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chore(config): add .env.example and overhaul README, DEPLOY, and RULES documentation

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Introduce a complete `.env.example` covering Telegram, AI provider,
proactive messaging, web search, and vision settings so new users can
bootstrap configuration without reading the source.

Rework README.md with a feature list, project structure, and variable
reference tables; restructure DEPLOY.md with a table of contents,
prerequisites, and env var tables; update RULES.md to declare English
as the interface and documentation language and to document the
`iniciar.sh` entry script. Also add docstrings to schedule and web
search helpers and rename `schedule_data` to `schedule_answers` for
consistency with the other wizard state variables.
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2026-10-26 14:25:47 -03:00
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README.md
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# PsAgentAI - Personal Conversational AI Agent
Personal Conversational AI Agent system via Telegram that behaves as a personal companion, chatting, cooperating and maintaining continuous context with the user.
A Telegram-based conversational AI agent that acts as a personal companion. It maintains long-term memory through user/agent profiles, manages daily routines, supports file uploads/workspace editing, performs web searches, analyzes images, and sends proactive messages based on configured schedules.
## Structure
## Key Features
- **Long-term memory**: User and agent profiles with auto-enrichment from conversations
- **Daily routine management**: Schedule activities, meals, work/study times
- **File workspace**: Create, edit, list and download files via natural language
- **Web search**: Automatic or on-demand search for up-to-date information
- **Vision**: Image analysis with configurable vision models
- **Voice**: Voice message transcription and response
- **Proactive messaging**: Scheduled automatic messages based on daily routine
- **Multi-provider AI**: OpenRouter, StepFun, QwenCloud, and llama.cpp (local)
- **System auto-improvement**: AI-driven suggestions to evolve the agent behavior
## Project Structure
```
app/
├── psagentai_agent.py # Main agent code
├── iniciar.sh # Installation and execution script
├── requirements.txt # Python dependencies
├── .env # Local settings (do not commit)
├── .env.example # Configuration example
├── user_profile.json # User profile
├── agent_profile.json # Agent profile (personality, traits, notes)
├── contexts/ # Conversation history by date
├── psagentai_agent.py # Main agent code (~5000 lines)
├── iniciar.sh # Setup and run script
├── requirements.txt # Python dependencies
├── .env # Local settings (do not commit)
├── user_profile.json # User profile (auto-created)
├── agent_profile.json # Agent profile (auto-created)
├── uploads_metadata.json # Uploaded files metadata (auto-created)
├── config.json # Schedule configuration (auto-created)
├── system_improvements.json # Auto-improvement history (auto-created)
├── contexts/ # Conversation history by date
│ └── YYYY-MM-DD.json
├── workspace/ # Created and edited files
│ └── projects/
├── README.md
├── DEPLOY.md
├── RULES.md
└── LICENSE
```
## Prerequisites
- Python 3.9+
- Telegram account with bot created via @BotFather
- At least one supported AI API key
- Telegram account with a bot created via [@BotFather](https://t.me/BotFather)
- At least one supported AI API key (OpenRouter, StepFun, or QwenCloud)
## Configuration
1. Copy `.env.example` to `.env` and fill in:
- `TELEGRAM_BOT_TOKEN` — Telegram bot token
- `TELEGRAM_CHAT_ID` — your Telegram chat ID
- `OPENROUTER_API_KEY` or other compatible API key
1. Copy `.env` from the example or create it manually:
2. Adjust intervals if desired:
- `MIN_INTERVAL_MINUTES`
- `MAX_INTERVAL_MINUTES`
- `MIN_MESSAGE_LINES` — defines the minimum number of lines per agent message (default: `15`)
```bash
cp .env.example .env # if .env.example exists
nano .env
```
## Installation and execution
2. Required variables:
| Variable | Required | Description |
|---|---|---|
| `TELEGRAM_BOT_TOKEN` | Yes | Token from @BotFather |
| `TELEGRAM_CHAT_ID` | Yes | Your Telegram chat ID |
| `AI_PROVIDER` | Yes | `openrouter`, `stepfun`, `qwencloud` or `llamacpp` |
| `DEFAULT_MODEL` | Yes | Model identifier for the chosen provider |
| `OPENROUTER_API_KEY` | Conditional | Required if using OpenRouter |
| `STEPFUN_API_KEY` | Conditional | Required if using StepFun |
| `QWENCLOUD_API_KEY` | Conditional | Required if using QwenCloud |
3. Optional tuning:
| Variable | Default | Description |
|---|---|---|
| `MIN_INTERVAL_MINUTES` | `3` | Minimum minutes between proactive messages |
| `MAX_INTERVAL_MINUTES` | `30` | Maximum minutes between proactive messages |
| `MIN_MESSAGE_LINES` | `3` | Minimum lines per agent response |
| `MAX_HISTORY_LENGTH` | `50` | Max messages kept in context |
| `UPLOAD_CONTEXT_MAX_CHARS` | `8000` | Max chars from uploads sent to AI (`0` = unlimited) |
| `WEB_SEARCH_ENABLED` | `true` | Enable automatic web search |
| `WEB_SEARCH_MAX_RESULTS` | `5` | Max search results returned |
| `VISION_MODEL` | `meta-llama/llama-4-maverick-17b-128b-instruct` | Model for image analysis |
| `VISION_PROVIDER` | auto | Provider for vision model |
| `AUTO_ENRICH_EVERY` | `2` | Update profiles every N messages (`0` = disabled) |
| `AUTO_IMPROVE_EVERY` | `20` | Run auto-improvement every N messages (`0` = disabled) |
## Installation
```bash
cd app
@@ -45,71 +88,185 @@ chmod +x iniciar.sh
./iniciar.sh
```
The script creates the virtual environment, installs dependencies and starts the agent.
