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Returns

Returns an InferenceResult object.

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Example

inference_result = galtea.inference_results.create(
    session_id="YOUR_SESSION_ID",
    input="What is the capital of France?",
    output="Paris is the capital of France."
)

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Parameters

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session_id
string
required
The session ID to log the inference result to.
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input
string
required
The input text/prompt.
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output
string
required
The generated output/response.
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retrieval_context
string
Context retrieved for RAG systems.
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latency
float
Latency in milliseconds.
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usage_info
dict[str, int]
Information about token usage during the model call. Possible keys include:
  • input_tokens: Number of input tokens sent to the model.
  • output_tokens: Number of output tokens generated by the model.
  • cache_read_input_tokens: Number of input tokens read from the cache.
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cost_info
dict[str, float]
Information about the cost per token during the model call. Possible keys include:
  • cost_per_input_token: Cost per input token sent to the model.
  • cost_per_output_token: Cost per output token generated by the model.
  • cost_per_cache_read_input_token: Cost per input token read from the cache.
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conversation_simulator_version
string
The version of Galtea’s conversation simulator used to generate the user message (input). This should only be provided when logging a conversation that was generated using the simulator.