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Make SIF fail fast and add low-cost remote LLM fallback

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2026-03-09 15:38:03 +05:30
parent 1565551765
commit 8b0547cdb5
7 changed files with 219 additions and 67 deletions
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28
backend/services/llm_providers/main_text_generation.py
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@@ -6,7 +6,7 @@ migrated from the legacy lib/gpt_providers/text_generation/main_text_generation.
import os
import json
from typing import Optional, Dict, Any
from typing import Optional, Dict, Any, List
from datetime import datetime
from loguru import logger
from fastapi import HTTPException
@@ -16,7 +16,13 @@ from .gemini_provider import gemini_text_response, gemini_structured_json_respon
from .huggingface_provider import huggingface_text_response, huggingface_structured_json_response
def llm_text_gen(prompt: str, system_prompt: Optional[str] = None, json_struct: Optional[Dict[str, Any]] = None, user_id: str = None) -> str:
def llm_text_gen(
prompt: str,
system_prompt: Optional[str] = None,
json_struct: Optional[Dict[str, Any]] = None,
user_id: str = None,
preferred_hf_models: Optional[List[str]] = None,
) -> str:
"""
Generate text using Language Model (LLM) based on the provided prompt.
@@ -54,7 +60,7 @@ def llm_text_gen(prompt: str, system_prompt: Optional[str] = None, json_struct:
model = "gemini-2.0-flash-001"
elif env_provider in ['hf_response_api', 'huggingface', 'hf']:
gpt_provider = "huggingface"
model = "mistralai/Mistral-7B-Instruct-v0.3"
model = "mistralai/Mistral-7B-Instruct-v0.3:groq"
# Default blog characteristics
blog_tone = "Professional"
@@ -80,7 +86,7 @@ def llm_text_gen(prompt: str, system_prompt: Optional[str] = None, json_struct:
model = "gemini-2.0-flash-001"
elif "huggingface" in available_providers:
gpt_provider = "huggingface"
model = "mistralai/Mistral-7B-Instruct-v0.3"
model = "mistralai/Mistral-7B-Instruct-v0.3:groq"
else:
logger.error("[llm_text_gen] No API keys found for supported providers.")
raise RuntimeError("No LLM API keys configured. Configure GEMINI_API_KEY or HF_TOKEN to enable AI responses.")
@@ -93,9 +99,13 @@ def llm_text_gen(prompt: str, system_prompt: Optional[str] = None, json_struct:
model = "gemini-2.0-flash-001"
elif "huggingface" in available_providers:
gpt_provider = "huggingface"
model = "mistralai/Mistral-7B-Instruct-v0.3"
model = "mistralai/Mistral-7B-Instruct-v0.3:groq"
else:
raise RuntimeError("No supported providers available.")
if gpt_provider == "huggingface" and preferred_hf_models:
model = preferred_hf_models[0]
logger.info(f"[llm_text_gen] Using preferred low-cost HF model: {model}")
logger.debug(f"[llm_text_gen] Using provider: {gpt_provider}, model: {model}")
@@ -303,7 +313,7 @@ def llm_text_gen(prompt: str, system_prompt: Optional[str] = None, json_struct:
elif fallback_provider == "huggingface":
provider_enum = APIProvider.MISTRAL
actual_provider_name = "huggingface"
fallback_model = "mistralai/Mistral-7B-Instruct-v0.3"
fallback_model = "mistralai/Mistral-7B-Instruct-v0.3:groq"
if fallback_provider == "google":
if json_struct:
@@ -330,7 +340,7 @@ def llm_text_gen(prompt: str, system_prompt: Optional[str] = None, json_struct:
response_text = huggingface_structured_json_response(
prompt=prompt,
schema=json_struct,
model="mistralai/Mistral-7B-Instruct-v0.3",
model="mistralai/Mistral-7B-Instruct-v0.3:groq",
temperature=temperature,
max_tokens=max_tokens,
system_prompt=system_instructions
@@ -338,7 +348,7 @@ def llm_text_gen(prompt: str, system_prompt: Optional[str] = None, json_struct:
else:
response_text = huggingface_text_response(
prompt=prompt,
model="mistralai/Mistral-7B-Instruct-v0.3",
model="mistralai/Mistral-7B-Instruct-v0.3:groq",
temperature=temperature,
max_tokens=max_tokens,
top_p=top_p,
@@ -394,4 +404,4 @@ def get_api_key(gpt_provider: str) -> Optional[str]:
return api_key_manager.get_api_key(mapped_provider)
except Exception as e:
logger.error(f"[get_api_key] Error getting API key for {gpt_provider}: {str(e)}")
return None
return None