Simplify HumanMessages in the quick start guide (#4026)

In the section `Get Message Completions from a Chat Model` of the quick
start guide, the HumanMessage doesn't need to include `Translate this
sentence from English to French.` when there is a system message.

Simplify HumanMessages in these examples can further demonstrate the
power of LLM.

docs/getting_started/getting_started.md

@@ -316,7 +316,7 @@ You can also pass in multiple messages for OpenAI's gpt-3.5-turbo and gpt-4 mode
 ```python
 messages = [
     SystemMessage(content="You are a helpful assistant that translates English to French."),
-    HumanMessage(content="Translate this sentence from English to French. I love programming.")
+    HumanMessage(content="I love programming.")
 ]
 chat(messages)
 # -> AIMessage(content="J'aime programmer.", additional_kwargs={})
@@ -327,22 +327,22 @@ You can go one step further and generate completions for multiple sets of messag
 batch_messages = [
     [
         SystemMessage(content="You are a helpful assistant that translates English to French."),
-        HumanMessage(content="Translate this sentence from English to French. I love programming.")
+        HumanMessage(content="I love programming.")
     ],
     [
         SystemMessage(content="You are a helpful assistant that translates English to French."),
-        HumanMessage(content="Translate this sentence from English to French. I love artificial intelligence.")
+        HumanMessage(content="I love artificial intelligence.")
     ],
 ]
 result = chat.generate(batch_messages)
 result
-# -> LLMResult(generations=[[ChatGeneration(text="J'aime programmer.", generation_info=None, message=AIMessage(content="J'aime programmer.", additional_kwargs={}))], [ChatGeneration(text="J'aime l'intelligence artificielle.", generation_info=None, message=AIMessage(content="J'aime l'intelligence artificielle.", additional_kwargs={}))]], llm_output={'token_usage': {'prompt_tokens': 71, 'completion_tokens': 18, 'total_tokens': 89}})
+# -> LLMResult(generations=[[ChatGeneration(text="J'aime programmer.", generation_info=None, message=AIMessage(content="J'aime programmer.", additional_kwargs={}))], [ChatGeneration(text="J'aime l'intelligence artificielle.", generation_info=None, message=AIMessage(content="J'aime l'intelligence artificielle.", additional_kwargs={}))]], llm_output={'token_usage': {'prompt_tokens': 57, 'completion_tokens': 20, 'total_tokens': 77}})
 ```
 
 You can recover things like token usage from this LLMResult:
 ```
 result.llm_output['token_usage']
-# -> {'prompt_tokens': 71, 'completion_tokens': 18, 'total_tokens': 89}
+# -> {'prompt_tokens': 57, 'completion_tokens': 20, 'total_tokens': 77}
 ```
 
 

docs/modules/models/chat/getting_started.ipynb

@@ -107,7 +107,7 @@
    "source": [
     "messages = [\n",
     "    SystemMessage(content=\"You are a helpful assistant that translates English to French.\"),\n",
-    "    HumanMessage(content=\"Translate this sentence from English to French. I love programming.\")\n",
+    "    HumanMessage(content=\"I love programming.\")\n",
     "]\n",
     "chat(messages)"
    ]
@@ -131,7 +131,7 @@
     {
      "data": {
       "text/plain": [
-       "LLMResult(generations=[[ChatGeneration(text=\"J'aime programmer.\", generation_info=None, message=AIMessage(content=\"J'aime programmer.\", additional_kwargs={}))], [ChatGeneration(text=\"J'aime l'intelligence artificielle.\", generation_info=None, message=AIMessage(content=\"J'aime l'intelligence artificielle.\", additional_kwargs={}))]], llm_output={'token_usage': {'prompt_tokens': 71, 'completion_tokens': 18, 'total_tokens': 89}})"
+       "LLMResult(generations=[[ChatGeneration(text=\"J'aime programmer.\", generation_info=None, message=AIMessage(content=\"J'aime programmer.\", additional_kwargs={}))], [ChatGeneration(text=\"J'aime l'intelligence artificielle.\", generation_info=None, message=AIMessage(content=\"J'aime l'intelligence artificielle.\", additional_kwargs={}))]], llm_output={'token_usage': {'prompt_tokens': 57, 'completion_tokens': 20, 'total_tokens': 77}})"
       ]
      },
      "execution_count": 5,
@@ -143,11 +143,11 @@
     "batch_messages = [\n",
     "    [\n",
     "        SystemMessage(content=\"You are a helpful assistant that translates English to French.\"),\n",
-    "        HumanMessage(content=\"Translate this sentence from English to French. I love programming.\")\n",
+    "        HumanMessage(content=\"I love programming.\")\n",
     "    ],\n",
     "    [\n",
     "        SystemMessage(content=\"You are a helpful assistant that translates English to French.\"),\n",
-    "        HumanMessage(content=\"Translate this sentence from English to French. I love artificial intelligence.\")\n",
+    "        HumanMessage(content=\"I love artificial intelligence.\")\n",
     "    ],\n",
     "]\n",
     "result = chat.generate(batch_messages)\n",
@@ -171,9 +171,9 @@
     {
      "data": {
       "text/plain": [
-       "{'token_usage': {'prompt_tokens': 71,\n",
+       "{'token_usage': {'prompt_tokens': 57,\n",
-       "  'completion_tokens': 18,\n",
+       "  'completion_tokens': 20,\n",
-       "  'total_tokens': 89}}"
+       "  'total_tokens': 77}}"
       ]
      },
      "execution_count": 6,