diff --git a/docs/ecosystem/atlas.md b/docs/ecosystem/atlas.md
index 160cfd7b..0b3f5e12 100644
--- a/docs/ecosystem/atlas.md
+++ b/docs/ecosystem/atlas.md
@@ -1,12 +1,12 @@
 # AtlasDB
 
-This page covers how to Nomic's Atlas ecosystem within LangChain.
+This page covers how to use Nomic's Atlas ecosystem within LangChain.
 It is broken into two parts: installation and setup, and then references to specific Atlas wrappers.
 
 ## Installation and Setup
 - Install the Python package with `pip install nomic`
 - Nomic is also included in langchains poetry extras `poetry install -E all`
-- 
+
 ## Wrappers
 
 ### VectorStore
diff --git a/docs/ecosystem/bananadev.md b/docs/ecosystem/bananadev.md
index f9be89fd..4961e5f8 100644
--- a/docs/ecosystem/bananadev.md
+++ b/docs/ecosystem/bananadev.md
@@ -5,7 +5,7 @@ It is broken into two parts: installation and setup, and then references to spec
 
 ## Installation and Setup
 
-- Install with `pip3 install banana-dev`
+- Install with `pip install banana-dev`
 - Get an Banana api key and set it as an environment variable (`BANANA_API_KEY`)
 
 ## Define your Banana Template
diff --git a/docs/ecosystem/graphsignal.md b/docs/ecosystem/graphsignal.md
index 2666f59c..45f040ad 100644
--- a/docs/ecosystem/graphsignal.md
+++ b/docs/ecosystem/graphsignal.md
@@ -1,6 +1,6 @@
 # Graphsignal
 
-This page covers how to use the Graphsignal to trace and monitor LangChain.
+This page covers how to use the Graphsignal ecosystem to trace and monitor LangChain.
 
 ## Installation and Setup
 
diff --git a/docs/ecosystem/helicone.md b/docs/ecosystem/helicone.md
index 88cf2e52..61a86eb4 100644
--- a/docs/ecosystem/helicone.md
+++ b/docs/ecosystem/helicone.md
@@ -1,6 +1,6 @@
 # Helicone
 
-This page covers how to use the [Helicone](https://helicone.ai) within LangChain.
+This page covers how to use the [Helicone](https://helicone.ai) ecosystem within LangChain.
 
 ## What is Helicone?
 
diff --git a/docs/modules/memory/key_concepts.md b/docs/modules/memory/key_concepts.md
index 4715c66f..711fad5c 100644
--- a/docs/modules/memory/key_concepts.md
+++ b/docs/modules/memory/key_concepts.md
@@ -10,7 +10,7 @@ One of the simpler forms of memory occurs in chatbots, where they remember previ
 There are a few different ways to accomplish this:
 - Buffer: This is just passing in the past `N` interactions in as context. `N` can be chosen based on a fixed number, the length of the interactions, or other!
 - Summary: This involves summarizing previous conversations and passing that summary in, instead of the raw dialouge itself. Compared to `Buffer`, this compresses information: meaning it is more lossy, but also less likely to run into context length limits.
-- Combination: A combination of the above two approaches, where you compute a summary but also pass in some previous interfactions directly!
+- Combination: A combination of the above two approaches, where you compute a summary but also pass in some previous interactions directly!
 
 ## Entity Memory
 A more complex form of memory is remembering information about specific entities in the conversation.