various updates to support new btree process

Author: cxbxmxcx

avatar2.png

@@ -0,0 +1,97 @@
+import time
+
+import py_trees
+
+from playground.behavior_trees import (
+    create_assistant_action,
+)
+
+search_term = "GPT Agents"
+# Create the root node (sequence)
+root = py_trees.composites.Sequence("RootSequence", memory=True)
+
+selector = py_trees.composites.Selector("Search Selector", memory=True)
+root.add_child(selector)
+
+search_term = "GPT Agents"
+search_youtube_action = create_assistant_action(
+    action_name=f"Search YouTube({search_term})",
+    assistant_name="YouTube Researcher v2",
+    assistant_instructions=f"""
+    Search Term: {search_term}
+    Use the query "{search_term}" to search for videos on YouTube.
+    then for each video download the transcript and summarize it for relevance to {search_term}
+    be sure to include a link to each of the videos,
+    and then save all summarizations to a file called youtube_transcripts.txt
+    If you encounter any errors, please return just the word FAILURE.
+    """,
+)
+selector.add_child(search_youtube_action)
+
+search_term = "OpenAI"
+search_youtube_action = create_assistant_action(
+    action_name=f"Search YouTube({search_term})",
+    assistant_name="YouTube Researcher v2",
+    assistant_instructions=f"""
+    Search Term: {search_term}
+    Use the query "{search_term}" to search for videos on YouTube.
+    then for each video download the transcript and summarize it for relevance to {search_term}
+    be sure to include a link to each of the videos,
+    and then save all summarizations to a file called youtube_transcripts.txt
+    If you encounter any errors, please return just the word FAILURE.
+    """,
+)
+selector.add_child(search_youtube_action)
+
+search_term = "GPT-4o"
+search_youtube_action = create_assistant_action(
+    action_name=f"Search YouTube({search_term})",
+    assistant_name="YouTube Researcher v2",
+    assistant_instructions=f"""
+    Search Term: {search_term}
+    Use the query "{search_term}" to search for videos on YouTube.
+    then for each video download the transcript and summarize it for relevance to {search_term}
+    be sure to include a link to each of the videos,
+    and then save all summarizations to a file called youtube_transcripts.txt
+    If you encounter any errors, please return just the word FAILURE.
+    """,
+)
+selector.add_child(search_youtube_action)
+
+write_post_action = create_assistant_action(
+    action_name="Write Post",
+    assistant_name="Twitter Post Writer",
+    assistant_instructions="""
+    Load the file called youtube_transcripts.txt,
+    analyze the contents for references to search term at the top and then select
+    the most exciting and relevant video related to: 
+    eductional, entertaining, or informative, to post on Twitter.
+    Then write a Twitter post that is relevant to the video,
+    and include a link to the video, along
+    with exciting highlights or mentions, 
+    and save it to a file called youtube_twitter_post.txt.
+    If you encounter any errors, please return just the word FAILURE.
+    """,
+)
+root.add_child(write_post_action)
+
+post_action = create_assistant_action(
+    action_name="Post",
+    assistant_name="Social Media Assistant",
+    assistant_instructions="""
+    Load the file called youtube_twitter_post.txt and post the content to Twitter.
+    If the content is empty please do not post anything.
+    If you encounter any errors, please return just the word FAILURE.
+    """,
+)
+root.add_child(post_action)
+
+
+# Create the behavior tree
+tree = py_trees.trees.BehaviourTree(root)
+
+# Tick the tree to run it
+for i in range(1000):
+    print(f"Tick {i + 1}")
+    tree.tick()
+    time.sleep(30)  # Simulate time between ticks

btree_v3.py

@@ -163,13 +163,22 @@ def stream_worker(assistant_id, thread_id, event_handler):
     overflow-y: auto; /* Enable vertical scrollbar when content exceeds max-height */
     box-sizing: border-box; /* Ensure padding and border are included in the height calculation */
 }
+
+#actionsnew { 
+    color: #000000; 
+ }
+
+#actions { 
+    color: #000000; 
+ }
 """
 
