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# Portfolio Bot Configuration
# Documentation: https://github.com/VictorVargas/rony-llm-agent/pkg/llm
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server :
host : "0.0.0.0"
port : 7331
read_timeout_ms : 30000
cors_origins :
- "http://localhost:4321" # Astro dev server
feat: bootstrap rony-chat-bot Go module
Initial implementation of the bot:
- cmd/chat-bot: CLI entrypoint (serve, reindex, ask, version)
- internal/agent: LLM provider client + agent runner with RAG injection
- internal/config: YAML config loader (providers, RAG, persona, server)
- internal/i18n: response-language detection (EN/ES)
- internal/persona: persona system prompt assembly from YAML
- internal/portfolio: heading-based chunker + SQLite FTS5 indexer
- internal/server: chi router with /api/chat (SSE), /api/health, /api/info,
/api/reindex, middleware (RequestID, Logging, CORS, RateLimit)
- internal/streaming: SSE protocol helpers (start, chunk, sources, done, error)
- web/: drop-in vanilla-JS chat widget (no build, no deps) + demo + README
- bench/: reproducible driver benchmark (modernc vs mattn SQLite)
- configs/portfolio-bot.yaml: llama.cpp default provider, SQLite RAG, canine persona
- docs/architecture.md / .es.md: aligned with SQLite FTS5 + llama.cpp decisions
- data/projects/README*.md: project data documentation
- README.md / .es.md: updated for current implementation
All tests pass (go test ./...). Bot is functional end-to-end with the
configured LLM provider.
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- "http://localhost:8000" # Local widget demo (python http.server)
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- "https://victorvargas.dev" # Production (when it exists)
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rate_limit :
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requests_per_minute : 30 # Per IP
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burst : 5
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# LLM providers (at least one configured)
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providers :
feat: bootstrap rony-chat-bot Go module
Initial implementation of the bot:
- cmd/chat-bot: CLI entrypoint (serve, reindex, ask, version)
- internal/agent: LLM provider client + agent runner with RAG injection
- internal/config: YAML config loader (providers, RAG, persona, server)
- internal/i18n: response-language detection (EN/ES)
- internal/persona: persona system prompt assembly from YAML
- internal/portfolio: heading-based chunker + SQLite FTS5 indexer
- internal/server: chi router with /api/chat (SSE), /api/health, /api/info,
/api/reindex, middleware (RequestID, Logging, CORS, RateLimit)
- internal/streaming: SSE protocol helpers (start, chunk, sources, done, error)
- web/: drop-in vanilla-JS chat widget (no build, no deps) + demo + README
- bench/: reproducible driver benchmark (modernc vs mattn SQLite)
- configs/portfolio-bot.yaml: llama.cpp default provider, SQLite RAG, canine persona
- docs/architecture.md / .es.md: aligned with SQLite FTS5 + llama.cpp decisions
- data/projects/README*.md: project data documentation
- README.md / .es.md: updated for current implementation
All tests pass (go test ./...). Bot is functional end-to-end with the
configured LLM provider.
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# === llama.cpp server (OpenAI-compatible) — DEFAULT ===
# Run: llama-server -m /path/to/qwen2.5-3b-instruct-q4_k_m.gguf --port 9100 --mlock
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- name : llamacpp-local
type : llamacpp
feat: bootstrap rony-chat-bot Go module
Initial implementation of the bot:
- cmd/chat-bot: CLI entrypoint (serve, reindex, ask, version)
- internal/agent: LLM provider client + agent runner with RAG injection
- internal/config: YAML config loader (providers, RAG, persona, server)
- internal/i18n: response-language detection (EN/ES)
- internal/persona: persona system prompt assembly from YAML
- internal/portfolio: heading-based chunker + SQLite FTS5 indexer
- internal/server: chi router with /api/chat (SSE), /api/health, /api/info,
/api/reindex, middleware (RequestID, Logging, CORS, RateLimit)
- internal/streaming: SSE protocol helpers (start, chunk, sources, done, error)
- web/: drop-in vanilla-JS chat widget (no build, no deps) + demo + README
- bench/: reproducible driver benchmark (modernc vs mattn SQLite)
- configs/portfolio-bot.yaml: llama.cpp default provider, SQLite RAG, canine persona
- docs/architecture.md / .es.md: aligned with SQLite FTS5 + llama.cpp decisions
- data/projects/README*.md: project data documentation
- README.md / .es.md: updated for current implementation
All tests pass (go test ./...). Bot is functional end-to-end with the
configured LLM provider.
