ALwrity Version 0.5.0 (Fastapi + React )
This commit is contained in:
ajaysi
234
backend/llm_providers/main_text_generation.py
Normal file
234
backend/llm_providers/main_text_generation.py
Normal file
@@ -0,0 +1,234 @@
|
||||
"""Main Text Generation Service for ALwrity Backend.
|
||||
|
||||
This service provides the main LLM text generation functionality,
|
||||
migrated from the legacy lib/gpt_providers/text_generation/main_text_generation.py
|
||||
"""
|
||||
|
||||
import os
|
||||
import json
|
||||
from typing import Optional, Dict, Any
|
||||
from loguru import logger
|
||||
from services.api_key_manager import APIKeyManager
|
||||
|
||||
from .openai_provider import openai_chatgpt
|
||||
from .gemini_provider import gemini_text_response, gemini_structured_json_response
|
||||
from .anthropic_provider import anthropic_text_response
|
||||
from .deepseek_provider import deepseek_text_response
|
||||
|
||||
def llm_text_gen(prompt: str, system_prompt: Optional[str] = None, json_struct: Optional[Dict[str, Any]] = None) -> str:
|
||||
"""
|
||||
Generate text using Language Model (LLM) based on the provided prompt.
|
||||
|
||||
Args:
|
||||
prompt (str): The prompt to generate text from.
|
||||
system_prompt (str, optional): Custom system prompt to use instead of the default one.
|
||||
json_struct (dict, optional): JSON schema structure for structured responses.
|
||||
|
||||
Returns:
|
||||
str: Generated text based on the prompt.
|
||||
"""
|
||||
try:
|
||||
logger.info("[llm_text_gen] Starting text generation")
|
||||
logger.debug(f"[llm_text_gen] Prompt length: {len(prompt)} characters")
|
||||
|
||||
# Initialize API key manager
|
||||
api_key_manager = APIKeyManager()
|
||||
|
||||
# Set default values for LLM parameters
|
||||
gpt_provider = "google" # Default to Google Gemini
|
||||
model = "models/gemini-2.0-flash"
|
||||
temperature = 0.7
|
||||
max_tokens = 4000
|
||||
top_p = 0.9
|
||||
n = 1
|
||||
fp = 16
|
||||
frequency_penalty = 0.0
|
||||
presence_penalty = 0.0
|
||||
|
||||
# Default blog characteristics
|
||||
blog_tone = "Professional"
|
||||
blog_demographic = "Professional"
|
||||
blog_type = "Informational"
|
||||
blog_language = "English"
|
||||
blog_output_format = "markdown"
|
||||
blog_length = 2000
|
||||
|
||||
# Try to get provider from environment or config
|
||||
try:
|
||||
# Check which providers have API keys available
|
||||
available_providers = []
|
||||
if api_key_manager.get_api_key("openai"):
|
||||
available_providers.append("openai")
|
||||
if api_key_manager.get_api_key("gemini"):
|
||||
available_providers.append("google")
|
||||
if api_key_manager.get_api_key("anthropic"):
|
||||
available_providers.append("anthropic")
|
||||
if api_key_manager.get_api_key("deepseek"):
|
||||
available_providers.append("deepseek")
|
||||
|
||||
# Prefer Google Gemini if available, otherwise use first available
|
||||
if "google" in available_providers:
|
||||
gpt_provider = "google"
|
||||
model = "models/gemini-2.0-flash"
|
||||
elif available_providers:
|
||||
gpt_provider = available_providers[0]
|
||||
if gpt_provider == "openai":
|
||||
model = "gpt-4o"
|
||||
elif gpt_provider == "anthropic":
|
||||
model = "claude-3-5-sonnet-20241022"
|
||||
elif gpt_provider == "deepseek":
|
||||
model = "deepseek-chat"
|
||||
else:
|
||||
logger.warning("[llm_text_gen] No API keys found, using mock response")
|
||||
return _get_mock_response(prompt)
|
||||
|
||||
logger.debug(f"[llm_text_gen] Using provider: {gpt_provider}, model: {model}")
|
||||
|
||||
except Exception as err:
|
||||
logger.warning(f"[llm_text_gen] Error determining provider, using defaults: {err}")
|
||||
gpt_provider = "google"
|
||||
model = "models/gemini-2.0-flash"
|
||||
|
||||
# Construct the system prompt if not provided
|
||||
if system_prompt is None:
|
||||
system_instructions = f"""You are a highly skilled content writer with a knack for creating engaging and informative content.
|
||||
Your expertise spans various writing styles and formats.
