Added video studio router and endpoints. Added research router and endpoints. Added youtube router and endpoints. Added onboarding utils router and endpoints. Added onboarding utils service. Added onboarding utils models. Added onboarding utils routes. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils. Added onboarding utils utils.
This commit is contained in:
ajaysi
14
backend/api/research/__init__.py
Normal file
14
backend/api/research/__init__.py
Normal file
@@ -0,0 +1,14 @@
|
||||
"""
|
||||
Research API Module
|
||||
|
||||
Standalone API endpoints for the Research Engine.
|
||||
Can be used by any tool or directly via API.
|
||||
|
||||
Author: ALwrity Team
|
||||
Version: 2.0
|
||||
"""
|
||||
|
||||
from .router import router
|
||||
|
||||
__all__ = ["router"]
|
||||
|
||||
739
backend/api/research/router.py
Normal file
739
backend/api/research/router.py
Normal file
@@ -0,0 +1,739 @@
|
||||
"""
|
||||
Research API Router
|
||||
|
||||
Standalone API endpoints for the Research Engine.
|
||||
These endpoints can be used by:
|
||||
- Frontend Research UI
|
||||
- Blog Writer (via adapter)
|
||||
- Podcast Maker
|
||||
- YouTube Creator
|
||||
- Any other content tool
|
||||
|
||||
Author: ALwrity Team
|
||||
Version: 2.0
|
||||
"""
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException, BackgroundTasks
|
||||
from pydantic import BaseModel, Field
|
||||
from typing import Optional, List, Dict, Any
|
||||
from loguru import logger
|
||||
import uuid
|
||||
import asyncio
|
||||
|
||||
from services.database import get_db
|
||||
from services.research.core import (
|
||||
ResearchEngine,
|
||||
ResearchContext,
|
||||
ResearchPersonalizationContext,
|
||||
ContentType,
|
||||
ResearchGoal,
|
||||
ResearchDepth,
|
||||
ProviderPreference,
|
||||
)
|
||||
from services.research.core.research_context import ResearchResult
|
||||
from middleware.auth_middleware import get_current_user
|
||||
|
||||
# Intent-driven research imports
|
||||
from models.research_intent_models import (
|
||||
ResearchIntent,
|
||||
IntentInferenceRequest,
|
||||
IntentInferenceResponse,
|
||||
IntentDrivenResearchResult,
|
||||
ResearchQuery,
|
||||
ExpectedDeliverable,
|
||||
ResearchPurpose,
|
||||
ContentOutput,
|
||||
ResearchDepthLevel,
|
||||
)
|
||||
from services.research.intent import (
|
||||
ResearchIntentInference,
|
||||
IntentQueryGenerator,
|
||||
IntentAwareAnalyzer,
|
||||
)
|
||||
|
||||
router = APIRouter(prefix="/api/research", tags=["Research Engine"])
|
||||
|
||||
|
||||
# Request/Response models
|
||||
class ResearchRequest(BaseModel):
|
||||
"""API request for research."""
|
||||
query: str = Field(..., description="Main research query or topic")
|
||||
keywords: List[str] = Field(default_factory=list, description="Additional keywords")
|
||||
|
||||
# Research configuration
|
||||
goal: Optional[str] = Field(default="factual", description="Research goal: factual, trending, competitive, etc.")
|
||||
depth: Optional[str] = Field(default="standard", description="Research depth: quick, standard, comprehensive, expert")
|
||||
provider: Optional[str] = Field(default="auto", description="Provider preference: auto, exa, tavily, google")
|
||||
|
||||
# Personalization
|
||||
content_type: Optional[str] = Field(default="general", description="Content type: blog, podcast, video, etc.")
