Clean and restructure the module

clarifai_grpc_helper.py

@@ -1,67 +1,71 @@
-from global_config import GlobalConfig
-
-######################################################################################################
-# In this section, we set the user authentication, user and app ID, model details, and the URL of
-# the text we want as an input. Change these strings to run your own example.
-######################################################################################################
-
-TEXT_FILE_URL = 'https://samples.clarifai.com/negative_sentence_12.txt'
-
-############################################################################
-# YOU DO NOT NEED TO CHANGE ANYTHING BELOW THIS LINE TO RUN THIS EXAMPLE
-############################################################################
-
 from clarifai_grpc.channel.clarifai_channel import ClarifaiChannel
 from clarifai_grpc.grpc.api import resources_pb2, service_pb2, service_pb2_grpc
 from clarifai_grpc.grpc.api.status import status_code_pb2
 
-channel = ClarifaiChannel.get_grpc_channel()
-stub = service_pb2_grpc.V2Stub(channel)
+from global_config import GlobalConfig
+
+
+CHANNEL = ClarifaiChannel.get_grpc_channel()
+STUB = service_pb2_grpc.V2Stub(CHANNEL)
 
-metadata = (
+METADATA = (
     ('authorization', 'Key ' + GlobalConfig.CLARIFAI_PAT),
-    # ('temp', '0.9'),  # Does not work
 )
 
-userDataObject = resources_pb2.UserAppIDSet(
+USER_DATA_OBJECT = resources_pb2.UserAppIDSet(
     user_id=GlobalConfig.CLARIFAI_USER_ID,
     app_id=GlobalConfig.CLARIFAI_APP_ID
 )
 
-RAW_TEXT = '''You are a helpful, intelligent chatbot. 
-Create the slides for a presentation on the given topic. 
-Include main headings for each slide, detailed bullet points for each slide. 
-Add relevant content to each slide.
-The output should be complete, coherent, and have maximum 255 tokens.
+RAW_TEXT = '''You are a helpful, intelligent chatbot. Create the slides for a presentation on the given topic. Include main headings for each slide, detailed bullet points for each slide. Add relevant content to each slide. Do not output any blank line.
 
 Topic:
 Talk about AI, covering what it is and how it works. Add its pros, cons, and future prospects. Also, cover its job prospects.
 '''
 
-post_model_outputs_response = stub.PostModelOutputs(
-    service_pb2.PostModelOutputsRequest(
-        user_app_id=userDataObject,  # The userDataObject is created in the overview and is required when using a PAT
-        model_id=GlobalConfig.CLARIFAI_MODEL_ID,
-        # version_id=MODEL_VERSION_ID,  # This is optional. Defaults to the latest model version
-        inputs=[
-            resources_pb2.Input(
-                data=resources_pb2.Data(
-                    text=resources_pb2.Text(
-                        # url=TEXT_FILE_URL,
-                        raw=RAW_TEXT
+
+def get_text_from_llm(prompt: str) -> str:
+    post_model_outputs_response = STUB.PostModelOutputs(
+        service_pb2.PostModelOutputsRequest(
+            user_app_id=USER_DATA_OBJECT,  # The userDataObject is created in the overview and is required when using a PAT
+            model_id=GlobalConfig.CLARIFAI_MODEL_ID,
+            # version_id=MODEL_VERSION_ID,  # This is optional. Defaults to the latest model version
+            inputs=[
+                resources_pb2.Input(
+                    data=resources_pb2.Data(
+                        text=resources_pb2.Text(
+                            raw=prompt
+                        )
                     )
                 )
-            )
-        ]
-    ),
-    metadata=metadata
-)
-if post_model_outputs_response.status.code != status_code_pb2.SUCCESS:
-    print(post_model_outputs_response.status)
-    raise Exception(f"Post model outputs failed, status: {post_model_outputs_response.status.description}")
+            ]
+        ),
+        metadata=METADATA
+    )
+
+    if post_model_outputs_response.status.code != status_code_pb2.SUCCESS:
+        print(post_model_outputs_response.status)
+        raise Exception(f"Post model outputs failed, status: {post_model_outputs_response.status.description}")
+
+    # Since we have one input, one output will exist here
+    output = post_model_outputs_response.outputs[0]
+
+    # print("Completion:\n")
+    # print(output.data.text.raw)
+
+    return output.data.text.raw
+
+
+if __name__ == '__main__':
+    topic = ('Talk about AI, covering what it is and how it works.'
+             ' Add its pros, cons, and future prospects.'
+             ' Also, cover its job prospects.'
+             )
+    print(topic)
 
-# Since we have one input, one output will exist here
-output = post_model_outputs_response.outputs[0]
+    with open(GlobalConfig.SLIDES_TEMPLATE_FILE, 'r') as in_file:
+        prompt_txt = in_file.read()
+        prompt_txt = prompt_txt.replace('{topic}', topic)
+        response_txt = get_text_from_llm(prompt_txt)
 
-print("Completion:\n")
-print(output.data.text.raw)
+        print('Output:\n', response_txt)