 
@@ -159,6 +186,7 @@ impresso.search.find(q="independence", date_range=DateRange("1921-05-21", "2001-
 Articles published at any time excluding the range (not the `~` that negates the range).
 
 {/* cell:28 cell_type:code */}
+
 ```python
 from impresso import DateRange
 
@@ -166,11 +194,13 @@ impresso.search.find(q="independence", date_range=~DateRange("1921-05-21", "2001
 ```
 
 {/* cell:29 cell_type:markdown */}
+
 ## Language
 
 Search for the term "banana" in English or Italian.
 
 {/* cell:30 cell_type:code */}
+
 ```python
 impresso.search.find(q="banana", language=OR("it", "en"))
 ```
@@ -179,235 +209,281 @@ impresso.search.find(q="banana", language=OR("it", "en"))
 And now search for the word "banana" in any language _except_ English or Italian.
 
 {/* cell:32 cell_type:code */}
+
 ```python
 impresso.search.find(q="banana", language=~OR("it", "en"))
 ```
 
 {/* cell:33 cell_type:markdown */}
+
 ## Entity mention
 
 Find articles that mention two entities.
 
 {/* cell:34 cell_type:code */}
+
 ```python
 impresso.search.find(mention=AND("Charlie Chaplin", "Switzerland"))
 ```
 
 {/* cell:35 cell_type:markdown */}
+
 ## Topic
 
 Find articles that match either of the two topics.
 
 {/* cell:36 cell_type:code */}
+
 ```python
 impresso.search.find(topic_id=OR("tm-fr-all-v2.0_tp07_fr", "tm-fr-all-v2.0_tp48_fr"))
 ```
 
 {/* cell:37 cell_type:markdown */}
+
 ## Collection
 
 Find all articles in a collection.
 
 {/* cell:38 cell_type:code */}
+
 ```python
 impresso.search.find(collection_id="REPLACEME")
 ```
 
 {/* cell:39 cell_type:markdown */}
+
 ## Country
 
 Find all articles published in either of the two specified countries.
 
 {/* cell:40 cell_type:code */}
+
 ```python
 impresso.search.find(q="Schengen", country=OR("FR", "CH"))
 ```
 
 {/* cell:41 cell_type:markdown */}
+
 ## Access rights
 
 Limit search to articles with specific access rights.
 
 {/* cell:42 cell_type:code */}
+
 ```python
 impresso.search.find(q="Schengen", access_rights="Closed")
 ```
 
 {/* cell:43 cell_type:markdown */}
+
 ## Partner
 
 Limit search to articles provided by a specific partner of the Impresso project.
 
 {/* cell:44 cell_type:code */}
+
 ```python
 impresso.search.find(q="Schengen", partner_id="Migros")
 ```
 
 {/* cell:45 cell_type:markdown */}
+
 ## Text reuse cluster
 
 Find all articles that are part of a specific text reuse cluster.
 
 {/* cell:46 cell_type:code */}
+
 ```python
 from impresso import OR
 impresso.search.find(text_reuse_cluster_id=OR("tr-nobp-all-v01-c29"))
 ```
 
 {/* cell:47 cell_type:markdown */}
+
 # Facets
 
-Facets are a way to get a summary of the search results from the perspective of a specific field. In a facet search result the field values are grouped together and the number of items in each group is displayed. 
+Facets are a way to get a summary of the search results from the perspective of a specific field. In a facet search result the field values are grouped together and the number of items in each group is displayed.
 
 Facet search method has the same attributes as the search method.
 
 {/* cell:48 cell_type:markdown */}
+
 ## Date range
 
 Get the number of articles that mention "Impresso", published on ever particular date.
 
 {/* cell:49 cell_type:code */}
+
 ```python
 impresso.search.facet("daterange", q="impresso")
 ```
 
 {/* cell:50 cell_type:markdown */}
+
 ## Year
 
 Get the number of articles that mention "impresso", published during every particular year.
 
 {/* cell:51 cell_type:code */}
+
 ```python
 impresso.search.facet("year", q="impresso")
 ```
 
 {/* cell:52 cell_type:markdown */}
+
 ## Content length
 
 Get the number of articles that mention "impresso", grouped by content length.
 
 {/* cell:53 cell_type:code */}
+
 ```python
 impresso.search.facet("contentLength", q="impresso")
 ```
 
 {/* cell:54 cell_type:markdown */}
+
 ## Month
 
 Get the number of articles that mention "impresso", published during every particular month.
 
 {/* cell:55 cell_type:code */}
+
 ```python
 impresso.search.facet("month", q="impresso")
 ```
 
 {/* cell:56 cell_type:markdown */}
+
 ## Country
 
 Get the number of articles that mention "impresso", grouped by country they were published in.
 
 {/* cell:57 cell_type:code */}
+
 ```python
 impresso.search.facet("country", q="impresso")
 ```
 
 {/* cell:58 cell_type:markdown */}
+
 ## Type
 
 Get the number of items that mention "impresso", grouped by type of item.
 
 {/* cell:59 cell_type:code */}
+
 ```python
 impresso.search.facet("type")
 ```
 
 {/* cell:60 cell_type:markdown */}
+
 ## Topic
 
 Find topics that the articles mentioning "impresso" are related to.
 
 {/* cell:61 cell_type:code */}
+
 ```python
 impresso.search.facet("topic", q="pomme")
 ```
 
 {/* cell:62 cell_type:markdown */}
+
 ## Collection
 
 Find collections the articles mentioning "pomme" are part of.
 
 {/* cell:63 cell_type:code */}
+
 ```python
 impresso.search.facet("collection", q="pomme")
 ```
 
 {/* cell:64 cell_type:markdown */}
+
 ## Newspaper
 
 Find newspapers that the articles mentioning "Schengen" were published in.
 
 {/* cell:65 cell_type:code */}
+
 ```python
 impresso.search.facet("newspaper", q="Schengen")
 ```
 
 {/* cell:66 cell_type:markdown */}
+
 ## Language
 
 Find all languages the articles mentioning "impresso" were published in.
 
 {/* cell:67 cell_type:code */}
+
 ```python
 impresso.search.facet("language", q="Schengen")
 ```
 
 {/* cell:68 cell_type:markdown */}
+
 ## Person
 
 Find all persons mentioned in articles that mention "Schengen". Get only the last page.
 
 {/* cell:69 cell_type:code */}
+
 ```python
 impresso.search.facet("person", q="Schengen", offset=7140)
 ```
 
 {/* cell:70 cell_type:markdown */}
+
 ## Location
 
 Find all locations mentioned in articles that mention "Schengen". Get only the last page.
 
 {/* cell:71 cell_type:code */}
+
 ```python
 impresso.search.facet("location", q="Schengen", offset=3310)
 ```
 
 {/* cell:72 cell_type:markdown */}
+
 ## NAG
 
 Find all entities without a known type mentioned in articles that mention "homme" and "femme".
 
 {/* cell:73 cell_type:code */}
+
 ```python
 from impresso import AND
 impresso.search.facet("nag", title=AND("homme", "femme"))
 ```
 
 {/* cell:74 cell_type:markdown */}
+
 ## Access rights
 
 Get access rights of articles mentioning "pomme".
 
 {/* cell:75 cell_type:code */}
+
 ```python
 impresso.search.facet("accessRight", q="pomme")
 ```
 
 {/* cell:76 cell_type:markdown */}
+
 ## Partner
 
 Get Impresso partners that provided articles mentioning "pomme".
 
 {/* cell:77 cell_type:code */}
+
 ```python
 impresso.search.facet("partner", q="pomme")
 ```