|
||||
industry: Optional[str] = None
|
||||
target_audience: Optional[str] = None
|
||||
tone: Optional[str] = None
|
||||
|
||||
# Constraints
|
||||
max_sources: int = Field(default=10, ge=1, le=25)
|
||||
recency: Optional[str] = None # day, week, month, year
|
||||
|
||||
# Domain filtering
|
||||
include_domains: List[str] = Field(default_factory=list)
|
||||
exclude_domains: List[str] = Field(default_factory=list)
|
||||
|
||||
# Advanced mode
|
||||
advanced_mode: bool = False
|
||||
|
||||
# Raw provider parameters (only if advanced_mode=True)
|
||||
exa_category: Optional[str] = None
|
||||
exa_search_type: Optional[str] = None
|
||||
tavily_topic: Optional[str] = None
|
||||
tavily_search_depth: Optional[str] = None
|
||||
tavily_include_answer: bool = False
|
||||
tavily_time_range: Optional[str] = None
|
||||
|
||||
|
||||
class ResearchResponse(BaseModel):
|
||||
"""API response for research."""
|
||||
success: bool
|
||||
task_id: Optional[str] = None # For async requests
|
||||
|
||||
# Results (if synchronous)
|
||||
sources: List[Dict[str, Any]] = Field(default_factory=list)
|
||||
keyword_analysis: Dict[str, Any] = Field(default_factory=dict)
|
||||
competitor_analysis: Dict[str, Any] = Field(default_factory=dict)
|
||||
suggested_angles: List[str] = Field(default_factory=list)
|
||||
|
||||
# Metadata
|
||||
provider_used: Optional[str] = None
|
||||
search_queries: List[str] = Field(default_factory=list)
|
||||
|
||||
# Error handling
|
||||
error_message: Optional[str] = None
|
||||
error_code: Optional[str] = None
|
||||
|
||||
|
||||
class ProviderStatusResponse(BaseModel):
|
||||
"""API response for provider status."""
|
||||
exa: Dict[str, Any]
|
||||
tavily: Dict[str, Any]
|
||||
google: Dict[str, Any]
|
||||
|
||||
|
||||
# In-memory task storage for async research
|
||||
_research_tasks: Dict[str, Dict[str, Any]] = {}
|
||||
|
||||
|
||||
def _convert_to_research_context(request: ResearchRequest, user_id: str) -> ResearchContext:
|
||||
"""Convert API request to ResearchContext."""
|
||||
|
||||
# Map string enums
|
||||
goal_map = {
|
||||
"factual": ResearchGoal.FACTUAL,
|
||||
"trending": ResearchGoal.TRENDING,
|
||||
"competitive": ResearchGoal.COMPETITIVE,
|
||||
"educational": ResearchGoal.EDUCATIONAL,
|
||||
"technical": ResearchGoal.TECHNICAL,
|
||||
"inspirational": ResearchGoal.INSPIRATIONAL,
|
||||
}
|
||||
|
||||
depth_map = {
|
||||
"quick": ResearchDepth.QUICK,
|
||||
"standard": ResearchDepth.STANDARD,
|
||||
"comprehensive": ResearchDepth.COMPREHENSIVE,
|
||||
"expert": ResearchDepth.EXPERT,
|
||||
}
|
||||
|
||||
provider_map = {
|
||||
"auto": ProviderPreference.AUTO,
|
||||
"exa": ProviderPreference.EXA,
|
||||
"tavily": ProviderPreference.TAVILY,
|
||||
"google": ProviderPreference.GOOGLE,
|
||||
"hybrid": ProviderPreference.HYBRID,
|
||||
}
|
||||
|
||||
content_type_map = {
|
||||
"blog": ContentType.BLOG,
|
||||
"podcast": ContentType.PODCAST,
|
||||
"video": ContentType.VIDEO,
|
||||
"social": ContentType.SOCIAL,
|
||||
"email": ContentType.EMAIL,
|
||||
"newsletter": ContentType.NEWSLETTER,
|
||||
"whitepaper": ContentType.WHITEPAPER,
|
||||
"general": ContentType.GENERAL,
|
||||
}
|
||||
|
||||
# Build personalization context
|
||||
personalization = ResearchPersonalizationContext(
|
||||
creator_id=user_id,
|
||||
content_type=content_type_map.get(request.content_type or "general", ContentType.GENERAL),
|
||||
industry=request.industry,
|
||||
target_audience=request.target_audience,
|
||||
tone=request.tone,
|