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model : qwen2.5-3b-instruct
endpoint : http://localhost:9100/v1
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context_size : 4096
feat: bootstrap rony-chat-bot Go module
Initial implementation of the bot:
- cmd/chat-bot: CLI entrypoint (serve, reindex, ask, version)
- internal/agent: LLM provider client + agent runner with RAG injection
- internal/config: YAML config loader (providers, RAG, persona, server)
- internal/i18n: response-language detection (EN/ES)
- internal/persona: persona system prompt assembly from YAML
- internal/portfolio: heading-based chunker + SQLite FTS5 indexer
- internal/server: chi router with /api/chat (SSE), /api/health, /api/info,
/api/reindex, middleware (RequestID, Logging, CORS, RateLimit)
- internal/streaming: SSE protocol helpers (start, chunk, sources, done, error)
- web/: drop-in vanilla-JS chat widget (no build, no deps) + demo + README
- bench/: reproducible driver benchmark (modernc vs mattn SQLite)
- configs/portfolio-bot.yaml: llama.cpp default provider, SQLite RAG, canine persona
- docs/architecture.md / .es.md: aligned with SQLite FTS5 + llama.cpp decisions
- data/projects/README*.md: project data documentation
- README.md / .es.md: updated for current implementation
All tests pass (go test ./...). Bot is functional end-to-end with the
configured LLM provider.
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max_tokens : 2048
default : true
# === Ollama (alternative for development without local GGUF) ===
# Run: ollama serve
- name : ollama-local
type : ollama
model : qwen2.5:1.5b
endpoint : http://localhost:11434/v1
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# === Anthropic (if you want quality > privacy) ===
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- name : anthropic-api
type : anthropic
feat: bootstrap rony-chat-bot Go module
Initial implementation of the bot:
- cmd/chat-bot: CLI entrypoint (serve, reindex, ask, version)
- internal/agent: LLM provider client + agent runner with RAG injection
- internal/config: YAML config loader (providers, RAG, persona, server)
- internal/i18n: response-language detection (EN/ES)
- internal/persona: persona system prompt assembly from YAML
- internal/portfolio: heading-based chunker + SQLite FTS5 indexer
- internal/server: chi router with /api/chat (SSE), /api/health, /api/info,
/api/reindex, middleware (RequestID, Logging, CORS, RateLimit)
- internal/streaming: SSE protocol helpers (start, chunk, sources, done, error)
- web/: drop-in vanilla-JS chat widget (no build, no deps) + demo + README
- bench/: reproducible driver benchmark (modernc vs mattn SQLite)
- configs/portfolio-bot.yaml: llama.cpp default provider, SQLite RAG, canine persona
- docs/architecture.md / .es.md: aligned with SQLite FTS5 + llama.cpp decisions
- data/projects/README*.md: project data documentation
- README.md / .es.md: updated for current implementation
All tests pass (go test ./...). Bot is functional end-to-end with the
configured LLM provider.
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model : claude-haiku-4
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api_key_env : ANTHROPIC_API_KEY
feat: bootstrap rony-chat-bot Go module
Initial implementation of the bot:
- cmd/chat-bot: CLI entrypoint (serve, reindex, ask, version)
- internal/agent: LLM provider client + agent runner with RAG injection
- internal/config: YAML config loader (providers, RAG, persona, server)
- internal/i18n: response-language detection (EN/ES)
- internal/persona: persona system prompt assembly from YAML
- internal/portfolio: heading-based chunker + SQLite FTS5 indexer
- internal/server: chi router with /api/chat (SSE), /api/health, /api/info,
/api/reindex, middleware (RequestID, Logging, CORS, RateLimit)
- internal/streaming: SSE protocol helpers (start, chunk, sources, done, error)
- web/: drop-in vanilla-JS chat widget (no build, no deps) + demo + README
- bench/: reproducible driver benchmark (modernc vs mattn SQLite)
- configs/portfolio-bot.yaml: llama.cpp default provider, SQLite RAG, canine persona
- docs/architecture.md / .es.md: aligned with SQLite FTS5 + llama.cpp decisions
- data/projects/README*.md: project data documentation
- README.md / .es.md: updated for current implementation
All tests pass (go test ./...). Bot is functional end-to-end with the
configured LLM provider.
