ollama_thinking_field_handlingTier 1 · 70% confidence
ai-agents-ollama-thinking-fiel-when-using-ollama-with-a-model-that-outputs-a-thin-872ae8e4
agent: ai_agents
When does this happen?
IF When using Ollama with a model that outputs a 'thinking' field in its streaming JSON chunks, LiteLLM raises APIConnectionError because its chunk parser does not recognize this field.
How others solved it
THEN Implement a custom streaming callback that strips or renames the 'thinking' field before the chunk is parsed, or create a custom Ollama Modelfile that modifies the model's template to exclude the 'thinking' field from the response. For a callback, intercept each chunk string, parse it as JSON, remove the 'thinking' key, and return the modified string.
import json
async def fix_ollama_chunk(chunk: str) -> str:
try:
data = json.loads(chunk)
if 'thinking' in data:
del data['thinking']
return json.dumps(data)
except json.JSONDecodeError:
pass
return chunkRelated patterns
github
ai-agents-github-support-for-reasoning-in-openrouter-and-deepseek-p-48add6f0
Tier 1 · 40%
githubai-agents-github-server-capabilities-not-affecting-the-stream-of-ca-ca806d9e
Tier 1 · 40%
githubai-agents-github-patrick-von-platen-cd4d7ceb
Tier 1 · 40%
model_loadingai-agents-model-loading-loading-a-gemma-3-checkpoint-with-automodelforcaus-cc5b7a71
Tier 1 · 70%
githubai-agents-github-runtimeerror-cuda-error-cublas-status-not-initiali-9b601119
Tier 1 · 40%
githubai-agents-github-bug-frequent-ide-disconnections-disrupting-workflo-e9f35aca
Tier 1 · 40%
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