Modify the code to only keep Gemini 3 related setup and remove all Gemini 2.5 setup

server/__init__.py

@@ -33,7 +33,6 @@
 from server.lib.disaster_dashboard import get_disaster_dashboard_data
 from server.lib.feature_flags import BIOMED_NL_FEATURE_FLAG
 from server.lib.feature_flags import DATA_OVERVIEW_FEATURE_FLAG
-from server.lib.feature_flags import ENABLE_GEMINI_3_FLASH
 from server.lib.feature_flags import ENABLE_NL_AGENT_DETECTOR
 from server.lib.feature_flags import is_feature_enabled
 import server.lib.i18n as i18n
@@ -435,10 +434,7 @@ def create_app(nl_root=DEFAULT_NL_ROOT):
                                                'palm-api-key')
       if is_feature_enabled(ENABLE_NL_AGENT_DETECTOR, app):
         os.environ['GEMINI_API_KEY'] = app.config['LLM_API_KEY']
-        if is_feature_enabled(ENABLE_GEMINI_3_FLASH, app):
-          default_model = "gemini-3-flash-preview"
-        else:
-          default_model = "gemini-2.5-flash"
+        default_model = "gemini-3-flash-preview"
         app.config['NL_DETECTION_AGENT'] = create_detection_agent(
             os.environ.get("AGENT_MODEL", default_model),
             os.environ.get("DC_MCP_URL"))

server/lib/feature_flags.py

@@ -33,7 +33,6 @@
 ENABLE_STAT_VAR_AUTOCOMPLETE = 'enable_stat_var_autocomplete'
 ENABLE_NL_AGENT_DETECTOR = 'enable_nl_agent_detector'
 NEW_RANKING_PAGE = 'new_ranking_page'
-ENABLE_GEMINI_3_FLASH = 'enable_gemini_3_flash'
 USE_V2_API = 'use_v2_api'
 # This flag controls the switching of detect-and-fulfill API to use v2/resolve from current nl search vars
 USE_V2_RESOLVE_FOR_NL_SEARCH_VARS = 'use_v2_resolve_for_nl_search_vars'

server/lib/nl/detection/llm_api.py

@@ -24,14 +24,10 @@
 from google.genai import types
 import json5
 
-from server.lib.feature_flags import ENABLE_GEMINI_3_FLASH
-from server.lib.feature_flags import is_feature_enabled
 from server.lib.nl.common import counters
 
 _GEMINI_3_0_FLASH = 'gemini-3-flash-preview'
-_GEMINI_2_5_FLASH = 'gemini-2.5-flash'
 _API_VERSION_3 = 'v1beta'
-_API_VERSION_2 = 'v1'
 
 # TODO: Consider tweaking this. And maybe consider passing as url param.
 _TEMPERATURE = 0.1
@@ -55,13 +51,7 @@
             "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
             "threshold": "BLOCK_MEDIUM_AND_ABOVE"
         },
-    ])
-
-_GEMINI_2_5_CONFIG = _GEMINI_CONFIG
-
-_GEMINI_3_CONFIG = types.GenerateContentConfig(
-    temperature=_TEMPERATURE,
-    safety_settings=_GEMINI_CONFIG.safety_settings,
+    ],
     thinking_config=types.ThinkingConfig(thinking_level="low"))
 
 _SKIP_BEGIN_CHARS = ['`', '*']
@@ -197,6 +187,4 @@ def _extract_answer(resp: str) -> str:
 
 
 def detect_model_name() -> tuple[str, str, types.GenerateContentConfig]:
-  if is_feature_enabled(ENABLE_GEMINI_3_FLASH):
-    return _GEMINI_3_0_FLASH, _API_VERSION_3, _GEMINI_3_CONFIG
-  return _GEMINI_2_5_FLASH, _API_VERSION_2, _GEMINI_2_5_CONFIG
+  return _GEMINI_3_0_FLASH, _API_VERSION_3, _GEMINI_CONFIG

server/lib/nl/explore/overview.py

@@ -20,8 +20,6 @@
 from pydantic import ConfigDict
 from pydantic.alias_generators import to_camel
 
