Agent RAG Tutorial with Ollama/ReActAgent failing in tool call because of "missing" Input value

[nea]

Describe the bug
When working on the https://ts.llamaindex.ai/docs/llamaindex/guide/agents/4_agentic_rag tutorial to create an Agent RAG, without OpenAI but with Ollama (command-r7g) locally, the solution does not work, as the required input for the QueryEngineTool is missing the Input: keyword, looked for in react.ts#L99 extractToolUse.

By my tests, I was able to reproduce thoughts as

error: Could not extract tool use from input text: "Thought: I need to use a tool to help me answer the question.
Action: san_francisco_budget_tool ({"query": "What is the budget of San Francisco in 2023-2024?"})"

which can be captured by making "Input:" optional, such as: /\s*Thought: (.*?)\nAction: ([a-zA-Z0-9_]+).*?\.*[Input:]*.*?(\{.*?\})/s
This worked fine for me, and I do not see a breaker to the previous logic. If you agree, I could create a PR or you just change it yourself.
Or am I missing something?

Thanks a lot in advance for your help

To Reproduce
Code to reproduce the behavior:

import {
  FunctionTool,
  HuggingFaceEmbedding,
  MetadataMode,
  Ollama,
  QueryEngineTool,
  ReActAgent,
  Settings,
  SimpleDirectoryReader,
  VectorStoreIndex,
  type NodeWithScore
} from "llamaindex";

Settings.llm = new Ollama({
  model: "command-r7b",
});

Settings.embedModel = new HuggingFaceEmbedding({
  modelType: "BAAI/bge-small-en-v1.5",
});

async function main() {
  Settings.callbackManager.on("llm-tool-call", (event) => {
    console.log(event.detail);
  });
  Settings.callbackManager.on("llm-tool-result", (event) => {
    console.log(event.detail);
  });

  // load our data and create a query engine
  const reader = new SimpleDirectoryReader();
  const documents = await reader.loadData("./data");
  const index = await VectorStoreIndex.fromDocuments(documents);
  const retriever = await index.asRetriever({
    similarityTopK: 10,
  });
  const queryEngine = await index.asQueryEngine({
    retriever,
  });

  // define the query engine as a tool
  const tools = [
    new QueryEngineTool({
      queryEngine: queryEngine,
      metadata: {
        name: "san_francisco_budget_tool",
        description: `This tool can answer detailed questions about the individual components of the budget of San Francisco in 2023-2024.`,    
      },
    }),
  ];

  // create the agent
  // const agent = new OllamaAgent({ tools });
  const agent = new ReActAgent({ tools });

  let response = await agent.chat({
    message: "What's the budget of San Francisco in 2023-2024?",
  });

  console.log(response);
}

main().catch(console.error);

Expected behavior
Tool calls work fine with input

Desktop (please complete the following information):

• OS: macOS
• JS Runtime / Framework / Bundler (select all applicable)
• Node.js
• Deno
• Bun
• Next.js
• ESBuild
• Rollup
• Webpack
• Turbopack
• Vite
• Waku
• Edge Runtime
• AWS Lambda
• Cloudflare Worker
• Others (please elaborate on this)
• Version [e.g. 22]