Update pdf.mdx

.github/CONTRIBUTING.md

@@ -212,7 +212,7 @@ ignore-words-list = 'momento,collison,ned,foor,reworkd,parth,whats,aapply,mysogy
 
 ## Working with Optional Dependencies
 
-Langchain relies heavily on optional dependencies to keep the Langchain package lightweight.
+Langchain relies heavily on optional dependencies to keep the LangChain package lightweight.
 
 You only need to add a new dependency if a **unit test** relies on the package.
 If your package is only required for **integration tests**, then you can skip these

docs/docs/community.md

@@ -32,7 +32,7 @@ One of our favorite things about working in AI is how much enthusiasm there is f
     - **Submit an event to our calendar:** Email us at events@langchain.dev with a link to your event page! We can also help you spread the word with our local communities.
 - **Host a meetup:** If you want to bring a group of builders together, we want to help! We can publicize your event on our event calendar/Twitter, share it with our local communities in Discord, send swag, or potentially hook you up with a sponsor. Email us at events@langchain.dev to tell us about your event!
 - **Become a meetup sponsor:** We often hear from groups of builders that want to get together, but are blocked or limited on some dimension (space to host, budget for snacks, prizes to distribute, etc.). If you’d like to help, send us an email to events@langchain.dev we can share more about how it works!
-- **Speak at an event:** Meetup hosts are always looking for great speakers, presenters, and panelists. If you’d like to do that at an event, send us an email to hello@langchain.dev with more information about yourself, what you want to talk about, and what city you’re based in and we’ll try to match you with an upcoming event!
+- **Speak at an event:** Meetup hosts are always looking for great speakers, presenters, and panellists. If you’d like to do that at an event, send us an email to hello@langchain.dev with more information about yourself, what you want to talk about, and what city you’re based in and we’ll try to match you with an upcoming event!
 - **Tell us about your LLM community:** If you host or participate in a community that would welcome support from LangChain and/or our team, send us an email at hello@langchain.dev and let us know how we can help.
 
 # 📣 Help Us Amplify Your Work

docs/docs/modules/agents/agent_types/xml_agent.ipynb

@@ -177,7 +177,7 @@
     {
      "data": {
       "text/plain": [
-       "{'question': 'whats the weather in New york?',\n",
+       "{'question': 'what's the weather in New york?',\n",
        " 'output': '\\nThe weather in New York is 32 degrees.\\n'}"
       ]
      },
@@ -187,7 +187,7 @@
     }
    ],
    "source": [
-    "agent_executor.invoke({\"question\": \"whats the weather in New york?\"})"
+    "agent_executor.invoke({\"question\": \"what's the weather in New york?\"})"
    ]
   },
   {
@@ -258,7 +258,7 @@
     {
      "data": {
       "text/plain": [
-       "{'input': 'whats the weather in New york?',\n",
+       "{'input': 'what's the weather in New york?',\n",
        " 'output': 'The weather in New York is 32 degrees'}"
       ]
      },
@@ -268,7 +268,7 @@
     }
    ],
    "source": [
-    "agent_executor.invoke({\"input\": \"whats the weather in New york?\"})"
+    "agent_executor.invoke({\"input\": \"what's the weather in New york?\"})"
    ]
   },
   {

docs/docs/modules/data_connection/document_loaders/pdf.mdx

@@ -72,7 +72,7 @@ for doc in docs:
     Fig. 4: Illustration of (a) the original historical Japanese document with layout
     detection results and (b) a recreated version of the document image that achieves
     much better character recognition recall. The reorganization algorithm rearranges
-    the tokens based on the their detect
+    the tokens based on their detect
     3: 4 Z. Shen et al.
     Efficient Data AnnotationC u s t o m i z e d  M o d e l  T r a i n i n gModel Cust omizationDI A Model HubDI A Pipeline SharingCommunity PlatformLa y out Detection ModelsDocument Images
     T h e  C o r e  L a y o u t P a r s e r  L i b r a r yOCR ModuleSt or age & VisualizationLa y ou
@@ -432,4 +432,4 @@ Besides the AWS configuration, it is very similar to the other PDF loaders, whil
 from langchain.document_loaders import AmazonTextractPDFLoader
 loader = AmazonTextractPDFLoader("example_data/alejandro_rosalez_sample-small.jpeg")
 documents = loader.load()
-```
+```

docs/docs/modules/model_io/llms/llm_caching.mdx

@@ -106,7 +106,7 @@ llm.predict("Tell me a joke")
 ## Optional caching in chains
 You can also turn off caching for particular nodes in chains. Note that because of certain interfaces, it's often easier to construct the chain first, and then edit the LLM afterwards.
 
-As an example, we will load a summarizer map-reduce chain. We will cache results for the map-step, but then not freeze it for the combine step.
+As an example, we will load a summarizer map-reduce chain. We will cache results for the map-step, but then not freeze it for the combined step.
 
 
 ```python