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OpenAI

Access GPT models including standard chat models and reasoning models (o1, o3, GPT-5).

Configuration

OPENAI_API_KEY=sk-...

Dual API Architecture

OpenAI provider automatically routes between two APIs based on model metadata:

  • Chat Completions API: Standard GPT models (gpt-4o, gpt-4-turbo, gpt-3.5-turbo)
  • Responses API: Reasoning models (o1, o3, o4-mini, gpt-5) with extended thinking

Provider Options

Passed via :provider_options keyword:

max_completion_tokens

  • Type: Integer
  • Purpose: Required for reasoning models (o1, o3, gpt-5)
  • Note: ReqLLM auto-translates max_tokens to max_completion_tokens for reasoning models
  • Example: provider_options: [max_completion_tokens: 4000]

openai_structured_output_mode

  • Type: :auto | :json_schema | :tool_strict
  • Default: :auto
  • Purpose: Control structured output strategy
  • :auto: Use json_schema when supported, else strict tools
  • :json_schema: Force response_format with json_schema
  • :tool_strict: Force strict: true on function tools
  • Example: provider_options: [openai_structured_output_mode: :json_schema]

response_format

  • Type: Map
  • Purpose: Custom response format configuration
  • Example: 
    provider_options: [
  response_format: %{
    type: "json_schema",
    json_schema: %{
      name: "person",
      schema: %{type: "object", properties: %{name: %{type: "string"}}}
    }
  }
]

openai_parallel_tool_calls

  • Type: Boolean | nil
  • Default: nil
  • Purpose: Override parallel tool call behavior
  • Example: provider_options: [openai_parallel_tool_calls: false]

reasoning_effort

  • Type: :low | :medium | :high
  • Purpose: Control reasoning effort (Responses API only)
  • Example: reasoning_effort: :high

service_tier

  • Type: :auto | :default | :flex | :priority | String
  • Purpose: Service tier for request prioritization
  • Example: service_tier: :auto

seed

  • Type: Integer
  • Purpose: Set seed for reproducible outputs
  • Example: provider_options: [seed: 42]

logprobs

  • Type: Boolean
  • Purpose: Request log probabilities
  • Example: provider_options: [logprobs: true, top_logprobs: 3]

top_logprobs

  • Type: Integer (1-20)
  • Purpose: Number of log probabilities to return
  • Requires: logprobs: true
  • Example: provider_options: [logprobs: true, top_logprobs: 5]

user

  • Type: String
  • Purpose: Track usage by user identifier
  • Example: provider_options: [user: "user_123"]

Embedding Options

dimensions

  • Type: Positive integer
  • Purpose: Control embedding dimensions (model-specific ranges)
  • Example: provider_options: [dimensions: 512]

encoding_format

  • Type: "float" | "base64"
  • Purpose: Format for embedding output
  • Example: provider_options: [encoding_format: "base64"]

Responses API Resume Flow

previous_response_id

  • Type: String
  • Purpose: Resume tool calling flow from previous response
  • Example: provider_options: [previous_response_id: "resp_abc123"]

tool_outputs

  • Type: List of %{call_id, output} maps
  • Purpose: Provide tool execution results for resume flow
  • Example: provider_options: [tool_outputs: [%{call_id: "call_1", output: "result"}]]

Usage Metrics

OpenAI provides comprehensive usage data including:

  • reasoning_tokens - For reasoning models (o1, o3, gpt-5)
  • cached_tokens - Cached input tokens
  • Standard input/output/total tokens and costs

Resources
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