New secretchat-api-example.py examples for all models

api-openwebui/secretchat-api-example.py

@@ -0,0 +1,154 @@
+#!/usr/bin/env python3
+
+"""
+secretchat-api-example.py
+
+• Prints model IDs at start
+• Shows which model handles each sentence, 5 sentences
+
+Requires:
+  pip install requests python-dotenv
+"""
+
+import os
+import random
+import time
+from typing import List, Union, Tuple, Optional
+
+import requests
+from dotenv import load_dotenv
+
+
+# ── API-key helper ───────────────────────────────────────────────────────────
+def load_api_key() -> str:
+    load_dotenv(os.path.join(os.path.expanduser("~"), ".secretlab.env"))
+    key = os.getenv("SECRETLAB_API_KEY")
+    if not key:
+        raise ValueError("SECRETLAB_API_KEY not found")
+    return key
+
+
+# ── /api/models helper ───────────────────────────────────────────────────────
+def fetch_model_ids(api_key: str, base_url: str) -> List[str]:
+    resp = requests.get(
+        f"{base_url}/api/models",
+        headers={"Authorization": f"Bearer {api_key}"},
+        timeout=300,
+    )
+    resp.raise_for_status()
+    raw: Union[list, dict] = resp.json()
+
+    if isinstance(raw, dict):  # unwrap {"models":[...]} or similar
+        for key in ("models", "data", "items", "result"):
+            if key in raw and isinstance(raw[key], list):
+                raw = raw[key]
+                break
+
+    if not isinstance(raw, list):
+        raise RuntimeError("Unexpected /api/models response")
+
+    ids: List[str] = []
+    for item in raw:
+        if isinstance(item, str):
+            ids.append(item)
+        elif isinstance(item, dict):
+            if isinstance(item.get("model"), str):
+                ids.append(item["model"])
+            elif isinstance(item.get("ollama"), dict) and isinstance(
+                item["ollama"].get("model"), str
+            ):
+                ids.append(item["ollama"]["model"])
+    if not ids:
+        raise RuntimeError("No model IDs found")
+    return ids
+
+
+# ── classify helper ──────────────────────────────────────────────────────────
+def classify(
+    sentence: str,
+    api_key: str,
+    base_url: str,
+    models: List[str],
+    retries: int = 6,
+    backoff: int = 2,
+) -> Tuple[str, Optional[str]]:
+    """Return (model_used, classification or None)."""
+    url = f"{base_url}/api/chat/completions"
+
+    for attempt in range(1, retries + 1):
+        model = random.choice(models)
+        payload = {
+            "model": model,
+            "messages": [
+                {
+                    "role": "system",
+                    "content": (
+                        "Respond ONLY with 'Positive' or 'Negative'. "
+                        "No other words or punctuation."
+                    ),
+                },
+                {"role": "user", "content": f"Classify this:\n{sentence}"},
+            ],
+            "temperature": 0.0,
+        }
+
+        try:
+            r = requests.post(
+                url,
+                headers={
+                    "Authorization": f"Bearer {api_key}",
+                    "Content-Type": "application/json",
+                },
+                json=payload,
+                timeout=300,
+            )
+            if r.status_code == 200:
+                result = r.json()["choices"][0]["message"]["content"].strip()
+                return model, result
+            print(f"API error {r.status_code}: {r.text}")
+            return model, None
+        except requests.exceptions.RequestException as e:
+            print(f"Network error ({attempt}/{retries}): {e}")
+            if attempt < retries:
+                time.sleep(backoff)
+                backoff *= 2
+            else:
+                return model, None
+
+
+# ── main loop ────────────────────────────────────────────────────────────────
+def main() -> None:
+    api_key = load_api_key()
+    BASE = "https://chat.secretlab.page"
+    models = fetch_model_ids(api_key, BASE)
+
+    print("Models:")
+    for m in models:
+        print(m)
+    print("-" * 40, "\n")
+
+    sentences = [
+        "I love sunny days!",
+        "This is a bland sandwich.",
+        "I really hate waiting in long lines.",
+        "The meeting was okay, nothing special.",
+        "I am so excited about the upcoming holidays!",
+    ]
+
+    for run in range(1):  # repeat 1 times
+        print(f"\n--- Run {run+1} ---\n")
+
+        for idx, s in enumerate(sentences, 1):
+            model_used, res = classify(s, api_key, BASE, models)
+
+            print(f"Sentence {idx}: {s}")
+            print(f"Model      : {model_used}")
+            print(f"Result     : {res or 'Failed'}\n")
+
+        time.sleep(1)  # optional pause between runs
+
+    print("\nAll runs complete!\n")
+
+
+if __name__ == "__main__":
+    main()