72 lines
1.6 KiB
Markdown
72 lines
1.6 KiB
Markdown
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# Quick Start
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## Setup (30 seconds)
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```bash
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pip install anthropic requests watchdog
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export ANTHROPIC_API_KEY="sk-ant-..." # Your Claude API key
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export GLM_API_KEY="..." # Optional: z.ai GLM key
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```
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## Usage
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### Basic Agent
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```python
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from agent import Agent
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# Initialize with Claude
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agent = Agent(provider="claude")
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# Chat (auto-loads SOUL + user context + relevant memory)
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response = agent.chat("What should I work on?", username="alice")
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# Switch to GLM
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agent.switch_model("glm")
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response = agent.chat("Explain SQLite FTS5")
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```
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### Memory Operations
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```python
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# Update personality
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agent.memory.update_soul("## New trait\n- Be concise", append=True)
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# User preferences
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agent.memory.update_user("alice", "## Preference\n- Likes Python")
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# Write memory
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agent.memory.write_memory("Completed task X", daily=True)
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# Search
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results = agent.memory.search("python")
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```
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### Task Tracking
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```python
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# Add task
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task_id = agent.memory.add_task(
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"Implement API endpoint",
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"Details: REST API for user auth"
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)
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# Update
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agent.memory.update_task(task_id, status="in_progress")
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# Get tasks
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pending = agent.memory.get_tasks(status="pending")
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all_tasks = agent.memory.get_tasks()
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```
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## Files Created
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- `llm_interface.py` - Claude/GLM integration
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- `agent.py` - Main agent class
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- `memory_workspace/MEMORY.md` - Instructions for future sessions
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- Task system added to memory_system.py
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## Context Retrieval
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Agent automatically loads:
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1. SOUL.md (personality)
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2. users/{username}.md (user prefs)
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3. Search results (top 3 relevant chunks)
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4. Recent conversation (last 5 messages)
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All indexed in SQLite for fast retrieval.
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