> ## Documentation Index
> Fetch the complete documentation index at: https://futureagi.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Conversation Coherence

> Evaluates how logically a conversation flows and maintains context throughout the dialogue. This metric assesses whether responses are consistent, contextually appropriate, and maintain a natural progression of ideas within the conversation thread.

<CodeGroup>
  ```python Python theme={null}
  result = evaluator.evaluate(
      eval_templates="conversation_coherence",
      inputs={
          "conversation": '''
                      User: My Wi-Fi keeps disconnecting every few minutes.
                      Assistant: You can try restarting your router and updating your network drivers.
                      User: I restarted the router and it's stable now. Thanks!
                      Assistant: Glad to hear that! Let me know if you need anything else.
                    '''
      },
      model_name="turing_flash"
  )

  print(result.eval_results[0].output)
  print(result.eval_results[0].reason)

  ```

  ```typescript JS/TS theme={null}
  import { Evaluator, Templates } from "@future-agi/ai-evaluation";

  const evaluator = new Evaluator();

  const result = await evaluator.evaluate(
    "conversation_coherence",
    {
      conversation: "User: My Wi-Fi keeps disconnecting every few minutes. Assistant: You can try restarting your router and updating your network drivers. User: I restarted the router and it's stable now. Thanks! Assistant: Glad to hear that! Let me know if you need anything else."
    },
    {
      modelName: "turing_flash",
    }
  );

  console.log(result);
  ```
</CodeGroup>

| **Input** |                    |          |                                                                                          |
| --------- | ------------------ | -------- | ---------------------------------------------------------------------------------------- |
|           | **Required Input** | **Type** | **Description**                                                                          |
|           | `conversation`     | `string` | Conversation history between the user and the model provided as query and response pairs |

| **Output** |            |                                                                          |
| ---------- | ---------- | ------------------------------------------------------------------------ |
|            | **Field**  | **Description**                                                          |
|            | **Result** | Returns a score, where higher scores indicate more coherent conversation |
|            | **Reason** | Provides a detailed explanation of the conversation coherence assessment |

***

### What to do when Conversation Coherence is Low

* Review conversation history to identify where context breaks occurred
* Implement context window management to ensure important information is retained
* Consider reducing the length of conversation threads if context loss is persistent

***

### Comparing Conversation Coherence with Similar Evals

1. [Conversation Resolution](https://docs.futureagi.com/future-agi/get-started/evaluation/builtin-evals/conversation-resolution): While Coherence focuses on the flow and context maintenance throughout the conversation, Resolution evaluates whether the conversation reaches a satisfactory conclusion.
2. [Context Adherence](https://docs.futureagi.com/future-agi/get-started/evaluation/builtin-evals/context-adherence): Coherence differs from Context Adherence as it evaluates the internal consistency of the conversation rather than adherence to external context.
3. [Completeness](https://docs.futureagi.com/future-agi/get-started/evaluation/builtin-evals/completeness): Coherence focuses on the logical flow between messages, while Completeness evaluates whether individual responses fully address their queries.