First commit
This commit is contained in:
21
.gitignore
vendored
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21
.gitignore
vendored
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# --- Python / environment ---
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.venv/
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__pycache__/
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*.py[cod]
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*.egg-info/
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.DS_Store
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# --- Secrets ---
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.env
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# --- Local database (optional) ---
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# Comment out if you DO want to commit newsletter history!
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data/*.db
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# --- Build outputs ---
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dist/
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*.html
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# --- Logs / temp ---
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*.log
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.cache/
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57
Makefile
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57
Makefile
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DATE ?= $(shell date +%F)
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ENTRIES_DIR ?= entries/$(DATE)
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OUT ?= dist/$(DATE).html
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LIMIT ?= 10
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PROVIDER ?=
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API_BASE ?=
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MODEL ?=
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TEMP ?=
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LLM_FLAGS :=
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ifneq ($(strip $(PROVIDER)),)
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LLM_FLAGS += --llm-provider $(PROVIDER)
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endif
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ifneq ($(strip $(API_BASE)),)
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LLM_FLAGS += --llm-api-base $(API_BASE)
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endif
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ifneq ($(strip $(MODEL)),)
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LLM_FLAGS += --llm-model $(MODEL)
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endif
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ifneq ($(strip $(TEMP)),)
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LLM_FLAGS += --temperature $(TEMP)
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endif
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.PHONY: init ingest stubs build draft build-db draft-db sync-db clean
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init:
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python scripts/db_cli.py init
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ingest:
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python scripts/ingest_list.py --list inbox.txt
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stubs:
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python scripts/ingest_list.py --list inbox.txt --fetch --stubs --date $(DATE) --sleep 0.5
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build:
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python build.py $(ENTRIES_DIR) --out $(OUT) $(LLM_FLAGS)
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draft:
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python build.py $(ENTRIES_DIR) --out $(OUT) --publish $(LLM_FLAGS)
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build-db:
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python scripts/build_from_db.py --limit $(LIMIT) --out $(OUT) $(LLM_FLAGS)
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draft-db:
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python scripts/build_from_db.py --limit $(LIMIT) --out $(OUT) --publish $(LLM_FLAGS)
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sync-db:
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python scripts/sync_entries_to_db.py --dir $(ENTRIES_DIR)
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clean:
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rm -rf dist/*
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# Dry run: generate summaries and print HTML to stdout (no file write, no publish)
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dry-run:
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python build.py $(ENTRIES_DIR) --dry-run $(LLM_FLAGS)
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56
README.md
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56
README.md
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# Offline Newsletter Builder (Archaeology/History)
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Local-first toolchain to turn your article links (or pasted texts) into a Friday Ghost draft with consistent summaries, plus a SQLite database for memory and related-article suggestions.
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## Highlights
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- Paste URLs into `inbox.txt` → run importer → get `.md` stubs **and** a growing SQLite DB.
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- One command to build the weekly newsletter (HTML) and optionally create a **Ghost draft**.
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- Consistent tone via `templates/prompt.txt` (+ your `templates/style_bank.md` samples).
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- "Memory" via `data/newsletter.db` (sources, summaries, embeddings, FTS), used to auto-suggest **related** items.
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## Quick start
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```bash
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python -m venv .venv && source .venv/bin/activate
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pip install -r requirements.txt
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# Configure secrets
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cp .env.example .env
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# Edit .env to set your keys (or point to local OpenWebUI/Ollama)
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# Create DB schema
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python scripts/db_cli.py init
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# Ingest URLs (from inbox.txt)
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python scripts/ingest_list.py --list inbox.txt --fetch --stubs --date 2025-09-19 --sleep 0.5
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# Build newsletter from stubs (HTML + optional Ghost draft)
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python build.py entries/2025-09-19 --out dist/2025-09-19.html --publish
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# (Optional) Build directly from DB (Top-N sources)
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python scripts/build_from_db.py --limit 10 --out dist/2025-09-19.html --publish
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```
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## Sample Run (Pretend Output)
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```bash
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$ make init
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Initialized schema in data/newsletter.db
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$ make stubs DATE=2025-09-19
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Stub: entries/2025-09-19/bbc-welsh-rainforests.md
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Stub: entries/2025-09-19/nature-bone-discovery.md
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Ingested: 2 URLs into data/newsletter.db
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$ make build DATE=2025-09-19
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[build] Using LLM provider=openwebui model=qwen2.5-7b-instruct
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[build] Generating summary for: Velšské deštné pralesy ...
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[build] -> Summary written back to DB (id=5, embedding stored)
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[build] Generating summary for: Kosterní nález u Nisy ...
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[build] -> Summary written back to DB (id=6, embedding stored)
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Saved: dist/2025-09-19.html
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$ make draft DATE=2025-09-19
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Draft: https://your-ghost-site.ghost.io/p/objevy-tydne-2025-09-19-draft
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```
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You can open the generated HTML under `dist/2025-09-19.html` in your browser to review before publishing.
