"Extract_text_generation_utilities_into_modular_structure"

backend/services/llm_providers/textgen_utils/model_utils.py

@@ -0,0 +1,77 @@
+"""
+Model Utilities Module
+
+This module contains model-related utility functions extracted from main_text_generation.py
+to resolve merge conflicts and improve maintainability.
+"""
+
+import os
+from typing import Optional, List
+
+from ..routing_policy import PREMIUM_DEFAULT_MODEL
+
+
+def _map_logical_model_to_provider_model(provider: str, model_name: str) -> str:
+    """Map logical model aliases/full names to provider-specific model IDs."""
+    raw = (model_name or "").strip()
+    if not raw:
+        return raw
+
+    # Full provider path supplied explicitly; use as-is.
+    if "/" in raw:
+        return raw
+
+    key = raw.lower()
+
+    hf_map = {
+        "gpt-oss": "openai/gpt-oss-120b:cerebras",
+        "gpt-oss-120b": "openai/gpt-oss-120b:cerebras",
+        "gpt-oss-20b": "openai/gpt-oss-20b:cerebras",
+        "mistral": "mistralai/Mistral-7B-Instruct-v0.3:cerebras",
+        "mistral-7b": "mistralai/Mistral-7B-Instruct-v0.3:cerebras",
+        "llama": "meta-llama/Llama-3.1-8B-Instruct:groq",
+        "llama-8b": "meta-llama/Llama-3.1-8B-Instruct:groq",
+        "llama-70b": "meta-llama/Llama-3.1-70B-Instruct:groq",
+    }
+
+    wavespeed_map = {
+        "gpt-oss": "openai/gpt-oss-120b",
+        "gpt-oss-120b": "openai/gpt-oss-120b",
+        "gpt-oss-20b": "openai/gpt-oss-20b",
+        "mistral": "mistralai/Mistral-7B-Instruct-v0.3",
+        "mistral-7b": "mistralai/Mistral-7B-Instruct-v0.3",
+        "llama": "meta-llama/Llama-3.1-8B-Instruct",
+        "llama-8b": "meta-llama/Llama-3.1-8B-Instruct",
+        "llama-70b": "meta-llama/Llama-3.1-70B-Instruct",
+    }
+
+    if provider in {"huggingface", "hf", "hf_response_api"}:
+        return hf_map.get(key, raw)
+    if provider == "wavespeed":
+        return wavespeed_map.get(key, raw)
+
+    return raw
+
+
+def _resolve_model_sequence(provider: str, preferred_hf_models: Optional[List[str]] = None) -> List[str]:
+    """Resolve model sequence for a given provider."""
+    models_env = _parse_csv_env(os.getenv("TEXTGEN_AI_MODELS", ""))
+
+    if provider == "google":
+        return ["gemini-2.0-flash-001"]
+
+    if preferred_hf_models:
+        return [_map_logical_model_to_provider_model(provider, m) for m in preferred_hf_models if m]
+
+    if not models_env:
+        return [PREMIUM_DEFAULT_MODEL]
+
+    resolved = [_map_logical_model_to_provider_model(provider, m) for m in models_env if m.strip()]
+    return resolved or [PREMIUM_DEFAULT_MODEL]
+
+
+def _parse_csv_env(value: Optional[str]) -> List[str]:
+    """Parse CSV environment variable into list of values."""
+    if not value:
+        return []
+    return [v.strip() for v in str(value).split(",") if v.strip()]