20230619

digester/chatgpt_service.py

@@ -96,6 +96,11 @@ class ChatGPTService:
             chatbot[-1] = (user_say, chatbot_say)
         yield chatbot, history, status, source_md
 
+    @staticmethod
+    def say_using_ginputs(user_say, chatbot_say, status, g_inputs: GradioInputs, is_append=True):
+        yield from ChatGPTService.say(user_say, chatbot_say,
+                                      g_inputs.chatbot, g_inputs.history, status, g_inputs.source_md, is_append)
+
     @staticmethod
     def get_reduce_token_percent(text):
         try:

digester/gradio_method_service.py

@@ -257,11 +257,6 @@ Example format:
 
     FINAL_SUMMARY_PROMPT = Prompt(
         prompt_prefix="""
-[VIDEO_TYPE]
-This is the video type
-N things: The youtube will shows N items that will be described in the video. For example "17 cheap purchases that save me time", "10 AMAZING Ways AutoGPT Is Being Used RIGHT NOW"
-Tutorials: how to do or make something in order to teach a skill or how to use a product or software
-
 [TITLE]
 {title}
 
@@ -272,7 +267,7 @@ Tutorials: how to do or make something in order to teach a skill or how to use a
 """,
         prompt_suffix="""
 [TASK]
-Summarize the above transcript. Step by step showing points for the main concepts.
+Summarize the above points under 30 words. Step by step showing points for the main concepts.
 Use markdown format.
 Must use language: {language}
 {task_constraint} 
@@ -288,6 +283,8 @@ Additionally, since it is a N things video, the summary should include the N ite
 """,
         "Tutorials": """
 Additionally, since it is a Tutorial video, provide step by step instructions for the tutorial. 
+""",
+        "Others": """
 """,
     }
     FINAL_SUMMARY_FORMAT_CONSTRAINTS = {
@@ -298,7 +295,14 @@ Items mentioned in the video: (content of N things. Put different appropriate em
 Instructions: (step by step instructions, up to five concise bullet points, less than 20 words. Put different appropriate emoji for each bullet point)
 """,
         "Others": """
-Highlights: [Emoji] (content of highlights, up to five concise bullet points, less than 20 words. Put different appropriate emoji for each bullet point)
+Highlights:
+- [Emoji] (content of highlights)
+- [Emoji] (content of highlights)
+- [Emoji] (content of highlights)
+- [Emoji] (content of highlights)
+- [Emoji] (content of highlights)
+
+For highlight, up to five concise bullet points, less than 15 words for each bullet point. Put different appropriate emoji for each bullet point
 """,
     }
 
@@ -334,10 +338,13 @@ Highlights: [Emoji] (content of highlights, up to five concise bullet points, le
                         )
         prompt_show_user = "Classify the video type for me"
         response, len_prompts = yield from ChatGPTService.trigger_callgpt_pipeline(prompt, prompt_show_user, g_inputs)
+        yield from ChatGPTService.say_using_ginputs(None, f"{provide_text_with_css('WARN', 'yellow')} test", "Success", g_inputs)
         try:
             video_type = json.loads(response)['type']
+            if video_type not in cls.FINAL_SUMMARY_TASK_CONSTRAINTS.keys():
+                raise Exception(f"Video type is not valid: {video_type}. Use default: Others")
         except Exception as e:
-            # TODO: Exception handling, show error in UI
+            yield from ChatGPTService.say_using_ginputs(None, f"{provide_text_with_css('WARN', 'yellow')} {e}", "Success", g_inputs)
             video_type = 'Others'
         return video_type
 

digester/gradio_ui_service.py

@@ -8,7 +8,7 @@ title_html = """
 <p align=\"center\">
 DigestEverythingGPT leverages ChatGPT/LLMs to help users quickly understand essential information from various forms of content, such as podcasts, YouTube videos, and PDF documents.<br>
 The prompt engineering is chained and tuned so that is result is of high quality and fast. It is not a simple single query and response tool.<br>
-Version 20230617 (
+Version 20230619 (
 <a href="https://github.com/michaelthwan/digest-everything-gpt"><i class="fa fa-github"></i> Github</a>
 ) (
 <a href="https://huggingface.co/spaces/michaelthwan/digest-everything-gpt"> HFSpace</a>

digester/util.py

@@ -22,6 +22,7 @@ class GradioInputs:
         self.language_textbox = language_textbox
         self.chatbot = chatbot
         self.history = history
+        self.source_md = f"[{self.source_textbox}] {self.source_target_textbox}"
 
 
 class Prompt:

requirements.txt

@@ -4,4 +4,4 @@ tiktoken>=0.3.3
 openai
 Markdown
 latex2mathml
-everything2text4prompt==0.0.14
+everything2text4prompt