Track, return cost and usage metrics in chat api response

- Track input, output token usage and cost for interactions
  via chat api with openai, anthropic and google chat models

- Get usage metadata from OpenAI using stream_options
- Handle openai proxies that do not support passing usage in response

- Add new usage, end response  events returned by chat api.
  - This can be optionally consumed by clients at a later point
  - Update streaming clients to mark message as completed after new
    end response event, not after end llm response event
- Ensure usage data from final response generation step is included
  - Pass usage data after llm response complete. This allows gathering
    token usage and cost for the final response generation step across
    streaming and non-streaming modes

src/interface/web/app/common/chatFunctions.ts

@@ -133,7 +133,7 @@ export function processMessageChunk(
         console.log(`Started streaming: ${new Date()}`);
     } else if (chunk.type === "end_llm_response") {
         console.log(`Completed streaming: ${new Date()}`);
-
+    } else if (chunk.type === "end_response") {
         // Append any references after all the data has been streamed
         if (codeContext) currentMessage.codeContext = codeContext;
         if (onlineContext) currentMessage.onlineContext = onlineContext;