Fix 1st person language

examples/gemini/python/langchain/Gemini_LangChain_QA_Chroma_WebLoad.ipynb

@@ -433,7 +433,7 @@
         "You'll now create a retriever that can retrieve website data embeddings from the newly created Chroma vector store. This retriever can be later used to pass embeddings that provide more context to the LLM for answering user's queries.\n",
         "\n",
         "\n",
-        "To load the vector store that we previously stored in the disk, you can specify the name of the directory that contains the vector store in `persist_directory` and the embedding model in the `embedding_function` arguments of Chroma's initializer.\n",
+        "To load the vector store that you previously stored in the disk, you can specify the name of the directory that contains the vector store in `persist_directory` and the embedding model in the `embedding_function` arguments of Chroma's initializer.\n",
         "\n",
         "You can then invoke the `as_retriever` function of `Chroma` on the vector store to create a retriever."
       ]
@@ -598,7 +598,7 @@
         "\n",
         "# Create stuff documents chain using LCEL.\n",
         "#\n",
-        "# This is called a chain because we are chaining together different elements\n",
+        "# This is called a chain because you are chaining together different elements\n",
         "# with the LLM. In the following example, to create the stuff chain, you will\n",
         "# combine the relevant context from the website data matching the question, the\n",
         "# LLM model, and the output parser together like a chain using LCEL.\n",

examples/gemini/python/langchain/Gemini_LangChain_Summarization_WebLoad.ipynb

@@ -345,7 +345,7 @@
       "outputs": [],
       "source": [
         "# Create Stuff documents chain using LCEL.\n",
-        "# This is called a chain because we are chaining\n",
+        "# This is called a chain because you are chaining\n",
         "# together different elements with the LLM.\n",
         "# In the following example, to create stuff chain,\n",
         "# you will combine content, prompt, LLM model and\n",