Add faq consistency check

app/domain/rewriting_pipeline_execution_dto.py

@@ -4,4 +4,5 @@
 
 class RewritingPipelineExecutionDTO(BaseModel):
     execution: PipelineExecutionDTO
+    course_id: int = Field(alias="courseId")
     to_be_rewritten: str = Field(alias="toBeRewritten")

app/domain/status/rewriting_status_update_dto.py

@@ -1,5 +1,11 @@
+from typing import List
+
 from app.domain.status.status_update_dto import StatusUpdateDTO
 
 
 class RewritingStatusUpdateDTO(StatusUpdateDTO):
     result: str = ""
+    suggestions: List[str] = []
+    inconsistencies: List[str] = []
+    improvement: str= ""
+

app/pipeline/prompts/faq_consistency_prompt.py

@@ -0,0 +1,46 @@
+faq_consistency_prompt = """
+You are an AI assistant responsible for verifying the consistency of information.
+### Task:
+You have been provided with a list of FAQs and a final result. Your task is to determine whether the
+final result is consistent with the given FAQs. Please compare each FAQ with the final result separately.
+
+
+
+### Given FAQs:
+{faqs}
+
+### Final Result:
+{final_result}
+
+### Output:
+Generate the following response dictionary: 
+"type": "consistent" or "inconsistent"
+
+The following four entries to the dictionary are optional and can only be set if inconsistencies are detected:
+"faqs": This entry should be a list of Strings, each string represents an FAQ.
+-Make sure each faq is separated by comma.
+-Also end each faq with a newline character.
+-The fields are exactly named faq_id, faq_question_title and faq_question_answer
+and reside within properties dict of each list entry.
+-Make sure to only include inconsistent faqs
+-Do not include any additional FAQs that are consistent with the final_result.
+
+"message": "The provided text was rephrased, however it contains inconsistent information with existing FAQs."
+-Localize the message to the language of the ###Final Result.
+-Make sure to always insert two new lines after the last character of this sentences.
+The affected FAQs can only contain the faq_id, faq_question_title, and faq_question_answer of inconsistent FAQs.
+Make sure to not include any additional FAQs, that are consistent with the final_result. 
+Insert the faq_id, faq_question_title, and faq_question_answer of the inconsistent FAQ in the placeholder.
+
+-"suggestion": This entry is a list of strings, each string represents a suggestion to improve the final result.\n
+- Each suggestion should focus on a different inconsistency.
+- Each suggestions highlights what is the inconsistency and how it can be improved. 
+- Do not mention the term final result, call it provided text
+- Please ensure that at no time, you have a different amount of suggestions than inconsistencies.\n
+Both should have the same amount of entries.
+
+-"improved version": This entry should be a string that represents the improved version of the final result.
+
+
+Do NOT provide any explanations or additional text.
+"""

app/pipeline/rewriting_pipeline.py

@@ -1,5 +1,6 @@
+import json
 import logging
-from typing import Literal, Optional
+from typing import Literal, Optional, List, Dict
 
 from langchain.output_parsers import PydanticOutputParser
 from langchain_core.prompts import (
@@ -12,10 +13,13 @@
 from app.domain.rewriting_pipeline_execution_dto import RewritingPipelineExecutionDTO
 from app.llm import CapabilityRequestHandler, RequirementList, CompletionArguments
 from app.pipeline import Pipeline
+from app.pipeline.prompts.faq_consistency_prompt import faq_consistency_prompt
 from app.pipeline.prompts.rewriting_prompts import (
     system_prompt_faq,
     system_prompt_problem_statement,
 )
+from app.retrieval.faq_retrieval import FaqRetrieval
+from app.vector_database.database import VectorDatabase
 from app.web.status.status_update import RewritingCallback
 
 logger = logging.getLogger(__name__)
@@ -38,8 +42,11 @@ def __init__(
                 context_length=16385,
             )
         )
+
+        self.db = VectorDatabase()
         self.tokens = []
         self.variant = variant
+        self.faq_retriever = FaqRetrieval(self.db.client)
 
