diff --git a/bots/admin.py b/bots/admin.py index d8357473f..d71972450 100644 --- a/bots/admin.py +++ b/bots/admin.py @@ -69,11 +69,11 @@ class Meta: widgets = { "platform": forms.Select( attrs={ - "--hideshow-fields": "fb_page_id,fb_page_name,fb_page_access_token,ig_account_id,ig_username,wa_phone_number,wa_phone_number_id,slack_channel_id,slack_channel_hook_url,slack_access_token", + "--hideshow-fields": "fb_page_id,fb_page_name,fb_page_access_token,ig_account_id,ig_username,wa_phone_number,wa_phone_number_id,slack_team_id,slack_team_name,slack_channel_id,slack_channel_name,slack_channel_hook_url,slack_access_token,slack_read_receipt_msg,slack_create_personal_channels", "--show-on-1": "fb_page_id,fb_page_name,fb_page_access_token", "--show-on-2": "fb_page_id,fb_page_name,fb_page_access_token,ig_account_id,ig_username", "--show-on-3": "wa_phone_number,wa_phone_number_id", - "--show-on-4": "slack_channel_id,slack_channel_hook_url,slack_access_token", + "--show-on-4": "slack_team_id,slack_team_name,slack_channel_id,slack_channel_name,slack_channel_hook_url,slack_access_token,slack_read_receipt_msg,slack_create_personal_channels", }, ), } @@ -93,13 +93,17 @@ class BotIntegrationAdmin(admin.ModelAdmin): "fb_page_id", "wa_phone_number", "slack_channel_id", + "billing_account_uid", ] list_display = [ - "__str__", + "name", + "get_display_name", "platform", "wa_phone_number", "created_at", "updated_at", + "billing_account_uid", + "saved_run", "analysis_run", ] list_filter = ["platform"] @@ -111,6 +115,7 @@ class BotIntegrationAdmin(admin.ModelAdmin): readonly_fields = [ "fb_page_access_token", "slack_access_token", + "slack_channel_hook_url", "view_analysis_results", "view_conversations", "view_messsages", @@ -142,9 +147,14 @@ class BotIntegrationAdmin(admin.ModelAdmin): "ig_username", "wa_phone_number", "wa_phone_number_id", + "slack_team_id", + "slack_team_name", "slack_channel_id", + "slack_channel_name", "slack_channel_hook_url", "slack_access_token", + "slack_read_receipt_msg", + "slack_create_personal_channels", ] }, ), @@ -165,7 +175,6 @@ class BotIntegrationAdmin(admin.ModelAdmin): "fields": [ "show_feedback_buttons", "analysis_run", - "enable_analysis", "view_analysis_results", ] }, @@ -234,7 +243,7 @@ def view_analysis_results(self, bi: BotIntegration): .order_by("-count") .values_list(key, "count") ) - if val + if val is not None ] for key in nested_keys } @@ -397,7 +406,7 @@ class MessageAdmin(admin.ModelAdmin): "role", "created_at", "feedbacks", - "wa_delivered", + "msg_delivered", ] readonly_fields = [ "conversation", @@ -405,7 +414,7 @@ class MessageAdmin(admin.ModelAdmin): "content", "display_content", "created_at", - "wa_msg_id", + "platform_msg_id", "saved_run", "analysis_run", "prev_msg_content", @@ -435,7 +444,7 @@ def get_fieldsets(self, request, msg: Message = None): "conversation", "role", "created_at", - "wa_msg_id", + "platform_msg_id", ] }, ), @@ -480,16 +489,19 @@ def get_fieldsets(self, request, msg: Message = None): ) return fieldsets - def wa_delivered(self, msg: Message): + def msg_delivered(self, msg: Message): if ( + # user messages are delivered already msg.role != CHATML_ROLE_ASSISSTANT - or msg.conversation.bot_integration.platform != Platform.WHATSAPP + # we only have delivery status for whatsapp and slack + or msg.conversation.bot_integration.platform + not in [Platform.WHATSAPP, Platform.SLACK] ): raise Message.DoesNotExist - return bool(msg.wa_msg_id) + return bool(msg.platform_msg_id) - wa_delivered.short_description = "Delivered" - wa_delivered.boolean = True + msg_delivered.short_description = "Delivered" + msg_delivered.boolean = True def prev_msg_content(self, message: Message): prev_msg = message.get_previous_by_created_at() diff --git a/bots/migrations/0038_remove_botintegration_enable_analysis.py b/bots/migrations/0038_remove_botintegration_enable_analysis.py new file mode 100644 index 000000000..f0b5938eb --- /dev/null +++ b/bots/migrations/0038_remove_botintegration_enable_analysis.py @@ -0,0 +1,16 @@ +# Generated by Django 4.2.3 on 2023-09-13 15:18 + +from django.db import migrations + + +class Migration(migrations.Migration): + dependencies = [ + ("bots", "0037_savedrun_parent_not_self"), + ] + + operations = [ + migrations.RemoveField( + model_name="botintegration", + name="enable_analysis", + ), + ] diff --git a/bots/migrations/0039_botintegration_slack_read_receipt_msg.py b/bots/migrations/0039_botintegration_slack_read_receipt_msg.py new file mode 100644 index 000000000..4a8e7c345 --- /dev/null +++ b/bots/migrations/0039_botintegration_slack_read_receipt_msg.py @@ -0,0 +1,21 @@ +# Generated by Django 4.2.5 on 2023-09-14 15:13 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + dependencies = [ + ("bots", "0038_remove_botintegration_enable_analysis"), + ] + + operations = [ + migrations.AddField( + model_name="botintegration", + name="slack_read_receipt_msg", + field=models.TextField( + blank=True, + default="Results may take up to 1 minute, we appreciate your patience.", + help_text="Bot's Slack read receipt message - if set, and platform is Slack, the bot will send this message to mark the user message as read and then delete it when it has a response ready", + ), + ), + ] diff --git a/bots/migrations/0040_remove_conversation_bots_conver_bot_int_a83907_idx_and_more.py b/bots/migrations/0040_remove_conversation_bots_conver_bot_int_a83907_idx_and_more.py new file mode 100644 index 000000000..fce918816 --- /dev/null +++ b/bots/migrations/0040_remove_conversation_bots_conver_bot_int_a83907_idx_and_more.py @@ -0,0 +1,296 @@ +# Generated by Django 4.2.3 on 2023-09-19 09:00 + +from django.db import migrations, models +from django.db.models import Q + +from bots.models import Platform + + +def forwards_func(apps, schema_editor): + Conversation = apps.get_model("bots", "Conversation") + BotIntegration = apps.get_model("bots", "BotIntegration") + db_alias = schema_editor.connection.alias + + # for backwards compatibility, we have to get the team id from the channel hook url + for bi in ( + BotIntegration.objects.using(db_alias) + .filter( + platform=Platform.SLACK, + ) + .exclude( + slack_channel_hook_url="", + ) + ): + bi.slack_team_id = ( + bi.slack_team_id + or bi.slack_channel_hook_url.removeprefix( + "https://hooks.slack.com/services/" + ).split("/")[0] + ) + bi.save() + + for conv in Conversation.objects.using(db_alias).all(): + bi = conv.bot_integration + if bi.platform == Platform.SLACK: + conv.slack_team_id = conv.slack_team_id or bi.slack_team_id + conv.slack_channel_id = conv.slack_channel_id or bi.slack_channel_id + conv.save() + + qs = Conversation.objects.using(db_alias).filter( + Q(slack_channel_id="") | Q(slack_user_id="") | Q(slack_team_id="") + ) + for convo in qs: + convo.slack_user_id = convo.slack_user_id or None + convo.save() + + +def backwards_func(apps, schema_editor): + Conversation = apps.get_model("bots", "Conversation") + db_alias = schema_editor.connection.alias + + qs = Conversation.objects.using(db_alias).filter( + Q(slack_channel_id=None) | Q(slack_user_id=None) | Q(slack_team_id=None) + ) + for convo in qs: + convo.slack_user_id = convo.slack_user_id or "" + convo.save() + + +class Migration(migrations.Migration): + dependencies = [ + ("bots", "0039_botintegration_slack_read_receipt_msg"), + ] + + operations = [ + migrations.RemoveIndex( + model_name="conversation", + name="bots_conver_bot_int_a83907_idx", + ), + migrations.RemoveField( + model_name="message", + name="wa_msg_id", + ), + migrations.AddField( + model_name="botintegration", + name="slack_channel_name", + field=models.TextField( + blank=True, + default="", + help_text="Bot's Public Slack channel name without # (only for display)", + ), + ), + migrations.AddField( + model_name="botintegration", + name="slack_create_personal_channels", + field=models.BooleanField( + default=False, + help_text="If set, the bot will create a personal channel for each user in the public channel", + ), + ), + migrations.AddField( + model_name="botintegration", + name="slack_team_id", + field=models.CharField( + blank=True, + default=None, + help_text="Bot's Slack team id (mandatory)", + max_length=256, + null=True, + ), + ), + migrations.AddField( + model_name="botintegration", + name="slack_team_name", + field=models.TextField( + blank=True, + default="", + help_text="Bot's Slack team/workspace name (only for display)", + ), + ), + migrations.AddField( + model_name="conversation", + name="slack_channel_id", + field=models.TextField( + blank=True, + default=None, + help_text="Slack channel id, can be different than the bot integration's public channel (mandatory)", + max_length=256, + null=True, + ), + ), + migrations.AddField( + model_name="conversation", + name="slack_channel_is_personal", + field=models.BooleanField( + default=False, + help_text="Whether this is a personal slack channel between the bot and the user", + ), + ), + migrations.AddField( + model_name="conversation", + name="slack_channel_name", + field=models.TextField( + blank=True, + default="", + help_text="Bot's Slack channel name without # (only for display)", + ), + ), + migrations.AddField( + model_name="conversation", + name="slack_team_id", + field=models.TextField( + blank=True, + default=None, + help_text="Slack team id - redundant with bot integration (mandatory)", + max_length=256, + null=True, + ), + ), + migrations.AddField( + model_name="conversation", + name="slack_user_name", + field=models.TextField( + blank=True, + default="", + help_text="User's name in slack (only for display)", + ), + ), + migrations.AddField( + model_name="message", + name="platform_msg_id", + field=models.TextField( + blank=True, default="", help_text="The platform's delivered message id" + ), + ), + migrations.AlterField( + model_name="botintegration", + name="fb_page_access_token", + field=models.TextField( + blank=True, + default="", + editable=False, + help_text="Bot's Facebook page access token (mandatory)", + ), + ), + migrations.AlterField( + model_name="botintegration", + name="fb_page_id", + field=models.CharField( + blank=True, + default=None, + help_text="Bot's Facebook page id (mandatory)", + max_length=256, + null=True, + unique=True, + ), + ), + migrations.AlterField( + model_name="botintegration", + name="ig_account_id", + field=models.CharField( + blank=True, + default=None, + help_text="Bot's Instagram account id (mandatory)", + max_length=256, + null=True, + unique=True, + ), + ), + migrations.AlterField( + model_name="botintegration", + name="slack_access_token", + field=models.TextField( + blank=True, + default="", + editable=False, + help_text="Bot's Slack access token (mandatory)", + ), + ), + migrations.AlterField( + model_name="botintegration", + name="slack_channel_hook_url", + field=models.TextField( + blank=True, + default="", + help_text="Bot's Slack channel hook url (mandatory)", + ), + ), + migrations.AlterField( + model_name="botintegration", + name="slack_channel_id", + field=models.CharField( + blank=True, + default=None, + help_text="Bot's Public Slack channel id (mandatory)", + max_length=256, + null=True, + ), + ), + migrations.AlterField( + model_name="botintegration", + name="wa_phone_number_id", + field=models.CharField( + blank=True, + default=None, + help_text="Bot's WhatsApp phone number id (mandatory)", + max_length=256, + null=True, + unique=True, + ), + ), + migrations.AlterField( + model_name="conversation", + name="fb_page_access_token", + field=models.TextField( + blank=True, + default="", + editable=False, + help_text="User's Facebook page access token (mandatory)", + ), + ), + migrations.AlterField( + model_name="conversation", + name="fb_page_id", + field=models.TextField( + blank=True, + db_index=True, + default="", + help_text="User's Facebook page id (mandatory)", + ), + ), + migrations.AlterField( + model_name="conversation", + name="slack_user_id", + field=models.TextField( + blank=True, + default=None, + help_text="User's Slack ID (mandatory)", + max_length=256, + null=True, + ), + ), + migrations.RunPython( + forwards_func, + backwards_func, + ), + migrations.AlterUniqueTogether( + name="botintegration", + unique_together={("slack_channel_id", "slack_team_id")}, + ), + migrations.AlterUniqueTogether( + name="conversation", + unique_together={("slack_channel_id", "slack_user_id", "slack_team_id")}, + ), + migrations.AddIndex( + model_name="conversation", + index=models.Index( + fields=[ + "bot_integration", + "slack_user_id", + "slack_team_id", + "slack_channel_is_personal", + ], + name="bots_conver_bot_int_d2c469_idx", + ), + ), + ] diff --git a/bots/migrations/0041_alter_botintegration_slack_create_personal_channels.py b/bots/migrations/0041_alter_botintegration_slack_create_personal_channels.py new file mode 100644 index 000000000..9513cda63 --- /dev/null +++ b/bots/migrations/0041_alter_botintegration_slack_create_personal_channels.py @@ -0,0 +1,20 @@ +# Generated by Django 4.2.3 on 2023-09-19 12:50 + +from django.db import migrations, models + + +class Migration(migrations.Migration): + dependencies = [ + ("bots", "0040_remove_conversation_bots_conver_bot_int_a83907_idx_and_more"), + ] + + operations = [ + migrations.AlterField( + model_name="botintegration", + name="slack_create_personal_channels", + field=models.BooleanField( + default=True, + help_text="If set, the bot will create a personal channel for each user in the public channel", + ), + ), + ] diff --git a/bots/models.py b/bots/models.py index e234b5ceb..bc2d9d9ca 100644 --- a/bots/models.py +++ b/bots/models.py @@ -337,7 +337,7 @@ class BotIntegration(models.Model): default=None, null=True, unique=True, - help_text="Bot's Facebook page id (required if platform is Facebook/Instagram)", + help_text="Bot's Facebook page id (mandatory)", ) fb_page_name = models.TextField( default="", @@ -347,7 +347,7 @@ class BotIntegration(models.Model): fb_page_access_token = models.TextField( blank=True, default="", - help_text="Bot's Facebook page access token (required if platform is Facebook/Instagram)", + help_text="Bot's Facebook page access token (mandatory)", editable=False, ) ig_account_id = models.CharField( @@ -356,13 +356,14 @@ class BotIntegration(models.Model): default=None, null=True, unique=True, - help_text="Bot's Instagram account id (required if platform is Instagram)", + help_text="Bot's Instagram account id (mandatory)", ) ig_username = models.TextField( blank=True, default="", help_text="Bot's Instagram username (only for display)", ) + wa_phone_number = PhoneNumberField( blank=True, default="", @@ -374,27 +375,53 @@ class BotIntegration(models.Model): default=None, null=True, unique=True, - help_text="Bot's WhatsApp phone number id (required if platform is WhatsApp)", + help_text="Bot's WhatsApp phone number id (mandatory)", + ) + + slack_team_id = models.CharField( + max_length=256, + blank=True, + default=None, + null=True, + help_text="Bot's Slack team id (mandatory)", + ) + slack_team_name = models.TextField( + blank=True, + default="", + help_text="Bot's Slack team/workspace name (only for display)", ) slack_channel_id = models.CharField( max_length=256, blank=True, default=None, null=True, - unique=True, - help_text="Bot's Slack channel id (required if platform is Slack)", + help_text="Bot's Public Slack channel id (mandatory)", + ) + slack_channel_name = models.TextField( + blank=True, + default="", + help_text="Bot's Public Slack channel name without # (only for display)", ) slack_channel_hook_url = models.TextField( blank=True, default="", - help_text="Bot's Slack channel hook url (required if platform is Slack)", + help_text="Bot's Slack channel hook url (mandatory)", ) slack_access_token = models.TextField( blank=True, default="", - help_text="Bot's Slack access token (required if platform is Slack)", + help_text="Bot's Slack access token (mandatory)", editable=False, ) + slack_read_receipt_msg = models.TextField( + blank=True, + default="Results may take up to 1 minute, we appreciate your patience.", + help_text="Bot's Slack read receipt message - if set, and platform is Slack, the bot will send this message to mark the user message as read and then delete it when it has a response ready", + ) + slack_create_personal_channels = models.BooleanField( + default=True, + help_text="If set, the bot will create a personal channel for each user in the public channel", + ) analysis_run = models.ForeignKey( "bots.SavedRun", @@ -405,10 +432,6 @@ class BotIntegration(models.Model): default=None, help_text="If provided, the message content will be analyzed for this bot using this saved run", ) - enable_analysis = models.BooleanField( - default=False, - help_text="Enable analysis for this bot (DEPRECATED)", - ) created_at = models.DateTimeField(auto_now_add=True) updated_at = models.DateTimeField(auto_now=True) @@ -417,23 +440,34 @@ class BotIntegration(models.Model): class Meta: ordering = ["-updated_at"] + unique_together = [ + ("slack_channel_id", "slack_team_id"), + ] indexes = [ models.Index(fields=["billing_account_uid", "platform"]), models.Index(fields=["fb_page_id", "ig_account_id"]), ] def __str__(self): - orig_name = ( + platform_name = self.get_display_name() + if self.name and platform_name and self.name != platform_name: + return f"{self.name} ({platform_name})" + else: + return self.name or platform_name + + def get_display_name(self): + return ( (self.wa_phone_number and self.wa_phone_number.as_international) or self.ig_username or self.fb_page_name or self.wa_phone_number_id or self.fb_page_id + or " | #".join( + filter(None, [self.slack_team_name, self.slack_channel_name]) + ) ) - if self.name and orig_name and self.name != orig_name: - return f"{self.name} ({orig_name})" - else: - return self.name or orig_name + + get_display_name.short_description = "Bot" class ConvoState(models.IntegerChoices): @@ -488,7 +522,7 @@ class Conversation(models.Model): blank=True, default="", db_index=True, - help_text="User's Facebook page id (required if platform is Facebook/Instagram)", + help_text="User's Facebook page id (mandatory)", ) fb_page_name = models.TextField( default="", @@ -498,7 +532,7 @@ class Conversation(models.Model): fb_page_access_token = models.TextField( blank=True, default="", - help_text="User's Facebook page access token (required if platform is Facebook/Instagram)", + help_text="User's Facebook page access token (mandatory)", editable=False, ) ig_account_id = models.TextField( @@ -512,17 +546,48 @@ class Conversation(models.Model): default="", help_text="User's Instagram username (only for display)", ) + wa_phone_number = PhoneNumberField( blank=True, default="", db_index=True, help_text="User's WhatsApp phone number (required if platform is WhatsApp)", ) + slack_user_id = models.TextField( + max_length=256, + blank=True, + default=None, + null=True, + help_text="User's Slack ID (mandatory)", + ) + slack_team_id = models.TextField( + max_length=256, + blank=True, + default=None, + null=True, + help_text="Slack team id - redundant with bot integration (mandatory)", + ) + slack_user_name = models.TextField( blank=True, default="", - db_index=True, - help_text="User's Slack ID (required if platform is Slack)", + help_text="User's name in slack (only for display)", + ) + slack_channel_id = models.TextField( + max_length=256, + blank=True, + default=None, + null=True, + help_text="Slack channel id, can be different than the bot integration's public channel (mandatory)", + ) + slack_channel_name = models.TextField( + blank=True, + default="", + help_text="Bot's Slack channel name without # (only for display)", + ) + slack_channel_is_personal = models.BooleanField( + default=False, + help_text="Whether this is a personal slack channel between the bot and the user", ) created_at = models.DateTimeField(auto_now_add=True) @@ -530,10 +595,20 @@ class Conversation(models.Model): objects = ConversationQuerySet.as_manager() class Meta: + unique_together = [ + ("slack_channel_id", "slack_user_id", "slack_team_id"), + ] indexes = [ models.Index(fields=["bot_integration", "fb_page_id", "ig_account_id"]), models.Index(fields=["bot_integration", "wa_phone_number"]), - models.Index(fields=["bot_integration", "slack_user_id"]), + models.Index( + fields=[ + "bot_integration", + "slack_user_id", + "slack_team_id", + "slack_channel_is_personal", + ], + ), ] def __str__(self): @@ -544,6 +619,9 @@ def get_display_name(self): (self.wa_phone_number and self.wa_phone_number.as_international) or self.ig_username or self.fb_page_name + or " in #".join( + filter(None, [self.slack_user_name, self.slack_channel_name]) + ) or self.fb_page_id or self.slack_user_id ) @@ -624,10 +702,10 @@ class Message(models.Model): help_text="The saved run that generated this message", ) - wa_msg_id = models.TextField( + platform_msg_id = models.TextField( blank=True, default="", - help_text="WhatsApp message id (required if platform is WhatsApp)", + help_text="The platform's delivered message id", ) created_at = models.DateTimeField(auto_now_add=True) diff --git a/bots/tasks.py b/bots/tasks.py index e02111f08..004a04408 100644 --- a/bots/tasks.py +++ b/bots/tasks.py @@ -3,11 +3,19 @@ from celery import shared_task from app_users.models import AppUser -from bots.models import Message, CHATML_ROLE_ASSISSTANT -from daras_ai_v2.functional import flatten +from bots.models import Message, CHATML_ROLE_ASSISSTANT, BotIntegration +from daras_ai_v2.functional import flatten, map_parallel +from daras_ai_v2.slack_bot import fetch_channel_members, create_personal_channel from daras_ai_v2.vector_search import references_as_prompt +@shared_task +def create_personal_channels_for_all_members(bi_id: int): + bi = BotIntegration.objects.get(id=bi_id) + users = list(fetch_channel_members(bi.slack_channel_id, bi.slack_access_token)) + map_parallel(lambda user: create_personal_channel(bi, user), users, max_workers=10) + + @shared_task def msg_analysis(msg_id: int): msg = Message.objects.get(id=msg_id) diff --git a/daras_ai_v2/azure_doc_extract.py b/daras_ai_v2/azure_doc_extract.py index 343b2b9b7..e4623b37f 100644 --- a/daras_ai_v2/azure_doc_extract.py +++ b/daras_ai_v2/azure_doc_extract.py @@ -13,11 +13,11 @@ auth_headers = {"Ocp-Apim-Subscription-Key": settings.AZURE_FORM_RECOGNIZER_KEY} -def azure_pdf_extract(pdf_url: str): +def azure_doc_extract_pages(pdf_url: str, model_id: str = "prebuilt-layout"): r = requests.post( str( furl(settings.AZURE_FORM_RECOGNIZER_ENDPOINT) - / "formrecognizer/documentModels/prebuilt-document:analyze" + / f"formrecognizer/documentModels/{model_id}:analyze" ), params={"api-version": "2023-07-31"}, headers=auth_headers, @@ -45,7 +45,6 @@ def azure_pdf_extract(pdf_url: str): sleep(1) -@redis_cache_decorator def extract_records(result: dict, page_num: int) -> list[dict]: table_polys = extract_tables(result, page_num) records = [] diff --git a/daras_ai_v2/base.py b/daras_ai_v2/base.py index 5fc7d97b0..638c143f6 100644 --- a/daras_ai_v2/base.py +++ b/daras_ai_v2/base.py @@ -517,12 +517,23 @@ def render_usage_guide(self): raise NotImplementedError def run(self, state: dict) -> typing.Iterator[str | None]: + # initialize request and response request = self.RequestModel.parse_obj(state) - response = SimpleNamespace() - for val in self.run_v2(request, response): - state.update(response.