docs: Simplified Prompts sample app.

examples/LangChain.Samples.Prompts/Program.cs

@@ -3,16 +3,15 @@
 using LangChain.Providers.OpenAI.Predefined;
 using LangChain.Schema;
 
-const string apiKey = "API-KEY";
-using var httpClient = new HttpClient();
-var llm = new OpenAiLatestFastChatModel(apiKey);
+var llm = new OpenAiLatestFastChatModel(Environment.GetEnvironmentVariable("OPENAI_API_KEY")!);
 
-var template = "What is a good name for a company that makes {product}?";
-var prompt = new PromptTemplate(new PromptTemplateInput(template, new List<string>(1) { "product" }));
+var prompt = new PromptTemplate(new PromptTemplateInput(
+    template: "What is a good name for a company that makes {product}?",
+    inputVariables: ["product"]));
 
 var chain = new LlmChain(new LlmChainInput(llm, prompt));
 
-var result = await chain.CallAsync(new ChainValues(new Dictionary<string, object>(1)
+var result = await chain.CallAsync(new ChainValues(new Dictionary<string, object>
 {
     { "product", "colourful socks" }
 }));
@@ -26,16 +25,13 @@
 
 Console.WriteLine(result2);
 
-// We can also construct an LLMChain from a ChatPromptTemplate and a chat model.
-var chat = new OpenAiLatestFastChatModel(apiKey);
-
-var chatPrompt = ChatPromptTemplate.FromPromptMessages(new List<BaseMessagePromptTemplate>(2)
-{
-    SystemMessagePromptTemplate.FromTemplate("You are a helpful assistant that translates {input_language} to {output_language}."),
+var chatPrompt = ChatPromptTemplate.FromPromptMessages([
+    SystemMessagePromptTemplate.FromTemplate(
+        "You are a helpful assistant that translates {input_language} to {output_language}."),
     HumanMessagePromptTemplate.FromTemplate("{text}")
-});
+]);
 
-var chainB = new LlmChain(new LlmChainInput(chat, chatPrompt)
+var chainB = new LlmChain(new LlmChainInput(llm, chatPrompt)
 {
     Verbose = true
 });