docs: update cohere documentation (#19700)

**Description:** Update of Cohere documentation (main provider page)
**Issue:** After addition of the Cohere partner package, the
documentation was out of date
**Dependencies:** None

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>

docs/docs/integrations/providers/cohere.mdx

@@ -16,7 +16,7 @@ Get a [Cohere api key](https://dashboard.cohere.ai/) and set it as an environmen
 |API|description|Endpoint docs|Import|Example usage|
 |---|---|---|---|---|
 |Chat|Build chat bots|[chat](https://docs.cohere.com/reference/chat)|`from langchain_cohere import ChatCohere`|[cohere.ipynb](/docs/integrations/chat/cohere)|
-|LLM|Generate text|[generate](https://docs.cohere.com/reference/generate)|`from langchain_cohere import Cohere`|[cohere.ipynb](/docs/integrations/llms/cohere)|
+|LLM|Generate text|[generate](https://docs.cohere.com/reference/generate)|`from langchain_cohere.llms import Cohere`|[cohere.ipynb](/docs/integrations/llms/cohere)|
 |RAG Retriever|Connect to external data sources|[chat + rag](https://docs.cohere.com/reference/chat)|`from langchain.retrievers import CohereRagRetriever`|[cohere.ipynb](/docs/integrations/retrievers/cohere)|
 |Text Embedding|Embed strings to vectors|[embed](https://docs.cohere.com/reference/embed)|`from langchain_cohere import CohereEmbeddings`|[cohere.ipynb](/docs/integrations/text_embedding/cohere)|
 |Rerank Retriever|Rank strings based on relevance|[rerank](https://docs.cohere.com/reference/rerank)|`from langchain.retrievers.document_compressors import CohereRerank`|[cohere.ipynb](/docs/integrations/retrievers/cohere-reranker)|
@@ -30,19 +30,22 @@ from langchain_cohere import ChatCohere
 from langchain_core.messages import HumanMessage
 chat = ChatCohere()
 messages = [HumanMessage(content="knock knock")]
-print(chat(messages))
+print(chat.invoke(messages))
 ```
 
+Usage of the Cohere [chat model](/docs/integrations/chat/cohere)
+
 ### LLM
 
 
 ```python
-from langchain_cohere import Cohere
+from langchain_cohere.llms import Cohere
 
-llm = Cohere(model="command")
+llm = Cohere()
 print(llm.invoke("Come up with a pet name"))
 ```
 
+Usage of the Cohere (legacy) [LLM model](/docs/integrations/llms/cohere) 
 ### ReAct Agent
 
 ```python
@@ -65,7 +68,7 @@ agent = create_cohere_react_agent(
     prompt
 )
 
-agent_executor = AgentExecutor(agent=agent, tools=[internet_search], verbose=True)```
+agent_executor = AgentExecutor(agent=agent, tools=[internet_search], verbose=True)
 
 agent_executor.invoke({
     "input": "In what year was the company that was founded as Sound of Music added to the S&P 500?",
@@ -83,6 +86,8 @@ rag = CohereRagRetriever(llm=ChatCohere())
 print(rag.get_relevant_documents("What is cohere ai?"))
 ```
 
+Usage of the Cohere [RAG Retriever](/docs/integrations/retrievers/cohere)
+
 ### Text Embedding
 
 ```python
@@ -91,3 +96,9 @@ from langchain_cohere import CohereEmbeddings
 embeddings = CohereEmbeddings(model="embed-english-light-v3.0")
 print(embeddings.embed_documents(["This is a test document."]))
 ```
+
+Usage of the Cohere [Text Embeddings model](/docs/integrations/text_embedding/cohere)
+
+### Reranker
+
+Usage of the Cohere [Reranker](/docs/integrations/retrievers/cohere-reranker)