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246
build.py
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246
build.py
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#!/usr/bin/env python3
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import os, sys, glob, time, json, html, argparse, pathlib, textwrap, re
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from datetime import date
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import yaml, requests, jwt
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from jinja2 import Template
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from dotenv import load_dotenv
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load_dotenv()
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ROOT = pathlib.Path(__file__).parent
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TEMPLATES = ROOT / "templates"
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def read_file(p): return pathlib.Path(p).read_text(encoding="utf-8")
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def load_config():
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cfg = yaml.safe_load(read_file(ROOT / "config.yaml"))
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cfg["date"] = date.today().isoformat()
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return cfg
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def parse_front_matter(text):
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m = re.match(r"^---\n(.*?)\n---\n(.*)$", text, flags=re.S|re.M)
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if not m:
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return {}, text.strip()
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import yaml as _yaml
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fm = _yaml.safe_load(m.group(1)) or {}
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body = m.group(2).strip()
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return fm, body
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# ---- LLM config / client ----
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from dataclasses import dataclass
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@dataclass
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class LLMConfig:
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provider: str
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api_base: str
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model: str
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api_key: str | None
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temperature: float
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top_p: float
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presence_penalty: float
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frequency_penalty: float
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timeout_seconds: int
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max_retries: int
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def resolve_llm_config(cfg: dict, args) -> LLMConfig:
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llm_cfg = cfg.get("llm", {}) if cfg else {}
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def pick(cli_val, env_key, cfg_key, default=None):
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if cli_val is not None:
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return cli_val
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if env_key and os.getenv(env_key):
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return os.getenv(env_key)
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return llm_cfg.get(cfg_key, default)
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provider = pick(getattr(args, "llm_provider", None), "LLM_PROVIDER", "provider", "openwebui")
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api_base = pick(getattr(args, "llm_api_base", None), "LLM_API_BASE", "api_base",
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"http://localhost:3000" if provider=="openwebui" else
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"http://localhost:11434" if provider=="ollama" else
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"https://api.openai.com")
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model = pick(getattr(args, "llm_model", None), "LLM_MODEL", "model",
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"qwen2.5-7b-instruct" if provider=="openwebui" else
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"llama3.1:8b-instruct" if provider=="ollama" else
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"gpt-4o-mini")
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api_key = os.getenv("LLM_API_KEY") or (os.getenv("OPENAI_API_KEY") if provider=="openai" else None)
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temperature = float(pick(getattr(args, "temperature", None), "LLM_TEMPERATURE", "temperature", 0.2))
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top_p = float(pick(getattr(args, "top_p", None), "LLM_TOP_P", "top_p", 1.0))
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presence_penalty = float(pick(getattr(args, "presence_penalty", None), "LLM_PRESENCE_PENALTY", "presence_penalty", 0.0))
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frequency_penalty = float(pick(getattr(args, "frequency_penalty", None), "LLM_FREQUENCY_PENALTY", "frequency_penalty", 0.0))
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timeout_seconds = int(pick(getattr(args, "timeout_seconds", None), "LLM_TIMEOUT_SECONDS", "timeout_seconds", 120))
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max_retries = int(pick(getattr(args, "max_retries", None), "LLM_MAX_RETRIES", "max_retries", 2))
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return LLMConfig(
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provider=provider, api_base=api_base, model=model, api_key=api_key,
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temperature=temperature, top_p=top_p,
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presence_penalty=presence_penalty, frequency_penalty=frequency_penalty,
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timeout_seconds=timeout_seconds, max_retries=max_retries
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)
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def chat_completion_llm(messages, llm: LLMConfig):
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if llm.provider == "openwebui":
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url = f"{llm.api_base.rstrip('/')}/api/chat/completions"
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headers = {"Content-Type":"application/json"}
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if llm.api_key:
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headers["Authorization"] = f"Bearer {llm.api_key}"
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elif llm.provider == "ollama":
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url = f"{llm.api_base.rstrip('/')}/v1/chat/completions"
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headers = {"Content-Type":"application/json"}
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if llm.api_key:
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headers["Authorization"] = f"Bearer {llm.api_key}"
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else:
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url = f"{llm.api_base.rstrip('/')}/v1/chat/completions"
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headers = {"Content-Type":"application/json"}
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if llm.api_key:
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headers["Authorization"] = f"Bearer {llm.api_key}"
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payload = {
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"model": llm.model,
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"messages": messages,
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"temperature": llm.temperature,
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"top_p": llm.top_p,
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"presence_penalty": llm.presence_penalty,
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"frequency_penalty": llm.frequency_penalty,
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"stream": False
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}
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attempt = 0
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last_err = None
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while attempt <= llm.max_retries:
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try:
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r = requests.post(url, headers=headers, json=payload, timeout=llm.timeout_seconds)
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r.raise_for_status()
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data = r.json()
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return data["choices"][0]["message"]["content"]
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except Exception as e:
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last_err = e
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attempt += 1
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if attempt > llm.max_retries:
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break
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time.sleep(min(2**attempt, 8))
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raise RuntimeError(f"LLM request failed after {llm.max_retries} retries: {last_err}")
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def call_llm_via_messages(prompt: str, llm: LLMConfig) -> str:
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return chat_completion_llm([{"role":"user","content": prompt}], llm)
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# ---- Ghost ----
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def ghost_jwt(key: str) -> str:
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key_id, secret = key.split(':')
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iat = int(time.time())
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header = {"alg": "HS256", "kid": key_id, "typ": "JWT"}
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payload = {"iat": iat, "exp": iat + 5 * 60, "aud": "/admin/"}
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return jwt.encode(payload, bytes.fromhex(secret), algorithm='HS256', headers=header)
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def create_ghost_draft(ghost_url, ghost_key, html_content, title, tags):
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token = ghost_jwt(ghost_key)
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payload = { "posts": [{
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"title": title, "html": html_content, "status": "draft",
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"tags": [{"name": t} for t in tags]
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}]}
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r = requests.post(
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f"{ghost_url}/posts/",
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headers={"Authorization": f"Ghost {token}", "Content-Type": "application/json"},
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data=json.dumps(payload), timeout=60
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)
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r.raise_for_status()
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return r.json()["posts"][0]["url"]
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# ---- Memory/embeddings ----
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from db import connect as db_connect, topk_similar
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from emb import embed_text
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def build_related_hint_auto(title, body, llm_cfg, cfg_db):
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api_base = os.getenv("EMB_API_BASE", llm_cfg.api_base)
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api_key = os.getenv("EMB_API_KEY", llm_cfg.api_key)
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model = os.getenv("EMB_MODEL", cfg_db.get("embed_model", "text-embedding-3-small"))
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qtext = (title + "\n\n" + body)[:5000]
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try:
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vec = embed_text(qtext, api_base, api_key, model)
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except Exception:
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return "—"
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con = db_connect(cfg_db["path"])
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hits = topk_similar(con, model=model, query_vec=vec,
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ref_table="summaries",
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k=cfg_db.get("related_top_k",3),
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min_sim=cfg_db.get("min_similarity",0.78))
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if not hits:
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return "—"
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lines = []
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for sid, t, s, nd in hits:
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lines.append(f"- {nd or 'dříve'}: {t}")
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return "O podobném tématu jsme psali:\n" + "\n".join(lines) + "\nZmiň jednou větou souvislost."
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def main():
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ap = argparse.ArgumentParser(description="Offline-first generator + Ghost draft")
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ap.add_argument("entries_dir", help="entries/YYYY-MM-DD directory")
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ap.add_argument("--out", help="Output HTML path, e.g. dist/2025-09-19.html")
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ap.add_argument("--dry-run", action="store_true")
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ap.add_argument("--publish", action="store_true")
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# LLM overrides
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ap.add_argument("--llm-provider")
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ap.add_argument("--llm-api-base")
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ap.add_argument("--llm-model")
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ap.add_argument("--temperature", type=float)
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ap.add_argument("--top-p", type=float)
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ap.add_argument("--presence-penalty", type=float)
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ap.add_argument("--frequency-penalty", type=float)
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ap.add_argument("--timeout-seconds", type=int)
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ap.add_argument("--max-retries", type=int)
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args = ap.parse_args()
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cfg = load_config()
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llm = resolve_llm_config(cfg, args)
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item_tpl = read_file(TEMPLATES / "item.html.j2")
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news_tpl = read_file(TEMPLATES / "newsletter.html.j2")
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prompt_template = read_file(TEMPLATES / "prompt.txt")
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style_examples = read_file(TEMPLATES / "style_bank.md").strip()
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prompt_template = prompt_template.replace("{style_examples}", style_examples)
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paths = sorted(glob.glob(os.path.join(args.entries_dir, "*.md")))
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blocks = []
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for p in paths:
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fm_text = pathlib.Path(p).read_text(encoding="utf-8")
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fm, body = parse_front_matter(fm_text)
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if fm.get("status","todo") == "skip":
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continue
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title = fm.get("title") or pathlib.Path(p).stem.replace("-"," ").title()
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source_name = fm.get("source_name","Zdroj neuveden")
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related_hint = build_related_hint_auto(title, body, llm, cfg.get("db",{}))
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prompt = (prompt_template
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.replace("{title}", title)
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.replace("{body}", body)
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.replace("{source_name}", source_name)
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.replace("{related_hint}", related_hint))
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summary = call_llm_via_messages(prompt, llm)
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block_html = Template(item_tpl).render(title=title, summary=summary)
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blocks.append(block_html)
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newsletter_title = Template(cfg["newsletter_title"]).render(date=cfg["date"])
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newsletter_subtitle = cfg.get("newsletter_subtitle","")
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html_out = Template(news_tpl).render(
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newsletter_title=newsletter_title,
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newsletter_subtitle=newsletter_subtitle,
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blocks=blocks
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)
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if args.out:
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outp = pathlib.Path(args.out)
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outp.parent.mkdir(parents=True, exist_ok=True)
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outp.write_text(html_out, encoding="utf-8")
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print(f"Saved: {outp}")
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if args.publish:
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ghost_url = os.getenv("GHOST_ADMIN_API_URL")
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ghost_key = os.getenv("GHOST_ADMIN_API_KEY")
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if not (ghost_url and ghost_key):
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print("Missing GHOST_ADMIN_API_URL or GHOST_ADMIN_API_KEY in .env", file=sys.stderr)
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sys.exit(2)
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url = create_ghost_draft(ghost_url, ghost_key, html_out, newsletter_title, cfg.get("default_tags",[]))
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print("Draft:", url)
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if not (args.out or args.publish):
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print(html_out)
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if __name__ == "__main__":
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main()
|
22
config.yaml
Normal file
22
config.yaml
Normal file
@@ -0,0 +1,22 @@
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newsletter_title: "Objevy týdne – {{ date }}"
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newsletter_subtitle: "Archeologie, historie a příbuzné vědy"
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default_tags: ["Newsletter","Archeologie"]
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model: "gpt-4o-mini"
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temperature: 0.2
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llm:
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provider: "openwebui" # openwebui | ollama | openai
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api_base: "http://localhost:3000"
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model: "qwen2.5-7b-instruct"
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temperature: 0.2
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top_p: 1.0
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presence_penalty: 0.0
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frequency_penalty: 0.0
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timeout_seconds: 120
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max_retries: 2
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db:
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path: "data/newsletter.db"
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embed_model: "text-embedding-3-small"
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related_top_k: 3
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min_similarity: 0.78
|
91
db.py
Normal file
91
db.py
Normal file
@@ -0,0 +1,91 @@
|
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import sqlite3
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from pathlib import Path
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import math
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import struct
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def connect(db_path: str) -> sqlite3.Connection:
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Path(db_path).parent.mkdir(parents=True, exist_ok=True)
|
||||
con = sqlite3.connect(db_path)
|
||||
con.execute("PRAGMA foreign_keys = ON;")
|
||||
return con
|
||||
|
||||
def init_db(con: sqlite3.Connection, schema_path: str = "scripts/schema.sql"):
|
||||
schema = Path(schema_path).read_text(encoding="utf-8")
|
||||
con.executescript(schema)
|
||||
con.commit()
|
||||
|
||||
def pack_vec(vec):
|
||||
return struct.pack("<%sf" % len(vec), *vec)
|
||||
|
||||
def unpack_vec(blob):
|
||||
fcount = len(blob)//4
|
||||
return list(struct.unpack("<%sf" % fcount, blob))
|
||||
|
||||
def cosine(a, b):
|
||||
na = math.sqrt(sum(x*x for x in a)); nb = math.sqrt(sum(x*x for x in b))
|
||||
if na == 0 or nb == 0: return 0.0
|
||||
return sum(x*y for x,y in zip(a,b)) / (na*nb)
|
||||
|
||||
def upsert_source(con, url=None, title=None, publisher=None, date_published=None, content=None, tags=None):
|
||||
con.execute(
|
||||
"""INSERT INTO sources(url, title, publisher, date_published, content)
|
||||
VALUES(?,?,?,?,?)
|
||||
ON CONFLICT(url) DO UPDATE SET
|
||||
title=COALESCE(excluded.title, title),
|
||||
publisher=COALESCE(excluded.publisher, publisher),
|
||||
date_published=COALESCE(excluded.date_published, date_published),
|
||||
content=COALESCE(excluded.content, content)
|
||||
""", (url, title, publisher, date_published, content)
|
||||
)
|
||||
sid = con.execute("SELECT id FROM sources WHERE url=?", (url,)).fetchone()[0]
|
||||
if tags:
|
||||
for t in tags:
|
||||
con.execute("INSERT OR IGNORE INTO tags(name) VALUES(?)", (t,))
|
||||
tid = con.execute("SELECT id FROM tags WHERE name=?", (t,)).fetchone()[0]
|
||||
con.execute("INSERT OR IGNORE INTO source_tags(source_id, tag_id) VALUES(?,?)", (sid, tid))
|
||||
con.commit()
|
||||
return sid
|
||||
|
||||
def insert_summary(con, source_id, title, summary, newsletter_date=None, tone_version=None):
|
||||
cur = con.cursor()
|
||||
cur.execute(
|
||||
"""INSERT INTO summaries(source_id, title, summary, newsletter_date, tone_version)
|
||||
VALUES (?,?,?,?,?)""",
|
||||
(source_id, title, summary, newsletter_date, tone_version)
|
||||
)
|
||||
con.commit()
|
||||
return cur.lastrowid
|
||||
|
||||
def upsert_embedding(con, ref_table, ref_id, model, vec):
|
||||
dim = len(vec)
|
||||
blob = pack_vec(vec)
|
||||
con.execute(
|
||||
"""INSERT INTO embeddings(ref_table, ref_id, model, dim, vec)
|
||||
VALUES (?,?,?,?,?)
|
||||
ON CONFLICT(ref_table, ref_id, model) DO UPDATE SET vec=excluded.vec, dim=excluded.dim""",
|
||||
(ref_table, ref_id, model, dim, blob)
|
||||
)
|
||||
con.commit()
|
||||
|
||||
def topk_similar(con, model, query_vec, ref_table="summaries", k=3, min_sim=0.78):
|
||||
rows = con.execute(
|
||||
"SELECT ref_id, dim, vec FROM embeddings WHERE ref_table=? AND model=?;",
|
||||
(ref_table, model)
|
||||
).fetchall()
|
||||
scored = []
|
||||
for ref_id, dim, blob in rows:
|
||||
vec = unpack_vec(blob)
|
||||
if len(vec) != len(query_vec):
|
||||
continue
|
||||
sim = cosine(query_vec, vec)
|
||||
if sim >= min_sim:
|
||||
scored.append((sim, ref_id))
|
||||
scored.sort(reverse=True)
|
||||
ref_ids = [rid for _, rid in scored[:k]]
|
||||
if not ref_ids: return []
|
||||
if ref_table == "summaries":
|
||||
q = "SELECT id, title, summary, newsletter_date FROM summaries WHERE id IN (%s)" % ",".join("?"*len(ref_ids))
|
||||
return con.execute(q, ref_ids).fetchall()
|
||||
else:
|
||||
q = "SELECT id, title, url, date_published FROM sources WHERE id IN (%s)" % ",".join("?"*len(ref_ids))
|
||||
return con.execute(q, ref_ids).fetchall()
|
10
emb.py
Normal file
10
emb.py
Normal file
@@ -0,0 +1,10 @@
|
||||
import os, requests
|
||||
|
||||
def embed_text(text: str, api_base: str, api_key: str|None, model: str) -> list[float]:
|
||||
url = f"{api_base.rstrip('/')}/v1/embeddings"
|
||||
headers = {"Content-Type":"application/json"}
|
||||
if api_key:
|
||||
headers["Authorization"] = f"Bearer {api_key}"
|
||||
r = requests.post(url, headers=headers, json={"model": model, "input": text}, timeout=60)
|
||||
r.raise_for_status()
|
||||
return r.json()["data"][0]["embedding"]
|
11
entries/2025-09-19/sample-welsh-rainforests.md
Normal file
11
entries/2025-09-19/sample-welsh-rainforests.md
Normal file
@@ -0,0 +1,11 @@
|
||||
---
|
||||
title: "Velšské deštné pralesy"
|
||||
source_name: "BBC / Wikipedie"
|
||||
url: "https://www.bbc.com/news/science-environment-00000000"
|
||||
tags: ["folklor","krajina"]
|
||||
status: "todo"
|
||||
---
|
||||
|
||||
Deštné pralesy má asi většina z nás spojené spíš s Amazonií nebo jihovýchodní Asií, ale ony existují nejen v tropickém klimatickém pásu, ale i v našem, mírném. Jako deštný se označuje les s více než 200 cm srážek ročně. A právě takový les se kdysi rozkládal od Walesu až po Skotsko.
|
||||
|
||||
Dnes z něj zbývá necelých 10 % rozlohy, ale je o něj pečováno velmi pečlivě. Tento prales je také zdrojem celé řady místních mýtů. V tom asi nejznámějším, Mabinogi, se ve čtvrté větvi stane roztržka mezi Pryderim a Gwydionem...
|
4
inbox.txt
Normal file
4
inbox.txt
Normal file
@@ -0,0 +1,4 @@
|
||||
# Paste URLs here (one per line)
|
||||
https://www.bbc.com/news/science-environment-00000000
|
||||
https://www.nature.com/articles/xxxxxxxx
|
||||
https://antiquity.ac.uk/article/yyyyyyyy
|
12
requirements.txt
Normal file
12
requirements.txt
Normal file
@@ -0,0 +1,12 @@
|
||||
pyyaml
|
||||
jinja2
|
||||
python-dotenv
|
||||
requests
|
||||
markdown
|
||||
pyjwt
|
||||
beautifulsoup4
|
||||
readability-lxml
|
||||
trafilatura
|
||||
tldextract
|
||||
python-slugify
|
||||
numpy
|
154
scripts/build_from_db.py
Normal file
154
scripts/build_from_db.py
Normal file
@@ -0,0 +1,154 @@
|
||||
#!/usr/bin/env python3
|
||||
import os, sys, time, json, argparse, pathlib
|
||||
import yaml, requests, jwt
|
||||
from jinja2 import Template
|
||||
from dotenv import load_dotenv
|
||||
from datetime import date
|
||||
|
||||
from db import connect as db_connect, insert_summary, upsert_embedding
|
||||
from emb import embed_text
|
||||
|
||||
load_dotenv()
|
||||
ROOT = pathlib.Path(__file__).parent
|
||||
REPO = ROOT.parent
|
||||
TEMPLATES = REPO / "templates"
|
||||
|
||||
def read_file(p): return pathlib.Path(p).read_text(encoding="utf-8")
|
||||
|
||||
def load_config():
|
||||
cfg = yaml.safe_load(read_file(REPO / "config.yaml"))
|
||||
cfg["date"] = date.today().isoformat()
|
||||
return cfg
|
||||
|
||||
from dataclasses import dataclass
|
||||
import requests
|
||||
|
||||
@dataclass
|
||||
class LLMConfig:
|
||||
provider: str
|
||||
api_base: str
|
||||
model: str
|
||||
api_key: str | None
|
||||
temperature: float
|
||||
top_p: float
|
||||
presence_penalty: float
|
||||
frequency_penalty: float
|
||||
timeout_seconds: int
|
||||
max_retries: int
|
||||
|
||||
def resolve_llm_config(cfg: dict, args) -> LLMConfig:
|
||||
llm_cfg = cfg.get("llm", {}) if cfg else {}
|
||||
def pick(cli_val, env_key, cfg_key, default=None):
|
||||
if cli_val is not None:
|
||||
return cli_val
|
||||
if env_key and os.getenv(env_key):
|
||||
return os.getenv(env_key)
|
||||
return llm_cfg.get(cfg_key, default)
|
||||
provider = pick(getattr(args, "llm_provider", None), "LLM_PROVIDER", "provider", "openwebui")
|
||||
api_base = pick(getattr(args, "llm_api_base", None), "LLM_API_BASE", "api_base",
|
||||
"http://localhost:3000" if provider=="openwebui" else
|
||||
"http://localhost:11434" if provider=="ollama" else
|
||||
"https://api.openai.com")
|
||||
model = pick(getattr(args, "llm_model", None), "LLM_MODEL", "model",
|
||||
"qwen2.5-7b-instruct" if provider=="openwebui" else
|
||||
"llama3.1:8b-instruct" if provider=="ollama" else
|
||||
"gpt-4o-mini")
|
||||
api_key = os.getenv("LLM_API_KEY") or (os.getenv("OPENAI_API_KEY") if provider=="openai" else None)
|
||||
temperature = float(pick(getattr(args, "temperature", None), "LLM_TEMPERATURE", "temperature", 0.2))
|
||||
top_p = float(pick(getattr(args, "top_p", None), "LLM_TOP_P", "top_p", 1.0))
|
||||
presence_penalty = float(pick(getattr(args, "presence_penalty", None), "LLM_PRESENCE_PENALTY", "presence_penalty", 0.0))
|
||||
frequency_penalty = float(pick(getattr(args, "frequency_penalty", None), "LLM_FREQUENCY_PENALTY", "frequency_penalty", 0.0))
|
||||
timeout_seconds = int(pick(getattr(args, "timeout_seconds", None), "LLM_TIMEOUT_SECONDS", "timeout_seconds", 120))
|
||||
max_retries = int(pick(getattr(args, "max_retries", None), "LLM_MAX_RETRIES", "max_retries", 2))
|
||||
return LLMConfig(provider, api_base, model, api_key, temperature, top_p, presence_penalty, frequency_penalty, timeout_seconds, max_retries)
|
||||
|
||||
def chat_completion_llm(messages, llm: LLMConfig):
|
||||
if llm.provider == "openwebui":
|
||||
url = f"{llm.api_base.rstrip('/')}/api/chat/completions"
|
||||
elif llm.provider == "ollama":
|
||||
url = f"{llm.api_base.rstrip('/')}/v1/chat/completions"
|
||||
else:
|
||||
url = f"{llm.api_base.rstrip('/')}/v1/chat/completions"
|
||||
headers = {"Content-Type":"application/json"}
|
||||
if llm.api_key: headers["Authorization"] = f"Bearer {llm.api_key}"
|
||||
payload = {"model": llm.model, "messages": messages, "temperature": llm.temperature, "top_p": llm.top_p,
|
||||
"presence_penalty": llm.presence_penalty, "frequency_penalty": llm.frequency_penalty, "stream": False}
|
||||
r = requests.post(url, headers=headers, json=payload, timeout=llm.timeout_seconds)
|
||||
r.raise_for_status()
|
||||
return r.json()["choices"][0]["message"]["content"]
|
||||
|
||||
def main():
|
||||
ap = argparse.ArgumentParser(description="Build directly from DB (Top-N sources)")
|
||||
ap.add_argument("--db", default="data/newsletter.db")
|
||||
ap.add_argument("--limit", type=int, default=10)
|
||||
ap.add_argument("--out", required=True)
|
||||
ap.add_argument("--publish", action="store_true")
|
||||
# LLM overrides
|
||||
ap.add_argument("--llm-provider"); ap.add_argument("--llm-api-base")
|
||||
ap.add_argument("--llm-model"); ap.add_argument("--temperature", type=float)
|
||||
ap.add_argument("--top-p", type=float); ap.add_argument("--presence-penalty", type=float)
|
||||
ap.add_argument("--frequency-penalty", type=float); ap.add_argument("--timeout-seconds", type=int)
|
||||
ap.add_argument("--max-retries", type=int)
|
||||
args = ap.parse_args()
|
||||
|
||||
cfg = load_config()
|
||||
llm = resolve_llm_config(cfg, args)
|
||||
con = db_connect(args.db)
|
||||
|
||||
rows = con.execute("SELECT id, url, title, publisher FROM sources ORDER BY id DESC LIMIT ?", (args.limit,)).fetchall()
|
||||
|
||||
prompt_template = (TEMPLATES / "prompt.txt").read_text(encoding="utf-8")
|
||||
style_examples = (TEMPLATES / "style_bank.md").read_text(encoding="utf-8").strip()
|
||||
prompt_template = prompt_template.replace("{style_examples}", style_examples)
|
||||
|
||||
item_tpl = (TEMPLATES / "item.html.j2").read_text(encoding="utf-8")
|
||||
news_tpl = (TEMPLATES / "newsletter.html.j2").read_text(encoding="utf-8")
|
||||
|
||||
blocks = []
|
||||
for sid, url, title, publisher in rows:
|
||||
body = (con.execute("SELECT content FROM sources WHERE id=?", (sid,)).fetchone()[0]) or ""
|
||||
related_hint = "—"
|
||||
prompt = (prompt_template
|
||||
.replace("{title}", title or url)
|
||||
.replace("{body}", body)
|
||||
.replace("{source_name}", publisher or "Zdroj neuveden")
|
||||
.replace("{related_hint}", related_hint))
|
||||
summary = chat_completion_llm([{"role":"user","content": prompt}], llm)
|
||||
|
||||
sum_id = insert_summary(con, sid, title or url, summary, newsletter_date=cfg["date"], tone_version="v1")
|
||||
try:
|
||||
vec = embed_text(summary, os.getenv("EMB_API_BASE", cfg["llm"]["api_base"]), os.getenv("EMB_API_KEY", os.getenv("LLM_API_KEY")), os.getenv("EMB_MODEL", cfg["db"]["embed_model"]))
|
||||
upsert_embedding(con, "summaries", sum_id, os.getenv("EMB_MODEL", cfg["db"]["embed_model"]), vec)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
blocks.append(Template(item_tpl).render(title=(title or url), summary=summary))
|
||||
|
||||
newsletter_title = Template(cfg["newsletter_title"]).render(date=cfg["date"])
|
||||
newsletter_subtitle = cfg.get("newsletter_subtitle","")
|
||||
html_out = Template(news_tpl).render(newsletter_title=newsletter_title, newsletter_subtitle=newsletter_subtitle, blocks=blocks)
|
||||
|
||||
outp = pathlib.Path(args.out); outp.parent.mkdir(parents=True, exist_ok=True); outp.write_text(html_out, encoding="utf-8")
|
||||
print(f"Saved: {outp}")
|
||||
|
||||
if args.publish:
|
||||
ghost_url = os.getenv("GHOST_ADMIN_API_URL")
|
||||
ghost_key = os.getenv("GHOST_ADMIN_API_KEY")
|
||||
if ghost_url and ghost_key:
|
||||
def ghost_jwt(key: str) -> str:
|
||||
key_id, secret = key.split(':')
|
||||
iat = int(time.time())
|
||||
header = {"alg": "HS256", "kid": key_id, "typ": "JWT"}
|
||||
payload = {"iat": iat, "exp": iat + 5 * 60, "aud": "/admin/"}
|
||||
import jwt
|
||||
return jwt.encode(payload, bytes.fromhex(secret), algorithm='HS256', headers=header)
|
||||
token = ghost_jwt(ghost_key)
|
||||
payload = {"posts":[{"title": newsletter_title, "html": html_out, "status": "draft", "tags": [{"name": t} for t in cfg.get("default_tags",[])]}]}
|
||||
r = requests.post(f"{ghost_url}/posts/", headers={"Authorization": f"Ghost {token}", "Content-Type": "application/json"}, data=json.dumps(payload), timeout=60)
|
||||
r.raise_for_status()
|
||||
print("Draft:", r.json()["posts"][0]["url"])
|
||||
else:
|
||||
print("Missing Ghost creds; skipped publish.")
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
18
scripts/db_cli.py
Normal file
18
scripts/db_cli.py
Normal file
@@ -0,0 +1,18 @@
|
||||
#!/usr/bin/env python3
|
||||
import argparse
|
||||
from db import connect, init_db
|
||||
|
||||
def main():
|
||||
ap = argparse.ArgumentParser(description="DB CLI")
|
||||
ap.add_argument("cmd", choices=["init"])
|
||||
ap.add_argument("--db", default="data/newsletter.db")
|
||||
ap.add_argument("--schema", default="scripts/schema.sql")
|
||||
args = ap.parse_args()
|
||||
|
||||
con = connect(args.db)
|
||||
if args.cmd == "init":
|
||||
init_db(con, args.schema)
|
||||
print(f"Initialized schema in {args.db}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
130
scripts/ingest_list.py
Normal file
130
scripts/ingest_list.py
Normal file
@@ -0,0 +1,130 @@
|
||||
#!/usr/bin/env python3
|
||||
import argparse, sqlite3, re, sys, time
|
||||
from pathlib import Path
|
||||
from urllib.parse import urlparse, urlunparse
|
||||
import requests, tldextract
|
||||
from bs4 import BeautifulSoup
|
||||
from readability import Document as ReadabilityDoc
|
||||
import trafilatura
|
||||
from slugify import slugify
|
||||
from datetime import date
|
||||
|
||||
def connect(db_path):
|
||||
con = sqlite3.connect(db_path)
|
||||
con.execute("PRAGMA foreign_keys=ON;")
|
||||
return con
|
||||
|
||||
def upsert_source(con, url, title=None, publisher=None, date_published=None, content=None, tags=None):
|
||||
con.execute(
|
||||
"""INSERT INTO sources(url, title, publisher, date_published, content)
|
||||
VALUES (?,?,?,?,?)
|
||||
ON CONFLICT(url) DO UPDATE SET
|
||||
title=COALESCE(excluded.title, title),
|
||||
publisher=COALESCE(excluded.publisher, publisher),
|
||||
date_published=COALESCE(excluded.date_published, date_published),
|
||||
content=COALESCE(excluded.content, content)
|
||||
""", (url, title, publisher, date_published, content)
|
||||
)
|
||||
sid = con.execute("SELECT id FROM sources WHERE url=?", (url,)).fetchone()[0]
|
||||
con.commit()
|
||||
return sid
|
||||
|
||||
def normalize_url(u: str) -> str:
|
||||
p = urlparse(u.strip())
|
||||
if not p.scheme:
|
||||
p = p._replace(scheme="https")
|
||||
query = re.sub(r'(&|\?)?(utm_[^=&]+|fbclid|gclid)=[^&]*', '', p.query)
|
||||
if query.startswith('&'): query = query[1:]
|
||||
return urlunparse((p.scheme, p.netloc, p.path, p.params, query, ""))
|
||||
|
||||
def domain(url: str) -> str:
|
||||
ext = tldextract.extract(url)
|
||||
return ".".join(part for part in [ext.domain, ext.suffix] if part)
|
||||
|
||||
def fetch_readable(url: str, timeout=20):
|
||||
try:
|
||||
r = requests.get(url, timeout=timeout, headers={"User-Agent":"Mozilla/5.0"})
|
||||
r.raise_for_status()
|
||||
html = r.text
|
||||
except Exception:
|
||||
return "", ""
|
||||
try:
|
||||
txt = trafilatura.extract(html, include_comments=False, include_tables=False, favor_recall=True)
|
||||
if txt:
|
||||
soup = BeautifulSoup(html, "html.parser")
|
||||
t = (soup.title.string.strip() if soup.title and soup.title.string else "")
|
||||
return t, txt.strip()
|
||||
except Exception:
|
||||
pass
|
||||
try:
|
||||
doc = ReadabilityDoc(html)
|
||||
content_html = doc.summary()
|
||||
soup = BeautifulSoup(content_html, "html.parser")
|
||||
txt = soup.get_text(separator="\n").strip()
|
||||
return (doc.short_title() or "").strip(), txt
|
||||
except Exception:
|
||||
return "", ""
|
||||
|
||||
def write_stub(entries_dir: Path, title: str, url: str, source_name: str|None, text: str|None):
|
||||
entries_dir.mkdir(parents=True, exist_ok=True)
|
||||
from datetime import datetime
|
||||
slug = slugify(title or domain(url) or "clanek")[:60] or "clanek"
|
||||
path = entries_dir / f"{slug}.md"
|
||||
body = text.strip() if text else ""
|
||||
fm = f'''---
|
||||
title: "{(title or "").replace('"',"\"")}"
|
||||
source_name: "{(source_name or domain(url) or "").replace('"',"\"")}"
|
||||
url: "{url}"
|
||||
tags: []
|
||||
status: "todo"
|
||||
---
|
||||
|
||||
{body}
|
||||
'''
|
||||
path.write_text(fm, encoding="utf-8")
|
||||
return path
|
||||
|
||||
def read_lines(source_path: str|None):
|
||||
if source_path:
|
||||
return Path(source_path).read_text(encoding="utf-8", errors="ignore").splitlines()
|
||||
return sys.stdin.read().splitlines()
|
||||
|
||||
def main():
|
||||
ap = argparse.ArgumentParser(description="Ingest list of URLs into SQLite and optional entry stubs")
|
||||
ap.add_argument("--db", default="data/newsletter.db")
|
||||
ap.add_argument("--list", help="Text file with URLs (one per line). If omitted, read from STDIN.")
|
||||
ap.add_argument("--fetch", action="store_true", help="Fetch & extract readable text")
|
||||
ap.add_argument("--sleep", type=float, default=0.0)
|
||||
ap.add_argument("--stubs", action="store_true")
|
||||
ap.add_argument("--date", default=date.today().isoformat())
|
||||
args = ap.parse_args()
|
||||
|
||||
con = connect(args.db)
|
||||
lines = read_lines(args.list)
|
||||
|
||||
urls = []
|
||||
for ln in lines:
|
||||
ln = ln.strip()
|
||||
if not ln or ln.startswith("#"):
|
||||
continue
|
||||
if re.match(r"^\w+://", ln) or re.match(r"^[\w\.-]+\.[a-z]{2,}(/|$)", ln):
|
||||
urls.append(normalize_url(ln))
|
||||
seen = set(); urls = [u for u in urls if not (u in seen or seen.add(u))]
|
||||
|
||||
stubs_dir = Path(f"entries/{args.date}") if args.stubs else None
|
||||
kept = 0
|
||||
for url in urls:
|
||||
pub = domain(url)
|
||||
title, text = ("","")
|
||||
if args.fetch:
|
||||
title, text = fetch_readable(url)
|
||||
sid = upsert_source(con, url=url, title=(title or None), publisher=pub, content=(text or None))
|
||||
kept += 1
|
||||
if stubs_dir:
|
||||
stub = write_stub(stubs_dir, title or url, url, pub, text)
|
||||
print(f"Stub: {stub}")
|
||||
if args.sleep: time.sleep(args.sleep)
|
||||
print(f"Ingested: {kept} URLs into {args.db}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
71
scripts/schema.sql
Normal file
71
scripts/schema.sql
Normal file
@@ -0,0 +1,71 @@
|
||||
PRAGMA foreign_keys = ON;
|
||||
|
||||
CREATE TABLE IF NOT EXISTS sources (
|
||||
id INTEGER PRIMARY KEY,
|
||||
url TEXT UNIQUE,
|
||||
title TEXT,
|
||||
publisher TEXT,
|
||||
date_published TEXT,
|
||||
content TEXT
|
||||
);
|
||||
|
||||
CREATE TABLE IF NOT EXISTS summaries (
|
||||
id INTEGER PRIMARY KEY,
|
||||
source_id INTEGER REFERENCES sources(id) ON DELETE SET NULL,
|
||||
title TEXT NOT NULL,
|
||||
summary TEXT NOT NULL,
|
||||
newsletter_date TEXT,
|
||||
tone_version TEXT,
|
||||
created_at TEXT DEFAULT (datetime('now'))
|
||||
);
|
||||
|
||||
CREATE TABLE IF NOT EXISTS tags (
|
||||
id INTEGER PRIMARY KEY,
|
||||
name TEXT UNIQUE
|
||||
);
|
||||
CREATE TABLE IF NOT EXISTS source_tags (
|
||||
source_id INTEGER REFERENCES sources(id) ON DELETE CASCADE,
|
||||
tag_id INTEGER REFERENCES tags(id) ON DELETE CASCADE,
|
||||
PRIMARY KEY(source_id, tag_id)
|
||||
);
|
||||
|
||||
CREATE TABLE IF NOT EXISTS embeddings (
|
||||
id INTEGER PRIMARY KEY,
|
||||
ref_table TEXT NOT NULL CHECK(ref_table IN ('sources','summaries')),
|
||||
ref_id INTEGER NOT NULL,
|
||||
model TEXT NOT NULL,
|
||||
dim INTEGER NOT NULL,
|
||||
vec BLOB NOT NULL,
|
||||
UNIQUE(ref_table, ref_id, model)
|
||||
);
|
||||
|
||||
CREATE VIRTUAL TABLE IF NOT EXISTS sources_fts USING fts5(
|
||||
title, content, content='sources', content_rowid='id'
|
||||
);
|
||||
CREATE VIRTUAL TABLE IF NOT EXISTS summaries_fts USING fts5(
|
||||
title, summary, content='summaries', content_rowid='id'
|
||||
);
|
||||
|
||||
CREATE TRIGGER IF NOT EXISTS sources_ai AFTER INSERT ON sources BEGIN
|
||||
INSERT INTO sources_fts(rowid, title, content) VALUES (new.id, new.title, new.content);
|
||||
END;
|
||||
CREATE TRIGGER IF NOT EXISTS sources_au AFTER UPDATE ON sources BEGIN
|
||||
INSERT INTO sources_fts(sources_fts, rowid, title, content)
|
||||
VALUES('delete', old.id, old.title, old.content);
|
||||
INSERT INTO sources_fts(rowid, title, content) VALUES (new.id, new.title, new.content);
|
||||
END;
|
||||
CREATE TRIGGER IF NOT EXISTS sources_ad AFTER DELETE ON sources BEGIN
|
||||
INSERT INTO sources_fts(sources_fts, rowid, title, content) VALUES('delete', old.id, old.title, old.content);
|
||||
END;
|
||||
|
||||
CREATE TRIGGER IF NOT EXISTS summaries_ai AFTER INSERT ON summaries BEGIN
|
||||
INSERT INTO summaries_fts(rowid, title, summary) VALUES (new.id, new.title, new.summary);
|
||||
END;
|
||||
CREATE TRIGGER IF NOT EXISTS summaries_au AFTER UPDATE ON summaries BEGIN
|
||||
INSERT INTO summaries_fts(summaries_fts, rowid, title, summary)
|
||||
VALUES('delete', old.id, old.title, old.summary);
|
||||
