update to SpringAI export

.gitignore

@@ -69,3 +69,4 @@ src/client/spring_ai/target/classes/*
 api_server_key
 .env
 
+optimizer_settings.json

docs/content/advanced/springai.md

@@ -41,7 +41,7 @@ export OPENAI_EMBEDDING_MODEL=text-embedding-3-small
 export OLLAMA_CHAT_MODEL="llama3.1"
 export OLLAMA_EMBEDDING_MODEL=mxbai-embed-large
 export OLLAMA_BASE_URL="http://<OLLAMA_SERVER>:11434"
-export CONTEXT_INSTR=" You are an assistant for question-answering tasks. Use the retrieved Documents and history to answer the question as accurately and comprehensively as possible. Keep your answer grounded in the facts of the Documents, be concise, and reference the Documents where possible. If you don't know the answer, just say that you are sorry as you don't haven't enough information. "
+export SYS_INSTR=" You are an assistant for question-answering tasks. Use the retrieved Documents and history to answer the question as accurately and comprehensively as possible. Keep your answer grounded in the facts of the Documents, be concise, and reference the Documents where possible. If you don't know the answer, just say that you are sorry as you don't haven't enough information. "
 export TOP_K=4
 export VECTOR_STORE=TEXT_EMBEDDING_3_SMALL_8191_1639_COSINE
 export PROVIDER=openai

src/client/content/config/tabs/settings.py

@@ -172,31 +172,32 @@ def spring_ai_conf_check(ll_model: dict, embed_model: dict) -> str:
 
 def spring_ai_obaas(src_dir, file_name, provider, ll_config, embed_config):
     """Get the users CTX Prompt"""
-    ctx_prompt = next(
+
+    sys_prompt = next(
         item["prompt"]
         for item in state.prompt_configs
-        if item["name"] == state.client_settings["prompts"]["ctx"] and item["category"] == "ctx"
+        if item["name"] == state.client_settings["prompts"]["sys"] and item["category"] == "sys"
     )
-
+    logger.info(f"Prompt used in export:\n{sys_prompt}")
     with open(src_dir / "templates" / file_name, "r", encoding="utf-8") as template:
         template_content = template.read()
 
     database_lookup = st_common.state_configs_lookup("database_configs", "name")
 
     formatted_content = template_content.format(
         provider=provider,
-        ctx_prompt=f"{ctx_prompt}",
+        sys_prompt=f"{sys_prompt}",
         ll_model=ll_config,
         vector_search=embed_config,
         database_config=database_lookup[state.client_settings["database"]["alias"]],
     )
 
     if file_name.endswith(".yaml"):
-        ctx_prompt = json.dumps(ctx_prompt, indent=True)  # Converts it into a valid JSON string (preserving quotes)
+        sys_prompt = json.dumps(sys_prompt, indent=True)  # Converts it into a valid JSON string (preserving quotes)
 
         formatted_content = template_content.format(
             provider=provider,
-            ctx_prompt=ctx_prompt,
+            sys_prompt=sys_prompt,
             ll_model=ll_config,
             vector_search=embed_config,
             database_config=database_lookup[state.client_settings["database"]["alias"]],

src/client/spring_ai/README.md

@@ -32,7 +32,7 @@ export OPENAI_EMBEDDING_MODEL=text-embedding-3-small
 export OLLAMA_CHAT_MODEL="llama3.1"
 export OLLAMA_EMBEDDING_MODEL=mxbai-embed-large
 export OLLAMA_BASE_URL="http://<OLLAMA_SERVER>:11434"
-export CONTEXT_INSTR=" You are an assistant for question-answering tasks. Use the retrieved Documents and history to answer the question as accurately and comprehensively as possible. Keep your answer grounded in the facts of the Documents, be concise, and reference the Documents where possible. If you don't know the answer, just say that you are sorry as you don't haven't enough information. "
+export SYS_INSTR=" You are an assistant for question-answering tasks. Use the retrieved Documents and history to answer the question as accurately and comprehensively as possible. Keep your answer grounded in the facts of the Documents, be concise, and reference the Documents where possible. If you don't know the answer, just say that you are sorry as you don't haven't enough information. "
 export TOP_K=4
 export VECTOR_STORE=TEXT_EMBEDDING_3_SMALL_8191_1639_COSINE
 export PROVIDER=openai

