fix on skip greeting response when query contains a substantive question (buerokratt#378)

* remove unwanted file

* updated changes

* fixed requested changes

* fixed issue

* service workflow implementation without calling service endpoints

* fixed requested changes

* fixed issues

* protocol related requested changes

* fixed requested changes

* update time tracking

* added time tracking and reloacate input guardrail before toolclassifiier

* fixed issue

* fixed issue

* added hybrid search for the service detection

* update tool classifier

* fixing merge conflicts

* fixed issue

* optimize first user query response generation time

* fixed pr reviewed issues

* service integration

* context based response generation flow

* fixed pr review suggested issues

* removed service project layer

* fixed issues

* delete unnessary files

* added requested changes

* fix on skip greeting response when query contains a substantive question

---------

Co-authored-by: Thiru Dinesh <56014038+Thirunayan22@users.noreply.github.com>

Author: nuwangeek

src/tool_classifier/context_analyzer.py

@@ -39,14 +39,19 @@ class ContextAnalysisSignature(dspy.Signature):
     This signature instructs the LLM to:
     1. Detect greetings in multiple languages (Estonian, English)
     2. Check if query references conversation history
-    3. Generate appropriate responses or extract answers from history
+    3. Generate appropriate responses based on context
 
     Supported greeting types:
     - hello: Tere, Hello, Hi, Hei, Hey, Moi, Good morning, Good afternoon, Good evening
     - goodbye: Nägemist, Bye, Goodbye, See you, Good night
     - thanks: Tänan, Aitäh, Thank you, Thanks, Much appreciated
     - casual: Tervist, Tšau, Moikka
 
+    IMPORTANT — Greeting + Question distinction:
+    - A message is a greeting ONLY if it contains NOTHING beyond the greeting itself.
+    - If the message contains a greeting AND a substantive question or request,
+      set is_greeting to FALSE so the question is answered properly.
+
     The LLM should respond in the SAME language as the user's query.
     """
 
@@ -139,6 +144,15 @@ class ContextDetectionSignature(dspy.Signature):
     - thanks: Tänan, Aitäh, Thank you, Thanks, Much appreciated
     - casual: Tervist, Tšau, Moikka
 
+    IMPORTANT — Greeting + Question distinction:
+    - A message is a greeting ONLY if it contains NOTHING beyond the greeting itself
+      (e.g. "Hello!", "Tere!", "Thanks!", "Aitäh!").
+    - If the message contains a greeting AND a substantive question or request
+      (e.g. "Hello, how to show uninterest to a policy?",
+       "Tere, mis on sünnitoetus?", "Hi, what are the tax benefits?"),
+      set is_greeting to FALSE. The question must be answered via RAG, not a greeting template.
+    - When in doubt, prefer is_greeting=false so the user's question is answered.
+
     Do NOT generate the answer here — only detect and extract a relevant context snippet.
     """
 
@@ -152,7 +166,8 @@ class ContextDetectionSignature(dspy.Signature):
         'greeting_type must be one of: "hello", "goodbye", "thanks", "casual" — '
         'set it only when is_greeting is true, defaulting to "hello" otherwise. '
         "context_snippet should contain the relevant excerpt from history if can_answer_from_context is true, "
-        "or null otherwise. Do NOT generate the final answer — only detect and extract."
+        "or null otherwise. Do NOT generate the final answer — only detect and extract. "
+        "CRITICAL: is_greeting must be false when the message contains a question or request alongside the greeting."
     )
 
 

src/tool_classifier/workflows/context_workflow.py

@@ -5,7 +5,7 @@
 import dspy
 from loguru import logger
 
-from models.request_models import OrchestrationRequest, OrchestrationResponse
+from src.models.request_models import OrchestrationRequest, OrchestrationResponse
 from tool_classifier.base_workflow import BaseWorkflow
 from tool_classifier.context_analyzer import ContextAnalyzer, ContextDetectionResult
 from tool_classifier.workflows.service_workflow import LLMServiceProtocol

src/utils/language_detector.py

@@ -83,6 +83,14 @@ def detect_language(text: str) -> LanguageCode:
         "nagu",
         "oli",
         "mis",
+        # Estonian greeting words
+        "tere",
+        "hei",
+        "tervist",
+        "tänan",
+        "aitäh",
+        "nägemist",
+        "moi",
     ]
 
     # Tokenize and check for Estonian markers