__dict__) + response = self.ResponseModel.construct() + + # run the recipe + gen = self.run_v2(request, response) + while True: + try: + val = next(gen) + except StopIteration: + break + finally: + state.update(response.dict()) yield val - state.update(self.ResponseModel.parse_obj(response.__dict__)) + + # validate the response if successful + self.ResponseModel.validate(response) def run_v2( self, request: BaseModel, response: BaseModel diff --git a/daras_ai_v2/bots.py b/daras_ai_v2/bots.py index 09a9df158..15caa4f29 100644 --- a/daras_ai_v2/bots.py +++ b/daras_ai_v2/bots.py @@ -70,12 +70,17 @@ def nice_filename(self, mime_type: str) -> str: return f"{self.platform}_{self.input_type}_from_{self.user_id}_to_{self.bot_id}{ext}" def _unpack_bot_integration(self, bi: BotIntegration): - self.page_cls = Workflow(bi.saved_run.workflow).page_cls - self.query_params = self.page_cls.clean_query_params( - example_id=bi.saved_run.example_id, - run_id=bi.saved_run.run_id, - uid=bi.saved_run.uid, - ) + if bi.saved_run: + self.page_cls = Workflow(bi.saved_run.workflow).page_cls + self.query_params = self.page_cls.clean_query_params( + example_id=bi.saved_run.example_id, + run_id=bi.saved_run.run_id, + uid=bi.saved_run.uid, + ) + else: + self.page_cls = None + self.query_params = {} + self.billing_account_uid = bi.billing_account_uid self.language = bi.user_language self.show_feedback_buttons = bi.show_feedback_buttons @@ -177,15 +182,21 @@ def _on_msg(bot: BotInterface): else: # set the asr output as the input text input_text = result["output"]["output_text"][0].strip() + if not input_text: + bot.send_msg(text=DEFAULT_RESPONSE) + return # send confirmation of asr bot.send_msg(text=AUDIO_ASR_CONFIRMATION.format(input_text)) case "text": - input_text = bot.get_input_text() + input_text = (bot.get_input_text() or "").strip() + if not input_text: + bot.send_msg(text=DEFAULT_RESPONSE) + return case _: bot.send_msg(text=INVALID_INPUT_FORMAT.format(bot.input_type)) return # handle reset keyword - if input_text.strip().lower() == RESET_KEYWORD: + if input_text.lower() == RESET_KEYWORD: # clear saved messages bot.convo.messages.all().delete() # reset convo state @@ -274,9 +285,9 @@ def _process_and_send_msg( ) if not msgs_to_save: return - # save the whatsapp message id for the sent message - if bot.platform in [Platform.WHATSAPP, Platform.SLACK] and msg_id: - msgs_to_save[-1].wa_msg_id = msg_id + # save the message id for the sent message + if msg_id: + msgs_to_save[-1].platform_msg_id = msg_id # save the messages for msg in msgs_to_save: msg.save() @@ -292,7 +303,7 @@ def _handle_interactive_msg(bot: BotInterface): # handle feedback button press case ButtonIds.feedback_thumbs_up | ButtonIds.feedback_thumbs_down: try: - context_msg = Message.objects.get(wa_msg_id=context_msg_id) + context_msg = Message.objects.get(platform_msg_id=context_msg_id) except Message.DoesNotExist as e: bot.send_msg(text=ERROR_MSG.format(e)) return @@ -337,6 +348,10 @@ def _handle_audio_msg(billing_account_user, bot: BotInterface): from recipes.asr import AsrPage from routers.api import call_api + input_audio = bot.get_input_audio() + if not input_audio: + raise HTTPException(status_code=400, detail="No audio found in request.") + # run asr language = None match bot.language.lower(): @@ -353,11 +368,12 @@ def _handle_audio_msg(billing_account_user, bot: BotInterface): selected_model = AsrModels.usm.name case _: selected_model = AsrModels.whisper_large_v2.name + result = call_api( page_cls=AsrPage, user=billing_account_user, request_body={ - "documents": [bot.get_input_audio()], + "documents": [input_audio], "selected_model": selected_model, "google_translate_target": None, "language": language, diff --git a/daras_ai_v2/doc_search_settings_widgets.py b/daras_ai_v2/doc_search_settings_widgets.py index 156a84566..1acd224d1 100644 --- a/daras_ai_v2/doc_search_settings_widgets.py +++ b/daras_ai_v2/doc_search_settings_widgets.py @@ -145,7 +145,12 @@ def doc_search_settings( return st.write("---") - st.write("##### 🎤 Document Speech Recognition") + st.write( + """ + ##### 🎤 Knowledge Base Speech Recognition + If your knowledge base documents contain audio or video files, we'll transcribe and optionally translate them to English, given we've found most vectorDBs and LLMs perform best in English (even if their final answers are translated into another language). + """ + ) enum_selector( AsrModels, diff --git a/daras_ai_v2/functional.py b/daras_ai_v2/functional.py index e3988fe17..625e9c026 100644 --- a/daras_ai_v2/functional.py +++ b/daras_ai_v2/functional.py @@ -41,6 +41,21 @@ def apply_parallel( return ret +def fetch_parallel( + fn: typing.Callable[[T], R], + *iterables: typing.Sequence[T], + max_workers: int = None, +) -> typing.Generator[R, None, None]: + assert iterables, "fetch_parallel() requires at least one iterable" + max_workers = max_workers or max(map(len, iterables)) + if not max_workers: + return + with ThreadPoolExecutor(max_workers=max_workers) as pool: + fs = [pool.submit(fn, *args) for args in zip(*iterables)] + for fut in as_completed(fs): + yield fut.result() + + def flatmap_parallel( fn: typing.Callable[[T], list[R]], *iterables: typing.Sequence[T], diff --git a/daras_ai_v2/prompt_vars.py b/daras_ai_v2/prompt_vars.py index 70ccf128f..80f13d906 100644 --- a/daras_ai_v2/prompt_vars.py +++ b/daras_ai_v2/prompt_vars.py @@ -1,3 +1,6 @@ +from datetime import datetime +from types import SimpleNamespace + import jinja2 import jinja2.meta import jinja2.sandbox @@ -5,30 +8,59 @@ import gooey_ui as st -def prompt_vars_widget(input_prompt: str, key: str = "variables"): +def prompt_vars_widget(*keys: str, variables_key: str = "variables"): + # find all variables in the prompts env = jinja2.sandbox.SandboxedEnvironment() - try: - parsed = env.parse(input_prompt) - except jinja2.exceptions.TemplateSyntaxError as e: - st.error(e.message) - return - template_vars = jinja2.meta.find_undeclared_variables(parsed) - if not template_vars: + template_vars = set() + + err = None + for k in keys: + try: + parsed = env.parse(st.session_state.get(k, "")) + except jinja2.exceptions.TemplateSyntaxError as e: + err = e + else: + template_vars |= jinja2.meta.find_undeclared_variables(parsed) + + # don't mistake globals for vars + template_vars -= set(context_globals().keys()) + + if not (template_vars or err): return + st.write("##### ⌥ Variables") - old_state = st.session_state.get(key, {}) + old_state = st.session_state.get(variables_key, {}) new_state = {} for name in sorted(template_vars): if name in st.session_state: continue - var_key = f"__{key}_{name}" + var_key = f"__{variables_key}_{name}" st.session_state.setdefault(var_key, old_state.get(name, "")) new_state[name] = st.text_area("`" + name + "`", key=var_key, height=300) - st.session_state[key] = new_state + st.session_state[variables_key] = new_state + + if err: + st.error(f"{type(err).__qualname__}: {err.message}") -def render_prompt_vars(prompt: str, *, variables: dict | None, state: dict | None): +def render_prompt_vars( + prompt: str, state: dict | None, variables_key: str = "variables" +): env = jinja2.sandbox.SandboxedEnvironment() - context = (state or {}) | (variables or {}) - context = {k: str(v).strip() if v else "" for k, v in context.items()} + state = state.copy() + variables = state.pop(variables_key, {}) + context = context_globals() | (state or {}) | (variables or {}) + for k, v in context.items(): + if v is None: + context[k] = "" + elif isinstance(v, str): + context[k] = v.strip() return env.from_string(prompt).render(**context) + + +def context_globals(): + return { + "datetime": SimpleNamespace( + utcnow=datetime.utcnow().strftime("%B %d, %Y %H:%M:%S %Z"), + ), + } diff --git a/daras_ai_v2/query_generator.py b/daras_ai_v2/query_generator.py new file mode 100644 index 000000000..849836e9b --- /dev/null +++ b/daras_ai_v2/query_generator.py @@ -0,0 +1,34 @@ +import jinja2 + +from daras_ai_v2.language_model import ( + run_language_model, + model_max_tokens, + LargeLanguageModels, +) +from daras_ai_v2.prompt_vars import render_prompt_vars + + +def generate_final_search_query( + *, + request, + response=None, + instructions: str, + context: dict = None, +): + if context is None: + context = request.dict() + if response: + context |= response.dict() + instructions = render_prompt_vars(instructions, context).strip() + if not instructions: + return "" + model = LargeLanguageModels[request.selected_model] + max_tokens = model_max_tokens[model] // 8 # just a sane default + return run_language_model( + model=request.selected_model, + prompt=instructions, + max_tokens=max_tokens, + quality=request.quality, + temperature=request.sampling_temperature, + avoid_repetition=request.avoid_repetition, + )[0] diff --git a/daras_ai_v2/search_ref.py b/daras_ai_v2/search_ref.py index c09fc10b2..657d2898c 100644 --- a/daras_ai_v2/search_ref.py +++ b/daras_ai_v2/search_ref.py @@ -202,8 +202,6 @@ def parse_refs( def render_output_with_refs(state, height): output_text = state.get("output_text", []) - if output_text: - gooey_ui.write("**Answer**") for text in output_text: html = render_text_with_refs(text, state.get("references", [])) scrollable_html(html, height=height) diff --git a/daras_ai_v2/serp_search.py b/daras_ai_v2/serp_search.py index 722894c58..3042ccc64 100644 --- a/daras_ai_v2/serp_search.py +++ b/daras_ai_v2/serp_search.py @@ -22,7 +22,7 @@ def get_related_questions_from_serp_api( search_type=SerpSearchType.SEARCH, search_location=search_location, ) - items = data.get("peopleAlsoAsk", []) + data.get("relatedSearches", []) + items = data.get("peopleAlsoAsk", []) or data.get("relatedSearches", []) related_questions = [ q for item in items if (q := item.get("question") or item.get("query")) ] diff --git a/daras_ai_v2/slack_bot.py b/daras_ai_v2/slack_bot.py index c0464a2a3..f293005e8 100644 --- a/daras_ai_v2/slack_bot.py +++ b/daras_ai_v2/slack_bot.py @@ -1,15 +1,20 @@ -import requests - +import re +import typing +from string import Template from typing import TypedDict +import requests +from django.db import transaction +from langcodes import Language +from requests import Response +from sentry_sdk import capture_exception + from bots.models import BotIntegration, Platform, Conversation -from daras_ai.image_input import upload_file_from_bytes, get_mimetype_from_response -from daras_ai_v2.text_splitter import text_splitter -from daras_ai_v2.asr import run_google_translate, audio_url_to_wav, audio_bytes_to_wav +from daras_ai.image_input import upload_file_from_bytes +from daras_ai_v2.asr import run_google_translate, audio_bytes_to_wav from daras_ai_v2.bots import BotInterface - -from langcodes import Language -from string import Template +from daras_ai_v2.functional import fetch_parallel +from daras_ai_v2.text_splitter import text_splitter SLACK_CONFIRMATION_MSG = """ Hi there! 