π Add AutoExec AI full application files for Hugging Face Space
Browse files
Dockerfile
CHANGED
@@ -7,6 +7,7 @@ RUN apt-get update && apt-get install -y redis-server && pip install --no-cache-
|
|
7 |
|
8 |
COPY . .
|
9 |
|
10 |
-
|
|
|
11 |
|
12 |
-
|
|
|
7 |
|
8 |
COPY . .
|
9 |
|
10 |
+
COPY start.sh /start.sh
|
11 |
+
RUN chmod +x /start.sh
|
12 |
|
13 |
+
ENTRYPOINT ["/start.sh"]
|
README.md
CHANGED
@@ -1,34 +1,74 @@
|
|
1 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2 |
|
3 |
-
|
4 |
|
5 |
-
|
6 |
|
7 |
-
|
8 |
-
- Streamlit UI
|
9 |
-
- FastAPI backend
|
10 |
-
- Celery worker (auto-task scheduling)
|
11 |
-
- Redis server
|
12 |
-
- SQLite memory DB
|
13 |
-
- LangGraph JSON config
|
14 |
-
- Dashboard for agent logs
|
15 |
|
16 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
17 |
|
18 |
```bash
|
19 |
-
uvicorn app.main:app --reload
|
20 |
-
|
21 |
-
|
22 |
```
|
23 |
|
24 |
-
|
25 |
|
26 |
-
|
27 |
|
28 |
-
|
29 |
-
|
30 |
-
|
31 |
-
|
32 |
-
|
|
|
|
|
|
|
33 |
|
34 |
-
Streamlit runs on port 7861. FastAPI on port 7860.
|
|
|
1 |
+
---
|
2 |
+
title: AutoExec AI
|
3 |
+
emoji: π
|
4 |
+
colorFrom: purple
|
5 |
+
colorTo: indigo
|
6 |
+
sdk: docker
|
7 |
+
app_file: app.py
|
8 |
+
pinned: true
|
9 |
+
---
|
10 |
|
11 |
+
# π AutoExec AI: Your Autonomous AI Business Builder
|
12 |
|
13 |
+
[](https://huggingface.co/spaces/mgbam/AICEO)
|
14 |
|
15 |
+
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
16 |
|
17 |
+
AutoExec AI is a fully autonomous AI-powered startup generator that builds, optimizes, and scales digital businesses for you using:
|
18 |
+
|
19 |
+
- π€ **LLMs** (Gemini Pro + GPT-4 fallback)
|
20 |
+
- π **LangGraph-style multi-agent coordination**
|
21 |
+
- π **Auto-optimization loops** (LoopAgent)
|
22 |
+
- π§ **Persistent agent memory** using SQLite
|
23 |
+
- βοΈ **FastAPI + Celery + Redis** for orchestration
|
24 |
+
- π₯οΈ **Streamlit UI** for interactive control panel
|
25 |
+
|
26 |
+
---
|
27 |
+
|
28 |
+
## π― Key Features
|
29 |
+
|
30 |
+
β
AI-driven product ideation by niche
|
31 |
+
β
Copy generation: product descriptions, landing pages, emails
|
32 |
+
β
Ad campaign builder with budget constraints
|
33 |
+
β
LoopAgent: re-optimizes your strategy daily
|
34 |
+
β
Scales to manage multiple businesses in parallel
|
35 |
+
β
Includes a dashboard to inspect every agent run
|
36 |
+
β
Full Docker deployment on Hugging Face Spaces
|
37 |
+
|
38 |
+
---
|
39 |
+
|
40 |
+
## π§ Tech Stack
|
41 |
+
|
42 |
+
| Layer | Tech |
|
43 |
+
|--------------|----------------------------------------|
|
44 |
+
| UI | `Streamlit` |
|
45 |
+
| Backend API | `FastAPI` |
|
46 |
+
| Scheduler | `Celery` + `Redis` |
|
47 |
+
| AI Models | `Gemini Pro`, `GPT-4` fallback (OpenAI) |
|
48 |
+
| Memory | `SQLite` (persistent logging) |
|
49 |
+
| Multi-Agent | `LangGraph-style config` |
|
50 |
+
| Hosting | `Docker` via Hugging Face Spaces |
|
51 |
+
|
52 |
+
---
|
53 |
+
|
54 |
+
## π Quickstart (Dev Mode)
|
55 |
|
56 |
```bash
|
57 |
+
uvicorn app.main:app --reload # Start FastAPI
|
58 |
+
celery -A celery_worker worker # Background optimization
|
59 |
+
streamlit run dashboard.py # View agent memory logs
|
60 |
```
|
61 |
|
62 |
+
---
|
63 |
|
64 |
+
## π Keywords for Discovery
|
65 |
|
66 |
+
`AI startup launcher`, `dropshipping AI`, `auto business generator`, `LangGraph AI`, `FastAPI Streamlit startup`, `Hugging Face Docker Spaces`, `Celery Redis orchestrator`, `GPT-4 product copy`, `autonomous agents`, `AutoExec AI`
|
67 |
+
|
68 |
+
---
|
69 |
+
|
70 |
+
## π€ Contributing
|
71 |
+
|
72 |
+
Feel free to fork, star, and contribute! PRs welcome.
|
73 |
+
For collaborations, reach out via Hugging Face or [LinkedIn](https://www.linkedin.com/in/your-profile).
|
74 |
|
|
git
ADDED
File without changes
|
start.sh
ADDED
@@ -0,0 +1,13 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
#!/bin/bash
|
2 |
+
|
3 |
+
# Start Redis server
|
4 |
+
redis-server &
|
5 |
+
|
6 |
+
# Start FastAPI backend
|
7 |
+
uvicorn app.main:app --host 0.0.0.0 --port 7860 &
|
8 |
+
|
9 |
+
# Start Celery worker
|
10 |
+
celery -A celery_worker worker --loglevel=info &
|
11 |
+
|
12 |
+
# Start Streamlit app
|
13 |
+
streamlit run app.py --server.port 7861
|