||||
)
|
||||
|
||||
return ResearchContext(
|
||||
query=request.query,
|
||||
keywords=request.keywords,
|
||||
goal=goal_map.get(request.goal or "factual", ResearchGoal.FACTUAL),
|
||||
depth=depth_map.get(request.depth or "standard", ResearchDepth.STANDARD),
|
||||
provider_preference=provider_map.get(request.provider or "auto", ProviderPreference.AUTO),
|
||||
personalization=personalization,
|
||||
max_sources=request.max_sources,
|
||||
recency=request.recency,
|
||||
include_domains=request.include_domains,
|
||||
exclude_domains=request.exclude_domains,
|
||||
advanced_mode=request.advanced_mode,
|
||||
exa_category=request.exa_category,
|
||||
exa_search_type=request.exa_search_type,
|
||||
tavily_topic=request.tavily_topic,
|
||||
tavily_search_depth=request.tavily_search_depth,
|
||||
tavily_include_answer=request.tavily_include_answer,
|
||||
tavily_time_range=request.tavily_time_range,
|
||||
)
|
||||
|
||||
|
||||
@router.get("/providers/status", response_model=ProviderStatusResponse)
|
||||
async def get_provider_status():
|
||||
"""
|
||||
Get status of available research providers.
|
||||
|
||||
Returns availability and priority of Exa, Tavily, and Google providers.
|
||||
"""
|
||||
engine = ResearchEngine()
|
||||
return engine.get_provider_status()
|
||||
|
||||
|
||||
@router.post("/execute", response_model=ResearchResponse)
|
||||
async def execute_research(
|
||||
request: ResearchRequest,
|
||||
current_user: Dict[str, Any] = Depends(get_current_user),
|
||||
):
|
||||
"""
|
||||
Execute research synchronously.
|
||||
|
||||
For quick research needs. For longer research, use /start endpoint.
|
||||
"""
|
||||
try:
|
||||
if not current_user:
|
||||
raise HTTPException(status_code=401, detail="Authentication required")
|
||||
|
||||
user_id = str(current_user.get('id', ''))
|
||||
if not user_id:
|
||||
raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
|
||||
|
||||
logger.info(f"[Research API] Execute request: {request.query[:50]}...")
|
||||
|
||||
engine = ResearchEngine()
|
||||
context = _convert_to_research_context(request, user_id)
|
||||
|
||||
result = await engine.research(context)
|
||||
|
||||
return ResearchResponse(
|
||||
success=result.success,
|
||||
sources=result.sources,
|
||||
keyword_analysis=result.keyword_analysis,
|
||||
competitor_analysis=result.competitor_analysis,
|
||||
suggested_angles=result.suggested_angles,
|
||||
provider_used=result.provider_used,
|
||||
search_queries=result.search_queries,
|
||||
error_message=result.error_message,
|
||||
error_code=result.error_code,
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[Research API] Execute failed: {e}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
@router.post("/start", response_model=ResearchResponse)
|
||||
async def start_research(
|
||||
request: ResearchRequest,
|
||||
background_tasks: BackgroundTasks,
|
||||
current_user: Dict[str, Any] = Depends(get_current_user),
|
||||
):
|
||||
"""
|
||||
Start research asynchronously.
|
||||
|
||||
Returns a task_id that can be used to poll for status.
|
||||
Use this for comprehensive research that may take longer.
|
||||
"""
|
||||
try:
|
||||
if not current_user:
|
||||
raise HTTPException(status_code=401, detail="Authentication required")
|
||||
|
||||
user_id = str(current_user.get('id', ''))
|
||||
if not user_id:
|
||||
raise HTTPException(status_code=401, detail="Invalid user ID in authentication token")
|
||||
|
||||
logger.info(f"[Research API] Start async request: {request.query[:50]}...")
