improve example

Author: Josephrp

src/distilabel/llms/oneai.py

@@ -60,31 +60,29 @@ class OneAI(AsyncLLM):
   
         ```python
         from distilabel.steps.tasks import TextGeneration
+        from distilabel.pipeline import Pipeline
         from distilabel.llms.oneai import OneAI
 
-        text_gen = TextGeneration(
-            llm = OneAI(api_key="api.key")  # yi-large is the default model
-        )
 
-        text_gen.load()
+        with Pipeline(name="pipeline") as pipeline:
+            text_gen = TextGeneration(
+                llm = OneAI(api_key="sk-01ww0611-qitFVu88O6")  # yi-large is the default model
+            )
 
-        wordphrases = "During his presidency, a number of improvements to the campus were made. The Georgetown University Hospital was opened and the first patient was accepted."
+            text_gen.load()
 
-        metadata_prompt = "WORD PHRASES:\n\n{wordphrases}\n\n you will recieve a text or a question, produce metadata operator pairs for the text . ONLY PROVIDE THE FINAL JSON , DO NOT PRODUCE ANY ADDITION INSTRUCTION , ONLY PRODUCE ONE METADATA STRING PER OPERATOR:"
+            metadata_prompt = "WORD PHRASES:\n\nDuring his presidency, a number of improvements to the campus were made. The Georgetown University Hospital was opened and the first patient was accepted.\n\n you will recieve a text or a question, produce metadata operator pairs for the text . ONLY PROVIDE THE FINAL JSON , DO NOT PRODUCE ANY ADDITION INSTRUCTION , ONLY PRODUCE ONE METADATA STRING PER OPERATOR:"
 
-        result = next(
-            text_gen.process(
-                [{"instruction": metadata_prompt}]
+            result = next(
+                        text_gen.process(
+                    [{"instruction": metadata_prompt}]
+                        )
             )
-        )
-        # result
-        # [
-        #     {
-        #         'instruction': 'your instruction',
-        #         'model_name': 'yi-large',
-        #         'generation': 'generation',
-        #     }
-        # ]
+
+            print(result)
+        #   [{'instruction': 'WORD PHRASES:\n\nDuring his presidency, a number of improvements to the campus were made. The Georgetown University Hospital was opened and the first patient was accepted.\n\n you will recieve a text or a question, produce metadata operator pairs for the text . ONLY PROVIDE THE FINAL JSON , DO NOT PRODUCE ANY ADDITION INSTRUCTION , ONLY PRODUCE ONE METADATA STRING PER OPERATOR:', 'generation': '```json\n{\n  "entities": [\n    {\n      "entity": "Georgetown University Hospital",\n      "start": 4,\n      "end": 27,\n      "type": "Organization"\n    },\n    {\n      "entity": "opened",\n      "start": 28,\n      "end": 34,\n      "type": "Event"\n    },\n    {\n      "entity": "the first patient",\n      "start": 35,\n      "end": 48,\n', 'distilabel_metadata': {'raw_output_text_generation_0': '```json\n{\n  "entities": [\n    {\n      "entity": "Georgetown University Hospital",\n      "start": 4,\n      "end": 27,\n      "type": "Organization"\n    },\n    {\n      "entity": "opened",\n      "start": 28,\n      "end": 34,\n      "type": "Event"\n    },\n    {\n      "entity": "the first patient",\n      "start": 35,\n      "end": 48,\n'}, 'model_name': 'yi-large'}]
+
+
         ```
     """