formatting

examples/langchain-python/README.md

@@ -1,8 +1,9 @@
-This example shows how to run a Python (LangChain) chain implementation with Promptfoo.  It compares GPT-4 versus LangChain's LLM Math module.
+This example shows how to run a Python (LangChain) chain implementation with Promptfoo. It compares GPT-4 versus LangChain's LLM Math module.
 
 To run it, first create a virtual env and install the requirements:
 
 Then activate the virtual env.
+
 ```
 python3 -m venv venv
 source venv/bin/activate
@@ -10,7 +11,7 @@ pip install -r requirements.txt
 ```
 
 Then run the eval:
+
 ```
 npx promptfoo eval
 ```
-

src/providers/anthropic.ts

@@ -25,7 +25,7 @@ export class AnthropicCompletionProvider implements ApiProvider {
   constructor(modelName: string, apiKey?: string, context?: AnthropicCompletionOptions) {
     this.modelName = modelName;
     this.apiKey = apiKey || process.env.ANTHROPIC_API_KEY;
-    this.anthropic = new Anthropic({apiKey: this.apiKey});
+    this.anthropic = new Anthropic({ apiKey: this.apiKey });
     this.options = context || {};
   }
 

test/providers.test.ts

@@ -79,7 +79,7 @@ describe('providers', () => {
     const provider = new AnthropicCompletionProvider('claude-1', 'test-api-key');
     provider.anthropic.completions.create = jest.fn().mockResolvedValue({
       completion: 'Test output',
-    })
+    });
     const result = await provider.callApi('Test prompt');
 
     expect(provider.anthropic.completions.create).toHaveBeenCalledTimes(1);