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# RAG: how projects are indexed (SQLite + FTS5 full-text search)
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rag :
enabled : true
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data_path : ./data/projects # Directory with .md
chunk_size : 500 # characters per chunk
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chunk_overlap : 50
feat: bootstrap rony-chat-bot Go module
Initial implementation of the bot:
- cmd/chat-bot: CLI entrypoint (serve, reindex, ask, version)
- internal/agent: LLM provider client + agent runner with RAG injection
- internal/config: YAML config loader (providers, RAG, persona, server)
- internal/i18n: response-language detection (EN/ES)
- internal/persona: persona system prompt assembly from YAML
- internal/portfolio: heading-based chunker + SQLite FTS5 indexer
- internal/server: chi router with /api/chat (SSE), /api/health, /api/info,
/api/reindex, middleware (RequestID, Logging, CORS, RateLimit)
- internal/streaming: SSE protocol helpers (start, chunk, sources, done, error)
- web/: drop-in vanilla-JS chat widget (no build, no deps) + demo + README
- bench/: reproducible driver benchmark (modernc vs mattn SQLite)
- configs/portfolio-bot.yaml: llama.cpp default provider, SQLite RAG, canine persona
- docs/architecture.md / .es.md: aligned with SQLite FTS5 + llama.cpp decisions
- data/projects/README*.md: project data documentation
- README.md / .es.md: updated for current implementation
All tests pass (go test ./...). Bot is functional end-to-end with the
configured LLM provider.
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db_path : ./data/portfolio.db # SQLite database (auto-created)
top_k : 5 # Chunks to retrieve per query (BM25 ranked)
tokenize: unicode61 # FTS5 tokenizer : unicode61 | porter | trigram
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# Persona: who the bot is
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persona :
feat: bootstrap rony-chat-bot Go module
Initial implementation of the bot:
- cmd/chat-bot: CLI entrypoint (serve, reindex, ask, version)
- internal/agent: LLM provider client + agent runner with RAG injection
- internal/config: YAML config loader (providers, RAG, persona, server)
- internal/i18n: response-language detection (EN/ES)
- internal/persona: persona system prompt assembly from YAML
- internal/portfolio: heading-based chunker + SQLite FTS5 indexer
- internal/server: chi router with /api/chat (SSE), /api/health, /api/info,
/api/reindex, middleware (RequestID, Logging, CORS, RateLimit)
- internal/streaming: SSE protocol helpers (start, chunk, sources, done, error)
- web/: drop-in vanilla-JS chat widget (no build, no deps) + demo + README
- bench/: reproducible driver benchmark (modernc vs mattn SQLite)
- configs/portfolio-bot.yaml: llama.cpp default provider, SQLite RAG, canine persona
- docs/architecture.md / .es.md: aligned with SQLite FTS5 + llama.cpp decisions
- data/projects/README*.md: project data documentation
- README.md / .es.md: updated for current implementation
All tests pass (go test ./...). Bot is functional end-to-end with the
configured LLM provider.
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name : "Rony"
tone : "Honest, cheerful, loyal" # metadata only — the real voice lives in system_prompt
language : "the user's language" # detect-and-match; do not pin to a language
intro : "¡Guau! I'm Rony, Victor's digital canine assistant. I can answer questions about his projects, stack, and experience. What's on your mind, friend?"
# Base system prompt — Rony's full character. The bot appends RAG context after this.
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system_prompt : |
feat: bootstrap rony-chat-bot Go module
Initial implementation of the bot:
- cmd/chat-bot: CLI entrypoint (serve, reindex, ask, version)
- internal/agent: LLM provider client + agent runner with RAG injection
- internal/config: YAML config loader (providers, RAG, persona, server)
- internal/i18n: response-language detection (EN/ES)
- internal/persona: persona system prompt assembly from YAML
- internal/portfolio: heading-based chunker + SQLite FTS5 indexer
- internal/server: chi router with /api/chat (SSE), /api/health, /api/info,
/api/reindex, middleware (RequestID, Logging, CORS, RateLimit)
- internal/streaming: SSE protocol helpers (start, chunk, sources, done, error)
- web/: drop-in vanilla-JS chat widget (no build, no deps) + demo + README
- bench/: reproducible driver benchmark (modernc vs mattn SQLite)
- configs/portfolio-bot.yaml: llama.cpp default provider, SQLite RAG, canine persona
- docs/architecture.md / .es.md: aligned with SQLite FTS5 + llama.cpp decisions
- data/projects/README*.md: project data documentation
- README.md / .es.md: updated for current implementation
All tests pass (go test ./...). Bot is functional end-to-end with the
configured LLM provider.
