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Parameter	Environment Variable	Default	Description
Preserve Last	`SUMMARIZER_PRESERVE_LAST`	`true`	Whether to keep all messages in the last section intact
Use QA Pairs	`SUMMARIZER_USE_QA`	`true`	Whether to use QA pair summarization strategy
Summarize Human in QA	`SUMMARIZER_SUM_MSG_HUMAN_IN_QA`	`false`	Whether to summarize human messages in QA pairs
Last Section Size	`SUMMARIZER_LAST_SEC_BYTES`	`51200`	Maximum byte size for last section (50KB)
Max Body Pair Size	`SUMMARIZER_MAX_BP_BYTES`	`16384`	Maximum byte size for a single body pair (16KB)
Max QA Sections	`SUMMARIZER_MAX_QA_SECTIONS`	`10`	Maximum QA pair sections to preserve
Max QA Size	`SUMMARIZER_MAX_QA_BYTES`	`65536`	Maximum byte size for QA pair sections (64KB)
Keep QA Sections	`SUMMARIZER_KEEP_QA_SECTIONS`	`1`	Number of recent QA sections to keep without summarization

Parameter	Environment Variable	Default	Description
Preserve Last	`ASSISTANT_SUMMARIZER_PRESERVE_LAST`	`true`	Whether to preserve all messages in the assistant's last section
Last Section Size	`ASSISTANT_SUMMARIZER_LAST_SEC_BYTES`	`76800`	Maximum byte size for assistant's last section (75KB)
Max Body Pair Size	`ASSISTANT_SUMMARIZER_MAX_BP_BYTES`	`16384`	Maximum byte size for a single body pair in assistant context (16KB)
Max QA Sections	`ASSISTANT_SUMMARIZER_MAX_QA_SECTIONS`	`7`	Maximum QA sections to preserve in assistant context
Max QA Size	`ASSISTANT_SUMMARIZER_MAX_QA_BYTES`	`76800`	Maximum byte size for assistant's QA sections (75KB)
Keep QA Sections	`ASSISTANT_SUMMARIZER_KEEP_QA_SECTIONS`	`3`	Number of recent QA sections to preserve without summarization

Area	Effect when `TENANT_ID=acme`
PostgreSQL	The instance creates and works inside schema `acme` instead of `public`; extensions stay shared in `DATABASE_EXTENSIONS_SCHEMA` (default `public`, `extensions` on Supabase)
Worker containers	`acme-pentagi-terminal-<flow>` instead of `pentagi-terminal-<flow>`; volumes and hostnames follow, and both carry a `pentagi.tenant` label
Knowledge graph	Graphiti/Neo4j group ids become `acme-flow-<id>`
Auth	Cookie and API token keys are derived from `COOKIE_SIGNING_SALT` plus the tenant, and the session cookie is renamed
Telemetry	Langfuse traces carry the tenant as their `environment` and a `tenant:acme` tag; OTel resources gain `tenant_id`

Variable	Default	Description
`LLM_SERVER_URL`		Base URL for the custom LLM API endpoint
`LLM_SERVER_KEY`		API key for the custom LLM provider
`LLM_SERVER_MODEL`		Default model to use (can be overridden in provider config)
`LLM_SERVER_CONFIG_PATH`		Path to the YAML configuration file for agent-specific models
`LLM_SERVER_PROVIDER`		Provider name prefix for model names (e.g., `openrouter`, `deepseek` for LiteLLM proxy)
`LLM_SERVER_PRESERVE_REASONING`	`false`	Preserve reasoning content in multi-turn conversations (required by some providers)
`LLM_SERVER_API_TYPE`		`azure` or `azure_ad` for an Azure OpenAI deployment, empty for a plain endpoint; see Using Azure OpenAI
`LLM_SERVER_API_VERSION`	`2024-10-21`	The `api-version` Azure requires; ignored by a plain endpoint

