Configure LLM providers, platforms, and features
Comprehensive guide to configuring every aspect of your nano bot installation
The nano bot uses configuration files to manage all settings. After installing nanobot ai, you'll need to configure LLM providers, messaging platforms, and optional features.
The nanobot stores configuration in your project directory or home directory. Typical locations include:
config.yaml or config.json in project root~/.nanobot/config.yaml for user-wide settingsThe nano bot supports YAML and JSON formats for configuration files. YAML is recommended for readability. The nanobot ai configuration is structured with clear sections for providers, platforms, tools, and memory.
Mandatory: At least one LLM provider with valid API key
Mandatory: At least one messaging platform configured
Optional: Memory system, tools, cron jobs
The nanobot cannot function without an LLM provider and platform.
The nano bot validates configuration on startup. Invalid settings, missing API keys, or permission errors will be reported clearly. Fix any errors before the nanobot ai can run.
The nano bot supports 11+ LLM providers through its Provider Registry. Configure one or more providers to give nanobot ai access to language models.
API: api.openrouter.ai
Key: OpenRouter API key
Models: Multiple providers through one key
The nanobot OpenRouter integration provides access to many models with a single API key configuration.
API: api.anthropic.com
Key: Anthropic API key
Models: Claude Opus, Sonnet, Haiku
Configure the nano bot to use Claude models from Anthropic for high-quality AI conversations.
API: api.openai.com
Key: OpenAI API key
Models: GPT-4, GPT-3.5, and others
The nanobot ai supports all OpenAI chat models through simple configuration.
API: DeepSeek endpoint
Key: DeepSeek API key
Models: DeepSeek models
Configure the nano bot to use DeepSeek for specialized reasoning capabilities.
API: Google AI API
Key: Google API key
Models: Gemini Pro and variants
The nanobot integrates with Google's Gemini models for multimodal AI.
Zhipu (ζΊθ°±), DashScope, Moonshot, Groq, AiHubMix, and vLLM for local models.
The nano bot Provider Registry makes adding any of these straightforward.
# Example nanobot LLM configuration (YAML)
llm_providers:
- name: anthropic
api_key: ${ANTHROPIC_API_KEY}
model: claude-sonnet-4
default: true
- name: openai
api_key: ${OPENAI_API_KEY}
model: gpt-4
- name: openrouter
api_key: ${OPENROUTER_API_KEY}
model: anthropic/claude-3.5-sonnet
Connect the nano bot to 8+ messaging platforms. Each platform requires specific credentials and configuration. The nanobot ai can manage all platforms simultaneously.
Credential: Bot token from @BotFather
Features: Full support, voice transcription
Setup: Create bot, get token, configure nanobot
The nano bot Telegram integration is the most feature-complete platform option.
Credential: Bot token from Discord Developer Portal
Features: Server integration, DMs, slash commands
Setup: Create application, add bot, configure permissions
Deploy the nanobot ai as a Discord bot for community management.
Credential: Business API credentials
Features: Personal and business chats
Setup: WhatsApp Business API access required
Connect the nano bot to WhatsApp for personal AI assistant workflows.
Credential: Bot token and app credentials
Features: Workspace integration, channels, DMs
Setup: Create Slack app, configure permissions
The nanobot integrates with Slack for team collaboration.
Credential: SMTP/IMAP settings
Features: Email receiving and sending
Setup: Configure email server details
Enable the nano bot to process and respond to emails.
QQ: Chinese messaging platform
DingTalk (ιι): Enterprise messaging
Feishu (ι£δΉ¦): Corporate communication
Mochat: Business messaging
The nanobot ai supports these platforms with appropriate credentials.
# Example nanobot platform configuration (YAML)
platforms:
telegram:
enabled: true
bot_token: ${TELEGRAM_BOT_TOKEN}
voice_transcription: true
discord:
enabled: true
bot_token: ${DISCORD_BOT_TOKEN}
server_id: your_server_id
slack:
enabled: false
bot_token: ${SLACK_BOT_TOKEN}
The nano bot memory system was redesigned on February 12, 2026, for improved reliability. Configure both long-term and short-term memory for the nanobot ai.
File: MEMORY.md in workspace
Format: Markdown
Purpose: Persistent knowledge
Create a MEMORY.md file where the nanobot stores important information that should persist across all sessions and conversations.
Directory: memory/
Files: YYYY-MM-DD.md
Purpose: Daily conversation logs
The nano bot automatically creates daily notes for short-term memory. Organize by date for easy navigation.
Algorithm: 70% vector + 30% BM25
Purpose: Efficient memory recall
Configurable: Adjust search weights
The nanobot ai uses hybrid search combining vector similarity and keyword matching for accurate memory retrieval.
Configure memory file locations and ensure the nano bot has read/write permissions. The nanobot memory system needs filesystem access to function properly.
# Example nanobot memory configuration (YAML)
memory:
long_term:
file: ./MEMORY.md
auto_update: true
short_term:
directory: ./memory
daily_notes: true
search:
vector_weight: 0.7
bm25_weight: 0.3
The nano bot tool system enables file operations, shell commands, and web access. Configure tool permissions and capabilities for the nanobot ai.
Capabilities: Read, write, create, delete files
Configuration: Allowed directories, permissions
Security: Restrict access to sensitive paths
Configure which directories the nanobot can access for file operations.
Capabilities: Execute shell commands
Configuration: Allowed commands, timeouts
Security: Whitelist safe commands only
Enable the nano bot to run specific shell commands with appropriate restrictions.
Capabilities: Fetch URLs, call APIs
Configuration: Allowed domains, request limits
Security: Rate limiting, domain whitelist
Configure the nanobot ai web tool for internet access and API integration.
Add custom tools to the nano bot by registering them in the tool system. The nanobot architecture makes extending tool capabilities straightforward for developers.
Set up time-based automation with the nano bot Cron system. The nanobot ai uses apscheduler for reliable job scheduling.
The nanobot Cron system is built on apscheduler, providing flexible scheduling options. Configure job schedules using cron syntax or interval-based timing.
Cron: 0 9 * * * (daily at 9am)
Interval: hours=1 (every hour)
Date: Specific date/time execution
Common nano bot automation examples:
Cron jobs can trigger any nanobot functionality: sending messages, running tools, updating memory, or executing custom workflows. The nano bot processes scheduled tasks as if they were user-initiated.
# Example nanobot cron configuration (YAML)
cron_jobs:
- name: daily_summary
schedule: "0 18 * * *" # 6pm daily
action: send_message
platform: telegram
message: "Daily summary time!"
- name: hourly_check
interval: {hours: 1}
action: run_tool
tool: health_check
Fine-tune the nano bot with advanced settings for logging, performance, security, and custom integrations.
Configure the nanobot logging verbosity:
Set appropriate log levels for development vs production environments.
Optimize the nano bot performance:
The nanobot ai is already lightweight; tuning improves efficiency further.
Harden the nanobot security:
Protect the nano bot from unauthorized access and misuse.
Extend the nanobot with custom integrations:
The nano bot architecture welcomes extensions and customization.
With this configuration guide, you have everything needed to set up the nano bot perfectly for your use case. Start with basic LLM and platform configuration, then expand to advanced features as needed.