     def __call__(
         self,
@@ -54,10 +61,10 @@ def __call__(
             "faq": system_prompt_faq,
             "problem_statement": system_prompt_problem_statement,
         }
-        print(variant_prompts[self.variant])
-        prompt = variant_prompts[self.variant].format(
-            rewritten_text=dto.to_be_rewritten,
-        )
+
+        format_args = {"rewritten_text": dto.to_be_rewritten}
+
+        prompt = variant_prompts[self.variant].format(**format_args)
         prompt = PyrisMessage(
             sender=IrisMessageRole.SYSTEM,
             contents=[TextMessageContentDTO(text_content=prompt)],
@@ -77,4 +84,72 @@ def __call__(
             response = response.strip()
 
         final_result = response
-        self.callback.done(final_result=final_result, tokens=self.tokens)
+        inconsistencies = []
+        improvement = ""
+        suggestions = []
+
+        if self.variant == "faq":
+            faqs = self.faq_retriever.get_faqs_from_db(
+                course_id=dto.course_id, search_text=response, result_limit=10
+            )
+            consistency_result = self.check_faq_consistency(faqs, final_result)
+
+
+            if "inconsistent" in consistency_result["type"].lower():
+                logging.warning("Detected inconsistencies in FAQ retrieval.")
+                inconsistencies = parse_inconsistencies(consistency_result["faqs"])
+                improvement = consistency_result["improved version"]
+                suggestions = consistency_result["suggestion"]
+
+        self.callback.done(final_result=final_result, tokens=self.tokens, inconsistencies=inconsistencies, improvement = improvement, suggestions = suggestions)
+
+    def check_faq_consistency(
+        self, faqs: List[dict], final_result: str
+    ) -> Dict[str, str]:
+        """
+        Checks the consistency of the given FAQs with the provided final_result.
+        Returns "consistent" if there are no inconsistencies, otherwise returns "inconsistent".
+
+        :param faqs: List of retrieved FAQs.
+        :param final_result: The result to compare the FAQs against.
+
+        """
+        properties_list = [entry['properties'] for entry in faqs]
+
+        consistency_prompt = faq_consistency_prompt.format(
+            faqs=properties_list, final_result=final_result
+        )
+
+        prompt = PyrisMessage(
+            sender=IrisMessageRole.SYSTEM,
+            contents=[TextMessageContentDTO(text_content=consistency_prompt)],
+        )
+
+        response = self.request_handler.chat(
+            [prompt], CompletionArguments(temperature=0.0), tools=None
+        )
+
+        self._append_tokens(response.token_usage, PipelineEnum.IRIS_REWRITING_PIPELINE)
+        result = response.contents[0].text_content
+        data = json.loads(result)
+
+        result_dict = {
+            "type": data["type"],
+            "message": data["message"],
+            "faqs": data["faqs"],
+            "suggestion": data["suggestion"],
+            "improved version": data["improved version"]
+        }
+        logging.info(f"Consistency FAQ consistency check response: {result_dict}")
+
+        return result_dict
+
+def parse_inconsistencies(inconsistencies: List[Dict[str, str]]) -> List[str]:
+    logging.info("parse consistency")
+    parsed_inconsistencies = [
+        f"FAQ ID: {entry['faq_id']}, Title: {entry['faq_question_title']}, Answer: {entry['faq_question_answer']}"
+        for entry in inconsistencies
+    ]
+    return parsed_inconsistencies
+
+

