forked from Archives/langchain
Updated a few things that seemed out of date in the getting started docs
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@ -12,28 +12,36 @@ This is easy to do with LangChain!
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First lets define the prompt:
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```python
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from langchain.prompts import PromptTemplate
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from langchain import Prompt
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prompt = PromptTemplate(
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prompt = Prompt(
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input_variables=["product"],
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template="What is a good name for a company that makes {product}?",
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)
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```
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Next, let's instantiate the LLM (we'll use OpenAI's text-davinci-002 model in this example, with a temperature setting of 0.5.
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```python
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from langchain import OpenAI
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llm = OpenAI(model_name="text-davinci-002", temperature=0.5)
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```
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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:
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```python
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from langchain.chains import LLMChain
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from langchain import LLMChain
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chain = LLMChain(llm=llm, prompt=prompt)
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```
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Now we can run that can only specifying the product!
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```python
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chain.run("colorful socks")
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chain.predict("colorful socks")
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```
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There we go! There's the first chain.
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That is it for the Getting Started example.
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That is it for the Getting Started example.
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As a next step, we would suggest checking out the more complex chains in the [Demos section](/examples/demos)
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