LLM provider reference

Per-provider configuration for all backends supported by kdeps. Backend and API keys go in ~/.kdeps/config.yaml. See LLM backends for routing, allowlists, and streaming.

Applies to both workflow mode and agent mode.

Every model listed here - OpenAI, Anthropic (Claude), Google (Gemini), Groq, Ollama, local llamafile / GGUF, and the rest - is probabilistic: the same prompt can return different text on each call. Determinism in kdeps comes from workflow mode wrapping the model, not from the model itself. See Deterministic by design.

Local backends

kdeps runs models locally with no API key: file (llamafile, the default), gguf (llama.cpp), or ollama (opt-in, requires the Ollama server). Setup, model alias tables, and the Docker installOllama flag live on one page - see LLM backends - local backends.

Cloud backends

Any API that implements the OpenAI chat completions API works with kdeps.

OpenAI

# ~/.kdeps/config.yaml
llm:
  backend: openai
  openai_api_key: sk-...

Model	Description
gpt-4o	Latest GPT-4 Omni
gpt-4o-mini	Smaller, faster GPT-4
gpt-4-turbo	GPT-4 Turbo
gpt-3.5-turbo	Fast, cost-effective

Azure and older-compat servers: see LLM Backends - legacy token param.

Anthropic (claude)

# ~/.kdeps/config.yaml
llm:
  backend: anthropic
  anthropic_api_key: sk-ant-...

Model	Description
claude-sonnet-4-20250514	Latest Claude Sonnet 4
claude-3-5-sonnet-20241022	Claude 3.5 Sonnet
claude-3-opus-20240229	Most capable Claude 3
claude-3-haiku-20240307	Fast, efficient

Prompt caching, extended 128K output, and custom beta headers: see LLM Backends - Anthropic.

Google (gemini / vertex AI)

# ~/.kdeps/config.yaml
llm:
  backend: google
  google_api_key: ...   # AI Studio key; omit to use Application Default Credentials for Vertex AI

Model	Description
gemini-1.5-pro	Latest Gemini Pro
gemini-1.5-flash	Fast inference
gemini-pro	Standard Gemini

Vertex AI: Set googleCloudProject and googleCloudLocation on the chat: resource to route to Vertex AI instead of AI Studio. See LLM Backends - Vertex AI.

CachedContent and safety threshold options (googleCachedContent, googleHarmThreshold): see LLM Backends - Google.

Mistral

# ~/.kdeps/config.yaml
llm:
  backend: mistral
  mistral_api_key: ...

Model	Description
mistral-large-latest	Most capable
mistral-medium-latest	Balanced
mistral-small-latest	Fast, efficient
open-mistral-7b	Open-source 7B
open-mixtral-8x7b	MoE model

Groq

Ultra-fast inference with Groq hardware.

# ~/.kdeps/config.yaml
llm:
  backend: groq
  groq_api_key: ...

Model	Description
llama-3.1-70b-versatile	Llama 3.1 70B
llama-3.1-8b-instant	Llama 3.1 8B (fastest)
mixtral-8x7b-32768	Mixtral with 32K context
gemma2-9b-it	Google Gemma 2 9B

Together AI

# ~/.kdeps/config.yaml
llm:
  backend: together
  together_api_key: ...

Model	Description
meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo	Llama 3.1 70B
meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo	Llama 3.1 8B
mistralai/Mixtral-8x7B-Instruct-v0.1	Mixtral 8x7B
Qwen/Qwen2-72B-Instruct	Qwen2 72B

Perplexity

Search-augmented LLM responses.

# ~/.kdeps/config.yaml
llm:
  backend: perplexity
  perplexity_api_key: ...

Model	Description
llama-3.1-sonar-large-128k-online	Large with web search
llama-3.1-sonar-small-128k-online	Small with web search
llama-3.1-sonar-large-128k-chat	Large chat only

Cohere

# ~/.kdeps/config.yaml
llm:
  backend: cohere
  cohere_api_key: ...

Model	Description
command-r-plus	Most capable
command-r	Fast and capable
command	Standard
command-light	Fast, efficient

DeepSeek

# ~/.kdeps/config.yaml
llm:
  backend: deepseek
  deepseek_api_key: ...

Model	Description
deepseek-v4-pro	Flagship
deepseek-v4-flash	Fast
deepseek-coder	Code generation

xAI (grok)

# ~/.kdeps/config.yaml
llm:
  backend: xai
  xai_api_key: xai-...

Model	Description
grok-2	Grok 2
grok-beta	Grok beta
grok-vision-beta	Grok with vision

OpenRouter

Access 100+ models from multiple providers through a single API.

# ~/.kdeps/config.yaml
llm:
  backend: openrouter
  openrouter_api_key: sk-or-...

Model names use the provider/model format, e.g. openai/gpt-4o, anthropic/claude-3.5-sonnet, meta-llama/llama-3.1-70b-instruct. See openrouter.ai/models for the full list.

AWS bedrock

# ~/.kdeps/config.yaml
llm:
  backend: bedrock

Authenticates via the standard AWS SDK credential chain, not a config.yaml API key - set AWS_ACCESS_KEY_ID, AWS_SECRET_ACCESS_KEY, and AWS_REGION as environment variables (or use an IAM instance role). model is the Bedrock model ID for your region, e.g. anthropic.claude-3-5-sonnet-20241022-v2:0 or meta.llama3-1-70b-instruct-v1:0.

IBM WatsonX

# ~/.kdeps/config.yaml
llm:
  backend: watsonx
  watsonx_api_key: ...

Also requires WATSONX_PROJECT_ID as an environment variable (no config.yaml field for it). model is a WatsonX model ID, e.g. ibm/granite-13b-chat-v2 or meta-llama/llama-3-70b-instruct.

M365 Copilot

Talks to Microsoft 365 Copilot's chat service through a local OpenAI-compatible server kdeps runs in front of it (m365 backend) - no API key, authentication is a signed-in Microsoft 365 account via a browser sign-in flow (interactive) or a scripted secrets.json (headless/CI).

See M365 Copilot for the full setup: sign-in flows, Linux dependencies, headless fallback, and the model list.

Self-hosted solutions

kdeps works with any self-hosted solution that implements the OpenAI API: vLLM, Text Generation Inference (TGI), LocalAI, LlamaCpp Server, LM Studio.

# ~/.kdeps/config.yaml
llm:
  backend: openai
  base_url: http://your-vllm-server:8000/v1

Custom base URL

Override the default API URL via base_url:

# Azure OpenAI
llm:
  backend: openai
  base_url: "https://my-resource.openai.azure.com/openai/deployments/my-deployment"
  openai_api_key: ...

See also

• LLM backends - Routing, allowlists, streaming, feature matrix
• LLM resource - Complete LLM resource documentation