RAG GetChatCompletionsAsync function response.

I have been dabbling with the RAG architecture for sometime. I liked how it makes one to focus on the grounding data and as a beginner this approach helped me a lot to explore using multiple data sources. All was going well until couple of days back when i revisited my project with some new ideas. 

The function call 

chatCompletionsOptions = new ChatCompletionsOptions()
            {
                Messages =
                {
                    new ChatMessage(ChatRole.System, systemPrompt),
                    new ChatMessage(ChatRole.User, userPrompt),
                },
                Temperature = (float)0.7,
                MaxTokens = 3000,
                NucleusSamplingFactor = (float)0.95,
                FrequencyPenalty = 0,
                PresencePenalty = 0,
                AzureExtensionsOptions = new AzureChatExtensionsOptions()
                {
                    Extensions =
                    {
                        new AzureCognitiveSearchChatExtensionConfiguration()
                        {
                            SearchEndpoint = new Uri(searchEndpoint),
                            IndexName = searchIndexName,
                            SearchKey = new AzureKeyCredential(searchKey),
                            EmbeddingEndpoint = new Uri(apiBase+"openai/deployments/"+ModelName+"/embeddings?api-version="+version+"),
                            EmbeddingKey = new AzureKeyCredential(apiKey),
                            SemanticConfiguration = semanticConfiguration,
                            QueryType = AzureCognitiveSearchQueryType.Vector,
                            ShouldRestrictResultScope = true
                        }
                    }
                },
            };
            Response<ChatCompletions> response = await client.GetChatCompletionsAsync(deploymentId, chatCompletionOption);
                var message = response.Value.Choices[0].Message;

 used to follow RAG and return a grounded response. But at least since the last couple of days this is responding with a generic message saying no information found on the documents looked up. I used the search explorer in the index to check if index was corrupted some how but that is not the case. 

I was also able to get response when I used AI search like below. 

var searchOptions = new SearchOptions
            {
                VectorSearch = new()
                {
                    Queries = { new VectorizedQuery(queryEmbeddings.ToArray()) { KNearestNeighborsCount = k, Fields = { "contentVector" } } }
                },
                Filter = filter,
                Select = { "title", "content", "category" },
            };

            SearchResults<SearchDocument> response = await searchClient.SearchAsync<SearchDocument>(null, searchOptions);

 I felt like the issue is the search is not happening when