👋 @@ -21,22 +26,25 @@ I have been configured for $user_language and will respond to you in that language. """.strip() -SLACK_MAX_SIZE = 4000 +SLACK_MAX_SIZE = 3000 class SlackMessage(TypedDict): - workspace_id: str application_id: str channel: str thread_ts: str text: str - user: str + user_id: str files: list[dict] actions: list[dict] msg_id: str + team_id: str class SlackBot(BotInterface): + _read_msg_id: str | None = None + _file: dict | None = None + def __init__( self, message: SlackMessage, @@ -45,44 +53,69 @@ def __init__( self.platform = Platform.SLACK self.bot_id = message["channel"] - self.user_id = message["user"] + self.user_id = message["user_id"] + + # Try to find an existing conversation, this could either be a personal channel or the main channel the integration was added to + try: + self.convo = Conversation.objects.get( + slack_channel_id=self.bot_id, + slack_user_id=self.user_id, + slack_team_id=message["team_id"], + ) + except Conversation.DoesNotExist: + # No existing conversation found, this could be a personal channel or the main channel the integration was added to + # find the bot integration for this main channel and use it to create a new conversation + self.convo = Conversation.objects.get_or_create( + slack_channel_id=self.bot_id, + slack_user_id=self.user_id, + slack_team_id=message["team_id"], + defaults=dict( + bot_integration=BotIntegration.objects.get( + slack_channel_id=self.bot_id, + slack_team_id=message["team_id"], + ), + ), + )[0] + + fetch_missing_convo_metadata(self.convo) + + bi = self.convo.bot_integration + self.name = bi.name + self.slack_access_token = bi.slack_access_token + self.read_msg = bi.slack_read_receipt_msg.strip() + self._unpack_bot_integration(bi) + + self._thread_ts = message["thread_ts"] self.input_type = "text" files = message.get("files", []) if files: - self.input_type = files[0].get("media_display_type", "") + self._file = files[0] # we only process the first file for now + # Additional check required to access file info - https://api.slack.com/apis/channels-between-orgs#check_file_info + if self._file.get("file_access") == "check_file_info": + self._file = fetch_file_info(self._file["id"], bi.slack_access_token) + self.input_type = self._file.get("mimetype", "").split("/")[0] or "unknown" if message.get("actions"): self.input_type = "interactive" - bi: BotIntegration = BotIntegration.objects.get(slack_channel_id=self.bot_id) - self.name = bi.name - self.slack_access_token = bi.slack_access_token - self.convo = Conversation.objects.get_or_create( - bot_integration=bi, - slack_user_id=self.user_id, - )[0] - self._unpack_bot_integration(bi) - def get_input_text(self) -> str | None: - return self.input_message["text"] + return self.input_message.get("text") def get_input_audio(self) -> str | None: - files = self.input_message.get("files", []) - if not files: + if not self._file: return None - url = files[0].get("url_private_download", "") - if not url: + url = self._file.get("url_private_download") + mime_type = self._file.get("mimetype") + if not (url and mime_type): return None + assert ( + "audio/" in mime_type or "video/" in mime_type + ), f"Unsupported mime type {mime_type} for {url}" # download file from slack r = requests.get( url, headers={"Authorization": f"Bearer {self.slack_access_token}"} ) r.raise_for_status() - # ensure file is audio/video - mime_type = get_mimetype_from_response(r) - assert ( - "audio/" in mime_type or "video/" in mime_type - ), f"Invalid mime type {mime_type} for {url}" # convert to wav data, _ = audio_bytes_to_wav(r.content) mime_type = "audio/wav" @@ -92,7 +125,6 @@ def get_input_audio(self) -> str | None: data=data, content_type=mime_type, ) - # print("found audio url: " + audio_url) return audio_url def get_interactive_msg_info(self) -> tuple[str, str]: @@ -114,46 +146,356 @@ def send_msg( return None if should_translate and self.language and self.language != "en": text = run_google_translate([text], self.language)[0] + + if self._read_msg_id and self._read_msg_id != self._thread_ts: + delete_msg( + channel=self.bot_id, + thread_ts=self._read_msg_id, + token=self.slack_access_token, + ) + self._read_msg_id = None + splits = text_splitter(text, chunk_size=SLACK_MAX_SIZE, length_function=len) for doc in splits[:-1]: - reply( + self._thread_ts = chat_post_message( text=doc.text, - audio=audio, - video=video, channel=self.bot_id, - thread_ts=self.input_message["thread_ts"], + channel_is_personal=self.convo.slack_channel_is_personal, + thread_ts=self._thread_ts, username=self.name, token=self.slack_access_token, - buttons=[], ) - msg_id = reply( + self._thread_ts = chat_post_message( text=splits[-1].text, audio=audio, video=video, channel=self.bot_id, - thread_ts=self.input_message["thread_ts"], + channel_is_personal=self.convo.slack_channel_is_personal, + thread_ts=self._thread_ts, username=self.name, token=self.slack_access_token, buttons=buttons or [], ) - return msg_id + return self._thread_ts def mark_read(self): - pass + if not self.read_msg: + return + text = self.read_msg + if self.language and self.language != "en": + text = run_google_translate([text], self.language)[0] + self._read_msg_id = chat_post_message( + text=text, + channel=self.bot_id, + channel_is_personal=self.convo.slack_channel_is_personal, + thread_ts=self._thread_ts, + token=self.slack_access_token, + username=self.name, + ) + + +def delete_msg( + channel: str, + thread_ts: str, + token: str, +): + res = requests.post( + "https://slack.com/api/chat.delete", + json={"channel": channel, "ts": thread_ts}, + headers={"Authorization": f"Bearer {token}"}, + ) + parse_slack_response(res) + + +def fetch_channel_members( + channel: str, + token: str, + cursor: str | None = None, +) -> typing.Generator[dict, None, None]: + query_params = {"channel": channel, "limit": "1000"} + if cursor: + query_params["cursor"] = cursor + res = requests.get( + "https://slack.com/api/conversations.members", + params=query_params, + headers={"Authorization": f"Bearer {token}"}, + ) + data = parse_slack_response(res) + yield from fetch_parallel( + lambda user_id: fetch_user_info(user_id, token), + data["members"], + max_workers=10, + ) + cursor = data.get("response_metadata", {}).get("next_cursor") + if not cursor: + return + for user_id in fetch_channel_members(channel, token, cursor): + yield user_id + + +def fetch_missing_convo_metadata(convo: Conversation): + try: + token = convo.bot_integration.slack_access_token + if not convo.slack_user_name: + user_data = fetch_user_info(convo.slack_user_id, token) + Conversation.objects.filter(id=convo.id).update( + slack_user_name=user_data["real_name"] + ) + if not convo.slack_channel_name: + channel_data = fetch_channel_info(convo.slack_channel_id, token) + Conversation.objects.filter(id=convo.id).update( + slack_channel_name=channel_data["name"] + ) + except SlackAPIError as e: + if e.error == "missing_scope": + print(f"Error: Missing scopes for - {convo!r}") + capture_exception(e) + else: + raise + + +def fetch_channel_info(channel: str, token: str) -> dict[str, typing.Any]: + res = requests.get( + "https://slack.com/api/conversations.info", + params={"channel": channel}, + headers={"Authorization": f"Bearer {token}"}, + ) + data = parse_slack_response(res) + return data["channel"] -def reply( +def fetch_user_info(user_id: str, token: str) -> dict[str, typing.Any]: + res = requests.get( + "https://slack.com/api/users.info", + params={"user": user_id}, + headers={"Authorization": f"Bearer {token}"}, + ) + data = parse_slack_response(res) + return data["user"] + + +def fetch_file_info(file_id: str, token: str) -> dict[str, typing.Any]: + res = requests.get( + "https://slack.com/api/files.info", + params={"file": file_id}, + headers={"Authorization": f"Bearer {token}"}, + ) + data = parse_slack_response(res) + return data["file"] + + +# https://api.slack.com/methods/conversations.rename#naming +CHANNEL_NAME_WHITELIST = re.compile(r"[a-z0-9-_]") +CHANNEL_NAME_MAX_LENGTH = 80 + + +def safe_channel_name(name: str) -> str: + name = name.lower().replace(" ", "-") + name = "".join(CHANNEL_NAME_WHITELIST.findall(name)) + name = name[:CHANNEL_NAME_MAX_LENGTH] + name = name.rstrip("-_") + return name + + +def create_personal_channel( + bi: BotIntegration, + user: dict, + *, + max_tries: int = 5, +) -> Conversation | None: + if user["is_bot"]: + return None + user_id = user["id"] + user_name = user["real_name"] + team_id = user["team_id"] + # lookup the personal convo with this bot and user + convo_lookup = dict( + bot_integration=bi, + slack_user_id=user_id, + slack_team_id=team_id, + slack_channel_is_personal=True, + ) + # if the slack channel exists, don't create a new one + convo = check_personal_convo_exists(convo_lookup, bi.slack_access_token) + if convo: + channel_id = convo.slack_channel_id + channel_name = convo.slack_channel_name + else: + channel_id, channel_name = create_personal_channel_brute_force( + bi, user_name, max_tries + ) + try: + # set the topic and invite the user to the channel + invite_user_to_channel( + user_id=user_id, + channel_id=channel_id, + token=bi.slack_access_token, + ) + except SlackAPIError as e: + # skip if the user is restricted + if e.error in ["user_is_ultra_restricted", "user_is_restricted"]: + return + else: + raise + set_slack_channel_topic( + bot_name=bi.name, + channel_id=channel_id, + token=bi.slack_access_token, + ) + # ensure the metadata like user name is up to date + convo_defaults = dict( + slack_user_name=user_name, + slack_channel_id=channel_id, + slack_channel_name=channel_name, + ) + # create the conversation and update the metadata + with transaction.atomic(): + bi, created = Conversation.objects.get_or_create( + **convo_lookup, + defaults=convo_defaults, + ) + if not created: + Conversation.objects.filter(pk=bi.pk).update(**convo_defaults) + return bi + + +def check_personal_convo_exists( + convo_lookup: dict, access_token: str +) -> Conversation | None: + try: + convo = Conversation.objects.get(**convo_lookup) + except Conversation.DoesNotExist: + return None + if check_channel_exists(convo.slack_channel_id, access_token): + return convo + else: + return None + + +def create_personal_channel_brute_force( + bi: BotIntegration, user_name: str, max_tries: int +) -> tuple[str, str]: + i = 0 + while True: + try: + channel_name_parts = [bi.slack_channel_name or bi.name, user_name, i] + channel_name = safe_channel_name( + "-".join(map(str, filter(None, channel_name_parts))), + ) + channel_id = create_channel( + channel_name=channel_name, + is_private=True, + token=bi.slack_access_token, + ) + except ChannelAlreadyExists: + i += 1 + if i > max_tries: + raise + else: + break + return channel_id, channel_name + + +def check_channel_exists(channel_id: str, token: str) -> bool: + res = requests.get( + "https://slack.com/api/conversations.info", + params={"channel": channel_id}, + headers={"Authorization": f"Bearer {token}"}, + ) + try: + data = parse_slack_response(res) + except SlackAPIError as e: + if e.error == "channel_not_found": + return False + else: + raise + if data["channel"]["is_archived"]: + res = requests.post( + "https://slack.com/api/conversations.unarchive", + params={"channel": channel_id}, + headers={"Authorization": f"Bearer {token}"}, + ) + parse_slack_response(res) + return True + + +def set_slack_channel_topic( + *, + bot_name: str, + channel_id: str, + token: str, +): + res = requests.post( + "https://slack.com/api/conversations.setTopic", + json={ + "channel": channel_id, + "topic": ( + f"Your personal conversation with {bot_name}. " + "This is a separate conversation history from the public channel and other people can't view your messages." + ), + }, + headers={"Authorization": f"Bearer {token}"}, + ) + parse_slack_response(res) + + +def invite_user_to_channel( + *, + user_id: str, + channel_id: str, + token: str, +): + res = requests.post( + "https://slack.com/api/conversations.invite", + json={ + "channel": channel_id, + "users": user_id, + }, + headers={"Authorization": f"Bearer {token}"}, + ) + try: + parse_slack_response(res) + except SlackAPIError as e: + if e.error not in ["already_in_channel", "cant_invite_self"]: + raise + + +def create_channel(*, channel_name: str, is_private: bool, token: str) -> str | None: + res = requests.post( + "https://slack.com/api/conversations.create", + json={"name": channel_name, "is_private": is_private}, + headers={"Authorization": f"Bearer {token}"}, + ) + try: + data = parse_slack_response(res) + except SlackAPIError as e: + if e.error == "name_taken": + raise ChannelAlreadyExists() from e + raise + return data["channel"]["id"] + + +class ChannelAlreadyExists(Exception): + pass + + +def chat_post_message( + *, text: str, channel: str, thread_ts: str, token: str, + channel_is_personal: bool = False, audio: str | None = None, video: str | None = None, username: str = "Video Bot", buttons: list | None = None, -): +) -> str | None: if buttons is None: buttons = [] + if channel_is_personal: + # don't thread in personal channels + thread_ts = None res = requests.post( "https://slack.com/api/chat.postMessage", json={ @@ -176,7 +518,8 @@ def reply( "Authorization": f"Bearer {token}", }, ) - return res.json().get("ts", thread_ts) + data = parse_slack_response(res) + return data.get("ts") def create_file_block( @@ -197,7 +540,7 @@ def create_file_block( "Authorization": f"Bearer {token}", }, ) - res.raise_for_status() + parse_slack_response(res) return [ { "type": "file", @@ -208,7 +551,9 @@ def create_file_block( def create_button_block( - buttons: list[dict[{"type": str, "reply": dict[{"id": str, "title": str}]}]] + buttons: list[ + dict[{"type": str, "chat_post_message": dict[{"id": str, "title": str}]}] + ] ) -> list[dict]: if not buttons: return [] @@ -239,7 +584,6 @@ def send_confirmation_msg(bot: BotIntegration): target_language=bot.user_language, source_language="en", )[0] - print("confirmation msg: " + text) res = requests.post( str(bot.slack_channel_hook_url), json={"text": text}, @@ -255,5 +599,24 @@ def invite_bot_account_to_channel(channel: str, bot_user_id: str, token: str): "Authorization": f"Bearer {token}", }, ) + try: + parse_slack_response(res) + except SlackAPIError as e: + if e.error != "already_in_channel": + raise + + +def parse_slack_response(res: Response): res.raise_for_status() - print("invited " + bot_user_id + " to " + channel) + data = res.json() + print(f'> {res.request.url.split("/")[-1]}: {data}') + if data.get("ok"): + return data + else: + raise SlackAPIError(data.get("error", data)) + + +class SlackAPIError(Exception): + def __init__(self, error: str | dict): + self.error = error + super().__init__(error) diff --git a/gooey_ui/components.py b/gooey_ui/components.py index eb3e651dc..f9b366d1c 100644 --- a/gooey_ui/components.py +++ b/gooey_ui/components.py @@ -15,6 +15,12 @@ LabelVisibility = typing.Literal["visible", "collapsed"] +def _default_format(value: typing.Any) -> str: + if value is None: + return "---" + return str(value) + + def dummy(*args, **kwargs): return state.NestingCtx() @@ -239,10 +245,13 @@ def text_area( if label_visibility != "visible": label = None if disabled: - style.setdefault("height", f"{height}px"), + max_height = f"{height}px" + rows = nrows_for_text(value, height, min_rows=1) else: - style.setdefault("maxHeight", "90vh"), - props.setdefault("rows", nrows_for_text(value, height)) + max_height = "90vh" + rows = nrows_for_text(value, height) + style.setdefault("maxHeight", max_height) + props.setdefault("rows", rows) state.RenderTreeNode( name="textarea", props=dict( @@ -276,7 +285,7 @@ def nrows_for_text( def multiselect( label: str, options: typing.Sequence[T], - format_func: typing.Callable[[T], typing.Any] = str, + format_func: typing.Callable[[T], typing.Any] = _default_format, key: str = None, help: str = None, allow_none: bool = False, @@ -317,7 +326,7 @@ def multiselect( def selectbox( label: str, options: typing.Sequence[T], - format_func: typing.Callable[[T], typing.Any] = str, + format_func: typing.Callable[[T], typing.Any] = _default_format, key: str = None, help: str = None, *, @@ -333,7 +342,7 @@ def selectbox( if not key: key = md5_values("select", label, options, help, label_visibility) value = state.session_state.get(key) - if value not in options: + if key not in state.session_state or value not in options: value = default_value or options[0] state.session_state.setdefault(key, value) state.RenderTreeNode( @@ -505,7 +514,7 @@ def table(df: "pd.DataFrame"): def radio( label: str, options: typing.Sequence[T], - format_func: typing.Callable[[T], typing.Any] = str, + format_func: typing.Callable[[T], typing.Any] = _default_format, key: str = None, help: str = None, *, @@ -518,7 +527,7 @@ def radio( if not key: key = md5_values("radio", label, options, help, label_visibility) value = state.session_state.get(key) - if value not in options: + if key not in state.session_state or value not in options: value = options[0] state.session_state.setdefault(key, value) if label_visibility != "visible": @@ -663,9 +672,10 @@ def _input_widget( default_value_attr: str = "defaultValue", **kwargs, ) -> typing.Any: - if key: - assert not value, "only one of value or key can be provided" - else: + # if key: + # assert not value, "only one of value or key can be provided" + # else: + if not key: key = md5_values("input", input_type, label, help, label_visibility) value = state.session_state.setdefault(key, value) if label_visibility != "visible": diff --git a/poetry.lock b/poetry.lock index 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"more-itertools", "p [metadata] lock-version = "2.0" python-versions = ">=3.10,<3.13" -content-hash = "e343d59b277dd6822c3ad39108a942bd5adb780acdd4cad5ce0b47cb6e1d6039" +content-hash = "d6562e5c259fa3bde5ae541012cfe4576413c97b8304756ecab8c49d2059ee5f" diff --git a/pyproject.toml b/pyproject.toml index a67546633..3169f751c 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -8,7 +8,7 @@ readme = "README.md" [tool.poetry.dependencies] python = ">=3.10,<3.13" streamlit = "^1.15.2" -openai = "0.27.0" +openai = "^0.27.0" python-decouple = "^3.6" requests = "^2.28.1" glom = "^22.1.0" diff --git a/recipes/CompareLLM.py b/recipes/CompareLLM.py index 41a2c3d5e..062e7f30a 100644 --- a/recipes/CompareLLM.py +++ b/recipes/CompareLLM.py @@ -55,7 +55,7 @@ def preview_description(self, state: dict) -> str: return "Which language model works best your prompt? Compare your text generations across multiple large language models (LLMs) like OpenAI's evolving and latest ChatGPT engines and others like Curie, Ada, Babbage." def render_form_v2(self): - input_prompt = st.text_area( + st.text_area( """ #### 👩‍💻 Prompt *Supports [ChatML](https://github.com/openai/openai-python/blob/main/chatml.md) & [Jinja](https://jinja.palletsprojects.com/templates/)* @@ -64,7 +64,7 @@ def render_form_v2(self): help="What a fine day..", height=300, ) - prompt_vars_widget(input_prompt) + prompt_vars_widget("input_prompt") enum_multiselect( LargeLanguageModels, @@ -85,9 +85,7 @@ def render_settings(self): def run(self, state: dict) -> typing.Iterator[str | None]: request: CompareLLMPage.RequestModel = self.RequestModel.parse_obj(state) - prompt = render_prompt_vars( - request.input_prompt, variables=request.variables, state=state - ) + prompt = render_prompt_vars(request.input_prompt, state) state["output_text"] = output_text = {} for selected_model in request.selected_models: diff --git a/recipes/DocExtract.py b/recipes/DocExtract.py index 3afc8f6ca..6a7fa7ed2 100644 --- a/recipes/DocExtract.py +++ b/recipes/DocExtract.py @@ -21,7 +21,7 @@ run_google_translate, audio_url_to_wav, ) -from daras_ai_v2.azure_doc_extract import azure_pdf_extract +from daras_ai_v2.azure_doc_extract import azure_doc_extract_pages from daras_ai_v2.base import BasePage from daras_ai_v2.doc_search_settings_widgets import document_uploader from daras_ai_v2.enum_selector_widget import enum_selector @@ -376,7 +376,7 @@ def process_source( transcript = run_asr(content_url, request.selected_asr_model) elif "application/pdf" in doc_meta.mime_type: yield "Extracting PDF" - transcript = str(azure_pdf_extract(content_url)[0]) + transcript = str(azure_doc_extract_pages(content_url)[0]) else: raise NotImplementedError( f"Unsupported type {doc_meta and doc_meta.mime_type} for {webpage_url}" diff --git a/recipes/DocSearch.py b/recipes/DocSearch.py index df20d5e21..6c96533fc 100644 --- a/recipes/DocSearch.py +++ b/recipes/DocSearch.py @@ -20,6 +20,8 @@ ) from daras_ai_v2.language_model_settings_widgets import language_model_settings from daras_ai_v2.loom_video_widget import youtube_video +from daras_ai_v2.prompt_vars import prompt_vars_widget, render_prompt_vars +from daras_ai_v2.query_generator import generate_final_search_query from daras_ai_v2.search_ref import ( SearchReference, render_output_with_refs, @@ -70,6 +72,8 @@ class RequestModel(DocSearchRequest): citation_style: typing.Literal[tuple(e.name for e in CitationStyles)] | None + variables: dict[str, typing.Any] | None + class ResponseModel(BaseModel): output_text: list[str] @@ -80,6 +84,7 @@ class ResponseModel(BaseModel): def render_form_v2(self): st.text_area("##### Search Query", key="search_query") document_uploader("##### Documents") + prompt_vars_widget("task_instructions", "query_instructions") def validate_form_v2(self): search_query = st.session_state.get("search_query", "").strip() @@ -117,10 +122,8 @@ def render_settings(self): height=300, ) st.write("---") - language_model_settings() st.write("---") - doc_search_settings() def preview_image(self, state: dict) -> str | None: @@ -130,17 +133,7 @@ def preview_description(self, state: dict) -> str: return "Add your PDF, Word, HTML or Text docs, train our AI on them with OpenAI embeddings & vector search and then process results with a GPT3 script. This workflow is perfect for anything NOT in ChatGPT: 250-page compliance PDFs, training manuals, your diary, etc." def render_steps(self): - final_search_query = st.session_state.get("final_search_query") - if final_search_query: - st.text_area( - "**Final Search Query**", value=final_search_query, disabled=True - ) - - render_doc_search_step( - st.session_state.get("final_prompt"), - st.session_state.get("output_text", []), - st.session_state.get("references", []), - ) + render_doc_search_step(st.session_state) def render_usage_guide(self): youtube_video("Xe4L_dQ2KvU") @@ -154,19 +147,8 @@ def run_v2( query_instructions = (request.query_instructions or "").strip() if query_instructions: - query_instructions = jinja2.Template(query_instructions).render( - **request.dict() - ) - final_search_query = run_language_model( - model=request.selected_model, - prompt=query_instructions, - max_tokens=model_max_tokens[model] // 