|
||||
|
||||
task_id = str(uuid.uuid4())
|
||||
|
||||
# Initialize task
|
||||
_research_tasks[task_id] = {
|
||||
"status": "pending",
|
||||
"progress_messages": [],
|
||||
"result": None,
|
||||
"error": None,
|
||||
}
|
||||
|
||||
# Start background task
|
||||
context = _convert_to_research_context(request, user_id)
|
||||
background_tasks.add_task(_run_research_task, task_id, context)
|
||||
|
||||
return ResearchResponse(
|
||||
success=True,
|
||||
task_id=task_id,
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[Research API] Start failed: {e}")
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
|
||||
async def _run_research_task(task_id: str, context: ResearchContext):
|
||||
"""Background task to run research."""
|
||||
try:
|
||||
_research_tasks[task_id]["status"] = "running"
|
||||
|
||||
def progress_callback(message: str):
|
||||
_research_tasks[task_id]["progress_messages"].append(message)
|
||||
|
||||
engine = ResearchEngine()
|
||||
result = await engine.research(context, progress_callback=progress_callback)
|
||||
|
||||
_research_tasks[task_id]["status"] = "completed"
|
||||
_research_tasks[task_id]["result"] = result
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[Research API] Task {task_id} failed: {e}")
|
||||
_research_tasks[task_id]["status"] = "failed"
|
||||
_research_tasks[task_id]["error"] = str(e)
|
||||
|
||||
|
||||
@router.get("/status/{task_id}")
|
||||
async def get_research_status(task_id: str):
|
||||
"""
|
||||
Get status of an async research task.
|
||||
|
||||
Poll this endpoint to get progress updates and final results.
|
||||
"""
|
||||
if task_id not in _research_tasks:
|
||||
raise HTTPException(status_code=404, detail="Task not found")
|
||||
|
||||
task = _research_tasks[task_id]
|
||||
|
||||
response = {
|
||||
"task_id": task_id,
|
||||
"status": task["status"],
|
||||
"progress_messages": task["progress_messages"],
|
||||
}
|
||||
|
||||
if task["status"] == "completed" and task["result"]:
|
||||
result = task["result"]
|
||||
response["result"] = {
|
||||
"success": result.success,
|
||||
"sources": result.sources,
|
||||
"keyword_analysis": result.keyword_analysis,
|
||||
"competitor_analysis": result.competitor_analysis,
|
||||
"suggested_angles": result.suggested_angles,
|
||||
"provider_used": result.provider_used,
|
||||
"search_queries": result.search_queries,
|
||||
}
|
||||
|
||||
# Clean up completed task after returning
|
||||
# In production, use Redis or database for persistence
|
||||
|
||||
elif task["status"] == "failed":
|
||||
response["error"] = task["error"]
|
||||
|
||||
return response
|
||||
|
||||
|
||||
@router.delete("/status/{task_id}")
|
||||
async def cancel_research(task_id: str):
|
||||
"""
|
||||
Cancel a running research task.
|
||||
"""
|
||||
if task_id not in _research_tasks:
|
||||
raise HTTPException(status_code=404, detail="Task not found")
|
||||
|
||||
task = _research_tasks[task_id]
|
||||
|
||||
if task["status"] in ["pending", "running"]:
|
||||
task["status"] = "cancelled"
|
||||
return {"message": "Task cancelled", "task_id": task_id}
|
||||
|
||||
return {"message": f"Task already {task['status']}", "task_id": task_id}
|
||||
|
||||
|
||||
# ============================================================================
|
||||
# Intent-Driven Research Endpoints
|
||||
# ============================================================================
|
||||
|
||||
class AnalyzeIntentRequest(BaseModel):
|
||||
"""Request to analyze user research intent."""
|
||||
user_input: str = Field(..., description="User's keywords, question, or goal")
|
||||
keywords: List[str] = Field(default_factory=list, description="Extracted keywords")
|
||||
use_persona: bool = Field(True, description="Use research persona for context")
|
||||
use_competitor_data: bool = Field(True, description="Use competitor data for context")
|
||||
|
||||
|
||||
class AnalyzeIntentResponse(BaseModel):
|
||||
"""Response from intent analysis."""
