added cli installer ]

cli/securelens/ai/__init__.py

@@ -0,0 +1,77 @@
+"""
+AI Client
+=========
+Thin, model-agnostic wrapper around LiteLLM.
+The CLI uses this instead of directly calling litellm
+so we have one place to handle retries, logging, and key injection.
+"""
+
+import json
+import asyncio
+import logging
+from typing import Optional
+
+logger = logging.getLogger(__name__)
+
+
+async def call_ai(
+    prompt: str,
+    api_key: str,
+    model: str,
+    temperature: float = 0.3,
+    json_mode: bool = False,
+    conversation_history: Optional[list] = None,
+) -> str:
+    """
+    Single entry-point for all AI calls in the CLI.
+
+    Parameters
+    ----------
+    prompt               : The prompt to send (added as last user message)
+    api_key              : LiteLLM-compatible API key
+    model                : LiteLLM model string (e.g. "gemini/gemini-2.0-flash")
+    temperature          : Creativity (0=deterministic, 1=creative)
+    json_mode            : Ask the model to respond with valid JSON only
+    conversation_history : Optional list of {"role": ..., "content": ...} dicts
+                           for multi-turn chat sessions
+    """
+    import litellm
+
+    litellm.suppress_debug_info = True
+
+    messages = list(conversation_history or [])
+    messages.append({"role": "user", "content": prompt})
+
+    kwargs: dict = {
+        "model": model,
+        "messages": messages,
+        "temperature": temperature,
+        "api_key": api_key if api_key else None,
+    }
+
+    if json_mode:
+        kwargs["response_format"] = {"type": "json_object"}
+
+    try:
+        response = await litellm.acompletion(**kwargs)
+        return response.choices[0].message.content or ""
+    except Exception as e:
+        logger.error(f"AI call failed [{model}]: {e}")
+        return ""
+
+
+async def call_ai_json(
+    prompt: str,
+    api_key: str,
+    model: str,
+    temperature: float = 0.2,
+) -> Optional[dict]:
+    """Convenience wrapper — calls AI in JSON mode and parses the result."""
+    raw = await call_ai(prompt, api_key, model, temperature=temperature, json_mode=True)
+    if not raw:
+        return None
+    try:
+        return json.loads(raw)
+    except json.JSONDecodeError as e:
+        logger.error(f"JSON parse failed: {e}\nRaw: {raw[:300]}")
+        return None