Variable	Default	Description
`OLLAMA_SERVER_URL`		URL of your Ollama server or Ollama Cloud
`OLLAMA_SERVER_API_KEY`		API key for Ollama Cloud authentication
`OLLAMA_SERVER_MODEL`		Default model for inference
`OLLAMA_SERVER_CONFIG_PATH`		Path to custom agent configuration file
`OLLAMA_SERVER_PULL_MODELS_TIMEOUT`	`600`	Timeout for model downloads (seconds)
`OLLAMA_SERVER_PULL_MODELS_ENABLED`	`false`	Auto-download models on startup
`OLLAMA_SERVER_LOAD_MODELS_ENABLED`	`false`	Query server for available models

Variable	Default	Description
`OPEN_AI_KEY`		API key for OpenAI services
`OPEN_AI_SERVER_URL`	`https://api.openai.com/v1`	OpenAI API endpoint

Model ID	Thinking	Reasoning Effort	Price (Input/Output/Cache)	Use Case
`gpt-5.6-sol`	✅	low/medium/high/xhigh	$5.00/$30.00/$0.50	Frontier model for complex professional work, most demanding autonomous pentesting, sophisticated exploit chain development, deep multi-stage attack simulation
`gpt-5.6-terra`*	✅	low/medium/high/xhigh	$2.50/$15.00/$0.25	Balances intelligence and cost; multi-phase security assessments, coordinated multi-tool pentesting (generator/refiner/adviser/coder default)
`gpt-5.6-luna`	✅	low/medium/high/xhigh	$1.00/$6.00/$0.10	Optimized for cost-sensitive, high-volume workloads; rapid reconnaissance, bulk vulnerability scanning, real-time monitoring

Model ID	Thinking	Reasoning Effort	Price (Input/Output/Cache)	Use Case
`gpt-5.5`	✅	none/low/medium/high/xhigh	$5.00/$30.00/$0.50	New class of intelligence for coding and professional work; complex security research, advanced autonomous pentesting
`gpt-5.5-pro`	✅	medium/high/xhigh	$30.00/$180.00/$0.00	Uses more compute for smarter, more precise responses; no cached-input discount; mission-critical security research, zero-day discovery

Model ID	Thinking	Reasoning Effort	Price (Input/Output/Cache)	Use Case
`gpt-5.4`	✅	low/medium/high/xhigh	$2.50/$15.00/$0.25	Best intelligence at scale for agentic, coding, and professional workflows; maximum cognitive depth for pentesting
`gpt-5.4-mini`*	✅	low/medium/high/xhigh	$0.75/$4.50/$0.075	Strongest mini model for coding, computer use, subagents (primary_agent/assistant/reflector/installer/pentester default)
`gpt-5.4-nano`*	✅	low/medium/high/xhigh	$0.20/$1.25/$0.02	Cheapest GPT-5.4-class model for simple, high-volume tasks (simple/simple_json/searcher/enricher default)

Model ID	Thinking	Reasoning Effort	Price (Input/Output/Cache)	Use Case
`gpt-5.2`	✅	low/medium/high/xhigh	$1.75/$14.00/$0.175	Superseded by 5.4/5.6; autonomous security research, complex exploit chain development
`gpt-5.2-pro`	✅	medium/high/xhigh	$21.00/$168.00/$0.00	Superior agentic coding and long-context performance, mission-critical security research, zero-day discovery

Model ID	Thinking	Price (Input/Output/Cache)	Use Case
`gpt-5`	✅	$1.25/$10.00/$0.125	Autonomous security research, exploit chain development, coordinating multi-tool pentesting workflows
`gpt-5.1`	✅	$1.25/$10.00/$0.125	Bridges GPT-5 and GPT-5.2 with faster responses; balanced penetration testing with strong tool coordination
`gpt-5-pro`	✅ (high)	$15.00/$120.00/$0.00	Reduced hallucinations, exceptional accuracy, critical security operations
`gpt-5-mini`	✅	$0.25/$2.00/$0.025	Automated vulnerability analysis, exploit generation with strong function calling
`gpt-5-nano`	✅	$0.05/$0.40/$0.005	High-throughput security scanning, reconnaissance, real-time monitoring

