{"data":{"slug":"neural-maze-ava-whatsapp-agent-course","name":"ava-whatsapp-agent-course","tagline":"Meet Ava, the WhatsApp Agent","github_url":"https://github.com/neural-maze/ava-whatsapp-agent-course","owner":"neural-maze","repo":"ava-whatsapp-agent-course","owner_avatar_url":"https://avatars.githubusercontent.com/u/151655127?v=4","primary_language":"Python","stars":1672,"forks":419,"topics":["agent","agent-based","agentic-workflow","agents","stt","tts","vector-database"],"archived":false,"github_pushed_at":"2025-10-20T19:12:20+00:00","maintenance_label":"Slowing","stars_delta_30d":8,"url":"https://www.graphcanon.com/tools/neural-maze-ava-whatsapp-agent-course","markdown_url":"https://www.graphcanon.com/tools/neural-maze-ava-whatsapp-agent-course.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/neural-maze-ava-whatsapp-agent-course","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=neural-maze-ava-whatsapp-agent-course","description":"Meet Ava, the WhatsApp Agent","homepage_url":null,"license":"MIT","open_issues":7,"watchers":23,"ai_summary":"A repository for creating an AI agent named Ava designed to interact via WhatsApp, leveraging speech-to-text (STT) and text-to-speech (TTS) technologies.","readme_excerpt":"## Getting started\n\nBefore you begin the course, there are a few things you need to do. \n\nI'm referring to the virtual environment creation, dependencies installation, `.env` file creation, etc. I know, it's very boring, but it's a necessary evil! 😅\n\nAll of this is detailed in the following doc: [GETTING STARTED.md](docs/GETTING_STARTED.md).\n\n> Make sure you follow the instructions in the doc, as it's crucial for the course to work.\n\n---\n\n## How much is this going to cost me?\n\nThe awesome thing about this project is **you can run it on your own computer for free!**\n\nThe **free tiers** from Groq, ElevenLabs, Qdrant Cloud, and Together AI are more than enough to get you going.\n\nIf you want to try it out on Google Cloud Run, you can get a free account and get $300 in free credits. Even if you've already used up your free credits, Cloud Run is super cheap - so it will take just a buck or two for your experiments.\n\n---\n\n---\n\n## License\n\nThis project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.\n\n---\n\n\n \n \n \n \n
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","github_created_at":"2024-12-17T09:25:28+00:00","created_at":"2026-07-07T17:44:26.329325+00:00","updated_at":"2026-08-21T12:01:22.788957+00:00","categories":[{"slug":"ai-agents","name":"AI Agents","url":"https://www.graphcanon.com/categories/ai-agents","markdown_url":"https://www.graphcanon.com/categories/ai-agents.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/ai-agents"},{"slug":"speech-audio","name":"Speech & Audio","url":"https://www.graphcanon.com/categories/speech-audio","markdown_url":"https://www.graphcanon.com/categories/speech-audio.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/speech-audio"}],"tags":[{"slug":"agent-based","name":"agent-based"},{"slug":"agentic-workflow","name":"agentic-workflow"},{"slug":"agents","name":"agents"},{"slug":"stt","name":"stt"},{"slug":"tts","name":"tts"},{"slug":"vector-database","name":"vector-database"}],"trust":{"provenance":{"is_fork":false,"github_id":904639064,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-21T12:01:21.427Z","maintenance":{"label":"Slowing","score":36,"methodology":"github_public_v1","releases_90d":0,"days_since_push":304,"last_release_at":null,"stars_delta_30d":8,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:25:47.439Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-21T12:01:22.374Z"},"deploy":{"source":"dockerfile:Dockerfile","self_host":true,"observed_at":"2026-08-21T12:01:22.374Z","managed_saas":false},"languages":{"value":["python"],"source":"github.language+pyproject.toml","observed_at":"2026-08-21T12:01:22.374Z"},"has_docker":{"value":true,"source":"dockerfile:Dockerfile","observed_at":"2026-08-21T12:01:22.374Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-08-21T12:01:22.374Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When you need a specialized agent for WhatsApp interactions","For projects requiring integration of both STT and TTS technologies"],"when_not_to_use":["If your workflow primarily uses platforms other than WhatsApp","Projects that do not require speech-to-text or text-to-speech capabilities"],"source":"enrich:decision_facts","observed_at":"2026-07-12T16:09:38.645Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Ava is a Python toolkit for developing WhatsApp AI agents with robust speech-to-text and text-to-speech capabilities suited for conversational workflows."}]}}