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SEO-optimized blog content (JSON)\n\nOutputs are written to `resources/drafts/`.\n\nStructured JSON outputs can be rendered into Markdown files under `resources/rendered/`.\n\n## Tech Stack\n\n- Python 3.13+\n- [CrewAI](https://docs.crewai.com/) with Google GenAI provider\n- CrewAI tools: Serper + website scraping\n- Pydantic models for structured JSON outputs\n- `python-dotenv` for environment variable loading\n\n## Project Structure\n\n```text\n.\n|-- marketing_crew.py              # Main crew definition + kickoff\n|-- render_markdown.py             # Converts generated JSON outputs to Markdown files\n|-- config/\n|   |-- agents.yaml                # Agent roles/goals/backstories\n|   `-- task.yaml                  # Task prompts + expected output formats\n`-- resources/drafts/\n    |-- market_research_report.md\n    |-- marketing_strategy.md\n    |-- content_calendar.md\n    |-- post_drafts.json\n    |-- reel_scripts.json\n    |-- seo_optimized_content.json\n    `-- blogs/\n        |-- blog_content_research.md\n        `-- blog_drafts.json\n\n`-- resources/rendered/\n    |-- post_drafts/\n    |-- reel_scripts/\n    |-- blogs/\n    `-- seo/\n```\n\n## Agents\n\nDefined in `config/agents.yaml`:\n\n- `head_of_marketing`\n- `content_creator_social_media`\n- `content_creator_blog`\n- `seo_specialist`\n\nAll agents currently use `gemini/gemini-3-flash-preview` and run with reasoning enabled.\n\n## Setup\n\n### 1. Install dependencies\n\nUsing `uv` (recommended):\n\n```bash\nuv sync\n```\n\nOr with pip:\n\n```bash\npip install -e .\n```\n\n### 2. Configure environment variables\n\nCreate/update `.env` in the project root:\n\n```env\nGEMINI_API_KEY=your_google_genai_api_key\nSERPER_API_KEY=your_serper_api_key\n```\n\n## Run\n\n```bash\npython marketing_crew.py\n```\n\nThe script uses default input values in `marketing_crew.py` (`product_name`, `product_description`, `target_audience`, `budget`, and current date), then executes tasks sequentially.\n\nTo render JSON outputs into individual Markdown files:\n\n```bash\npython render_markdown.py\n```\n\n## Output Format\n\nSome tasks return structured JSON validated by this schema:\n\n```json\n{\n  \"items\": [\n    {\n      \"content_type\": \"social_media | blog_post | video_script\",\n      \"topic\": \"string\",\n      \"target_audience\": \"string\",\n      \"tags\": [\"tag1\", \"tag2\"],\n      \"content\": \"full content text\"\n    }\n  ]\n}\n```\n\nMarkdown outputs are generated for research and calendar artifacts.\n\n`render_markdown.py` also generates Markdown files from JSON content items (`post_drafts`, `reel_scripts`, `blog_drafts`, and `seo_optimized_content`) into `resources/rendered/<content_group>/`.\n\n## Customize\n\n### Change business inputs\n\nEdit the `inputs` dict in `marketing_crew.py` to switch product, audience, budget, or description.\n\n### Tune prompts\n\n- Agent behavior: `config/agents.yaml`\n- Task behavior and expected outputs: `config/task.yaml`\n\n### Change model/provider\n\nUpdate the `LLM(...)` configuration in `marketing_crew.py`.\n\n## Notes\n\n- Workflow is `Process.sequential` with `planning=False`.\n- Rate limits are configured via `max_rpm` per agent and crew.\n- Draft directories are ensured at runtime (`resources/drafts` and `resources/drafts/blogs`).\n- Rendered output directories are created automatically by `render_markdown.py` (`resources/rendered/...`).\n\n## Next Improvements\n\n- Add CLI args for dynamic runtime inputs instead of hardcoded values.\n- Add task-level unit tests for JSON schema compliance.\n- Add logging/telemetry and retry handling for tool/network failures.\n- Add CI checks for formatting, linting, and type validation.\n","readmeExcerpt":"Social Media AI Agent Multi-agent marketing workflow built with CrewAI to generate market research, strategy, content calendars, social posts, reels, blog drafts, and SEO-optimized content. 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