The setup script will:
1. Create a Python virtual environment (`venv/`)
2. Upgrade `pip`
3. Install dependencies from `requirements.txt`
4. Validate `.env` configuration
5. Start the agent
## Features
## Running
- Initial onboarding with questions to build the profile
- Conversation history by day in `contexts/`
- User profile persisted in `user_profile.json`
- Agent profile persisted in `agent_profile.json` (name, personality, traits and notes)
- Proactive messages at configurable random intervals
- Minimum lines per agent message configurable via `.env`
- Support for multiple AI providers:
- OpenRouter
- StepFun
- QwenCloud
- llama.cpp (local)
- Dynamic profile update via natural commands in chat
```bash
# From the app directory:
python3 psagentai_agent.py
## Available commands
# Or use the setup script:
./iniciar.sh
```
- `/start` — starts or restarts the conversation
- `/help` — displays help
- `/profile` — shows user and agent profile summary
- `/agentprofile` — shows only the agent profile
- `/reset` — resets user and agent profiles
- `/clear` — deletes all data (profiles, contexts, chat_id)
- `/onboarding` — restarts onboarding
- `/newconfig` — reconfigures everything from scratch
- `/cancel` — cancels ongoing operation
- `/viewai` — shows current AI provider and model
- `/configai` — interactively configures AI provider and model with button selection
- `/about` — displays system information, version, author and license
- `/viewvision` — shows current vision provider and model
- `/configvision` — interactively configures vision model with button selection
- `/download <name>` — downloads a workspace file by name
## Available Commands
## Editing workspace files
### Core
- `/start` — Starts or restarts the conversation and onboarding if needed
- `/help` — Displays quick command reference
- `/manual` — Full user manual with examples and tips
- `/about` — System information, version, author and license
You can ask to edit existing files in `workspace/` using commands like:
### Profile
- `/profile` — Displays your profile and agent summary
- `/editprofile` — Edit your profile fields interactively
- `/addtouserprofile <text>` — Add information to your profile
- `/agentprofile` — Displays the full agent profile
- `/editagentprofile` — Edit agent profile fields interactively
- `/configagentprofile` — Configure agent profile interactively (name, personality, traits, notes)
- `/addtoagentprofile <text>` — Add a note/characteristic to the agent profile
- `/onboarding` — Re-run your profile onboarding
### AI Configuration
- `/viewai` — Shows current AI provider and model
- `/configai` — Configure AI provider and model interactively with buttons
- `/viewvision` — Shows current vision provider and model
- `/configvision` — Configure vision model interactively with buttons
- `/updatesystem` — Force analysis and application of auto improvements
### Files and Documents
- `/uploadfile` — Instructions for sending files (`.pdf`, `.txt`, `.docx`, `.png`, `.jpg`)
- `/listfiles` — List all uploaded and created files
- `/download <name>` — Download a workspace file by name
You can also send files directly in the chat. The agent will read text-based files and images automatically.
### Workspace Editing
You can ask the agent to create or edit files in `workspace/`:
**Create:**
- `create a python script to calculate fibonacci`
- `develop a web project with html css and js`
- `generate a document about home automation`
**Edit:**
- `edit the file test.txt and add line 4`
- `modify the file hello.py to print hello world`
- `in the file test.txt replace Line 2 with Line 2 edited`
The Agent will locate the file, apply the requested change and save the result.