|
||||
|
||||
Writing Style Guidelines:
|
||||
- Tone: {blog_tone}
|
||||
- Target Audience: {blog_demographic}
|
||||
- Content Type: {blog_type}
|
||||
- Language: {blog_language}
|
||||
- Output Format: {blog_output_format}
|
||||
- Target Length: {blog_length} words
|
||||
|
||||
Please provide responses that are:
|
||||
- Well-structured and easy to read
|
||||
- Engaging and informative
|
||||
- Tailored to the specified tone and audience
|
||||
- Professional yet accessible
|
||||
- Optimized for the target content type
|
||||
"""
|
||||
else:
|
||||
system_instructions = system_prompt
|
||||
|
||||
# Generate response based on provider
|
||||
if gpt_provider == "openai":
|
||||
return openai_chatgpt(
|
||||
prompt=prompt,
|
||||
model=model,
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
top_p=top_p,
|
||||
n=n,
|
||||
fp=fp,
|
||||
system_prompt=system_instructions
|
||||
)
|
||||
elif gpt_provider == "google":
|
||||
if json_struct:
|
||||
return gemini_structured_json_response(
|
||||
prompt=prompt,
|
||||
schema=json_struct,
|
||||
temperature=temperature,
|
||||
top_p=top_p,
|
||||
top_k=n,
|
||||
max_tokens=max_tokens,
|
||||
system_prompt=system_instructions
|
||||
)
|
||||
else:
|
||||
return gemini_text_response(
|
||||
prompt=prompt,
|
||||
temperature=temperature,
|
||||
top_p=top_p,
|
||||
n=n,
|
||||
max_tokens=max_tokens,
|
||||
system_prompt=system_instructions
|
||||
)
|
||||
elif gpt_provider == "anthropic":
|
||||
return anthropic_text_response(
|
||||
prompt=prompt,
|
||||
model=model,
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
system_prompt=system_instructions
|
||||
)
|
||||
elif gpt_provider == "deepseek":
|
||||
return deepseek_text_response(
|
||||
prompt=prompt,
|
||||
model=model,
|
||||
temperature=temperature,
|
||||
max_tokens=max_tokens,
|
||||
system_prompt=system_instructions
|
||||
)
|
||||
else:
|
||||
logger.error(f"[llm_text_gen] Unknown provider: {gpt_provider}")
|
||||
return _get_mock_response(prompt)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[llm_text_gen] Error during text generation: {str(e)}")
|
||||
return _get_mock_response(prompt)
|
||||
|
||||
def _get_mock_response(prompt: str) -> str:
|
||||
"""Get a mock response when no API keys are available."""
|
||||
logger.warning("[llm_text_gen] Using mock response - no API keys configured")
|
||||
|
||||
# Return a structured mock response for style detection
|
||||
if "style analysis" in prompt.lower() or "writing style" in prompt.lower():
|
||||
return json.dumps({
|
||||
"writing_style": {
|
||||
"tone": "professional",
|
||||
"voice": "active",
|
||||
"complexity": "moderate",
|
||||
"engagement_level": "high"
|
||||
},
|
||||
"content_characteristics": {
|
||||
"sentence_structure": "well-structured",
|
||||
"vocabulary_level": "intermediate",
|
||||
"paragraph_organization": "logical flow",
|
||||
"content_flow": "smooth transitions"
|
||||
},
|
||||
"target_audience": {
|
||||
"demographics": ["professionals", "business users"],
|
||||
"expertise_level": "intermediate",
|
||||
"industry_focus": "technology",
|
||||
"geographic_focus": "global"
|
||||
},
|
||||
"content_type": {
|
||||
"primary_type": "blog",
|
||||
"secondary_types": ["article", "guide"],
|
||||
"purpose": "inform",
|
||||
"call_to_action": "moderate"
|
||||
},
|
||||
"recommended_settings": {
|
||||
"writing_tone": "professional",
|
||||
"target_audience": "business professionals",
|
||||
"content_type": "blog",
|
||||
"creativity_level": "medium",
|
||||
"geographic_location": "global"
|
||||
}
|
||||
})
|
||||
|
||||
# Generic mock response
|
||||
return "This is a mock response. Please configure API keys for real content generation."
|
||||
|
||||
def check_gpt_provider(gpt_provider: str) -> bool:
|
||||
"""Check if the specified GPT provider is supported."""
|
||||
supported_providers = ["openai", "google", "anthropic", "deepseek"]
|
||||
return gpt_provider in supported_providers
|
||||
|
||||
def get_api_key(gpt_provider: str) -> Optional[str]:
|
||||
"""Get API key for the specified provider."""
|
||||
try:
|
||||
api_key_manager = APIKeyManager()
|
||||
provider_mapping = {
|
||||
"openai": "openai",
|
||||
"google": "gemini",
|
||||
"anthropic": "anthropic",
|
||||
"deepseek": "deepseek"
|
||||
}
|
||||
|
||||
mapped_provider = provider_mapping.get(gpt_provider, gpt_provider)
|
||||
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
|
||||
Reference in New Issue
Block a user