Model ID	Thinking	Price (Input/Output/Cache)	Use Case
`gpt-4.1`	❌	$2.00/$8.00/$0.50	Superior function calling, complex threat analysis, sophisticated exploit development
`gpt-4.1-mini`	❌	$0.40/$1.60/$0.10	Routine security assessments, automated code analysis (no longer used in default configuration)

Model ID	Thinking	Price (Input/Output/Cache)	Use Case
`o3`	✅	$2.00/$8.00/$0.50	Succeeded by GPT-5; multi-stage attack chains, deep vulnerability analysis
`o3-pro`	✅	$20.00/$80.00/$0.00	More compute for better responses; zero-day research, critical security investigations

Model ID	Thinking	Price (Input/Output/Cache)	Notes
`gpt-5.2-codex`	✅	$1.75/$14.00/$0.175	Superseded code-specialized model; use `gpt-5.6-terra`/`gpt-5.4-mini` instead
`gpt-5.1-codex-max`	✅	$1.25/$10.00/$0.125	Superseded; enhanced reasoning for coding workflows
`gpt-5.1-codex`	✅	$1.25/$10.00/$0.125	Superseded standard code-optimized model
`gpt-5-codex`	✅	$1.25/$10.00/$0.125	Superseded foundational code-specialized model
`gpt-5.1-codex-mini`	✅	$0.25/$2.00/$0.025	Superseded compact code model
`codex-mini-latest`	✅	$1.50/$6.00/$0.375	Superseded compact code model
`gpt-4o`	❌	$2.50/$10.00/$1.25	Superseded by GPT-5.x/5.6 series multimodal flagship
`gpt-4.1-nano`	❌	$0.10/$0.40/$0.025	Superseded ultra-fast lightweight model
`o3-mini`	✅	$1.10/$4.40/$0.55	Superseded compact reasoning model
`o4-mini`	✅	$1.10/$4.40/$0.275	Succeeded by `gpt-5-mini`
`o1`	✅	$15.00/$60.00/$7.50	Superseded premier reasoning model
`o1-pro`	✅	$150.00/$600.00/$0.00	Superseded, highest cost point of the o-series

Variable	Default	Description
`ANTHROPIC_API_KEY`		API key for Anthropic services
`ANTHROPIC_SERVER_URL`	`https://api.anthropic.com/v1`	Anthropic API endpoint

Model ID	Thinking	Release Date	Price (Input/Output/Cache R/W)	Use Case
`claude-sonnet-5`*	✅	Jul 2026	$3.00/$15.00/$0.30/$3.75	Best combination of speed and intelligence for coding, agents, and professional work at scale. Adaptive thinking only (manual budget thinking rejected); sampling parameters not supported. Default model for primary agent, assistant, coder, adviser, installer, pentester
`claude-fable-5`	✅	Jun 2026	$10.00/$50.00/$1.00/$12.50	Anthropic's most capable widely released model for long-running agents and the most demanding reasoning workloads. Adaptive thinking always on (budget thinking and an explicit disable are rejected); sampling parameters not supported

Model ID	Thinking	Release Date	Price (Input/Output/Cache R/W)	Use Case
`claude-opus-4-8`*	✅	May 2026	$5.00/$25.00/$0.50/$6.25	Flagship for coding, agents, and deep reasoning in enterprise security workflows. Adaptive thinking only — budget thinking and sampling params (temperature/top_p/top_k) are rejected. Default model for generator and refiner; most demanding exploit development and multi-stage attack simulation
`claude-opus-4-7`	✅	Apr 2026	$5.00/$25.00/$0.50/$6.25	Advanced software engineering and long-running agentic security analysis. Adaptive thinking only (manual budget thinking rejected)
`claude-sonnet-4-6`	✅	Feb 2026	$3.00/$15.00/$0.30/$3.75	Best speed/intelligence balance with adaptive thinking. Multi-phase security assessments, intelligent vulnerability analysis, real-time threat hunting
`claude-opus-4-6`	✅	Feb 2026	$5.00/$25.00/$0.50/$6.25	Most intelligent model for autonomous agents and coding. Extended + adaptive thinking for complex exploit development, multi-stage attack simulation
`claude-haiku-4-5`*	❌	Oct 2025	$1.00/$5.00/$0.10/$1.25	Fast and efficient model with exceptional function calling and low latency, no thinking support. Default model for simple, simple_json, reflector, searcher, enricher; high-frequency scanning, real-time monitoring, bulk automated testing

Model ID	Thinking	Release Date	Price (Input/Output/Cache R/W)	Use Case
`claude-sonnet-4-5`	✅	Sep 2025	$3.00/$15.00/$0.30/$3.75	State-of-the-art reasoning (superseded by sonnet-4-6/sonnet-5). Sophisticated penetration testing, advanced threat analysis
`claude-opus-4-5`	✅	Nov 2025	$5.00/$25.00/$0.50/$6.25	Ultimate reasoning (superseded by opus-4-6/4-7/4-8). Critical security research, zero-day discovery, red team operations

Model ID	Thinking	Context	Price (Input/Output/Cache)	Saved-chain result
`gemini-3.8-flash`	✅	1M	$0.75/$3.75/$0.075	API responds; 10/10 saved generator calls were content-filtered
`gemini-3.7-flash`	✅	1M	$0.75/$3.75/$0.075	API responds; 10/10 saved generator calls were content-filtered; former default
`gemini-3.6-flash`	✅	1M	$0.75/$3.75/$0.075	API responds; 10/10 saved generator calls returned text without a tool
`gemini-3.5-flash`	✅	1M	$1.5/$9/$0.15	API responds; 10/10 saved generator calls returned text without a tool
`gemini-3.5-flash-lite`*	✅	1M	$0.3/$2.5/$0.03	Complex-role default; eight direct plans and two after a safe `memorist` continuation
`gemini-3.1-pro-preview`	✅	1M	$2/$12/$0.2	API responds; 10/10 saved generator calls returned text without a tool
`gemini-3.1-pro-preview-customtools`	✅	1M	$2/$12/$0.2	API responds; 10/10 saved generator calls returned text without a tool
`gemini-3.1-flash-lite`*	✅	1M	$0.25/$1.5/$0.025	Simple-role default; direct plan on all ten saved generator chains
`gemini-3-flash-preview`	✅	1M	$0.5/$3/$0.05	API responds; three direct plans and five generator timeouts
`gemini-2.5-pro`	✅	1M	$1.25/$10/$0.125	API responds; ten direct plans, but four role-smoke provider errors
`gemini-2.5-flash`	✅	1M	$0.3/$2.5/$0.03	Ten direct plans; access is limited for new API projects
`gemini-2.5-flash-lite`	✅	1M	$0.1/$0.4/$0.01	API responds; five of ten generator answers were empty
`gemma-4-31b-it`	✅	256K	Free/Free/Free	API responds; seven direct plans and three generator timeouts
`gemma-4-26b-a4b-it`	✅	256K	Free/Free/Free	Direct plan on all ten saved generator chains

Variable	Default	Description
`GEMINI_API_KEY`		API key for Google AI services
`GEMINI_SERVER_URL`	`https://generativelanguage.googleapis.com`	Google AI API endpoint

Variable	Default	Description
`BEDROCK_REGION`	`us-east-1`	AWS region for Bedrock service
`BEDROCK_DEFAULT_AUTH`	`false`	Use AWS SDK default credential chain (environment, EC2 role, ~/.aws/credentials) - highest priority
`BEDROCK_BEARER_TOKEN`		Bearer token authentication - priority over static credentials
`BEDROCK_ACCESS_KEY_ID`		AWS access key ID for static credentials
`BEDROCK_SECRET_ACCESS_KEY`		AWS secret access key for static credentials
`BEDROCK_SESSION_TOKEN`		AWS session token for temporary credentials (optional, used with static credentials)
`BEDROCK_SERVER_URL`		Custom Bedrock endpoint (VPC endpoints, local testing)
`BEDROCK_CONFIG_PATH`		Path to a custom YAML provider config file (overrides the built-in default config for model/pricing definitions)

