working on retrieve

Docker/docker-compose.yaml

@@ -13,6 +13,7 @@ services:
       LANGFUSE_HOST: ${LANGFUSE_HOST}
       LANGFUSE_PUBLIC_KEY: ${LANGFUSE_PUBLIC_KEY}
       LANGFUSE_SECRET_KEY: ${LANGFUSE_SECRET_KEY}
+      ELASTICSEARCH_INDEX: ${ELASTICSEARCH_INDEX}
     
     extra_hosts:
       - "host.docker.internal:host-gateway"

Docker/src/server.py

@@ -14,6 +14,7 @@ from langchain_core.prompts import ChatPromptTemplate
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger("brunix-engine")
 
+
 class BrunixEngine(brunix_pb2_grpc.AssistanceEngineServicer):
     def __init__(self):
 
@@ -24,25 +25,47 @@ class BrunixEngine(brunix_pb2_grpc.AssistanceEngineServicer):
 
         self.llm = Ollama(base_url=self.base_url, model=self.model_name)
 
-        self.embeddings = OllamaEmbeddings(base_url=self.base_url, model="nomic-embed-text")
+        self.embeddings = OllamaEmbeddings(
+            base_url=self.base_url, model="qwen3-embedding:0.6b"
+        )
 
         es_url = os.getenv("ELASTICSEARCH_URL", "http://elasticsearch:9200")
         logger.info(f"ElasticSearch on: {es_url}")
 
         self.vector_store = ElasticsearchStore(
             es_url=es_url,
-            index_name="avap_manuals",
-            embedding=self.embeddings
+            index_name=os.getenv("ELASTICSEARCH_INDEX"),
+            embedding=self.embeddings,
+            query_field="text",
+            vector_query_field="embedding",
         )
 
+    def format_context(docs) -> str:
+        parts = []
+        for i, d in enumerate(docs, start=1):
+            meta = d.metadata or {}
+            source = meta.get("source", "unknown")
+            doc_id = meta.get("doc_id", "unknown")
+            chunk_id = meta.get("chunk_id", "unknown")
+
+            parts.append(
+                f"[{i}] source={source} doc_id={doc_id} chunk_id={chunk_id}\n{d.page_content}"
+            )
+        return "\n\n---\n\n".join(parts)
+
     def AskAgent(self, request, context):
         logger.info(f"request {request.session_id}): {request.query[:50]}.")
 
+        docs_and_scores = self.vector_store.similarity_search_with_score(
+            request.query, k=4
+        )
+
         try:
-            context_text = "AVAP is a virtual programming language for API development."
+            context_text = self.format_context([doc for doc, _ in docs_and_scores])
             # 4. Prompt Engineering
             prompt = ChatPromptTemplate.from_template("""
-            You are Brunix, the 101OBEX artificial intelligence for the AVAP Sphere platform. Respond in a professional manner.
+            You are a helpful assistant. Use the following retrieved documents to answer the question. 
+                                                      If you don't know the answer, say you don't know.
             
             CONTEXT:
             {context}
@@ -53,18 +76,21 @@ class BrunixEngine(brunix_pb2_grpc.AssistanceEngineServicer):
 
             chain = prompt | self.llm
 
-            for chunk in chain.stream({"context": context_text, "question": request.query}):
+            for chunk in chain.stream(
+                {"context": context_text, "question": request.query}
+            ):
                 yield brunix_pb2.AgentResponse(
-                    text=str(chunk),
-                    avap_code="AVAP-2026",
-                    is_final=False
+                    text=str(chunk), avap_code="AVAP-2026", is_final=False
                 )
 
             yield brunix_pb2.AgentResponse(text="", avap_code="", is_final=True)
 
         except Exception as e:
             logger.error(f"Error in AskAgent: {str(e)}")
-            yield brunix_pb2.AgentResponse(text=f"[Error Motor]: {str(e)}", is_final=True)
+            yield brunix_pb2.AgentResponse(
+                text=f"[Error Motor]: {str(e)}", is_final=True
+            )
+
 
 def serve():
 
@@ -73,15 +99,16 @@ def serve():
     brunix_pb2_grpc.add_AssistanceEngineServicer_to_server(BrunixEngine(), server)
 
     SERVICE_NAMES = (
-        brunix_pb2.DESCRIPTOR.services_by_name['AssistanceEngine'].full_name,
+        brunix_pb2.DESCRIPTOR.services_by_name["AssistanceEngine"].full_name,
         reflection.SERVICE_NAME,
     )
     reflection.enable_server_reflection(SERVICE_NAMES, server)
 
-    server.add_insecure_port('[::]:50051')
+    server.add_insecure_port("[::]:50051")
     logger.info("Brunix Engine on port 50051")
     server.start()
     server.wait_for_termination()
 
-if __name__ == '__main__':
+
+if __name__ == "__main__":
     serve()