Harrison/redo docs (#130)

Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>

docs/getting_started/chains.md

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+# Using Chains
+
+Calling an LLM is a great first step, but it's just the beginning.
+Normally when you use an LLM in an application, you are not sending user input directly to the LLM.
+Instead, you are probably taking user input and constructing a prompt, and then sending that to the LLM.
+
+For example, in the previous example, the text we passed in was hardcoded to ask for a name for a company that made colorful socks.
+In this imaginary service, what we would want to do is take only the user input describing what the company does, and then format the prompt with that information.
+
+This is easy to do with LangChain!
+
+First lets define the prompt:
+
+```python
+from langchain.prompts import Prompt
+prompt = Prompt(
+    input_variables=["product"], 
+    template="What is a good name for a company that makes {product}?",
+)
+```
+
+We can now create a very simple chain that will take user input, format the prompt with it, and then send it to the LLM:
+
+```python
+from langchain.chains import LLMChain
+chain = LLMChain(llm=llm, prompt=prompt)
+```
+
+Now we can run that can only specifying the product!
+
+```python
+chain.run("colorful socks")
+```
+
+There we go! There's the first chain.
+
+That is it for the Getting Started example. 
+As a next step, we would suggest checking out the more complex chains in the [Demos section](/examples/demos.rst)

docs/getting_started/environment.md

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+# Setting up your environment
+
+Using LangChain will usually require integrations with one or more model providers, data stores, apis, etc.
+There are two components to setting this up, installing the correct python packages and setting the right environment variables.
+
+## Python packages
+The python package needed varies based on the integration. See the list of integrations for details.
+There should also be helpful error messages raised if you try to run an integration and are missing any required python packages.
+
+## Environment Variables
+The environment variable needed varies based on the integration. See the list of integrations for details.
+There should also be helpful error messages raised if you try to run an integration and are missing any required environment variables.
+
+You can set the environment variable in a few ways. 
+If you are trying to set the environment variable `FOO` to value `bar`, here are the ways you could do so:
+- From the command line:
+```
+export FOO=bar
+```
+- From the python notebook/script:
+```python
+import os
+os.environ["FOO"] = "bar"
+```
+
+For the Getting Started example, we will be using OpenAI's APIs, so we will first need to install their SDK:
+
+```
+pip install openai
+```
+
+We will then need to set the environment variable. Let's do this from inside the Jupyter notebook (or Python script).
+
+```python
+import os
+os.environ["OPENAI_API_KEY"] = "..."
+```

docs/getting_started/installation.md

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+# Installation
+
+LangChain is available on PyPi, so to it is easily installable with: 
+
+```
+pip install langchain
+```
+
+For more involved installation options, see the [Installation Reference](/installation.md) section.
+
+That's it! LangChain is now installed. You can now use LangChain from a python script or Jupyter notebook.

docs/getting_started/llm.md

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+# Calling a LLM
+
+The most basic building block of LangChain is calling an LLM on some input.
+Let's walk through a simple example of how to do this. 
+For this purpose, let's pretend we are building a service that generates a company name based on what the company makes.
+
+In order to do this, we first need to import the LLM wrapper.
+
+```python
+from langchain.llms import OpenAI
+```
+
+We can then initialize the wrapper with any arguments.
+In this example, we probably want the outputs to be MORE random, so we'll initialize it with a HIGH temperature.
+
+```python
+llm = OpenAI(temperature=0.9)
+```
+
+We can now call it on some input!
+
+```python
+text = "What would be a good company name a company that makes colorful socks?"
+llm(text)
+```