Update uncertainty/README.md

uncertainty/README.md

@@ -70,7 +70,49 @@ Scenario 2. Predicting the certainty score from the question only, *prior* to ge
 
 ### Quickstart Example
 
-
+First, see information elsewhere in this repo on how to start up a vLLM server hosting the LoRAs and/or aLoRAs. Once this server is started, it can be queried via the OpenAI API. 
+An example for this intrinsic follows. 
+
+
+```
+import os
+import openai
+import json
+import granite_common
+
+QUESTION = "What is IBM?"
+RESPONSE = ... # this should be generated by the base model corresponding to the chosen adapter
+
+request = {
+  "messages": [
+    {
+      "content": QUESTION,
+      "role": "user"
+    },
+    {
+      "content": RESPONSE,
+      "role": "assistant"
+    }
+  ],
+  "model": "uncertainty",
+  "temperature": 0.0
+}
+openai_base_url = ...
+openai_api_key = ...
+io_yaml_file = "./rag_intrinsics_lib/uncertainty/.../io.yaml"
+
+rewriter = granite_common.IntrinsicsRewriter(config_file=io_yaml_file)
+result_processor = granite_common.IntrinsicsResultProcessor(config_file=io_yaml_file)
+
+rewritten_request = rewriter.transform(request)
+
+client = openai.OpenAI(base_url=openai_base_url, api_key=openai_api_key)
+chat_completion = client.chat.completions.create(**rewritten_request.model_dump())
+
+transformed_completion = result_processor.transform(chat_completion)
+
+print(transformed_completion.model_dump_json(indent=2))
+```