-theme = gr.themes.Default()
+# theme = gr.themes.Default()
 
 # theme = gr.themes.Glass()
 # theme = gr.themes.Monochrome()
 # theme = gr.themes.Soft()
+theme = "gstaff/sketch"
 
 with gr.Blocks(css=custom_css, theme=theme) as demo:
     with gr.Tab(label="Playground"):
@@ -225,4 +234,4 @@ def stream_worker(assistant_id, thread_id, event_handler):
 if __name__ == "__main__":
     demo.launch()
     # use the following to launch in browser with a shareable link
-    #demo.launch(share=True, inbrowser=True)
+    # demo.launch(share=True, inbrowser=True)

main.py

@@ -16,8 +16,8 @@ def __init__(self, search_terms: str, max_results=None):
     def _search(self):
         encoded_search = urllib.parse.quote_plus(self.search_terms)
         BASE_URL = "https://youtube.com"
-        # This filter shows only videos uploaded today, sorted by relevance and between 4 and 20 minutes long
-        url = f"{BASE_URL}/results?search_query={encoded_search}&sp=EgIIAQ%253D%253D"
+        # This filter shows only videos uploaded in the last hour, sorted by relevance
+        url = f"{BASE_URL}/results?search_query={encoded_search}&sp=EgQIARAB"
         response = requests.get(url).text
         while "ytInitialData" not in response:
             response = requests.get(url).text
@@ -97,13 +97,31 @@ def to_json(self, clear_cache=True):
 
 
 @agent_action
-def search_youtube_videos(query: str, max_results=5):
+def search_youtube_videos(query: str, max_results=10):
     """Searches for videos on YouTube based on the query string and returns the video titles and IDs."""
     results = YoutubeSearch(query, max_results=max_results)
     videos = results.videos
     return [{"title": video["title"], "id": video["id"]} for video in videos]
 
 
+search_cache = []
+
+
+@agent_action
+def search_new_youtube_videos(query: str, max_results=10):
+    """Searches for new videos on YouTube based on the query string and returns the video titles and IDs."""
+    global search_cache
+    results = YoutubeSearch(query, max_results=max_results)
+    videos = results.videos
+    new_videos = [
+        {"title": video["title"], "id": video["id"]}
+        for video in videos
+        if video["id"] not in search_cache
+    ]
+    search_cache += [video["id"] for video in videos]
+    return new_videos
+
+
 @agent_action
 def download_transcripts(video_ids):
     """Downloads the transcripts for the given video IDs."""

playground/assistant_actions/youtube_search.py

@@ -65,7 +65,7 @@ def list_assistants(self):
     def get_assistant_by_name(self, name):
         assistants = self.list_assistants()
         for assistant in assistants.data:
-            if assistant.name.lower().startswith(name.lower()):
+            if assistant.name and assistant.name.lower().startswith(name.lower()):
                 return assistant
         return None
 

playground/assistants_api.py

@@ -182,7 +182,7 @@ def assistant_selected_change(assistant_key):
         # assistant_files_new = gr.Textbox(
         #     label="Add Files or Functions", placeholder="+ Files, + Functions"
         # )
-        with gr.Accordion("Actions", open=False):
+        with gr.Accordion("Actions", open=False, elem_id="actionsnew"):
             assistant_actions_new = gr.CheckboxGroup(
                 label="Actions", choices=action_choices, interactive=True
             )
@@ -223,7 +223,7 @@ def assistant_selected_change(assistant_key):
         assistant_tools = gr.CheckboxGroup(
             label="Tools", choices=["File search", "Code interpreter"]
         )
-        with gr.Accordion("Actions", open=False):
+        with gr.Accordion("Actions", open=False, elem_id="actions"):
             assistant_actions = gr.CheckboxGroup(
                 label="Actions", choices=action_choices, interactive=True
             )