666ghj/MiroFish · error · Error

t('step5.noResponse')

Error message

t('step5.noResponse')

What it means

Thrown in sendToAgent when the interviewAgents call succeeded (res.success && res.data) but the per-agent response could not be extracted: the results dictionary (keys like reddit_<id> / twitter_<id>) had no entry for the selected agent_id, or the entry existed but contained neither response nor answer. It marks a shape/empty-content mismatch between what the backend interview pipeline returned and what the component expects.

Solutions

1. Log the raw resultsDict (res.data.result.results) when the error fires to see which keys the backend actually returned.
2. Check the backend interview/simulation logs for the failing agent_id to find the worker or LLM failure.
3. Confirm the key mapping: the component looks up `reddit_${agentId}` then `twitter_${agentId}` then the first value — verify agentId matches the backend's numbering.
4. If keys exist but values are empty, fix the LLM call for that agent (prompt/model/timeout) server-side.
5. Add a schema check on the backend so it always returns response or answer per requested agent_id, or an explicit per-agent error entry.

Example fix

// before
if (agentResult) {
  responseContent = agentResult.response || agentResult.answer
}
// ...
} else {
  throw new Error(t('step5.noResponse'))
}

// after - include the agent id and returned keys for diagnosis
if (agentResult) {
  responseContent = agentResult.response || agentResult.answer
}
// ...
} else {
  throw new Error(
    t('step5.noResponse') +
    ` (agent_id=${agentId}, keys=${Object.keys(resultsDict).join(',')})`
  )
}

const resultData = res.data.result || res.data
const resultsDict = resultData.results || resultData
const agentId = selectedAgentIndex.value
const hasEntry =
  (typeof resultsDict === 'object' && resultsDict !== null && !Array.isArray(resultsDict) &&
    (resultsDict[`reddit_${agentId}`] || resultsDict[`twitter_${agentId}`] || Object.values(resultsDict).length > 0)) ||
  (Array.isArray(resultsDict) && resultsDict.length > 0)

function extractAgentResponse(resultsDict, agentId) {
  if (Array.isArray(resultsDict)) {
    const hit = resultsDict[0]
    return hit?.response ?? hit?.answer ?? null
  }
  if (resultsDict && typeof resultsDict === 'object') {
    const entry = resultsDict[`reddit_${agentId}`] || resultsDict[`twitter_${agentId}`] || Object.values(resultsDict)[0]
    return entry?.response ?? entry?.answer ?? null
  }
  return null
}

try {
  const responseContent = extractAgentResponse(resultsDict, agentId)
  if (!responseContent) {
    throw new Error(`${t('step5.noResponse')} (agent_id=${agentId}, keys=${Object.keys(resultsDict).join(',')})`)
  }
  /* push assistant message */
} catch (err) {
  addLog(t('log.sendFailed', { error: err.message }))
}

When it happens

Trigger: interviewAgents returns results keyed for different agent ids (e.g. reddit_0 exists but user selected agent 2); the platform worker for that agent crashed so its key is missing; the LLM returned an empty string so response/answer are empty; or the backend changed its results schema (renamed fields, nested deeper).

Common situations: Agent id mismatch after profiles list and results list get out of sync (frontend indexes by array position, backend by platform agent id); one social-platform worker failing silently in a multi-platform simulation; upstream schema drift after a backend update; LLM returning empty content under strict token limits.

Related errors

• res.error || t('step5.requestFailed')
• t('step5.selectAgentFirst')
• LLM returned empty JSON content
• LLM returned no choices
• Zep Batch API returned no batch_id

AI-assisted analysis of 666ghj/MiroFish@b5b53acc57 (2026-08-14). Data as JSON: /api/errors/98932e5954474d4a. Report an issue: GitHub.

Appendix: source

Thrown at frontend/src/components/Step5Interaction.vue:769

      const twitterKey = `twitter_${agentId}`
      const agentResult = resultsDict[redditKey] || resultsDict[twitterKey] || Object.values(resultsDict)[0]
      if (agentResult) {
        responseContent = agentResult.response || agentResult.answer
      }
    } else if (Array.isArray(resultsDict) && resultsDict.length > 0) {
      // 兼容数组格式
      responseContent = resultsDict[0].response || resultsDict[0].answer
    }
    
    if (responseContent) {
      chatHistory.value.push({
        role: 'assistant',
        content: responseContent,
        timestamp: new Date().toISOString()
      })
      addLog(t('log.agentReplied', { name: selectedAgent.value.username }))
    } else {
      throw new Error(t('step5.noResponse'))
    }
  } else {
    throw new Error(res.error || t('step5.requestFailed'))
  }
}

const scrollToBottom = () => {
  nextTick(() => {
    if (chatMessages.value) {
      chatMessages.value.scrollTop = chatMessages.value.scrollHeight
    }
  })
}

// Survey Methods
const toggleAgentSelection = (idx) => {
  const newSet = new Set(selectedAgents.value)
  if (newSet.has(idx)) {

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