Fixes

examples/demo_llama_index_guardrails.py

@@ -1,9 +1,7 @@
 from nemoguardrails import LLMRails, RailsConfig
-from llama_index import GPTVectorStoreIndex, SimpleDirectoryReader, LLMPredictor
-from llama_index.indices.query.base import BaseQueryEngine
 from langchain.llms.base import BaseLLM
 
-from typing import Callable
+from typing import Callable, Any, Coroutine
 
 COLANG_CONFIG = """
 define user express greeting
@@ -26,7 +24,7 @@
 
 # Question answering flow
 define flow
-  user express question
+  user ...
   $answer = execute llama_index_query(query=$last_user_message)
   bot $answer
 
@@ -40,29 +38,49 @@
 """
 
 
-def _get_llama_index_query_engine(llm: BaseLLM):
-    docs = SimpleDirectoryReader(
-        input_files=["../examples/grounding_rail/kb/report.md"]
-    ).load_data()
-    llm_predictor = LLMPredictor(llm=llm)
-    index = GPTVectorStoreIndex.from_documents(docs, llm_predictor=llm_predictor)
-    default_query_engine = index.as_query_engine()
-    return default_query_engine
-
-
-def _get_callable_query_engine(
-    query_engine: BaseQueryEngine
-) -> Callable[[str], str]:
-    async def get_query_response(query: str) -> str:
-        return query_engine.query(query).response
-
-    return get_query_response
+def demo():
+    try:
+        import llama_index
+        from llama_index.indices.query.base import BaseQueryEngine
+        from llama_index.response.schema import StreamingResponse
 
+    except ImportError:
+        raise ImportError(
+            "Could not import llama_index, please install it with "
+            "`pip install llama_index`."
+        )
 
-def demo():
     config = RailsConfig.from_content(COLANG_CONFIG, YAML_CONFIG)
     app = LLMRails(config)
-    query_engine: BaseQueryEngine = _get_llama_index_query_engine(app.llm)
+
+    def _get_llama_index_query_engine(llm: BaseLLM):
+        docs = llama_index.SimpleDirectoryReader(
+            input_files=["../examples/grounding_rail/kb/report.md"]
+        ).load_data()
+        llm_predictor = llama_index.LLMPredictor(llm=llm)
+        index = llama_index.GPTVectorStoreIndex.from_documents(
+            docs, llm_predictor=llm_predictor
+        )
+        default_query_engine = index.as_query_engine()
+        return default_query_engine
+
+    def _get_callable_query_engine(
+        query_engine: BaseQueryEngine,
+    ) -> Callable[[str], Coroutine[Any, Any, str]]:
+        async def get_query_response(query: str) -> str:
+            response = query_engine.query(query)
+            if isinstance(response, StreamingResponse):
+                typed_response = response.get_response()
+            else:
+                typed_response = response
+            response_str = typed_response.response
+            if response_str is None:
+                return ""
+            return response_str
+
+        return get_query_response
+
+    query_engine = _get_llama_index_query_engine(app.llm)
     app.register_action(
         _get_callable_query_engine(query_engine), name="llama_index_query"
     )

requirements.txt

@@ -12,5 +12,4 @@ starlette==0.26.1
 uvicorn==0.21.1
 httpx==0.23.3
 simpleeval==0.9.13
-typing-extensions==4.5.0
-llama_index==0.6.14
+typing-extensions==4.5.0