|
||||
success: bool
|
||||
intent: Dict[str, Any]
|
||||
analysis_summary: str
|
||||
suggested_queries: List[Dict[str, Any]]
|
||||
suggested_keywords: List[str]
|
||||
suggested_angles: List[str]
|
||||
quick_options: List[Dict[str, Any]]
|
||||
error_message: Optional[str] = None
|
||||
|
||||
|
||||
class IntentDrivenResearchRequest(BaseModel):
|
||||
"""Request for intent-driven research."""
|
||||
# Intent from previous analyze step, or minimal input for auto-inference
|
||||
user_input: str = Field(..., description="User's original input")
|
||||
|
||||
# Optional: Confirmed intent from UI (if user modified the inferred intent)
|
||||
confirmed_intent: Optional[Dict[str, Any]] = None
|
||||
|
||||
# Optional: Specific queries to run (if user selected from suggested)
|
||||
selected_queries: Optional[List[Dict[str, Any]]] = None
|
||||
|
||||
# Research configuration
|
||||
max_sources: int = Field(default=10, ge=1, le=25)
|
||||
include_domains: List[str] = Field(default_factory=list)
|
||||
exclude_domains: List[str] = Field(default_factory=list)
|
||||
|
||||
# Skip intent inference (for re-runs with same intent)
|
||||
skip_inference: bool = False
|
||||
|
||||
|
||||
class IntentDrivenResearchResponse(BaseModel):
|
||||
"""Response from intent-driven research."""
|
||||
success: bool
|
||||
|
||||
# Direct answers
|
||||
primary_answer: str = ""
|
||||
secondary_answers: Dict[str, str] = Field(default_factory=dict)
|
||||
|
||||
# Deliverables
|
||||
statistics: List[Dict[str, Any]] = Field(default_factory=list)
|
||||
expert_quotes: List[Dict[str, Any]] = Field(default_factory=list)
|
||||
case_studies: List[Dict[str, Any]] = Field(default_factory=list)
|
||||
trends: List[Dict[str, Any]] = Field(default_factory=list)
|
||||
comparisons: List[Dict[str, Any]] = Field(default_factory=list)
|
||||
best_practices: List[str] = Field(default_factory=list)
|
||||
step_by_step: List[str] = Field(default_factory=list)
|
||||
pros_cons: Optional[Dict[str, Any]] = None
|
||||
definitions: Dict[str, str] = Field(default_factory=dict)
|
||||
examples: List[str] = Field(default_factory=list)
|
||||
predictions: List[str] = Field(default_factory=list)
|
||||
|
||||
# Content-ready outputs
|
||||
executive_summary: str = ""
|
||||
key_takeaways: List[str] = Field(default_factory=list)
|
||||
suggested_outline: List[str] = Field(default_factory=list)
|
||||
|
||||
# Sources and metadata
|
||||
sources: List[Dict[str, Any]] = Field(default_factory=list)
|
||||
confidence: float = 0.8
|
||||
gaps_identified: List[str] = Field(default_factory=list)
|
||||
follow_up_queries: List[str] = Field(default_factory=list)
|
||||
|
||||
# The inferred/confirmed intent
|
||||
intent: Optional[Dict[str, Any]] = None
|
||||
|
||||
# Error handling
|
||||
error_message: Optional[str] = None
|
||||
|
||||
|
||||
@router.post("/intent/analyze", response_model=AnalyzeIntentResponse)
|
||||
async def analyze_research_intent(
|
||||
request: AnalyzeIntentRequest,
|
||||
current_user: Dict[str, Any] = Depends(get_current_user),
|
||||
):
|
||||
"""
|
||||
Analyze user input to understand research intent.
|
||||
|
||||
This endpoint uses AI to infer what the user really wants from their research:
|
||||
- What questions need answering
|
||||
- What deliverables they expect (statistics, quotes, case studies, etc.)
|
||||
- What depth and focus is appropriate
|
||||
|
||||
The response includes quick options that can be shown in the UI for user confirmation.
