agentscope-ai/agentscope · error · RuntimeError

DashScope text embedding API error: {response}

Error message

DashScope text embedding API error: {response}

What it means

Raised when the DashScope text embedding HTTP API returns a non-200 status code; the whole response object is embedded in the message for diagnosis (auth errors, quota, invalid model name, bad request).

Source

Thrown at src/agentscope/embedding/_dashscope/_model.py:379

            )
            if cached:
                return EmbeddingResponse(
                    embeddings=cached,
                    usage=EmbeddingUsage(tokens=0, time=0),
                    source="cache",
                )

        import dashscope

        start_time = datetime.now()
        response = dashscope.embeddings.TextEmbedding.call(
            api_key=self.api_key,
            **api_kwargs,
        )
        time = (datetime.now() - start_time).total_seconds()

        if response.status_code != 200:
            raise RuntimeError(
                f"DashScope text embedding API error: {response}",
            )

        embeddings = [
            entry["embedding"] for entry in response.output["embeddings"]
        ]
        if self.embedding_cache:
            await self.embedding_cache.store(
                identifier=api_kwargs,
                embeddings=embeddings,
            )
        return EmbeddingResponse(
            embeddings=embeddings,
            usage=EmbeddingUsage(
                tokens=response.usage["total_tokens"],
                time=time,
            ),
        )

View on GitHub (pinned to e90f1c7592)

Solutions

1. Print the response body to identify the exact status code and message, then fix credentials/model/quota accordingly
2. Verify DASHSCOPE_API_KEY is set and valid for the model used
3. Retry with the built-in retry/backoff for transient 429/5xx and reduce batch size

Example fix

# before
resp = await model(texts)  # raises RuntimeError on failure
# after
try:
    resp = await model(texts)
except RuntimeError as e:
    logging.error("dashscope failed: %s", e)
    raise

assert os.getenv(\"DASHSCOPE_API_KEY\"), \"set DASHSCOPE_API_KEY\"

try:\n    await model(texts)\nexcept RuntimeError as e:\n    log.error(\"dashscope: %s\", e)\n    if is_transient(str(e)): await asyncio.sleep(backoff); await model(texts)\n    else: raise

When it happens

Trigger: Calling the text embedding model and DashScope returns status != 200: wrong/missing API key, unknown model name, malformed request payload, rate limits, or service outages.

Common situations: DASHSCOPE_API_KEY not set or revoked; using a model id not enabled for the account; hitting QPS/quota limits at high batch sizes.

Related errors

• DashScope multimodal embedding API error: {res}
• Text embedding model {self.model!r} only accepts str inputs,
• Invalid input: {item!r}. Expected str or DataBlock.
• Multimodal embedding API only supports URL input for video d
• Unsupported media type {media_type!r} in DataBlock. Expected

AI-assisted analysis of agentscope-ai/agentscope@e90f1c7592 (2026-08-28). Data as JSON: /api/errors/bc8fbdee7de8acc1. Report an issue: GitHub.