2, - quality=request.quality, - temperature=request.sampling_temperature, - avoid_repetition=request.avoid_repetition, - )[0] - response.final_search_query = ( - final_search_query.strip().strip('"').strip("'") + response.final_search_query = generate_final_search_query( + request=request, instructions=query_instructions ) else: response.final_search_query = request.search_query @@ -185,16 +167,16 @@ def run_v2( raise EmptySearchResults(request.search_query) response.final_prompt = "" + # add search results to the prompt + response.final_prompt += references_as_prompt(response.references) + "\n\n" + # add task instructions task_instructions = (request.task_instructions or "").strip() if not task_instructions: response.output_text = [] return - # add time to instructions - utcnow = datetime.datetime.utcnow().strftime("%B %d, %Y %H:%M:%S %Z") - task_instructions = task_instructions.replace("{{ datetime.utcnow }}", utcnow) - # add search results to the prompt - response.final_prompt += references_as_prompt(response.references) + "\n\n" - # add task instructions + task_instructions = render_prompt_vars( + prompt=task_instructions, state=request.dict() | response.dict() + ) response.final_prompt += task_instructions.strip() + "\n\n" # add the question response.final_prompt += f"Question: {request.search_query}\nAnswer:" @@ -242,11 +224,17 @@ def render_documents(state, label="**Documents**", *, key="documents"): st.write(f"🔗[*{filename}*]({doc})") -def render_doc_search_step( - final_prompt: str, output_text: list[str], references: list[dict] -): - st.write("**References**") - st.json(references, expanded=False) +def render_doc_search_step(state: dict): + final_search_query = state.get("final_search_query") + if final_search_query: + st.text_area("**Final Search Query**", value=final_search_query, disabled=True) + + references = state.get("references") + if references: + st.write("**References**") + st.json(references, expanded=False) + + final_prompt = state.get("final_prompt") if final_prompt: st.text_area( "**Final Prompt**", @@ -254,6 +242,8 @@ def render_doc_search_step( height=400, disabled=True, ) + + output_text = state.get("output_text", []) for idx, text in enumerate(output_text): st.text_area( f"**Output Text**", diff --git a/recipes/GoogleGPT.py b/recipes/GoogleGPT.py index 663a2cd91..636798b71 100644 --- a/recipes/GoogleGPT.py +++ b/recipes/GoogleGPT.py @@ -16,6 +16,8 @@ ) from daras_ai_v2.language_model_settings_widgets import language_model_settings from daras_ai_v2.loom_video_widget import youtube_video +from daras_ai_v2.prompt_vars import render_prompt_vars, prompt_vars_widget +from daras_ai_v2.query_generator import generate_final_search_query from daras_ai_v2.search_ref import ( SearchReference, render_output_with_refs, @@ -50,7 +52,7 @@ class GoogleGPTPage(BasePage): keywords="outdoor rugs,8x10 rugs,rug sizes,checkered rugs,5x7 rugs", title="Ruggable", company_url="https://ruggable.com", - serp_serach_type=SerpSearchType.SEARCH, + serp_search_type=SerpSearchType.SEARCH, serp_search_location=SerpSearchLocation.UNITED_STATES, enable_html=False, selected_model=LargeLanguageModels.text_davinci_003.name, @@ -95,6 +97,8 @@ class RequestModel(GoogleSearchMixin, BaseModel): "dense_weight" ].field_info + variables: dict[str, typing.Any] | None + class ResponseModel(BaseModel): output_text: list[str] @@ -108,6 +112,7 @@ class ResponseModel(BaseModel): def render_form_v2(self): st.text_area("##### Google Search Query", key="search_query") st.text_input("Search on a specific site *(optional)*", key="site_filter") + prompt_vars_widget("task_instructions", "query_instructions") def validate_form_v2(self): assert st.session_state.get( @@ -134,13 +139,12 @@ def render_settings(self): key="task_instructions", height=300, ) - + st.write("---") language_model_settings() - doc_search_settings(asr_allowed=False) - st.write("---") - serp_search_settings() + st.write("---") + doc_search_settings(asr_allowed=False) def related_workflows(self) -> list: from recipes.SEOSummary import SEOSummaryPage @@ -211,19 +215,9 @@ def run_v2( query_instructions = (request.query_instructions or "").strip() if query_instructions: - query_instructions = jinja2.Template(query_instructions).render( - **request.dict() - ) - final_search_query = run_language_model( - model=request.selected_model, - prompt=query_instructions, - max_tokens=model_max_tokens[model] // 2, - quality=request.quality, - temperature=request.sampling_temperature, - avoid_repetition=request.avoid_repetition, - )[0] - response.final_search_query = ( - final_search_query.strip().strip('"').strip("'") + yield "Generating final search query..." + response.final_search_query = generate_final_search_query( + request=request, response=response, instructions=query_instructions ) else: response.final_search_query = request.search_query @@ -231,18 +225,18 @@ def run_v2( yield "Googling..." if request.site_filter: f = furl(request.site_filter) - serp_search_query = f"site:{f.host}{f.path} {response.final_search_query}" - else: - serp_search_query = response.final_search_query + response.final_search_query = ( + f"site:{f.host}{f.path} {response.final_search_query}" + ) response.serp_results, links = get_links_from_serp_api( - serp_search_query, + response.final_search_query, search_type=request.serp_search_type, search_location=request.serp_search_location, ) # extract links & their corresponding titles link_titles = {item.url: f"{item.title} | {item.snippet}" for item in links} if not link_titles: - raise EmptySearchResults(serp_search_query) + raise EmptySearchResults(response.final_search_query) # run vector search on links response.references = yield from get_top_k_references( @@ -250,7 +244,7 @@ def run_v2( { **request.dict(), "documents": list(link_titles.keys()), - "search_query": response.final_search_query, + "search_query": request.search_query, }, ), ) @@ -264,14 +258,12 @@ def run_v2( raise EmptySearchResults(request.search_query) response.final_prompt = "" - # add time to instructions - utcnow = datetime.datetime.utcnow().strftime("%B %d, %Y %H:%M:%S %Z") - task_instructions = request.task_instructions.replace( - "{{ datetime.utcnow }}", utcnow - ) # add search results to the prompt response.final_prompt += references_as_prompt(response.references) + "\n\n" # add task instructions + task_instructions = render_prompt_vars( + prompt=request.task_instructions, state=request.dict() | response.dict() + ) response.final_prompt += task_instructions.strip() + "\n\n" # add the question response.final_prompt += f"Question: {request.search_query}\nAnswer:" diff --git a/recipes/GoogleImageGen.py b/recipes/GoogleImageGen.py index 5678724e7..795e716a6 100644 --- a/recipes/GoogleImageGen.py +++ b/recipes/GoogleImageGen.py @@ -43,7 +43,7 @@ class GoogleImageGenPage(BasePage): sd_2_upscaling=False, seed=42, image_guidance_scale=1.2, - serp_serach_type=SerpSearchType.SEARCH, + serp_search_type=SerpSearchType.SEARCH, serp_search_location=SerpSearchLocation.UNITED_STATES, ) diff --git a/recipes/RelatedQnA.py b/recipes/RelatedQnA.py index 194a4f069..6ad08fb04 100644 --- a/recipes/RelatedQnA.py +++ b/recipes/RelatedQnA.py @@ -1,17 +1,14 @@ -import typing - from pydantic import BaseModel import gooey_ui as st from bots.models import Workflow from daras_ai_v2.base import BasePage -from daras_ai_v2.doc_search_settings_widgets import doc_search_settings -from daras_ai_v2.functional import map_parallel -from daras_ai_v2.language_model import LargeLanguageModels -from daras_ai_v2.language_model_settings_widgets import language_model_settings +from daras_ai_v2.functional import apply_parallel +from daras_ai_v2.language_model import ( + LargeLanguageModels, +) from daras_ai_v2.serp_search import get_related_questions_from_serp_api from daras_ai_v2.serp_search_locations import ( - serp_search_settings, SerpSearchLocation, SerpSearchType, ) @@ -38,7 +35,7 @@ class RelatedQnAPage(BasePage): max_context_words=200, scroll_jump=5, dense_weight=1.0, - serp_serach_type=SerpSearchType.SEARCH, + serp_search_type=SerpSearchType.SEARCH, serp_search_location=SerpSearchLocation.UNITED_STATES, ) @@ -53,13 +50,28 @@ def render_description(self) -> str: return "This workflow gets the related queries for your Google search, searches your custom domain and builds answers using the results and GPT." def render_form_v2(self): - st.text_input("##### Google Search Query", key="search_query") - st.text_input("Search on a specific site *(optional)*", key="site_filter") + GoogleGPTPage.render_form_v2(self) def validate_form_v2(self): - assert st.session_state.get( - "search_query", "" - ).strip(), "Please enter a search query" + GoogleGPTPage.validate_form_v2(self) + + def render_steps(self): + serp_results = st.session_state.get( + "serp_results", st.session_state.get("scaleserp_results") + ) + if serp_results: + st.write("**Web Search Results**") + st.json(serp_results) + + output_queries = st.session_state.get("output_queries", []) + for i, result in enumerate(output_queries): + st.write("---") + st.write(f"##### {i+1}. _{result.get('search_query')}_") + serp_results = result.get("serp_results", result.get("scaleserp_results")) + if serp_results: + st.write("**Web Search Results**") + st.json(serp_results) + render_doc_search_step(result) def render_output(self): render_qna_outputs(st.session_state, 300) @@ -73,19 +85,7 @@ def render_example(self, state: dict): render_qna_outputs(state, 200, show_count=1) def render_settings(self): - st.text_area( - "### Task Instructions", - key="task_instructions", - height=300, - ) - - language_model_settings() - st.write("---") - - doc_search_settings(asr_allowed=False) - st.write("---") - - serp_search_settings() + GoogleGPTPage.render_settings(self) def related_workflows(self) -> list: from recipes.SEOSummary import SEOSummaryPage @@ -102,59 +102,44 @@ def related_workflows(self) -> list: def preview_description(self, state: dict) -> str: return 'Input your Google Search query and discover related Q&As that your audience is asking, so you can create content that is more relevant and engaging. This workflow finds the related queries (aka "People also ask") for your Google search, browses through the URL you provide for all related results from your query and finally, generates cited answers from those results. A great way to quickly improve your website\'s SEO rank if you already rank well for a given query.' - def render_steps(self): - serp_results = st.session_state.get( - "serp_results", st.session_state.get("scaleserp_results") - ) - if serp_results: - st.write("**Web Search Results**") - st.json(serp_results) - - output_queries = st.session_state.get("output_queries", []) - for i, result in enumerate(output_queries): - st.write("---") - st.write(f"##### {i+1}. _{result.get('search_query')}_") - serp_results = result.get("serp_results", result.get("scaleserp_results")) - if serp_results: - st.write("**Web Search Results**") - st.json(serp_results) - render_doc_search_step( - result.get("final_prompt", ""), - result.get("output_text", []), - result.get("references", []), - ) - - def run(self, state: dict) -> typing.Iterator[str | None]: - request: RelatedQnAPage.RequestModel = self.RequestModel.parse_obj(state) - search_query = request.search_query - + def run_v2( + self, + request: "RelatedQnAPage.RequestModel", + response: "RelatedQnAPage.ResponseModel", + ): yield "Googling Related Questions..." - serp_results, related_questions = get_related_questions_from_serp_api( - search_query, + ( + response.serp_results, + related_questions, + ) = get_related_questions_from_serp_api( + request.search_query, search_location=request.serp_search_location, ) - state["serp_results"] = serp_results - state["related_questions"] = related_questions - all_queries = [search_query] + related_questions + all_questions = [request.search_query] + related_questions[:9] - yield f"Generating answers using {LargeLanguageModels[request.selected_model].value}..." - output_queries = map_parallel( - lambda ques: run_google_gpt(state.copy(), ques), - all_queries, + response.output_queries = [] + yield from apply_parallel( + lambda ques: run_google_gpt(request.copy(), ques, response.output_queries), + all_questions, max_workers=4, + message=f"Generating answers using {LargeLanguageModels[request.selected_model].value}...", ) - output_queries = list(filter(None, output_queries)) - if not output_queries: - raise EmptySearchResults(search_query) - state["output_queries"] = output_queries - - -def run_google_gpt(state: dict, related_question: str) -> dict | None: - state["search_query"] = related_question + if not response.output_queries: + raise EmptySearchResults(request.search_query) + + +def run_google_gpt( + request: GoogleGPTPage.RequestModel, + related_question: str, + outputs: list[RelatedGoogleGPTResponse], +): + response = RelatedGoogleGPTResponse.construct() + request.search_query = related_question + response.search_query = related_question try: - for _ in GoogleGPTPage().run(state): + for _ in GoogleGPTPage().run_v2(request, response): pass except EmptySearchResults: - return None - return RelatedGoogleGPTResponse.parse_obj(state).dict() + return + outputs.append(response) diff --git a/recipes/RelatedQnADoc.py b/recipes/RelatedQnADoc.py index 177041649..046f9571b 100644 --- a/recipes/RelatedQnADoc.py +++ b/recipes/RelatedQnADoc.py @@ -1,18 +1,13 @@ -import typing - from pydantic import BaseModel import gooey_ui as st from bots.models import Workflow from daras_ai_v2.base import BasePage -from daras_ai_v2.doc_search_settings_widgets import document_uploader -from daras_ai_v2.functional import map_parallel +from daras_ai_v2.functional import apply_parallel from daras_ai_v2.language_model import LargeLanguageModels -from daras_ai_v2.language_model_settings_widgets import language_model_settings from daras_ai_v2.search_ref import CitationStyles from daras_ai_v2.serp_search import get_related_questions_from_serp_api from daras_ai_v2.serp_search_locations import ( - serp_search_settings, SerpSearchLocation, SerpSearchType, ) @@ -37,7 +32,7 @@ class RelatedQnADocPage(BasePage): sane_defaults = dict( citation_style=CitationStyles.number.name, dense_weight=1.0, - serp_serach_type=SerpSearchType.SEARCH, + serp_search_type=SerpSearchType.SEARCH, serp_search_location=SerpSearchLocation.UNITED_STATES, ) @@ -52,14 +47,10 @@ def render_description(self) -> str: return "This workflow gets the related queries for your Google search, searches your custom domain and builds answers using the results and GPT." def render_form_v2(self): - st.text_input("##### Search Query", key="search_query") - document_uploader("##### Documents") + DocSearchPage.render_form_v2(self) def validate_form_v2(self): - assert st.session_state.get( - "search_query", "" - ).strip(), "Please enter a search query" - assert st.session_state.get("documents"), "Please provide at least 1 Document" + DocSearchPage.validate_form_v2(self) def render_output(self): render_qna_outputs(st.session_state, 300) @@ -73,17 +64,7 @@ def render_example(self, state: dict): render_qna_outputs(state, 200, show_count=1) def render_settings(self): - st.text_area( - "### Task Instructions", - key="task_instructions", - height=300, - ) - - language_model_settings() - - st.write("---") - - serp_search_settings() + DocSearchPage.render_settings(self) def related_workflows(self) -> list: from recipes.SEOSummary import SEOSummaryPage @@ -113,58 +94,61 @@ def render_steps(self): for i, result in enumerate(output_queries): st.write("---") st.write(f"##### {i + 1}. _{result.get('search_query')}_") - render_doc_search_step( - result.get("final_prompt", ""), - result.get("output_text", []), - result.get("references", []), - ) - - def run(self, state: dict) -> typing.Iterator[str | None]: - request: RelatedQnADocPage.RequestModel = self.RequestModel.parse_obj(state) - search_query = request.search_query + render_doc_search_step(result) + def run_v2( + self, + request: "RelatedQnADocPage.RequestModel", + response: "RelatedQnADocPage.ResponseModel", + ): yield "Googling Related Questions..." - serp_results, related_questions = get_related_questions_from_serp_api( - search_query, + ( + response.serp_results, + related_questions, + ) = get_related_questions_from_serp_api( + request.search_query, search_location=request.serp_search_location, ) - state["serp_results"] = serp_results - state["related_questions"] = related_questions - all_queries = [search_query] + related_questions + all_questions = [request.search_query] + related_questions[:9] - yield f"Generating answers using {LargeLanguageModels[request.selected_model].value}..." - output_queries = map_parallel( - lambda ques: run_doc_search(state.copy(), ques), - all_queries, + response.output_queries = [] + yield from apply_parallel( + lambda ques: run_doc_search(request.copy(), ques, response.output_queries), + all_questions, max_workers=4, + message=f"Generating answers using {LargeLanguageModels[request.selected_model].value}...", ) - output_queries = list(filter(None, output_queries)) - if not output_queries: - raise EmptySearchResults(search_query) - state["output_queries"] = output_queries - - -def run_doc_search(state: dict, related_question: str): - state["search_query"] = related_question + if not response.output_queries: + raise EmptySearchResults(request.search_query) + + +def run_doc_search( + request: DocSearchPage.RequestModel, + related_question: str, + outputs: list[RelatedDocSearchResponse], +): + response = RelatedDocSearchResponse.construct() + request.search_query = related_question + response.search_query = related_question try: - for _ in DocSearchPage().run(state): + for _ in DocSearchPage().run_v2(request, response): pass except EmptySearchResults: return None - return RelatedDocSearchResponse.parse_obj(state).dict() + outputs.append(response) def render_qna_outputs(state, height, show_count=None): - output_queries = state.get("output_queries", []) - for output in output_queries[:show_count]: - output_text = output.get("output_text", []) + output_queries = state.get("output_queries", [])[:show_count] + for i, result in enumerate(output_queries): + output_text = result.get("output_text", []) if not output_text: continue - references = output.get("references", []) - st.write(f"**{output.get('search_query')}**") + references = result.get("references", []) + st.write(f"##### _{i + 1}. {result.get('search_query')}_") render_output_with_refs( {"output_text": output_text, "references": references}, height ) render_sources_widget(references) - st.write("---") + st.write("
") diff --git a/recipes/SEOSummary.py b/recipes/SEOSummary.py index a23f0786a..ebe1f4e12 100644 --- a/recipes/SEOSummary.py +++ b/recipes/SEOSummary.py @@ -70,7 +70,7 @@ def preview_description(self, state: dict) -> str: keywords="outdoor rugs,8x10 rugs,rug sizes,checkered rugs,5x7 rugs", title="Ruggable", company_url="https://ruggable.com", - serp_serach_type=SerpSearchType.SEARCH, + serp_search_type=SerpSearchType.SEARCH, serp_search_location=SerpSearchLocation.UNITED_STATES, enable_html=False, selected_model=LargeLanguageModels.text_davinci_003.name, diff --git a/recipes/VideoBots.py b/recipes/VideoBots.py index 09beb250f..59697a0c6 100644 --- a/recipes/VideoBots.py +++ b/recipes/VideoBots.py @@ -15,6 +15,8 @@ from daras_ai.image_input import ( truncate_text_words, ) +from daras_ai_v2.prompt_vars import render_prompt_vars, prompt_vars_widget +from daras_ai_v2.query_generator import generate_final_search_query from recipes.GoogleGPT import SearchReference from daras_ai_v2.asr import ( run_google_translate, @@ -175,6 +177,7 @@ class VideoBotsPage(BasePage): "documents": [], "task_instructions": "Make sure to use only the following search results to guide your response. " 'If the Search Results do not contain enough information, say "I don\'t know".', + "query_instructions": " \n{{ messages }} \n\n \n{{ input_prompt }} \n\n \nGiven the conversation, only rephrase the last message to be a standalone statement in 2nd person's perspective. Make sure you include only the relevant parts of the conversation required to answer the follow-up question, and not the answer to the question. If the conversation is irrelevant to the current question being asked, discard it. Don't use quotes in your response. \n\n", "max_references": 3, "max_context_words": 200, "scroll_jump": 5, @@ -233,6 +236,8 @@ class RequestModel(BaseModel): user_language: str | None + variables: dict[str, typing.Any] | None + class ResponseModel(BaseModel): final_prompt: str raw_input_text: str | None @@ -304,6 +309,13 @@ def render_form_v2(self): """ ) + prompt_vars_widget( + "bot_script", + "task_instructions", + "query_instructions", + "keyword_instructions", + ) + def render_usage_guide(self): youtube_video("-j2su1r8pEg") @@ -553,9 +565,7 @@ def run(self, state: dict) -> typing.Iterator[str | None]: # consturct the system prompt if system_message: - # add time to prompt - utcnow = datetime.datetime.utcnow().strftime("%B %d, %Y %H:%M:%S %Z") - system_message = system_message.replace("{{ datetime.utcnow }}", utcnow) + system_message = render_prompt_vars(system_message, state) # insert to top system_prompt = {"role": CHATML_ROLE_SYSTEM, "content": system_message} else: @@ -596,17 +606,11 @@ def run(self, state: dict) -> typing.Iterator[str | None]: query_instructions = (request.query_instructions or "").strip() if query_instructions: yield "Generating search query..." - query_instructions = jinja2.Template(query_instructions).render( - {**state, "messages": chat_history}, + state["final_search_query"] = generate_final_search_query( + request=request, + instructions=query_instructions, + context={**state, "messages": chat_history}, ) - state["final_search_query"] = run_language_model( - model=request.selected_model, - prompt=query_instructions, - max_tokens=model_max_tokens[model] // 2, - quality=request.quality, - temperature=request.sampling_temperature, - avoid_repetition=request.avoid_repetition, - )[0].strip() else: query_msgs.reverse() state["final_search_query"] = "\n---\n".join( @@ -616,17 +620,11 @@ def run(self, state: dict) -> typing.Iterator[str | None]: keyword_instructions = (request.keyword_instructions or "").strip() if keyword_instructions: yield "Exctracting keywords..." - keyword_instructions = jinja2.Template(keyword_instructions).render( - {**state, "messages": chat_history}, + state["final_keyword_query"] = generate_final_search_query( + request=request, + instructions=keyword_instructions, + context={**state, "messages": chat_history}, ) - state["final_keyword_query"] = run_language_model( - model=request.selected_model, - prompt=keyword_instructions, - max_tokens=model_max_tokens[model] // 