2e8c2c11d0
Vocabulary study with FSRS spaced repetition, AI tutoring (Ollama/Claude), essay marking, idioms browser, Anki export, and dashboard. 918 vocabulary entries across 39 categories. 41 tests passing. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
45 lines
1.3 KiB
Python
45 lines
1.3 KiB
Python
"""Dual AI backend: Ollama (fast/local) and Claude CLI (smart)."""
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import subprocess
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import ollama
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DEFAULT_OLLAMA_MODEL = "qwen2.5:7b"
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def ask_ollama(prompt, system=None, model=DEFAULT_OLLAMA_MODEL):
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"""Query Ollama with an optional system prompt."""
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messages = []
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if system:
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messages.append({"role": "system", "content": system})
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messages.append({"role": "user", "content": prompt})
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response = ollama.chat(model=model, messages=messages)
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return response.message.content
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def ask_claude(prompt):
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"""Query Claude via the CLI subprocess."""
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result = subprocess.run(
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["claude", "-p", prompt],
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capture_output=True,
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text=True,
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)
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return result.stdout.strip()
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def ask(prompt, system=None, quality="fast"):
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"""Unified interface. quality='fast' uses Ollama, 'smart' uses Claude."""
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if quality == "smart":
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return ask_claude(prompt)
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return ask_ollama(prompt, system=system)
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def chat_ollama(messages, system=None, model=DEFAULT_OLLAMA_MODEL):
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"""Multi-turn conversation with Ollama."""
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all_messages = []
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if system:
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all_messages.append({"role": "system", "content": system})
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all_messages.extend(messages)
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response = ollama.chat(model=model, messages=all_messages)
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return response.message.content
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