|
||||
"""
|
||||
try:
|
||||
if not current_user:
|
||||
raise HTTPException(status_code=401, detail="Authentication required")
|
||||
|
||||
user_id = str(current_user.get('id', ''))
|
||||
if not user_id:
|
||||
raise HTTPException(status_code=401, detail="Invalid user ID")
|
||||
|
||||
logger.info(f"[Intent API] Analyzing intent for: {request.user_input[:50]}...")
|
||||
|
||||
# Get research persona if requested
|
||||
research_persona = None
|
||||
competitor_data = None
|
||||
|
||||
if request.use_persona or request.use_competitor_data:
|
||||
from services.research.research_persona_service import ResearchPersonaService
|
||||
from services.onboarding_service import OnboardingService
|
||||
from sqlalchemy.orm import Session
|
||||
|
||||
# Get database session
|
||||
db = next(get_db())
|
||||
try:
|
||||
persona_service = ResearchPersonaService(db)
|
||||
onboarding_service = OnboardingService()
|
||||
|
||||
if request.use_persona:
|
||||
research_persona = persona_service.get_or_generate(user_id)
|
||||
|
||||
if request.use_competitor_data:
|
||||
competitor_data = onboarding_service.get_competitor_analysis(user_id, db)
|
||||
finally:
|
||||
db.close()
|
||||
|
||||
# Infer intent
|
||||
intent_service = ResearchIntentInference()
|
||||
response = await intent_service.infer_intent(
|
||||
user_input=request.user_input,
|
||||
keywords=request.keywords,
|
||||
research_persona=research_persona,
|
||||
competitor_data=competitor_data,
|
||||
industry=research_persona.default_industry if research_persona else None,
|
||||
target_audience=research_persona.default_target_audience if research_persona else None,
|
||||
)
|
||||
|
||||
# Generate targeted queries
|
||||
query_generator = IntentQueryGenerator()
|
||||
query_result = await query_generator.generate_queries(
|
||||
intent=response.intent,
|
||||
research_persona=research_persona,
|
||||
)
|
||||
|
||||
# Update response with queries
|
||||
response.suggested_queries = [q.dict() for q in query_result.get("queries", [])]
|
||||
response.suggested_keywords = query_result.get("enhanced_keywords", [])
|
||||
response.suggested_angles = query_result.get("research_angles", [])
|
||||
|
||||
return AnalyzeIntentResponse(
|
||||
success=True,
|
||||
intent=response.intent.dict(),
|
||||
analysis_summary=response.analysis_summary,
|
||||
suggested_queries=response.suggested_queries,
|
||||
suggested_keywords=response.suggested_keywords,
|
||||
suggested_angles=response.suggested_angles,
|
||||
quick_options=response.quick_options,
|
||||
)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[Intent API] Analyze failed: {e}")
|
||||
return AnalyzeIntentResponse(
|
||||
success=False,
|
||||
intent={},
|
||||
analysis_summary="",
|
||||
suggested_queries=[],
|
||||
suggested_keywords=[],
|
||||
suggested_angles=[],
|
||||
quick_options=[],
|
||||
error_message=str(e),
|
||||
)
|
||||
|
||||
|
||||
@router.post("/intent/research", response_model=IntentDrivenResearchResponse)
|
||||
async def execute_intent_driven_research(
|
||||
request: IntentDrivenResearchRequest,
|
||||
current_user: Dict[str, Any] = Depends(get_current_user),
|
||||
):
|
||||
"""
|
||||
Execute research based on user intent.
|
||||
|
||||
This is the main endpoint for intent-driven research. It:
|
||||
1. Uses the confirmed intent (or infers from user_input if not provided)
|
||||
2. Generates targeted queries for each expected deliverable
|
||||
3. Executes research using Exa/Tavily/Google
|
||||
4. Analyzes results through the lens of user intent
|
||||
5. Returns exactly what the user needs
|
||||
|
||||
The response is organized by deliverable type (statistics, quotes, case studies, etc.)