2, - quality=request.quality, - temperature=request.sampling_temperature, - avoid_repetition=request.avoid_repetition, - )[0].strip() # perform doc search references = yield from get_top_k_references( @@ -648,9 +646,11 @@ def run(self, state: dict) -> typing.Iterator[str | None]: state["references"] = references # if doc search is successful, add the search results to the user prompt if references: + # add task instructions + task_instructions = render_prompt_vars(request.task_instructions, state) user_prompt["content"] = ( references_as_prompt(references) - + f"\n**********\n{request.task_instructions.strip()}\n**********\n" + + f"\n**********\n{task_instructions.strip()}\n**********\n" + user_prompt["content"] ) @@ -875,14 +875,14 @@ def messenger_bot_integration(self): integrations: QuerySet[BotIntegration] = BotIntegration.objects.filter( billing_account_uid=self.request.user.uid - ).order_by("platform") + ).order_by("platform", "-created_at") if not integrations: return current_sr = self.get_sr_from_query_params_dict(gooey_get_query_params()) for bi in integrations: is_connected = bi.saved_run == current_sr - col1, col2, *_ = st.columns([1, 1, 2]) + col1, col2, col3, *_ = st.columns([1, 1, 2]) with col1: favicon = Platform(bi.platform).get_favicon() st.markdown( @@ -897,12 +897,44 @@ def messenger_bot_integration(self): "🔌💔️ Disconnect" if is_connected else "🖇️ Connect", key=f"btn_connect_{bi.id}", ) + with col3: + if bi.platform == Platform.SLACK: + with st.expander("📨 Slack Settings"): + read_receipt_key = "slack_read_receipt_" + str(bi.id) + st.session_state.setdefault( + read_receipt_key, bi.slack_read_receipt_msg + ) + read_msg = st.text_input( + "Read Receipt (leave blank to disable)", + key=read_receipt_key, + placeholder=bi.slack_read_receipt_msg, + ) + bot_name_key = "slack_bot_name_" + str(bi.id) + st.session_state.setdefault(bot_name_key, bi.name) + bot_name = st.text_input( + "Channel Specific Bot Name (to be displayed in Slack)", + key=bot_name_key, + placeholder=bi.name, + ) + if st.button("Reset to Default"): + bi.name = st.session_state.get( + StateKeys.page_title, bi.name + ) + bi.slack_read_receipt_msg = BotIntegration._meta.get_field( + "slack_read_receipt_msg" + ).default + bi.save() + st.experimental_rerun() + if st.button("Update"): + bi.slack_read_receipt_msg = read_msg + bi.name = bot_name + bi.save() + st.experimental_rerun() if not pressed: continue if is_connected: bi.saved_run = None else: - bi.name = st.session_state.get(StateKeys.page_title, bi.name) bi.saved_run = current_sr if bi.platform == Platform.SLACK: from daras_ai_v2.slack_bot import send_confirmation_msg diff --git a/routers/slack.py b/routers/slack.py index 1ac277052..e71149169 100644 --- a/routers/slack.py +++ b/routers/slack.py @@ -1,19 +1,26 @@ -import requests -from furl import furl import json +import requests +from django.db import transaction from fastapi import APIRouter, HTTPException, Depends, Request, Response +from furl import furl from requests.auth import HTTPBasicAuth from sentry_sdk import capture_exception from starlette.background import BackgroundTasks from starlette.responses import RedirectResponse, HTMLResponse from bots.models import BotIntegration, Platform +from bots.tasks import create_personal_channels_for_all_members from daras_ai_v2 import settings from daras_ai_v2.bots import _on_msg, request_json, request_urlencoded_body - -from daras_ai_v2.slack_bot import SlackBot, SlackMessage, invite_bot_account_to_channel -from django.db import transaction +from daras_ai_v2.slack_bot import ( + SlackBot, + SlackMessage, + invite_bot_account_to_channel, + create_personal_channel, + SlackAPIError, + fetch_user_info, +) router = APIRouter() @@ -32,10 +39,13 @@ "groups:history", "groups:read", "groups:write", + "groups:write.invites", + "groups:write.topic", "incoming-webhook", "remote_files:read", "remote_files:share", "remote_files:write", + "users:read", ] ), user_scope=",".join( @@ -44,7 +54,6 @@ "channels:write.invites", "groups:write", "groups:write.invites", - # "chat:write", ] ), ), @@ -66,49 +75,65 @@ def slack_connect_redirect(request: Request): + retry_button, status_code=400, ) - res = requests.post( + r = requests.post( furl( "https://slack.com/api/oauth.v2.access", query_params=dict(code=code), ).url, auth=HTTPBasicAuth(settings.SLACK_CLIENT_ID, settings.SLACK_CLIENT_SECRET), ) - res.raise_for_status() - print(res.text) - res = res.json() - slack_access_token = res["access_token"] - slack_workspace = res["team"]["name"] - slack_channel = res["incoming_webhook"]["channel"] - slack_channel_id = res["incoming_webhook"]["channel_id"] - slack_channel_hook_url = res["incoming_webhook"]["url"] - slack_bot_user_id = res["bot_user_id"] - slack_user_access_token = res["authed_user"]["access_token"] - - invite_bot_account_to_channel( - slack_channel_id, slack_bot_user_id, slack_user_access_token - ) + r.raise_for_status() + print("> slack_connect_redirect:", r.text) + + data = r.json() + slack_access_token = data["access_token"] + slack_team_id = data["team"]["id"] + slack_team_name = data["team"]["name"] + slack_channel_id = data["incoming_webhook"]["channel_id"] + slack_channel_name = data["incoming_webhook"]["channel"].strip("#") + slack_channel_hook_url = data["incoming_webhook"]["url"] + slack_bot_user_id = data["bot_user_id"] + slack_user_access_token = data["authed_user"]["access_token"] + + try: + invite_bot_account_to_channel( + slack_channel_id, slack_bot_user_id, slack_user_access_token + ) + except SlackAPIError as e: + capture_exception(e) + return HTMLResponse( + f"

Oh No! Something went wrong here.

{repr(e)}

" + retry_button, + status_code=400, + ) config = dict( slack_access_token=slack_access_token, slack_channel_hook_url=slack_channel_hook_url, billing_account_uid=request.user.uid, + slack_team_name=slack_team_name, + slack_channel_name=slack_channel_name, ) with transaction.atomic(): bi, created = BotIntegration.objects.get_or_create( slack_channel_id=slack_channel_id, + slack_team_id=slack_team_id, defaults=dict( **config, - name=slack_workspace + " - " + slack_channel, + name=f"{slack_team_name} | #{slack_channel_name}", platform=Platform.SLACK, show_feedback_buttons=True, ), ) if not created: BotIntegration.objects.filter(pk=bi.pk).update(**config) + bi.refresh_from_db() + + if bi.slack_create_personal_channels: + create_personal_channels_for_all_members.delay(bi.id) return HTMLResponse( - f"Sucessfully Connected to {slack_workspace} workspace on {slack_channel}! You may now close this page." + f"Sucessfully Connected to {slack_team_name} workspace on #{slack_channel_name}! You may now close this page." ) @@ -118,28 +143,28 @@ def slack_interaction( data: dict = Depends(request_urlencoded_body), ): data = json.loads(data.get("payload", ["{}"])[0]) - print("slack_interaction: " + str(data)) + print("> slack_interaction:", data) if not data: raise HTTPException(400, "No payload") if data["token"] != settings.SLACK_VERIFICATION_TOKEN: raise HTTPException(403, "Only accepts requests from Slack") - if data["type"] == "block_actions": - workspace_id = data["team"]["id"] - application_id = data["api_app_id"] - bot = SlackBot( - SlackMessage( - workspace_id=workspace_id, - application_id=application_id, - channel=data["channel"]["id"], - thread_ts=data["container"]["thread_ts"], - text="", - user=data["user"]["id"], - files=[], - actions=data["actions"], - msg_id=data["container"]["message_ts"], - ) + if data["type"] != "block_actions": + return + bot = SlackBot( + SlackMessage( + application_id=data["api_app_id"], + channel=data["channel"]["id"], + thread_ts=data["container"]["thread_ts"], + text="", + user_id=data["user"]["id"], + # user_name=data["user"]["id"], + files=[], + actions=data["actions"], + msg_id=data["container"]["message_ts"], + team_id=data["team"]["id"], ) - background_tasks.add_task(_on_msg, bot) + ) + background_tasks.add_task(_on_msg, bot) @router.post("/__/slack/event/") @@ -151,41 +176,67 @@ def slack_event( raise HTTPException(403, "Only accepts requests from Slack") if data["type"] == "url_verification": return data["challenge"] - print("slack_eventhook: " + str(data)) - if data["type"] == "event_callback": - workspace_id = data["team_id"] - application_id = data["api_app_id"] - event = data["event"] - if event["type"] == "message": - if event.get("subtype", "text") not in [ - "text", - "slack_audio", - "file_share", - ]: - print("ignoring message subtype: " + event.get("subtype")) - return Response("OK") # ignore messages from bots, and service messages - try: + print("> slack_event:", data) + _handle_slack_event(data, background_tasks) + return Response("OK") + + +def _handle_slack_event(data: dict, background_tasks: BackgroundTasks): + if data["type"] != "event_callback": + return + event = data["event"] + if event["type"] != "message": + return + + try: + match event.get("subtype", "any"): + case "channel_join": + bi = BotIntegration.objects.get( + slack_channel_id=event["channel"], + slack_team_id=data["team_id"], + ) + if not bi.slack_create_personal_channels: + return + try: + user = fetch_user_info(event["user"], bi.slack_access_token) + except SlackAPIError as e: + if e.error == "missing_scope": + print(f"Error: Missing scopes for - {event!r}") + capture_exception(e) + else: + raise + else: + create_personal_channel(bi, user) + + case "any" | "slack_audio" | "file_share": + files = event.get("files", []) + if not files: + event.get("messsage", {}).get("files", []) + if not files: + attachments = event.get("attachments", []) + files = [ + file + for attachment in attachments + for file in attachment.get("files", []) + ] bot = SlackBot( SlackMessage( - workspace_id=workspace_id, - application_id=application_id, + application_id=(data["api_app_id"]), channel=event["channel"], thread_ts=event["event_ts"], text=event.get("text", ""), - user=event["user"], - files=event.get("files", []), + user_id=event["user"], + files=files, actions=[], msg_id=event["ts"], + team_id=event.get("team", data["team_id"]), ) ) - except BotIntegration.DoesNotExist as e: - capture_exception(e) - print("contacted from an on-monitored channel, ignoring:", e) - return Response( - "OK" - ) # contacted from a channel that this integration has not been explicitly connected to (we recieve events from all channels in WorkSpace), ignore message - background_tasks.add_task(_on_msg, bot) - return Response("OK") + background_tasks.add_task(_on_msg, bot) + + except BotIntegration.DoesNotExist as e: + print(f"Error: contacted from an unknown channel - {e!r}") + capture_exception(e) @router.get("/__/slack/redirect/shortcuts/") diff --git a/tests/test_prompt_vars.py b/tests/test_prompt_vars.py index 52a384f28..a8ac43063 100644 --- a/tests/test_prompt_vars.py +++ b/tests/test_prompt_vars.py @@ -24,4 +24,5 @@ ], ) def test_prompt_vars(prompt, state, variables, expected): - assert render_prompt_vars(prompt, state=state, variables=variables) == expected + state["variables"] = variables + assert render_prompt_vars(prompt, state) == expected diff --git a/tests/test_slack.py b/tests/test_slack.py new file mode 100644 index 000000000..6a82b1113 --- /dev/null +++ b/tests/test_slack.py @@ -0,0 +1,6 @@ +from daras_ai_v2.slack_bot import safe_channel_name + + +def test_slack_safe_channel_name(): + assert safe_channel_name("hello world!") == "hello-world" + assert safe_channel_name("My, Awesome, Channel %") == "my-awesome-channel"