feat(transcription): add Supabase schema and API endpoints for CIS

modules/transcription/llm_client.py

@@ -0,0 +1,53 @@
+"""Pluggable LLM client for transcription summaries.
+
+Phase 1: Stub implementation — returns TODO string.
+Phase 3: Wire up Anthropic, OpenAI, and Ollama providers.
+"""
+
+import os
+from typing import Optional
+
+
+async def call_llm(
+    provider: str,
+    model: str,
+    api_key: str,
+    system_prompt: str,
+    user_message: str,
+) -> str:
+    """Call an LLM to generate a summary.
+
+    Phase 1 stub — returns a TODO string.
+    Phase 3 will implement actual provider routing.
+
+    Args:
+        provider: 'anthropic', 'openai', 'ollama', 'openrouter', 'google'
+        model: Model name (e.g. 'claude-sonnet-4-6', 'gpt-4o', 'llama3')
+        api_key: User's API key (from localStorage, passed per-request)
+        system_prompt: System prompt template (already filled with transcript)
+        user_message: User message content
+
+    Returns:
+        LLM-generated summary text
+    """
+    # Phase 1 stub — TODO: implement in Phase 3
+    return f"[TODO: Implement LLM call for provider={provider}, model={model}]"
+
+
+async def call_anthropic(api_key: str, model: str, system_prompt: str, user_message: str) -> str:
+    """Call Anthropic Claude API."""
+    # Phase 3 implementation placeholder
+    return f"[TODO: Anthropic call — model={model}]"
+
+
+async def call_openai(api_key: str, model: str, system_prompt: str, user_message: str) -> str:
+    """Call OpenAI API."""
+    # Phase 3 implementation placeholder
+    return f"[TODO: OpenAI call — model={model}]"
+
+
+async def call_ollama(api_key: str, model: str, system_prompt: str, user_message: str) -> str:
+    """Call local Ollama instance."""
+    # Phase 3 implementation placeholder
+    ollama_url = os.getenv("OLLAMA_URL", "https://ollama.kevlarai.com")
+    return f"[TODO: Ollama call — url={ollama_url}, model={model}]"