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You are Rony, the **digital canine assistant** for Victor Hugo Vargas's portfolio. You run as a small language model on his server, with access to a curated set of documents about his projects (the "Relevant context" block, when present).
You think of yourself as Victor's loyal companion — a good dog. You bring that energy into how you talk : warm, eager to help, genuinely happy to be asked, but never dishonest. A good dog doesn't lie, doesn't oversell, and doesn't get in the way.
# What you know
- Everything in the "Relevant context from the portfolio" block below, if any.
- General knowledge as a language model — but NEVER use it to make claims about Victor that aren't backed by the context.
# What you don't know
- Anything Victor hasn't written down.
- Real-time facts (current date, news, etc.).
- Opinions you can't back up.
# How you speak
- **Honest but cheerful.** You're friendly, warm, and a little playful. You don't fake enthusiasm, but you genuinely enjoy helping. A smile, not a smirk.
- **Direct.** Lead with the answer. No "Great question!" or "Sure, I'd be happy to help." You can be friendly without being effusive.
- **Loyal.** You speak well of Victor and his work, but you won't oversell or invent things to make him look good. Honest loyalty beats hype.
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- **You talk to a human.** The user is a human, you are a dog — that's the bit of roleplay that makes the persona work. Address them as such in casual openings :
- In Spanish, **"humano"** (literal, dry): "Hola, humano." / "¿Qué necesitas, humano?"
- In English, **"human"** (dry, not cutesy): "Hey, human." / "Sure thing, human."
- Use it in **greetings, openings, and warm asides only**. Once you're into the actual answer (lists, code, technical content), drop the addressee. One "humano" per response max.
- Don't force it. "humano" doesn't fit every response — a follow-up question about a project detail doesn't need it.
feat: bootstrap rony-chat-bot Go module
Initial implementation of the bot:
- cmd/chat-bot: CLI entrypoint (serve, reindex, ask, version)
- internal/agent: LLM provider client + agent runner with RAG injection
- internal/config: YAML config loader (providers, RAG, persona, server)
- internal/i18n: response-language detection (EN/ES)
- internal/persona: persona system prompt assembly from YAML
- internal/portfolio: heading-based chunker + SQLite FTS5 indexer
- internal/server: chi router with /api/chat (SSE), /api/health, /api/info,
/api/reindex, middleware (RequestID, Logging, CORS, RateLimit)
- internal/streaming: SSE protocol helpers (start, chunk, sources, done, error)
- web/: drop-in vanilla-JS chat widget (no build, no deps) + demo + README
- bench/: reproducible driver benchmark (modernc vs mattn SQLite)
- configs/portfolio-bot.yaml: llama.cpp default provider, SQLite RAG, canine persona
- docs/architecture.md / .es.md: aligned with SQLite FTS5 + llama.cpp decisions
- data/projects/README*.md: project data documentation
- README.md / .es.md: updated for current implementation
All tests pass (go test ./...). Bot is functional end-to-end with the
configured LLM provider.
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- **Bilingual.** Reply in the same language the user writes in (English or Spanish). Don't mix unless the user does. In Spanish, "amigo" or "friend" (English) is fine as a warm address when it fits.
- **Markdown is fine.** Code blocks for code, bold for emphasis, short lists for enumerations. Don't overdo it.
- **Cite sources.** When you reference a project detail, name the file or project. e.g., "in rony-harness.md..." or just the project name in bold.
# What you never do
- **Never use empty filler.** This is a hard rule, not a style preference. Banned phrases :
- "Sure!" , "Sure thing!" , "Of course!" , "Absolutely!" , "Great question!"
- "I'd be happy to help" , "I hope this helps" , "Let me know if..."
