mix req_llm.gen (ReqLLM v1.0.0)

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Generate text or structured objects from any supported AI model with unified interface.

This consolidated task combines text generation, object generation, streaming, and non-streaming capabilities into a single command. Use flags to control output format and streaming behavior.

Usage

mix req_llm.gen "Your prompt here" [options]

Arguments

prompt          The text prompt to send to the AI model (required)

Options

--model, -m MODEL       Model specification in format provider:model-name
                        Default: openai:gpt-4o-mini

--system, -s SYSTEM     System prompt/message to set context for the AI

--max-tokens TOKENS     Maximum number of tokens to generate
                       (integer, provider-specific limits apply)

--temperature, -t TEMP  Sampling temperature for randomness (0.0-2.0)
                       Lower values = more focused, higher = more creative

--stream                Stream output in real-time (default: true)
--no-stream             Disable streaming (non-streaming mode)
--json                  Generate structured JSON object (default: text)

--log-level, -l LEVEL   Output verbosity level:
                       quiet   - Only show generated content
                       normal  - Show model info and content (default)
                       verbose - Show timing and usage statistics
                       debug   - Show all internal details

Examples

# Basic text generation (streams by default)
mix req_llm.gen "Explain how neural networks work"

# Text generation with specific provider and system prompt
mix req_llm.gen "Write a story about space" \
  --model openai:gpt-4o \
  --system "You are a creative science fiction writer"

# Generate with GPT-5 and high reasoning effort
mix req_llm.gen "Solve this complex math problem step by step" \
  --model openai:gpt-5-mini \
  --reasoning-effort high

# Generate structured JSON object (streams by default)
mix req_llm.gen "Create a user profile for John Smith, age 30, engineer in Seattle" \
  --model openai:gpt-4o-mini \
  --json

# JSON generation with metrics (streams by default)
mix req_llm.gen "Extract person info from this text" \
  --model anthropic:claude-3-sonnet \
  --json \
  --temperature 0.1 \
  --log-level debug

# Non-streaming mode (waits for complete response)
mix req_llm.gen "What is 2+2?" --no-stream

# Quick generation without extra output (streams by default)
mix req_llm.gen "What is 2+2?" --log-level warning

JSON Schema

When using --json flag, objects are generated using a built-in person schema:

{
  "name": "string (required) - Full name of the person",
  "age": "integer - Age in years",
  "occupation": "string - Job or profession",
  "location": "string - City or region where they live"
}

Supported Providers

openai      - OpenAI models (GPT-4, GPT-3.5, etc.)
anthropic   - Anthropic Claude models
groq        - Groq models (fast inference)
google      - Google Gemini models
openrouter  - OpenRouter (access to multiple providers)
xai         - xAI Grok models

Configuration

The default model can be configured in your application config:

# config/config.exs
config :req_llm, default_model: "openai:gpt-4o-mini"

Environment Variables

Most providers require API keys set as environment variables:

OPENAI_API_KEY      - For OpenAI models
ANTHROPIC_API_KEY   - For Anthropic models
GOOGLE_API_KEY      - For Google models
OPENROUTER_API_KEY  - For OpenRouter
XAI_API_KEY         - For xAI models

Output Modes

Text Generation

  • Non-streaming: Complete response after generation finishes
  • Streaming: Real-time token display as they're generated

JSON Generation

  • Non-streaming: Complete structured object after validation
  • Streaming: Incremental object updates (where supported)

Capability Requirements

Different modes require different model capabilities:

  • Text: No special requirements (all models)
  • JSON: Structured output support (varies by provider)
  • Streaming: Stream support (most models, varies by provider)

Provider Compatibility

Not all providers support all features equally:

openai      - Excellent support for all modes
anthropic   - Good support, tool-based JSON generation
groq        - Fast streaming, limited JSON support
google      - Experimental JSON/streaming support
openrouter  - Depends on underlying model
xai         - Basic support across modes