|
||||
instead of generic search results.
|
||||
"""
|
||||
try:
|
||||
if not current_user:
|
||||
raise HTTPException(status_code=401, detail="Authentication required")
|
||||
|
||||
user_id = str(current_user.get('id', ''))
|
||||
if not user_id:
|
||||
raise HTTPException(status_code=401, detail="Invalid user ID")
|
||||
|
||||
logger.info(f"[Intent API] Executing intent-driven research for: {request.user_input[:50]}...")
|
||||
|
||||
# Get database session
|
||||
db = next(get_db())
|
||||
|
||||
try:
|
||||
# Get research persona
|
||||
from services.research.research_persona_service import ResearchPersonaService
|
||||
persona_service = ResearchPersonaService(db)
|
||||
research_persona = persona_service.get_or_generate(user_id)
|
||||
|
||||
# Determine intent
|
||||
if request.confirmed_intent:
|
||||
# Use confirmed intent from UI
|
||||
intent = ResearchIntent(**request.confirmed_intent)
|
||||
elif not request.skip_inference:
|
||||
# Infer intent from user input
|
||||
intent_service = ResearchIntentInference()
|
||||
intent_response = await intent_service.infer_intent(
|
||||
user_input=request.user_input,
|
||||
research_persona=research_persona,
|
||||
)
|
||||
intent = intent_response.intent
|
||||
else:
|
||||
# Create basic intent from input
|
||||
intent = ResearchIntent(
|
||||
primary_question=f"What are the key insights about: {request.user_input}?",
|
||||
purpose="learn",
|
||||
content_output="general",
|
||||
expected_deliverables=["key_statistics", "best_practices", "examples"],
|
||||
depth="detailed",
|
||||
original_input=request.user_input,
|
||||
confidence=0.6,
|
||||
)
|
||||
|
||||
# Generate or use provided queries
|
||||
if request.selected_queries:
|
||||
queries = [ResearchQuery(**q) for q in request.selected_queries]
|
||||
else:
|
||||
query_generator = IntentQueryGenerator()
|
||||
query_result = await query_generator.generate_queries(
|
||||
intent=intent,
|
||||
research_persona=research_persona,
|
||||
)
|
||||
queries = query_result.get("queries", [])
|
||||
|
||||
# Execute research using the Research Engine
|
||||
engine = ResearchEngine(db_session=db)
|
||||
|
||||
# Build context from intent
|
||||
personalization = ResearchPersonalizationContext(
|
||||
creator_id=user_id,
|
||||
industry=research_persona.default_industry if research_persona else None,
|
||||
target_audience=research_persona.default_target_audience if research_persona else None,
|
||||
)
|
||||
|
||||
# Use the highest priority query for the main search
|
||||
# (In a more advanced version, we could run multiple queries and merge)
|
||||
primary_query = queries[0] if queries else ResearchQuery(
|
||||
query=request.user_input,
|
||||
purpose=ExpectedDeliverable.KEY_STATISTICS,
|
||||
provider="exa",
|
||||
priority=5,
|
||||
expected_results="General research results",
|
||||
)
|
||||
|
||||
context = ResearchContext(
|
||||
query=primary_query.query,
|
||||
keywords=request.user_input.split()[:10],
|
||||
goal=_map_purpose_to_goal(intent.purpose),
|
||||
depth=_map_depth_to_engine_depth(intent.depth),
|
||||
provider_preference=_map_provider_to_preference(primary_query.provider),
|
||||
personalization=personalization,
|
||||
max_sources=request.max_sources,
|
||||
include_domains=request.include_domains,
|
||||
exclude_domains=request.exclude_domains,
|
||||
)
|
||||
|
||||
# Execute research
|
||||
raw_result = await engine.research(context)
