MQL5-Google-Onedrive/pentagi/example.ollama.provider.yml

# Basic tasks - moderate determinism for general interactions
simple:
  model: "llama3.1:8b-instruct-q8_0"
  temperature: 0.2
  top_p: 0.85
  n: 1
  max_tokens: 4000

# JSON formatting - maximum determinism for structured output
simple_json:
  model: "llama3.1:8b-instruct-q8_0"
  temperature: 0.0
  top_p: 1.0
  n: 1
  max_tokens: 4000

# Orchestrator - balanced: needs reliability + some flexibility in delegation decisions
primary_agent:
  model: "llama3.1:8b-instruct-q8_0"
  temperature: 0.2
  top_p: 0.85
  n: 1
  max_tokens: 4000

# Assistant - user-facing, needs balance between accuracy and natural conversation
assistant:
  model: "llama3.1:8b-instruct-q8_0"
  temperature: 0.25
  top_p: 0.85
  n: 1
  max_tokens: 4000

# Generator - subtask planning requires creativity and diverse approaches
generator:
  model: "llama3.1:8b-instruct-q8_0"
  temperature: 0.4
  top_p: 0.9
  n: 1
  max_tokens: 5000

# Refiner - plan optimization needs both analysis and creative problem-solving
refiner:
  model: "llama3.1:8b-instruct-q8_0"
  temperature: 0.35
  top_p: 0.9
  n: 1
  max_tokens: 4000

# Adviser - strategic consultation requires creative solutions and diverse thinking
adviser:
  model: "llama3.1:8b-instruct-q8_0"
  temperature: 0.35
  top_p: 0.9
  n: 1
  max_tokens: 4000

# Reflector - error analysis requires precision and clear guidance
reflector:
  model: "llama3.1:8b-instruct-q8_0"
  temperature: 0.2
  top_p: 0.85
  n: 1
  max_tokens: 3000

# Searcher - information retrieval needs precision and efficiency
searcher:
  model: "llama3.1:8b-instruct-q8_0"
  temperature: 0.15
  top_p: 0.85
  n: 1
  max_tokens: 4000

# Enricher - context enhancement needs accuracy
enricher:
  model: "llama3.1:8b-instruct-q8_0"
  temperature: 0.15
  top_p: 0.85
  n: 1
  max_tokens: 4000

# Coder - code generation requires maximum precision and determinism
coder:
  model: "llama3.1:8b-instruct-q8_0"
  temperature: 0.1
  top_p: 0.8
  n: 1
  max_tokens: 8000

# Installer - DevOps tasks need high reliability and exact commands
installer:
  model: "llama3.1:8b-instruct-q8_0"
  temperature: 0.1
  top_p: 0.8
  n: 1
  max_tokens: 6000

# Pentester - security testing needs precision but also creative attack vectors
pentester:
  model: "llama3.1:8b-instruct-q8_0"
  temperature: 0.25
  top_p: 0.85
  n: 1
  max_tokens: 8000