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fix: Auto-detect and use GLM-4V vision model for character analysis

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2026-01-07 03:33:56 +08:00
parent 8c35b0066f
commit 8d82cf91d5
1 changed files with 15 additions and 3 deletions
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18
pixelle_video/services/quality/character_analyzer.py
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@@ -155,15 +155,27 @@ Output ONLY the JSON object, no additional text."""
base_url=llm_config.base_url base_url=llm_config.base_url
) )
# Use vision model - GLM-4V for ZhiPu, or fall back to configured model
# Vision models: glm-4v, glm-4v-flash, gpt-4-vision-preview
vision_model = llm_config.model
if "glm" in llm_config.model.lower() and "v" not in llm_config.model.lower():
vision_model = "glm-4v-flash" # Use GLM-4V for vision tasks
logger.info(f"Using vision model: {vision_model}")
# Call VLM # Call VLM
response = await client.chat.completions.create( response = await client.chat.completions.create(
model=llm_config.model, model=vision_model,
messages=messages, messages=messages,
temperature=0.3, temperature=0.3,
max_tokens=800 max_tokens=800
) )
vlm_response = response.choices[0].message.content
logger.debug(f"VLM character analysis response: {vlm_response[:150]}...") vlm_response = response.choices[0].message.content if response.choices else None
if vlm_response:
logger.debug(f"VLM character analysis response: {vlm_response[:150] if len(vlm_response) > 150 else vlm_response}...")
else:
logger.warning(f"VLM returned empty content. Full response: {response}")
# Parse response # Parse response
return self._parse_response(vlm_response) return self._parse_response(vlm_response)