-from server.lib.feature_flags import ENABLE_GEMINI_3_FLASH
-from server.lib.feature_flags import is_feature_enabled
 from server.lib.nl.explore.gemini_prompts import PAGE_OVERVIEW_PROMPT
 from server.lib.utils.gemini_utils import call_gemini
 
@@ -81,12 +79,8 @@ def generate_page_overview(
   formatted_page_overview_prompt = PAGE_OVERVIEW_PROMPT.format(
       initial_query=query, stat_var_titles=stat_var_titles)
 
-  if is_feature_enabled(ENABLE_GEMINI_3_FLASH):
-    overview_gemini_model = _OVERVIEW_GEMINI_3_1_LITE
-    use_thinking_config = True
-  else:
-    overview_gemini_model = _OVERVIEW_GEMINI_2_5_LITE
-    use_thinking_config = False
+  overview_gemini_model = _OVERVIEW_GEMINI_3_1_LITE
+  use_thinking_config = True
 
   page_overview = call_gemini(api_key=gemini_api_key,
                               formatted_prompt=formatted_page_overview_prompt,

server/lib/nl/explore/related.py

@@ -21,8 +21,6 @@
 from flask import current_app
 from pydantic import BaseModel
 
-from server.lib.feature_flags import ENABLE_GEMINI_3_FLASH
-from server.lib.feature_flags import is_feature_enabled
 import server.lib.nl.common.topic as topic
 import server.lib.nl.common.utils as utils
 import server.lib.nl.detection.types as dtypes
@@ -316,12 +314,8 @@ def generate_follow_up_questions(query: str,
   formatted_follow_up_questions_prompt = FOLLOW_UP_QUESTIONS_PROMPT.format(
       initial_query=query, related_topics=related_topics)
 
-  if is_feature_enabled(ENABLE_GEMINI_3_FLASH):
-    gemini_model = _QUESTIONS_GEMINI_3
-    use_thinking_config = True
-  else:
-    gemini_model = _QUESTIONS_GEMINI_2
-    use_thinking_config = False
+  gemini_model = _QUESTIONS_GEMINI_3
+  use_thinking_config = True
 
   follow_up_questions = call_gemini(
       api_key=gemini_api_key,

server/lib/utils/gemini_utils.py

@@ -19,38 +19,34 @@
 from pydantic import BaseModel
 
 
-def get_gemini_config(schema: Optional[BaseModel] = None,
-                      use_thinking_config: bool = False) -> dict:
+def get_gemini_config(schema: Optional[BaseModel] = None) -> dict:
   config = {
       "response_mime_type": "application/json",
-      "response_schema": schema
+      "response_schema": schema,
+      "thinking_config": genai.types.ThinkingConfig(thinking_level="low")
   } if schema else {}
-  if use_thinking_config:
-    config["thinking_config"] = genai.types.ThinkingConfig(thinking_level="low")
   return config
 
 
 def call_gemini(
     api_key: str,
     formatted_prompt: str,
     gemini_model: str,
-    schema: Optional[BaseModel] = None,
-    use_thinking_config: bool = False) -> Optional[Union[BaseModel, str]]:
+    schema: Optional[BaseModel] = None) -> Optional[Union[BaseModel, str]]:
   """A helper for all Gemini generations through the Python Gen AI client.
     Args:
         api_key: A string representing the API key required for authentication with the Gemini service.
         formatted_prompt: A string containing the structured prompt or input to be sent to the Gemini model for generation.
         schema: A Pydantic BaseModel class that defines the expected model's JSON response.
         gemini_model: A string specifying the name of the Gemini model to utilize.
-        use_thinking_config: Boolean advising whether to use thinking configuration for Gemini 3.
 
     Returns:
     The output of the call.
     """
   if not api_key or not formatted_prompt:
     return None
 
-  generate_content_config = get_gemini_config(schema, use_thinking_config)
+  generate_content_config = get_gemini_config(schema)
   gemini = genai.Client(api_key=api_key)
 
   try: