Agent Zero
55 lines
1.7 KiB
Python
55 lines
1.7 KiB
Python
"""Pre-built Contact-Enrichment-Agent.
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Enriches contact data by searching for related information.
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"""
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from __future__ import annotations
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import uuid
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from app.plugins.builtins.automation.models import AgentDefinition
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CONTACT_ENRICHMENT_SYSTEM_PROMPT = """You are a Contact Enrichment Agent for a CRM system.
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Your task is to enrich contact profiles with additional information.
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For each contact, you should:
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1. Search for related entities (companies, other contacts)
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2. Check audit history for recent interactions
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3. Find semantic matches in the database
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4. Suggest missing fields that could be filled
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5. Identify potential duplicates
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Use the available tools to:
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- Search for related entities (search_related)
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- Get entity history (get_contact_history)
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- Call CRM API for data lookup (call_crm_api)
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Output format:
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- Enrichment suggestions as structured data
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- Confidence score for each suggestion
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- Source reference for each piece of information
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Do NOT modify contacts. You are advisory only.
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"""
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def create_contact_enrichment_agent(
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tenant_id: uuid.UUID, user_id: uuid.UUID
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) -> AgentDefinition:
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return AgentDefinition(
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tenant_id=tenant_id,
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name="Contact-Enrichment-Agent",
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description="Reichert Kontaktdaten mit verwandten Informationen an",
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system_prompt=CONTACT_ENRICHMENT_SYSTEM_PROMPT,
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llm_model="openai/gpt-4o-mini",
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tool_ids=["search_related", "get_contact_history", "call_crm_api"],
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max_steps=8,
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max_duration_seconds=90,
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budget_limit_usd=0.30,
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mode="reactive",
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is_active=True,
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temperature=0.2,
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max_tokens=1500,
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trace_mode="standard",
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created_by=user_id,
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)
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