- `/addtouserprofile <text>` — updates information in your profile
- `/addtoagentprofile <text>` — adds characteristics to the agent profile
### Daily Routine and Schedule
- `/schedule` — Set days and times for automatic messages
- `/viewschedule` — View current schedule
- `/dailyroutine` — Manage your daily routine (wake up, meals, work/study, sleep)
- `/viewdailyroutine` — View current daily routine
- `/addactivity` — Add a new activity to your routine
- `/editactivity` — Edit an existing activity
- `/deleteactivity` — Delete an activity
## Updating profile during conversation
### Management
- `/newconfig` — Reset everything and reconfigure from scratch
- `/reset` — Reset only user and agent profiles
- `/clear` — Remove all data (profiles, contexts, chat_id)
- `/removetopic <topic>` — Remove all content related to a topic from the system
- `/cancel` — Cancel an ongoing operation
### User profile
### Utilities
- `/debug` — Shows system debug information
- `/reload` — Reload .env settings without restarting
- `/timezone` — Shows the server timezone (read-only)
You can update your profile at any time using phrases like:
### Natural Language Profile Updates
During conversation, you can update profiles using phrases:
**User profile:**
- `Include this in my profile: ...`
- `Note in my profile: ...`
- `Add to my profile: ...`
- `Save in my profile: ...`
### Agent profile
Use `/addtoagentprofile <text>` to add characteristics to the agent profile.
Or use phrases like:
**Agent profile:**
- `Include this in the agent profile: ...`
- `Note in the agent profile: ...`
## How It Works
1. **Onboarding**: When you first start, the agent asks questions to build your profile (name, age, gender, location, interests, personality, etc.)
2. **Context**: Every message is saved to a daily context file (`contexts/YYYY-MM-DD.json`)
3. **Profiles**: User and agent profiles are persisted as JSON and enriched automatically based on conversations
4. **AI Calls**: The agent uses the configured provider/model to generate responses with full context
5. **Proactive Messages**: Based on your schedule and routine, the agent may initiate conversations
6. **Web Search**: When enabled, the agent searches the web for questions requiring current information
7. **Vision**: Images are analyzed using the configured vision model
8. **Auto-improvement**: The system periodically analyzes conversations and suggests improvements
## File Upload and Analysis
Supported formats:
- **Documents**: `.pdf`, `.txt`, `.docx`
- **Images**: `.png`, `.jpg`, `.jpeg`
When you upload a file:
1. It's saved to `workspace/` or `uploads/`
2. Text is extracted and stored in `uploads_metadata.json`
3. Images are analyzed automatically
4. You can ask questions about the file content
## Workspace Editing
The agent can create and edit files in `workspace/` using AI. Files are organized in subdirectories based on the request type.
To edit an existing file:
- Use `/listfiles` to see available files
- Use `/download <name>` to download a file
- Ask the agent to edit by name or partial name
## Conversation Context
- Contexts are stored in `contexts/YYYY-MM-DD.json`
- Old messages are automatically cleaned when limits are exceeded
- The agent references recent context to maintain coherent conversations
## Scheduling
The agent sends proactive messages only within the configured schedule:
- Configure days of the week and time range with `/schedule`
- Messages are sent at random intervals within the configured window
- The agent always uses server time
## Security Notes
- Never commit `.env` to version control
- Restrict `.env` permissions: `chmod 600 .env`
- Sensitive data (emails, phones) is preserved but not exposed in logs
- File paths are validated to prevent traversal attacks
## Backups
Regularly back up these files:
- `user_profile.json`
- `agent_profile.json`
- `system_improvements.json`
- `uploads_metadata.json`
- `config.json`
- `contexts/` folder
- `workspace/` folder
Example backup:
```bash
tar czf /root/backups/psagentai-$(date +%F).tar.gz -C /opt/psagentai/app user_profile.json agent_profile.json system_improvements.json uploads_metadata.json config.json contexts workspace
```
## Troubleshooting
- **Bot not responding**: Ensure `/start` has been sent once in the Telegram chat
- **AI errors**: Check API keys and provider configuration with `/viewai`
- **Voice not working**: Ensure `ffmpeg` is installed
- **Image analysis not working**: Check vision configuration with `/viewvision`
## Development
See `RULES.md` for development standards, code conventions, and contribution guidelines.
## License
Proprietary use. See the `LICENSE` file.
Proprietary for Syspanel.com.br. See `LICENSE` file.