Evan
4f8dd2404d
* feat(providers): expand ollama model catalog with thinking-capable models Add commonly used local models with accurate capability flags: - gemma4, gemma3: supports_thinking, supports_vision - deepseek-r1: supports_thinking (fix missing flag) - deepseek-v3: supports_tools - qwen3, qwq: supports_thinking - llama4: supports_vision - llama3.3: supports_tools - phi4: supports_tools Previously only 6 models were listed and none had supports_thinking (except deepseek-r1), causing the dashboard to hide thinking toggles for models that actually support it. * chore(providers): major cleanup — remove defunct providers and old models Delete 21 defunct/obscure providers: aion-labs, arcee-ai, deepcogito, eleutherai, essentialai, ibm-granite, inception, inflection, kwaipilot, lemonade, liquid, morph, nex-agi, nousresearch, prime-intellect, reka, relace, switchpoint, tngtech, upstage, writer Clean up 10 major providers — keep only latest generation models: - anthropic: remove claude-3.5-sonnet (superseded by 4.x) - openai: remove gpt-4o/4-turbo/3.5/o1/o3-mini (superseded by gpt-5/4.1/o3/o4-mini) - gemini: remove 1.5-*/2.0-flash (superseded by 2.5/3.x) - deepseek: remove coder/chat-v3-0324 (superseded by r1/v3) - qwen: remove turbo/2.5-coder (superseded by qwen3) - groq: remove old llama/mixtral/gemma (keep latest only) - mistral: remove medium/nemo/pixtral-large (keep large/small/codestral) - xai: remove grok-2 (superseded by grok-3/4) - meta-llama: remove 3.x/guard (keep llama-4 + 3.3) - ollama: rewrite with current models (gemma4, qwen3, qwq, llama4, etc) Total: 90 → 48 models across major providers. All thinking-capable models now have supports_thinking = true. * chore: add pre-commit hook for automatic TOML formatting - .githooks/pre-commit: runs taplo fmt on staged .toml files - Makefile: add setup target + auto-configure hooks on first make - .gitignore: add .make-setup-done and .sync_marker
50 lines
1.4 KiB
TOML
50 lines
1.4 KiB
TOML
name = "hello-world"
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version = "0.4.3-beta3-20260314"
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description = "A friendly greeting agent that can read files, search the web, and answer everyday questions."
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author = "librefang"
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module = "builtin:chat"
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[metadata.routing]
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aliases = [
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"hello world",
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"greeting",
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"say hello",
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"introduce yourself",
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"new user welcome",
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]
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weak_aliases = ["hello", "welcome", "intro", "getting started"]
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[model]
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provider = "default"
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model = "default"
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max_tokens = 4096
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temperature = 0.6
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system_prompt = """You are Hello World, a friendly and approachable agent in the LibreFang Agent OS.
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You are the first agent new users interact with. Be warm, concise, and helpful.
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Answer questions directly. If you can look something up to give a better answer, do it.
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When the user asks a factual question, use web_search to find current information rather than relying on potentially outdated knowledge. Present findings clearly without dumping raw search results.
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Keep responses brief (2-4 paragraphs max) unless the user asks for detail.
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Always reply in the same language the user uses. Never literally translate proper nouns, product names, or technical terms (e.g. "Hello World", "LibreFang", "Agent OS" stay as-is)."""
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[resources]
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max_llm_tokens_per_hour = 100000
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[capabilities]
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tools = [
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"file_read",
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"file_write",
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"file_list",
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"web_fetch",
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"web_search",
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"memory_store",
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"memory_recall",
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]
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network = ["*"]
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memory_read = ["*"]
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memory_write = ["self.*"]
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agent_spawn = false
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