# `LangChain.Chains.LLMChain.Modes.WhileNeedsResponse`
[🔗](https://github.com/brainlid/langchain/blob/v0.15.3/lib/chains/llm_chain/modes/while_needs_response.ex#L1)

Execution mode that loops while the chain needs a response.

After each LLM call, if the response contains tool calls, this mode:
1. Executes the pending tool calls
2. Applies any `LangChain.MessageExpansion` those tools asked for
3. Calls the LLM again with the tool results
4. Repeats until `needs_response` is false (no more tool calls)

The LLM always gets the last word after tool execution.

An assistant message that leaves the model's turn open (see
`LangChain.Message.continues_turn?/1`) also leaves `needs_response` true, so
the LLM is called again to finish its turn.

Step 2 costs nothing for a tool that asks for no expansion, which is every
tool that has not opted in. It is included so that a tool carrying one is
honoured under the standard mode rather than silently ignored.

## Options

- `:max_runs` - Maximum LLM calls in one run before returning
  `%LangChainError{type: "exceeded_max_runs"}`. Default: 25. The count starts
  at 0 on every `LLMChain.run/2`, so a chain that is run again after a new
  message gets a fresh budget.

## Usage

    LLMChain.run(chain, mode: :while_needs_response)
    # or
    LLMChain.run(chain, mode: LangChain.Chains.LLMChain.Modes.WhileNeedsResponse)

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*Consult [api-reference.md](api-reference.md) for complete listing*