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36bc547 | 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 | import os
import sys
import json
# Add the project root to sys.path
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
from app.config import GEMINI_API_KEY, GEMINI_MODEL
from langchain_google_genai import ChatGoogleGenerativeAI
from langchain_core.messages import HumanMessage, SystemMessage
from google.genai import types
def test_debug():
text = "Is the company 'DeepSeek' currently in the news for anything related to AI or data privacy? Could this be a scam related to them?"
system = "You are a phishing analyst. Reply ONLY with valid JSON: {'risk_score': 0.0, 'threat_types': [], 'explanation': 'test'}"
messages = [SystemMessage(content=system), HumanMessage(content=text)]
search_tool = types.Tool(google_search=types.GoogleSearch())
# Try passing model_kwargs={"response_format": {"type": "json_object"}} or similar if supported
# In ChatGoogleGenerativeAI, it is sometimes supported. Let's try without it first but with a stronger prompt.
system_stronger = (
"You are an automated JSON API. You must return your analysis strictly as a JSON object, and absolutely no other text. "
"Use this exact schema:\n"
"{\n"
' "risk_score": 0.5,\n'
' "threat_types": [],\n'
' "explanation": "..."\n'
"}\n"
"DO NOT write markdown or explanations outside the JSON block."
)
messages = [SystemMessage(content=system_stronger), HumanMessage(content=text)]
llm = ChatGoogleGenerativeAI(model=GEMINI_MODEL, google_api_key=GEMINI_API_KEY, temperature=0.1)
print("Invoking with tools and stronger prompt...")
resp_with_tools = llm.invoke(messages, tools=[search_tool])
print(f"Content: {resp_with_tools.content}\n")
test_debug()
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