Provider Setup

sharur supports five LLM providers. All configuration lives in config.json files or environment variables; environment variables take priority over config file values.

Model Naming

Models can be specified as provider/model shorthand or with separate flags:

# Shorthand: provider inferred from the slash-prefix
shr --model anthropic/claude-sonnet-4-6

# Explicit: provider and model as separate flags
shr --provider anthropic --model claude-sonnet-4-6

Both forms are equivalent. The shorthand is convenient for one-off overrides; the config file form is better for persistent defaults.

Environment Variables

API keys set via environment variable take priority over values in config.json. The env var names use the SHARUR_ prefix:

Ollama and llama.cpp are local servers and do not use API keys.

Ollama

Ollama runs models locally. It is the default provider.

// ~/.sharur/config.json or .sharur/config.json
{
  "defaultProvider": "ollama",
  "defaultModel": "llama3.2",
  "ollamaBaseURL": "http://localhost:11434"
}

# Pull a model and launch
ollama pull llama3.2
shr

# Use a specific model
shr --model ollama/llama3.2

# Point at a remote Ollama server
shr --model llama3.2 --provider ollama

Notes:

• Default base URL is http://localhost:11434. Override with ollamaBaseURL.
• Ollama models support tools and images (vision models).
• Use shr --list-models to see all locally available models.
• Thinking is supported on models that emit <think> tokens (e.g. qwq, deepseek-r1).

llama.cpp

llama.cpp exposes an OpenAI-compatible HTTP server.

{
  "defaultProvider": "llamacpp",
  "llamaCppBaseURL": "http://localhost:8080"
}

# Start the llama.cpp server (example)
./llama-server -m model.gguf --port 8080

# Connect with sharur
shr --provider llamacpp --model my-model

Notes:

• Default base URL is http://localhost:8080. Override with llamaCppBaseURL.
• The model name passed to shr is forwarded to the server as-is.
• Image attachments are not supported.
• The server’s own context window size is used; sharur queries /v1/models to detect it.

OpenAI

{
  "defaultProvider": "openai",
  "defaultModel": "gpt-4o",
  "openAIApiKey": "",
  "openAIBaseURL": "https://api.openai.com/v1"
}

# Via environment variable (recommended)
export SHARUR_OPENAI_API_KEY=sk-...
shr --model openai/gpt-4o

# One-off key override
shr --provider openai --model gpt-4o --api-key sk-...

OpenAI-compatible endpoints:

Any server that implements the OpenAI chat completions API can be used by pointing openAIBaseURL at it:

{
  "defaultProvider": "openai",
  "openAIBaseURL": "http://localhost:11434/v1",
  "openAIApiKey": "unused"
}

This works with vLLM, LM Studio, and others.

Notes:

• Reasoning models (o3, o4-mini) emit thinking deltas that appear in the TUI and JSON event stream.
• Supports tools and vision (images) for compatible models.

Anthropic

{
  "defaultProvider": "anthropic",
  "defaultModel": "claude-sonnet-4-6",
  "anthropicApiKey": "",
  "anthropicApiVersion": ""
}

export SHARUR_ANTHROPIC_API_KEY=sk-ant-...
shr --model anthropic/claude-sonnet-4-6

# Extended thinking (claude-3-7-sonnet and later)
shr --model anthropic/claude-3-7-sonnet-20250219 --thinking high

Notes:

• Extended thinking is supported for models that enable it (e.g. claude-3-7-sonnet). Use --thinking medium or --thinking high.
• medium thinking uses a 10,000-token budget; high uses 20,000 tokens. Temperature is automatically set to the required value.
• anthropicApiVersion overrides the anthropic-version request header; leave empty to use the library default.

Google Gemini

{
  "defaultProvider": "google",
  "defaultModel": "gemini-2.0-flash",
  "googleApiKey": ""
}

export SHARUR_GOOGLE_API_KEY=AIza...
shr --model google/gemini-2.0-flash

Notes:

• Gemini 1.5 Pro and later have a 1M+ token context window.
• Supports tools and vision (images).
• Use shr --list-models to see available Gemini models.

Listing Available Models

All five providers implement model listing. Use --list-models to query the active provider:

# List Ollama models
shr --list-models

# List models from a specific provider
shr --provider anthropic --list-models

# Filter results
shr --provider openai --list-models gpt-4

The output is a plain list of model names, suitable for piping:

shr --list-models | fzf | xargs -I{} shr --model {}

Provider Feature Matrix