Configure cli

src/rag_eval/agent.py

@@ -52,7 +52,7 @@ async def conocimiento(ctx: RunContext[Deps], query: str) -> str:
     t_embed = time.perf_counter()
 
     search_results = await ctx.deps.vector_search.async_run_query(
-        deployed_index_id=settings.index_name,
+        deployed_index_id=settings.index_deployed_id,
         query=list(query_embedding.embeddings[0]),
         limit=5,
     )
@@ -82,3 +82,11 @@ async def conocimiento(ctx: RunContext[Deps], query: str) -> str:
         for i, result in enumerate(search_results, start=1)
     ]
     return "\n".join(formatted_results)
+
+
+if __name__ == "__main__":
+    deps = Deps(
+        vector_search=settings.vector_search,
+        embedder=settings.embedder,
+    )
+    agent.to_cli_sync(deps=deps)

src/rag_eval/config.py

@@ -22,7 +22,7 @@ class Settings(BaseSettings):
 
     project_id: str
     location: str
-    service_account: str
+    bucket: str
 
     agent_name: str
     agent_instructions: str
@@ -31,6 +31,7 @@ class Settings(BaseSettings):
     agent_thinking: int
 
     index_name: str
+    index_deployed_id: str
     index_endpoint: str
     index_dimensions: int
     index_machine_type: str = "e2-standard-16"
@@ -38,14 +39,6 @@ class Settings(BaseSettings):
     index_destination: str
     index_chunk_limit: int
 
-    bigquery_dataset_id: str
-    bigquery_project_id: str | None = None
-    bigquery_table_ids: dict[str, str]
-
-    bucket: str
-    base_image: str
-    dialogflow_agent_id: str
-    processing_image: str
 
     model_config = SettingsConfigDict(yaml_file=CONFIG_FILE_PATH)
 
@@ -75,12 +68,14 @@ class Settings(BaseSettings):
     @cached_property
     def vector_search(self) -> GoogleCloudVectorSearch:
         """Return a configured vector search client."""
-        return GoogleCloudVectorSearch(
+        vs = GoogleCloudVectorSearch(
             project_id=self.project_id,
             location=self.location,
             bucket=self.bucket,
             index_name=self.index_name,
         )
+        vs.load_index_endpoint(self.index_endpoint)
+        return vs
 
     @cached_property
     def embedder(self) -> Embedder: