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One verified story.\n\nA [CrewAI](https://docs.crewai.com/) demo that turns a topic into a fact-checked\nnews article. A crew of three agents — a **Researcher**, a **Fact-Checker** and\nan **Editor** — runs in sequence, each receiving the previous agent's output as\ncontext, while a Gradio UI streams live progress and shows every intermediate\nartifact.\n\n```\nTopic → 🔬 Researcher → 🔍 Fact-Checker → ✍️ Editor → Article\n        (web search)     (verifies claims)  (writes prose)\n```\n\n## What makes it a *crew*, not one big prompt\n\n- **Three distinct agents**, each with its own role, goal, backstory,\n  temperature and iteration limit — the fact-checker runs cold (0.1) because it\n  must classify claims conservatively; the editor runs warmer (0.5) because it\n  writes prose.\n- **Chained tasks** via CrewAI's `context` mechanism on a `Process.sequential`\n  pipeline: research → fact-check → editing.\n- **A real web search tool** (DuckDuckGo, no API key needed) available to the\n  Researcher and Fact-Checker, so the article is grounded in current\n  information — and agents are explicitly instructed to mark unverifiable\n  claims `NEEDS_SOURCE` rather than invent citations.\n- **Transparency UI**: watch each stage complete in real time, then read the\n  research brief, the fact-check report, all cited sources and a\n  \"how this story was produced\" breakdown with per-stage timing and token\n  usage.\n\n## Quick start\n\n```bash\npython3.12 -m venv .venv\nsource .venv/bin/activate\npip install -r requirements.txt\n\ncp env-example .env\n# edit .env and paste your OpenAI API key (https://platform.openai.com/api-keys)\n\npython app.py\n```\n\nThen open http://127.0.0.1:7860, type a topic, pick a style and length, and\npress **Generate Story**.\n\n## Configuration\n\nAll config lives in `.env` (see `.env.example`) and `config.py`:\n\n| Variable | Default | Purpose |\n|---|---|---|\n| `OPENAI_API_KEY` | — | Required. OpenAI API key |\n| `NEWSROOM_TIMEOUT_SECONDS` | `900` | Hard limit for one full pipeline run |\n| `NEWSROOM_SEARCH_MAX_RESULTS` | `6` | Results per web search |\n| `NEWSROOM_PORT` / `NEWSROOM_HOST` | `7860` / `127.0.0.1` | Gradio bind address |\n| `NEWSROOM_OPEN_BROWSER` | `1` | Open a browser tab on launch |\n\nThe model is `gpt-4o-mini` served by OpenAI (set `OPENAI_MODEL_ID` in\n`config.py` to change it).\n\n## Project layout\n\n```\napp.py              Gradio UI: streams progress, fills output tabs\ncrew.py             Crew assembly, pipeline runner, Progress tracker\nagents.py           The three agents (role, goal, backstory, LLM settings)\ntasks.py            The three tasks and their context chaining\ntools.py            web_search tool (DuckDuckGo via ddgs, no API key)\nconfig.py           Settings, model IDs, temperatures, styles, lengths\ncompat.py           Compat shim for a CrewAI↔LiteLLM request-schema issue\nutils/formatting.py Progress panel, source extraction, process rendering\n```\n\n## Notes on the compat shim\n\nRecent CrewAI versions tag outgoing messages with a prompt-caching marker\n(`cache_breakpoint`) that providers with strict request schemas (the original\ntrigger was Groq) reject as an unrecognized field. `compat.py` neutralizes that\nmarker before any agent is constructed — it only disables a caching\noptimization that never worked through LiteLLM routing in the first place;\nmodel behaviour is unchanged.\n\n## Troubleshooting\n\n- **401 / invalid API key** — check `OPENAI_API_KEY` in `.env`, restart the app.\n- **429 rate limit** — wait a minute, or generate a shorter article.\n- **\"No sources were cited\"** — the search tool likely couldn't reach the\n  network during the run; check connectivity and regenerate.\n","readmeExcerpt":"AI Newsroom Three AI journalists. 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