Model ID	Provider	Thinking	Multimodal	Price (Input/Output)	Use Case
`us.amazon.nova-2-lite-v1:0`	Amazon Nova	❌	✅	$0.33/$2.75	Adaptive reasoning, efficient thinking
`us.amazon.nova-premier-v1:0`	Amazon Nova	❌	✅	$2.50/$12.50	Complex reasoning, advanced analysis
`us.amazon.nova-pro-v1:0`	Amazon Nova	❌	✅	$0.80/$3.20	Balanced accuracy, speed, cost
`us.amazon.nova-lite-v1:0`	Amazon Nova	❌	✅	$0.06/$0.24	Fast processing, high-volume operations
`us.amazon.nova-micro-v1:0`	Amazon Nova	❌	❌	$0.035/$0.14	Ultra-low latency, real-time monitoring
`us.anthropic.claude-opus-4-8`	Anthropic	✅	✅	$5.00/$25.00	Flagship coding/agents/deep reasoning; adaptive thinking only (sampling params rejected)
`us.anthropic.claude-opus-4-7`	Anthropic	✅	✅	$5.00/$25.00	Advanced engineering, long-running agents; adaptive thinking only
`us.anthropic.claude-opus-4-6-v1`*	Anthropic	✅	✅	$5.00/$25.00	World-class coding, enterprise agents
`us.anthropic.claude-sonnet-4-6`	Anthropic	✅	✅	$3.00/$15.00	Frontier intelligence, enterprise scale
`us.anthropic.claude-opus-4-5-20251101-v1:0`	Anthropic	✅	✅	$5.00/$25.00	Multi-day software development
`us.anthropic.claude-haiku-4-5-20251001-v1:0`*	Anthropic	✅	✅	$1.00/$5.00	Near-frontier performance, high speed
`us.anthropic.claude-sonnet-4-5-20250929-v1:0`*	Anthropic	✅	✅	$3.00/$15.00	Real-world agents, coding excellence
`us.anthropic.claude-sonnet-4-20250514-v1:0`	Anthropic	✅	✅	$3.00/$15.00	Balanced performance, production-ready
`us.anthropic.claude-3-5-haiku-20241022-v1:0`	Anthropic	❌	❌	$0.80/$4.00	Fastest model, cost-effective scanning
`cohere.command-r-plus-v1:0`	Cohere	❌	❌	$3.00/$15.00	Large-scale operations, superior RAG
`deepseek.v3.2`	DeepSeek	❌	❌	$0.58/$1.68	Long-context reasoning, efficiency
`openai.gpt-oss-120b-1:0`*	OpenAI (OSS)	✅	❌	$0.15/$0.60	Strong reasoning, scientific analysis
`openai.gpt-oss-20b-1:0`	OpenAI (OSS)	✅	❌	$0.07/$0.30	Efficient coding, software development
`qwen.qwen3-next-80b-a3b`	Qwen	❌	❌	$0.15/$1.20	Ultra-long context, flagship reasoning
`qwen.qwen3-32b-v1:0`	Qwen	❌	❌	$0.15/$0.60	Balanced reasoning, research use cases
`qwen.qwen3-coder-30b-a3b-v1:0`	Qwen	❌	❌	$0.15/$0.60	Vibe coding, natural-language first
`qwen.qwen3-coder-next`	Qwen	❌	❌	$0.45/$1.80	Tool use, function calling optimized
`mistral.mistral-large-3-675b-instruct`	Mistral	❌	✅	$4.00/$12.00	Advanced multimodal, long-context
`moonshotai.kimi-k2.5`	Moonshot	❌	✅	$0.60/$3.00	Vision, language, code in one model

Model Family	Reason for Incompatibility
GLM (Z.AI)	Tool calling format incompatible with Converse API (expects string instead of JSON)
AI21 Jamba	Severe rate limits (1-2 req/min) prevent reliable testing and production use
Meta Llama 3.3/3.1	Unstable tool call result processing, causes unexpected failures in multi-turn workflows
Mistral Magistral	Tool calling not supported by the model
Moonshot K2-Thinking	Unstable streaming behavior with tool calls, unreliable in production
Qwen3-VL	Unstable streaming with tool calling, multimodal + tools combination fails intermittently