|
||||
|
||||
# Analyze results using intent-aware analyzer
|
||||
analyzer = IntentAwareAnalyzer()
|
||||
analyzed_result = await analyzer.analyze(
|
||||
raw_results={
|
||||
"content": raw_result.raw_content or "",
|
||||
"sources": raw_result.sources,
|
||||
"grounding_metadata": raw_result.grounding_metadata,
|
||||
},
|
||||
intent=intent,
|
||||
research_persona=research_persona,
|
||||
)
|
||||
|
||||
# Build response
|
||||
return IntentDrivenResearchResponse(
|
||||
success=True,
|
||||
primary_answer=analyzed_result.primary_answer,
|
||||
secondary_answers=analyzed_result.secondary_answers,
|
||||
statistics=[s.dict() for s in analyzed_result.statistics],
|
||||
expert_quotes=[q.dict() for q in analyzed_result.expert_quotes],
|
||||
case_studies=[cs.dict() for cs in analyzed_result.case_studies],
|
||||
trends=[t.dict() for t in analyzed_result.trends],
|
||||
comparisons=[c.dict() for c in analyzed_result.comparisons],
|
||||
best_practices=analyzed_result.best_practices,
|
||||
step_by_step=analyzed_result.step_by_step,
|
||||
pros_cons=analyzed_result.pros_cons.dict() if analyzed_result.pros_cons else None,
|
||||
definitions=analyzed_result.definitions,
|
||||
examples=analyzed_result.examples,
|
||||
predictions=analyzed_result.predictions,
|
||||
executive_summary=analyzed_result.executive_summary,
|
||||
key_takeaways=analyzed_result.key_takeaways,
|
||||
suggested_outline=analyzed_result.suggested_outline,
|
||||
sources=[s.dict() for s in analyzed_result.sources],
|
||||
confidence=analyzed_result.confidence,
|
||||
gaps_identified=analyzed_result.gaps_identified,
|
||||
follow_up_queries=analyzed_result.follow_up_queries,
|
||||
intent=intent.dict(),
|
||||
)
|
||||
|
||||
finally:
|
||||
db.close()
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"[Intent API] Research failed: {e}")
|
||||
import traceback
|
||||
traceback.print_exc()
|
||||
return IntentDrivenResearchResponse(
|
||||
success=False,
|
||||
error_message=str(e),
|
||||
)
|
||||
|
||||
|
||||
def _map_purpose_to_goal(purpose: str) -> ResearchGoal:
|
||||
"""Map intent purpose to research goal."""
|
||||
mapping = {
|
||||
"learn": ResearchGoal.EDUCATIONAL,
|
||||
"create_content": ResearchGoal.FACTUAL,
|
||||
"make_decision": ResearchGoal.FACTUAL,
|
||||
"compare": ResearchGoal.COMPETITIVE,
|
||||
"solve_problem": ResearchGoal.EDUCATIONAL,
|
||||
"find_data": ResearchGoal.FACTUAL,
|
||||
"explore_trends": ResearchGoal.TRENDING,
|
||||
"validate": ResearchGoal.FACTUAL,
|
||||
"generate_ideas": ResearchGoal.INSPIRATIONAL,
|
||||
}
|
||||
return mapping.get(purpose, ResearchGoal.FACTUAL)
|
||||
|
||||
|
||||
def _map_depth_to_engine_depth(depth: str) -> ResearchDepth:
|
||||
"""Map intent depth to research engine depth."""
|
||||
mapping = {
|
||||
"overview": ResearchDepth.QUICK,
|
||||
"detailed": ResearchDepth.STANDARD,
|
||||
"expert": ResearchDepth.COMPREHENSIVE,
|
||||
}
|
||||
return mapping.get(depth, ResearchDepth.STANDARD)
|
||||
|
||||
|
||||
def _map_provider_to_preference(provider: str) -> ProviderPreference:
|
||||
"""Map query provider to engine preference."""
|
||||
mapping = {
|
||||
"exa": ProviderPreference.EXA,
|
||||
"tavily": ProviderPreference.TAVILY,
|
||||
"google": ProviderPreference.GOOGLE,
|
||||
}
|
||||
return mapping.get(provider, ProviderPreference.AUTO)
|
||||
|
||||
Reference in New Issue
Block a user