src/client/spring_ai/pom.xml

@@ -6,7 +6,7 @@
 	<parent>
 		<groupId>org.springframework.boot</groupId>
 		<artifactId>spring-boot-starter-parent</artifactId>
-		<version>3.4.5</version>
+		<version>3.4.9</version>
 		<relativePath /> <!-- lookup parent from repository -->
 	</parent>
 	<groupId>com.example</groupId>

src/client/spring_ai/src/main/java/org/springframework/ai/openai/samples/helloworld/Config.java

@@ -35,7 +35,7 @@ public String legacyTable(@Value("${aims.vectortable.name}") String table) {
     }
 
     @Bean
-    public String contextInstr(@Value("${aims.context_instr}") String instr) {
+    public String contextInstr(@Value("${aims.sys_instr}") String instr) {
         return instr;
     }
 

src/client/spring_ai/src/main/java/org/springframework/ai/openai/samples/helloworld/PromptBuilderService.java

@@ -37,14 +37,15 @@ public Prompt buildPrompt(String message, String contextInstr, int topK) {
 
                 INSTRUCTIONS:""";
 
+        // That's a standard RAG instruction, provided for convenience to change the contextInstr coming by the Oracle AI Optimizer export
         String defaultInstr = """
                 Answer the users question using the DOCUMENTS text above.
                 Keep your answer ground in the facts of the DOCUMENTS.
                 If the DOCUMENTS doesn’t contain the facts to answer the QUESTION, return:
                 I'm sorry but I haven't enough information to answer.
                 """;
 
-        template += "\n" + defaultInstr;
+        template += "\n" + contextInstr;
 
         List<Document> similarDocuments = vectorStore.similaritySearch(
                 SearchRequest.builder().query(message).topK(topK).build());

src/client/spring_ai/src/main/resources/application-dev.yml

@@ -52,7 +52,7 @@ spring:
         options: 
           model: ${OLLAMA_EMBEDDING_MODEL}
 aims:
-  context_instr: ${CONTEXT_INSTR}
+  sys_instr: ${SYS_INSTR}
   vectortable:
     name: ${VECTOR_STORE}
   rag_params: 

src/client/spring_ai/templates/obaas.yaml

@@ -41,7 +41,7 @@ spring:
         options: 
           model: \"{vector_search[id]}\"        
 aims:
-  context_instr: \"{ctx_prompt}\"
+  sys_instr: \"{sys_prompt}\"
   vectortable:
     name: {vector_search[vector_store]}
   rag_params: 

src/client/spring_ai/templates/start.sh

@@ -38,7 +38,7 @@ export DB_USERNAME="{database_config[user]}"
 export DB_PASSWORD="{database_config[password]}"
 export DISTANCE_TYPE="{vector_search[distance_metric]}"
 export INDEX_TYPE="{vector_search[index_type]}"
-export CONTEXT_INSTR="{ctx_prompt}"
+export SYS_INSTR="{sys_prompt}"
 export TOP_K="{vector_search[top_k]}"
 
 export VECTOR_STORE="{vector_search[vector_store]}"

src/pyproject.toml

@@ -46,7 +46,7 @@ server = [
     "langchain-perplexity==0.1.2",
     "langchain-xai==0.2.5",
     "langgraph==0.6.6",
-    "litellm==1.76.1",
+    "litellm==1.77.1",
     "llama-index==0.13.3",
     "lxml==6.0.0",
     "matplotlib==3.10.6",