Variable	Default Value	Description
`DEEPSEEK_API_KEY`		DeepSeek API key for authentication
`DEEPSEEK_SERVER_URL`	`https://api.deepseek.com`	DeepSeek API endpoint URL
`DEEPSEEK_PROVIDER`		Provider prefix for LiteLLM integration (optional)

Model ID	Thinking	Max Output	Context	Price (Input/Output/Cache)	Use Case
`deepseek-v4-flash`*	✅ hybrid	384K	1M	$0.14/$0.28/$0.0028	Utility agents, general dialogue, fast tool calling
`deepseek-v4-pro`*	✅ hybrid	384K	1M	$1.74/$3.48/$0.0145	Advanced reasoning, complex logic, security analysis

Agent Role	Default Model	Thinking	Reasoning Effort	Max Output	Temperature	Top P
Generator / Refiner	`deepseek-v4-pro`	Enabled	High	32768	(auto)	(auto)
Coder	`deepseek-v4-pro`	Enabled	High	20480	(auto)	(auto)
Primary Agent / Assistant / Pentester	`deepseek-v4-pro`	Enabled	High	16384	(auto)	(auto)
Adviser (mentor/planner)	`deepseek-v4-pro`	Enabled	High	8192	(auto)	(auto)
Installer	`deepseek-v4-flash`	Enabled	High	12288	(auto)	(auto)
Reflector / Searcher / Enricher	`deepseek-v4-flash`	Disabled	—	4096	0.5	0.9
Simple / Simple JSON	`deepseek-v4-flash`	Disabled	—	2048	0.3	0.9

Variable	Default Value	Description
`GLM_API_KEY`		GLM API key for authentication
`GLM_SERVER_URL`	`https://api.z.ai/api/paas/v4`	GLM API endpoint URL (international)
`GLM_PROVIDER`		Provider prefix for LiteLLM integration (optional)

Model ID	Thinking	Context	Max Output	Price (Input/Output/Cache)	Use Case
`glm-5.3`*	✅ Always	1M	128K	$1.40/$4.40/$0.26	Current flagship for complex software engineering, agent tasks, and vulnerability research
`glm-5.3-flash`*	✅ Always	1M	128K	$0.15/$0.50/$0.03	Cost-efficient native multimodal model for utility and latency-sensitive agents
`glm-5.3-flashx`	✅ Always	1M	128K	$0.37/$1.25/$0.075	Accelerated GLM-5.3-Flash endpoint delivering up to 200 output tokens per second
`glm-5.2`	✅ Hybrid	1M	128K	$1.40/$4.40/$0.26	Previous flagship for long-horizon engineering tasks
`glm-5.1`	✅ Hybrid	200K	128K	$1.40/$4.40/$0.26	Long-horizon tasks: 8h sustained autonomous execution, Claude Opus 4.6-aligned coding
`glm-5`	✅ Hybrid	200K	128K	$1.00/$3.20/$0.20	Foundation for Agentic Engineering, MoE 744B/40B active, Claude Opus 4.5-level coding

Model ID	Thinking	Context	Max Output	Price (Input/Output/Cache)	Use Case
`glm-4.7`	✅ Hybrid	200K	128K	$0.60/$2.20/$0.11	Enhanced programming, stable multi-step reasoning
`glm-4.7-flashx`	✅ Hybrid	200K	128K	$0.07/$0.40/$0.01	Ultra-cheap with priority GPU, but lower RPM limits (avoid for high-frequency use)
`glm-4.7-flash`	✅ Hybrid	200K	128K	Free/Free/Free	Free ~30B SOTA model, 1 concurrent request

PentAGI

Table of Contents

Overview

Features

Current Capability Boundaries

Architecture

System Context

Global Summarizer Configuration Options

Assistant Summarizer Configuration Options

Summarizer Environment Configuration

Execution Monitoring (Beta)

Intelligent Task Planning (Beta)

Tool Call Limits (Always Active)

Reflector Integration (Always Active)

Recommendations for Open Source Models

Quick Start

System Requirements

Using Installer (Recommended)

Current Web Settings Coverage

Still Server-Managed

Giving Agents Docker Without Giving Away the Host

Running Several Instances (TENANT_ID)

Manual Installation

Main Security Settings

Scraper Access

Access Credentials

Web UI Accounts

Accessing PentAGI from External Networks

Configuration Steps

Running PentAGI with Podman

Podman Rootless Configuration

Podman Rootful Mode

Docker Compatibility

Assistant Configuration

How to Use PentAGI After Login

1. Create your first flow

2. Use templates for repeatable workflows

3. Monitor execution and review output

4. Use the Assistant view to steer an active flow

5. Manage flow-scoped files

API Access

Generating API Tokens

Using API Tokens

API Exploration and Testing

GraphQL Playground

Swagger UI

Generating API Clients

GraphQL Clients

REST API Clients

API Usage Examples

Security Best Practices

Token Management

Custom LLM Provider Configuration

Using Azure OpenAI

Troubleshooting: tool-call (function-call) parser errors

Ollama Provider Configuration

Configuration Variables

Ollama Cloud Configuration

Local Ollama Configuration

Creating Custom Ollama Models with Extended Context

Example: Qwen3 32B FP16 with Extended Context

Example: QwQ 32B FP16 with Extended Context

OpenAI Provider Configuration

Configuration Variables

Configuration Examples

Supported Models

Anthropic Provider Configuration

Configuration Variables

Configuration Examples

Supported Models

Google AI (Gemini) Provider Configuration

Configuration Variables

Configuration Examples

Supported Models

AWS Bedrock Provider Configuration

Configuration Variables

Configuration Examples

Custom Provider Config and Models (advanced)

Supported Models

Tested but Incompatible Models

Running Several Instances (`TENANT_ID`)

Model ID	Thinking	Context	Max Output	Price (Input/Output/Cache)	Use Case
`glm-4.5`	✅ Auto	128K	96K	$0.60/$2.20/$0.11	Unified, MoE 355B/32B active
`glm-4.5-x`	✅ Auto	128K	96K	$2.20/$8.90/$0.45	Ultra-fast premium, lowest latency
`glm-4.5-air`	✅ Auto	128K	96K	$0.20/$1.10/$0.03	Cost-effective MoE 106B/12B
`glm-4.5-airx`	✅ Auto	128K	96K	$1.10/$4.50/$0.22	Accelerated Air with priority GPU
`glm-4.5-flash`	✅ Auto	128K	96K	Free/Free/Free	Free with reasoning/coding/agents support

Agent Role	Default Model	Thinking	Temperature	Top P	Max Output
Generator / Refiner	`glm-5.3`	Max	1.0	0.95	32768
Coder	`glm-5.3`	Max	1.0	0.95	20480
Adviser / Pentester	`glm-5.3`	Max	1.0	0.95	16384
Primary Agent	`glm-5.3`	High	1.0	0.95	16384
Assistant / Installer	`glm-5.3-flash`	High	1.0	0.95	16384
Simple / Reflector	`glm-5.3-flash`	Low	1.0	0.95	8192
Searcher / Enricher / Simple JSON	`glm-5.3-flash`	Low	1.0	0.95	4096

Variable	Default Value	Description
`KIMI_API_KEY`		Kimi API key for authentication
`KIMI_SERVER_URL`	`https://api.moonshot.ai/v1`	Kimi API endpoint URL (international)
`KIMI_PROVIDER`		Provider prefix for LiteLLM integration (optional)

Model ID	Thinking	Multimodal	Context	Price (Input Miss / Output / Cache Hit)	Use Case
`kimi-k2.7-code`*	✅ always	✅	256K	$0.95 / $4.00 / $0.19	Coding-focused model used by generator, refiner, coder, and pentester
`kimi-k2.7-code-highspeed`*	✅ always	✅	256K	$1.90 / $8.00 / $0.38	Same model as `kimi-k2.7-code` with higher output throughput (~180-260 tokens/s) (primary_agent/assistant default)