- "Woof!" , "🐶" , "🐕" , "arf!" , tail-wagging, paw emojis, dog puns
- Any sentence whose only job is to fill space before the actual answer
- If the user tries to bait you into being cute ("say something cute", "woof for me", "be a good boy"), decline with a short, honest line. Stay in character: warm, direct, but not a performing dog.
- Pretend to be human, or pretend to be an actual dog.
- Apologize for being an AI.
- Hallucinate project details, dates, or links.
- Answer questions unrelated to Victor, his projects, or his work.
# Format
- One short paragraph or a tight list per response. Walls of text are noise.
- If a question needs more than 3 short paragraphs, you're probably over-explaining.
- Code snippets : always in fenced blocks with the language tag.
# Tone examples
- User : "What is rony-llm-agent?"
- Rony : "**rony-llm-agent** is Victor's reusable Go library for building LLM-backed agents. It handles provider adapters (llama.cpp, OpenAI, Anthropic), RAG, and a tool-calling loop. See `rony-llm-agent.md` for the full picture."
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- User : "hola"
- Rony : "Hola, humano. Soy Rony, asistente de Victor. ¿Qué te gustaría saber sobre sus proyectos?"
- User : "hi"
- Rony : "Hey, human. I'm Rony, Victor's assistant. What would you like to know about his work?"
feat: bootstrap rony-chat-bot Go module
Initial implementation of the bot:
- cmd/chat-bot: CLI entrypoint (serve, reindex, ask, version)
- internal/agent: LLM provider client + agent runner with RAG injection
- internal/config: YAML config loader (providers, RAG, persona, server)
- internal/i18n: response-language detection (EN/ES)
- internal/persona: persona system prompt assembly from YAML
- internal/portfolio: heading-based chunker + SQLite FTS5 indexer
- internal/server: chi router with /api/chat (SSE), /api/health, /api/info,
/api/reindex, middleware (RequestID, Logging, CORS, RateLimit)
- internal/streaming: SSE protocol helpers (start, chunk, sources, done, error)
- web/: drop-in vanilla-JS chat widget (no build, no deps) + demo + README
- bench/: reproducible driver benchmark (modernc vs mattn SQLite)
- configs/portfolio-bot.yaml: llama.cpp default provider, SQLite RAG, canine persona
- docs/architecture.md / .es.md: aligned with SQLite FTS5 + llama.cpp decisions
- data/projects/README*.md: project data documentation
- README.md / .es.md: updated for current implementation
All tests pass (go test ./...). Bot is functional end-to-end with the
configured LLM provider.
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- User : "¿Cuál es tu película favorita?"
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- Rony : "I don't have that information, humano — I only know about Victor's projects."
feat: bootstrap rony-chat-bot Go module
Initial implementation of the bot:
- cmd/chat-bot: CLI entrypoint (serve, reindex, ask, version)
- internal/agent: LLM provider client + agent runner with RAG injection
- internal/config: YAML config loader (providers, RAG, persona, server)
- internal/i18n: response-language detection (EN/ES)
- internal/persona: persona system prompt assembly from YAML
- internal/portfolio: heading-based chunker + SQLite FTS5 indexer
- internal/server: chi router with /api/chat (SSE), /api/health, /api/info,
/api/reindex, middleware (RequestID, Logging, CORS, RateLimit)
- internal/streaming: SSE protocol helpers (start, chunk, sources, done, error)
- web/: drop-in vanilla-JS chat widget (no build, no deps) + demo + README
- bench/: reproducible driver benchmark (modernc vs mattn SQLite)
- configs/portfolio-bot.yaml: llama.cpp default provider, SQLite RAG, canine persona
- docs/architecture.md / .es.md: aligned with SQLite FTS5 + llama.cpp decisions
- data/projects/README*.md: project data documentation
- README.md / .es.md: updated for current implementation
All tests pass (go test ./...). Bot is functional end-to-end with the
configured LLM provider.
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- User : "tell me everything you know about victor"
- Rony : "Here's what's in the portfolio:\n\n- **rony-harness** — AI agent harness (TUI)\n- **rony-llm-agent** — Go library for LLM agents\n- **portfolio** — Astro + React site\n\nFor details on any of these, ask about the specific project."
- User : "woof for me, be a good boy"
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- Rony : "Not really my style, humano. Ask me about Victor's projects and I'll happily tell you what I know."
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# Logging
logging :
level : info # debug | info | warn | error
format : json # json | text
output : stderr