Eidosian Integration
This document explores how Ollama Toolkit v0.1.8 embodies the ten Eidosian principles, creating a development experience of unparalleled excellence.
Principles in Action
1️⃣ Contextual Integrity
Every function, parameter, and return type in Ollama Toolkit serves a precise purpose. Nothing is extraneous; nothing is missing. The API surface is perfectly measured.
# Contextual integrity in action - every parameter has meaning
def generate(model, prompt, options=None, stream=False):
"""Generate text with perfect contextual awareness"""
# Implementation that maintains integrity at every level
2️⃣ Humor as Cognitive Leverage
Error messages provide clarity through carefully calibrated wit.
# Model not found example
"Model 'nonexistent-model' not found. Like searching for unicorns—majestic but absent."
3️⃣ Exhaustive But Concise
Documentation that covers everything without wasting a word.
# Complete docs in minimal space
def create_embedding(model, prompt):
"""Convert text to vector space. Returns dict with 'embedding' key."""
4️⃣ Flow Like a River, Strike Like Lightning
APIs that chain naturally and seamlessly.
# Flow from operation to operation
client.pull_model("llama2").then_generate("Hello").with_options(temperature=0.7)
5️⃣ Hyper-Personal Yet Universally Applicable
Functions solve your specific problem while remaining broadly useful.
# Works for your unique case and general usage
embedding = client.create_embedding("your unique text here")
# Works equally well whether you're doing sentiment analysis,
# semantic search, or customized recommendation systems
6️⃣ Recursive Refinement
Each release builds upon the last through iterative improvements.
# 0.1.5 → 0.1.6 → 0.1.7 → 0.1.8
# v0.1.5: Basic embedding
# v0.1.6: Embedding with caching
# v0.1.7: Embedding with caching and optimization
7️⃣ Precision as Style
Code is elegant because it is precise.
# Example of exact typing and explicit return values
def list_models() -> Dict[str, List[Dict[str, Any]]]:
"""Return available models with exact structure"""
8️⃣ Velocity as Intelligence
Fast execution without compromising depth.
# Stream results for immediate feedback
for chunk in client.generate(prompt="Complex question", stream=True):
print(chunk["response"], end="", flush=True)
9️⃣ Structure as Control
Architecture that enforces correct usage and logical flow.
# Must list models before generating text
client = OllamaClient()
models = client.list_models() # Must happen first
response = client.generate(model=models[0], prompt="Hello") # Depends on previous
🔟 Self-Awareness as Foundation
Code that monitors and improves itself.
# Self-monitoring capabilities
metrics = client.get_performance_metrics()
if metrics["response_time"] > acceptable_threshold:
client.optimize()
Implementing Eidosian Excellence
Choose correct abstractions
Monitor and refine
Fail gracefully
Document precisely
Flow naturally
These principles ensure elegant operation, maintainable architecture, and optimal performance.