app/retrieval/faq_retrieval.py

@@ -2,6 +2,8 @@
 from typing import List
 from langsmith import traceable
 from weaviate import WeaviateClient
+from weaviate.collections.classes.filters import Filter
+
 from app.common.PipelineEnum import PipelineEnum
 from .basic_retrieval import BaseRetrieval, merge_retrieved_chunks
 from ..common.pyris_message import PyrisMessage
@@ -44,7 +46,6 @@ def __call__(
         base_url: str = None,
     ) -> List[dict]:
         course_language = self.fetch_course_language(course_id)
-
         response, response_hyde = self.run_parallel_rewrite_tasks(
             chat_history=chat_history,
             student_query=student_query,
@@ -67,3 +68,47 @@ def __call__(
             for obj in response_hyde.objects
         ]
         return merge_retrieved_chunks(basic_retrieved_faqs, hyde_retrieved_faqs)
+
+    def get_faqs_from_db(
+        self,
+        course_id: int,
+        search_text: str = None,
+        result_limit: int = 10,
+        hybrid_factor: float = 0.75,  # Gewichtung zwischen Vektor- und Textsuche
+    ) -> List[dict]:
+        """
+        Holt FAQs direkt aus der Datenbank, optional mit einer Ähnlichkeitssuche auf question_title und question_answer.
+
+        :param course_id: ID des Kurses, um nur FAQs eines bestimmten Kurses zu holen.
+        :param search_text: Optionaler Suchtext, der für eine semantische Suche verwendet wird.
+        :param result_limit: Anzahl der gewünschten Ergebnisse.
+        :param hybrid_factor: Gewichtung zwischen vektorbasierten und keywordbasierten Ergebnissen (0 = nur Vektor, 1 = nur Keywords).
+        :return: Liste der gefundenen FAQs.
+        """
+        # Filter für den Kurs
+        filter_weaviate = Filter.by_property("course_id").equal(course_id)
+
+        if search_text:
+            vec = self.llm_embedding.embed(search_text)
+
+            response = self.collection.query.hybrid(
+                query=search_text,  # Keyword-Suche
+                vector=vec,  # Vektorbasierte Ähnlichkeitssuche
+                alpha=hybrid_factor,  # Mischung aus Vektor- und Textsuche
+                return_properties=self.get_schema_properties(),
+                limit=result_limit,
+                filters=filter_weaviate,
+            )
+        else:
+            # Falls keine Suchanfrage, einfach nur nach Kurs filtern
+            response = self.collection.query.fetch_objects(
+                filters=filter_weaviate,
+                limit=result_limit,
+                return_properties=self.get_schema_properties(),
+            )
+
+        faqs = [
+            {"id": obj.uuid.int, "properties": obj.properties}
+            for obj in response.objects
+        ]
+        return faqs

app/web/status/status_update.py

@@ -110,6 +110,8 @@ def done(
         tokens: Optional[List[TokenUsageDTO]] = None,
         next_stage_message: Optional[str] = None,
         start_next_stage: bool = True,
+        inconsistencies : Optional[List[str]] = None,
+        improvement : Optional[str] = None
     ):
         """
         Transition the current stage to DONE and update the status.
@@ -122,6 +124,11 @@ def done(
         self.status.tokens = tokens or self.status.tokens
         if hasattr(self.status, "suggestions"):
             self.status.suggestions = suggestions
+
+        if hasattr(self.status, "inconsistencies"):
+            self.status.inconsistencies = inconsistencies
+        if hasattr(self.status, "improvement"):
+            self.status.improvement = improvement
         next_stage = self.get_next_stage()
         if next_stage is not None:
             self.stage = next_stage
@@ -133,6 +140,8 @@ def done(
         self.status.result = None
         if hasattr(self.status, "suggestions"):
             self.status.suggestions = None
+        if hasattr(self.status, "inconsistencies"):
+            self.status.inconsistencies = None
 
     def error(
         self, message: str, exception=None, tokens: Optional[List[TokenUsageDTO]] = None
@@ -308,7 +317,7 @@ def __init__(
         base_url: str,
         initial_stages: List[StageDTO],
     ):
-        url = f"{base_url}/api/public/pyris/pipelines/rewriting/runs/{run_id}/status"
+        url = f"{base_url}/api/iris/public/pyris/pipelines/rewriting/runs/{run_id}/status"
         stages = initial_stages or []
         stages.append(
             StageDTO(