add v4

docs/snippets/get_started/quickstart/import_llms.mdx

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+```python
+from langchain.llms import OpenAI
+from langchain.chat_models import ChatOpenAI
+
+llm = OpenAI()
+chat_model = ChatOpenAI()
+
+llm.predict("hi!")
+>>> "Hi"
+
+chat_model.predict("hi!")
+>>> "Hi"
+```

docs/snippets/get_started/quickstart/input_messages.mdx

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+```python
+from langchain.schema import HumanMessage
+
+text = "What would be a good company name for a company that makes colorful socks?"
+messages = [HumanMessage(content=text)]
+
+llm.predict_messages(messages)
+# >> Feetful of Fun
+
+chat_model.predict_messages(messages)
+# >> Socks O'Color
+```

docs/snippets/get_started/quickstart/input_string.mdx

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+```python
+text = "What would be a good company name for a company that makes colorful socks?"
+
+llm.predict(text)
+# >> Feetful of Fun
+
+chat_model.predict(text)
+# >> Socks O'Color
+```

docs/snippets/get_started/quickstart/installation.mdx

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+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+import CodeBlock from "@theme/CodeBlock";
+
+<Tabs>
+  <TabItem value="pip" label="Pip" default>
+    <CodeBlock language="bash">pip install langchain</CodeBlock>
+  </TabItem>
+  <TabItem value="conda" label="Conda">
+    <CodeBlock language="bash">conda install langchain -c conda-forge</CodeBlock>
+  </TabItem>
+</Tabs>

docs/snippets/get_started/quickstart/llm_chain.mdx

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+```python
+from langchain.chat_models import ChatOpenAI
+from langchain.prompts.chat import (
+    ChatPromptTemplate,
+    SystemMessagePromptTemplate,
+    HumanMessagePromptTemplate,
+)
+from langchain.chains import LLMChain
+from langchain.schema import BaseOutputParser
+
+class CommaSeparatedListOutputParser(BaseOutputParser):
+    """Parse the output of an LLM call to a comma-separated list."""
+
+
+    def parse(self, text: str):
+        """Parse the output of an LLM call."""
+        return text.strip().split(", ")
+
+template = """You are a helpful assistant who generates comma separated lists.
+A user will pass in a category, and you should generated 5 objects in that category in a comma separated list.
+ONLY return a comma separated list, and nothing more."""
+system_message_prompt = SystemMessagePromptTemplate.from_template(template)
+human_template = "{text}"
+human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)
+
+chat_prompt = ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])
+chain = LLMChain(
+    llm=ChatOpenAI(),
+    prompt=chat_prompt,
+    output_parser=CommaSeparatedListOutputParser()
+)
+chain.run("colors")
+# >> ['red', 'blue', 'green', 'yellow', 'orange']
+```

docs/snippets/get_started/quickstart/openai_setup.mdx

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+First we'll need to install their Python package:
+
+```bash
+pip install openai
+```
+
+Accessing the API requires an API key, which you can get by creating an account and heading [here](https://platform.openai.com/account/api-keys). Once we have a key we'll want to set it as an environment variable by running:
+
+```bash
+export OPENAI_API_KEY="..."
+```
+
+If you'd prefer not to set an environment variable you can pass the key in directly via the `openai_api_key` named parameter when initiating the OpenAI LLM class:
+
+```python
+from langchain.llms import OpenAI
+
+llm = OpenAI(openai_api_key="...")
+```

docs/snippets/get_started/quickstart/output_parser.mdx

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+```python
+from langchain.schema import BaseOutputParser
+
+class CommaSeparatedListOutputParser(BaseOutputParser):
+    """Parse the output of an LLM call to a comma-separated list."""
+
+
+    def parse(self, text: str):
+        """Parse the output of an LLM call."""
+        return text.strip().split(", ")
+
+CommaSeparatedListOutputParser().parse("hi, bye")
+# >> ['hi', 'bye']
+```

docs/snippets/get_started/quickstart/prompt_templates_chat_models.mdx

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+```python
+from langchain.prompts.chat import (
+    ChatPromptTemplate,
+    SystemMessagePromptTemplate,
+    HumanMessagePromptTemplate,
+)
+
+template = "You are a helpful assistant that translates {input_language} to {output_language}."
+system_message_prompt = SystemMessagePromptTemplate.from_template(template)
+human_template = "{text}"
+human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)
+
+chat_prompt = ChatPromptTemplate.from_messages([system_message_prompt, human_message_prompt])
+
+chat_prompt.format_messages(input_language="English", output_language="French", text="I love programming.")
+```
+
+```pycon
+[
+    SystemMessage(content="You are a helpful assistant that translates English to French.", additional_kwargs={}),
+    HumanMessage(content="I love programming.")
+]
+```

docs/snippets/get_started/quickstart/prompt_templates_llms.mdx

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+```python
+from langchain.prompts import PromptTemplate
+
+prompt = PromptTemplate.from_template("What is a good name for a company that makes {product}?")
+prompt.format(product="colorful socks")
+```
+
+```pycon
+What is a good name for a company that makes colorful socks?
+```