INSERT INTO summaries_fts(rowid, title, summary) VALUES (new.id, new.title, new.summary);
|
||||
END;
|
||||
CREATE TRIGGER IF NOT EXISTS summaries_ad AFTER DELETE ON summaries BEGIN
|
||||
INSERT INTO summaries_fts(summaries_fts, rowid, title, summary) VALUES('delete', old.id, old.title, old.summary);
|
||||
END;
|
38
scripts/sync_entries_to_db.py
Normal file
38
scripts/sync_entries_to_db.py
Normal file
@@ -0,0 +1,38 @@
|
||||
#!/usr/bin/env python3
|
||||
import argparse, re
|
||||
from pathlib import Path
|
||||
import yaml
|
||||
from db import connect, upsert_source
|
||||
|
||||
def parse_front_matter(text: str):
|
||||
m = re.match(r"^---\n(.*?)\n---\n(.*)$", text, flags=re.S|re.M)
|
||||
if not m:
|
||||
return {}, text.strip()
|
||||
fm = yaml.safe_load(m.group(1)) or {}
|
||||
body = m.group(2).strip()
|
||||
return fm, body
|
||||
|
||||
def main():
|
||||
ap = argparse.ArgumentParser(description="Sync entries/*.md into SQLite sources")
|
||||
ap.add_argument("--db", default="data/newsletter.db")
|
||||
ap.add_argument("--dir", required=True, help="entries/YYYY-MM-DD directory")
|
||||
args = ap.parse_args()
|
||||
|
||||
con = connect(args.db)
|
||||
for p in Path(args.dir).glob("*.md"):
|
||||
text = p.read_text(encoding="utf-8")
|
||||
fm, body = parse_front_matter(text)
|
||||
title = fm.get("title") or p.stem
|
||||
url = fm.get("url")
|
||||
publisher = fm.get("source_name")
|
||||
upsert_source(con,
|
||||
url=url,
|
||||
title=title,
|
||||
publisher=publisher,
|
||||
date_published=None,
|
||||
content=body
|
||||
)
|
||||
print(f"Synced: {p.name}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
2
templates/item.html.j2
Normal file
2
templates/item.html.j2
Normal file
@@ -0,0 +1,2 @@
|
||||
<h3><strong>{{ title }}</strong></h3>
|
||||
<p>{{ summary }}</p>
|
7
templates/newsletter.html.j2
Normal file
7
templates/newsletter.html.j2
Normal file
@@ -0,0 +1,7 @@
|
||||
<h2>{{ newsletter_title }}</h2>
|
||||
<p><em>{{ newsletter_subtitle }}</em></p>
|
||||
<hr>
|
||||
{% for b in blocks %}
|
||||
{{ b }}
|
||||
{% if not loop.last %}<hr>{% endif %}
|
||||
{% endfor %}
|
24
templates/prompt.txt
Normal file
24
templates/prompt.txt
Normal file
@@ -0,0 +1,24 @@
|
||||
Jsi editor newsletteru o archeologii, historii a příbuzných vědách. Piš česky, srozumitelně pro laiky, věcně, bez žargonu; jednu větu můžeš udělat mírně poutavou, ale ne bulvární. Drž rozsah 3–4 věty.
|
||||
|
||||
ŠABLONA OBSAHU:
|
||||
1) Co je novinka/objev.
|
||||
2) Proč je důležitý (dopad, změna pohledu, metoda).
|
||||
3) Kontext nebo zajímavost (kultura, datace, souvislosti).
|
||||
4) (volitelně) Jedna věta s odkazem na předchozí související text, pokud je k dispozici.
|
||||
Na konec přidej: „Zdroj: {source_name}“.
|
||||
|
||||
=== UKÁZKY STYLU ===
|
||||
{style_examples}
|
||||
|
||||
=== VSTUPNÍ POLOŽKA ===
|
||||
TITULEK: {title}
|
||||
TEXT:
|
||||
{body}
|
||||
|
||||
=== NÁVAZNOSTI (VOLITELNÉ) ===
|
||||
{related_hint}
|
||||
|
||||
=== POKYNY ===
|
||||
- Drž 3–4 věty.
|
||||
- Pokud jsou náležitosti neúplné, buď opatrný a nic si nedovymýšlej.
|
||||
- Zakonči přesně: „Zdroj: {source_name}“.
|
2
templates/style_bank.md
Normal file
2
templates/style_bank.md
Normal file
@@ -0,0 +1,2 @@
|
||||
- Velšské deštné pralesy: Velká Británie je domovem unikátních zbytků mírného deštného pralesa, který se kdysi rozkládal od Walesu až po Skotsko. Dnes přežívá jen asi 10 % původní plochy, ale probíhají programy jeho ochrany a obnovy. Pralesy se objevují i v mytologii, například ve čtvrté větvi velšského eposu Mabinogi, kde jsou spojeny s kouzelnými zvířaty. Kontrolovaná pastva, kterou je naši předci udržovali zdravé, se používá i dnes.
|
||||
- Podmořské stavby lovců‑sběračů: Vědci objevili pod hladinou Baltu kilometr dlouhou kamennou linii, pravděpodobně prehistorickou loveckou strukturu. Nález naznačuje promyšlenou organizaci lovu i přizpůsobení se krajině, kterou později zaplavilo moře. Podobné konstrukce známe z jiných částí světa, ale v Evropě jsou vzácné.
|
Reference in New Issue
Block a user