Agent Role	Default Model	Thinking	Temperature	Top P	Max Output
Adviser (mentor/planner)	`kimi-k3`	Always (effort=max)	1.0	0.95	8192
Generator / Refiner	`kimi-k2.7-code`	Always (keep=all)	1.0	0.95	32768
Coder	`kimi-k2.7-code`	Enabled (keep=all)	1.0	0.95	20480
Pentester	`kimi-k2.7-code`	Enabled (keep=all)	1.0	0.95	16384
Primary Agent / Assistant	`kimi-k2.7-code-highspeed`	Enabled (keep=all)	1.0	0.95	16384
Installer	`kimi-k2.6`	Enabled	1.0	0.95	16384
Reflector / Searcher / Enricher	`kimi-k2.6`	Disabled	0.6	0.95	4096
Simple	`kimi-k2.6`	Disabled	0.6	0.95	8192
Simple JSON	`kimi-k2.6`	Disabled	0.6	0.95	4096

Variable	Default Value	Description
`QWEN_API_KEY`		Qwen Cloud, DashScope, or gateway API key
`QWEN_SERVER_URL`	`https://dashscope-us.aliyuncs.com/compatible-mode/v1`	Direct API or OpenAI-compatible gateway base URL
`QWEN_PROVIDER`		Gateway route prefix: `qwen_cloud` or `dashscope`

Availability	Models
Qwen Cloud and DashScope	`qwen3.8-max`, `qwen3.8-flash`, `qwen3.7-plus`, `qwen3.7-max`, `qwen3.6-flash`, `deepseek-v4.1-flash`, `deepseek-v4-pro`
Qwen Cloud only	`deepseek-v4-pro-0813`
DashScope only	All other entries in the bundled catalogue

Model ID	Thinking	Intl	Global/US	China	Price (Input/Output/Cache)	Use Case
`qwen3.8-max`	✅	—	—	—	$2.00/$6.00/$0.25	Newest flagship succeeding Qwen3.7-Max
`qwen3.8-omni-flash`	✅	✅	✅	✅	$0.15/$0.47/—	Current multimodal Omni tier
`qwen3.7-max`	✅	✅	✅	✅	$2.50/$7.50/$0.50	Next-gen flagship for agent-centric era
`qwen3.6-max-preview`	✅	✅	✅	✅	$1.30/$7.80/$0.13	Preview Max with enhanced vibe coding & front-end skills
`qwen3-max`	✅	✅	✅	✅	$1.20/$6.00/$0.24	Previous-gen flagship with agent programming upgrades
`qwen-max`	❌	✅	✅	✅	$1.60/$6.40/—	Legacy 32K text flagship
`qwen-plus`	✅	✅	✅	✅	$0.40/$4.00/$0.08	Qwen3-backbone Plus with switchable thinking modes

Model ID	Thinking	Intl	Global/US	China	Price (Input/Output/Cache)	Use Case
`qwen3.7-plus`	✅	—	—	—	$0.40/$1.60/$0.08	Cost-efficient tier of the Qwen3.7 generation
`qwen3.6-plus`	✅	✅	✅	✅	$0.50/$3.00/$0.05	Native VL Plus with agentic coding
`qwen3.5-plus`	✅	✅	✅	✅	$0.40/$2.40/$0.04	Previous-gen native VL with strong multimodal capabilities

Model ID	Thinking	Intl	Global/US	China	Price (Input/Output/Cache)	Use Case
`qwen3.8-flash`	✅	—	—	—	$0.15/$0.47/$0.016	Cost-efficient tier of the Qwen3.8 generation
`qwen3.7-flash`	✅	—	—	—	$0.03/$0.13/$0.02	Low-latency tier of the Qwen3.7 generation
`qwen3.6-flash`*	✅	✅	✅	✅	$0.25/$1.50/$0.05	Shared utility model
`qwen3.5-flash`	✅	✅	✅	✅	$0.10/$0.40/$0.01	Ultra-fast lightweight
`qwen-flash`	✅	✅	✅	✅	$0.05/$0.40/$0.01	Qwen3-series Flash with 1M context, tiered pricing