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905e3b7 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 | """Intent classification node for DocIntel."""
from app.agents.state import AgentState
from app.config import settings
import json
try:
from groq import Groq
client = Groq(api_key=settings.GROQ_API_KEY) if settings.GROQ_API_KEY else None
except ImportError:
client = None
def classify_intent(state: AgentState) -> AgentState:
"""Classify user intent"""
print(f"📋 Classifying intent for: {state['query']}")
# Simple keyword-based classification first (faster, no API call)
query = state["query"].lower()
# Check for summary intent
summary_keywords = ["summarize", "summary", "brief", "overview", "summarise"]
if any(word in query for word in summary_keywords):
state["intent"] = "summary"
print(f"✅ Intent: summary (keyword match)")
return state
# Check for email intent
email_keywords = ["email", "draft", "send", "compose", "write an email"]
if any(word in query for word in email_keywords):
state["intent"] = "email"
print(f"✅ Intent: email (keyword match)")
return state
# Check for extraction intent
extract_keywords = [
"extract", "list", "find", "show me",
"what are", "dates", "amounts", "numbers",
"entities", "names", "people", "organizations"
]
if any(word in query for word in extract_keywords):
state["intent"] = "extract"
print(f"✅ Intent: extract (keyword match)")
return state
# Use LLM fallback for better classification
if client is not None:
try:
prompt = f"""
Analyze this user query and classify it into one of these intents:
1. "qa" - General question about document content
2. "summary" - Request for document summary
3. "email" - Need to draft an email based on documents
4. "extract" - Need specific data extraction (dates, amounts, names, etc.)
Query: {state["query"]}
Return ONLY a JSON object with:
{{
"intent": "category",
"reasoning": "brief explanation"
}}
"""
response = client.chat.completions.create(
model=settings.GROQ_MODEL,
messages=[{"role": "user", "content": prompt}],
temperature=0.1,
max_tokens=200
)
result = json.loads(response.choices[0].message.content)
state["intent"] = result.get("intent", "qa")
print(f"✅ Intent: {state['intent']} (LLM)")
except Exception as e:
print(f"⚠️ Classification error: {e}")
state["intent"] = "qa"
state["error"] = str(e)
else:
# Default to Q&A if no client
state["intent"] = "qa"
print(f"✅ Intent: qa (no LLM client)")
return state |