diff --git a/agents-api/notebooks/main-3-Copy1.ipynb b/agents-api/notebooks/main-3-Copy1.ipynb deleted file mode 100644 index 3e6b53ce4..000000000 --- a/agents-api/notebooks/main-3-Copy1.ipynb +++ /dev/null @@ -1,4343 +0,0 @@ -{ - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "6c15055f-a62e-49d4-87e3-18a759c1b8c0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Collecting yamlmagic\n", - " Downloading yamlmagic-0.2.0-py2.py3-none-any.whl.metadata (3.8 kB)\n", - "Downloading yamlmagic-0.2.0-py2.py3-none-any.whl (5.5 kB)\n", - "Installing collected packages: yamlmagic\n", - "Successfully installed yamlmagic-0.2.0\n", - "\n", - "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m24.0\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.2\u001b[0m\n", - "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n" - ] - } - ], - "source": [ - "!pip install yamlmagic" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "17243984-ad4b-4f0f-98ee-bcccbdab43b1", - "metadata": {}, - "outputs": [], - "source": [ - "%reload_ext yamlmagic" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "e2ace0ea-679d-4ec6-b810-d71aee64bc31", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "UsageError: Cell magic `%%yaml` not found.\n" - ] - } - ], - "source": [ - "%%yaml\n", - "name: recommend news articles\n", - "\n", - "input_schema:\n", - " type: object\n", - " properties:\n", - " user_ppid:\n", - " type: string\n", - " \n", - "tools:\n", - " - name: get_user_from_ppid\n", - " description: Get a user from the user ppid\n", - " system:\n", - " resource: user\n", - " operation: list\n", - "\n", - " - name: get_user_docs\n", - " description: Get user docs\n", - " system:\n", - " resource: user\n", - " subresource: doc\n", - " operation: list\n", - " \n", - " - name : search_agent_docs\n", - " description: Get agent docs\n", - " system: \n", - " resource: agent\n", - " subresource: doc\n", - " operation: search \n", - " \n", - "main:\n", - " # Get the user from the ppid using metadata_filter (returns a list)\n", - " - tool: get_user_from_ppid\n", - " arguments:\n", - " limit: \"1\"\n", - " metadata_filter:\n", - " ppid: inputs[0]['user_ppid']\n", - "\n", - " # Unwrap the list to get the user\n", - " - evaluate:\n", - " user: _[0]\n", - "\n", - " - tool: get_user_docs\n", - " arguments:\n", - " user_id: _.user.id\n", - " limit: \"1\"\n", - " sort_by: \"'created_at'\"\n", - " direction: \"'desc'\"\n", - "\n", - " #user persona will always be available here\n", - " - evaluate:\n", - " user_embedding: _[0].embeddings\n", - " persona: _[0].content\n", - "\n", - " #Embedding similarity it will rank the docs\n", - " - tool: search_agent_docs\n", - " arguments:\n", - " vector: _.user_embedding\n", - " agent_id: \"'847b03b1-856a-4ae1-a1f5-ad994ba5c87d'\"\n", - "\n", - " #not sure how to evaluate news_titles\n", - " - evaluate:\n", - " top_titles: \"{{ [doc['title'] for doc in _['docs'][:50]] }}\"\n", - "\n", - " - prompt: \n", - " - role: user\n", - " content: Which of these {{_.top_titles}} do you think the user will like. Rank them according to the users' \n", - " persona {{inputs[2].biodata}} and give me the top 5 as valid yaml\n", - " unwrap: true\n", - " \n", - " - evaluate:\n", - " titles: load_yaml(_)\n", - " \n", - " - prompt: \n", - " - role: user\n", - " content: based on these 5 news {{_.titles}} and users' persona {{inputs[2].biodata}}, draft a catchy newsletter title.\n", - " unwrap: true\n", - " \n", - " - evaluate:\n", - " newsletter_title: _\n", - " titles: output[7].titles\n" - ] - }, - { - "cell_type": "markdown", - "id": "36cdb647", - "metadata": {}, - "source": [ - "### Imports" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "469351b4", - "metadata": {}, - "outputs": [], - "source": [ - "from julep import Julep\n", - "import yaml\n", - "import pandas as pd\n", - "import uuid\n", - "from tqdm import tqdm" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "e226d8a8", - "metadata": {}, - "outputs": [], - "source": [ - "# Keys\n", - "api_key = \"eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzUxMiJ9.eyJleHAiOjE3MzM2OTkxOTEsImlhdCI6MTcyODUxNTE5MSwic3ViIjoiMDAwMDAwMDAtMDAwMC0wMDAwLTAwMDAtMDAwMDAwMDAwMDAwIn0.OOiS_MkP1QEOMQ2Gs13JeZsFCPkR-ldbNtedK9iS3qIxSN_fSPGzajcdbLtedZZYD9OwMsBg4sKvmkeyrBti9w\"\n", - "environment = \"local_multi_tenant\"" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "d3ae8ee1", - "metadata": {}, - "outputs": [], - "source": [ - "client = Julep(api_key=api_key, environment=environment)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "a9be17de", - "metadata": {}, - "outputs": [], - "source": [ - "# df = pd.read_csv('power_users.csv')\n", - "# df.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "fde31169", - "metadata": {}, - "outputs": [], - "source": [ - "# df1 = pd.read_csv('titles_10k.csv')\n", - "# df1.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "c914cc2d", - "metadata": {}, - "outputs": [], - "source": [ - "# df1.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "b602a821", - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "# articles = df1['titles'].unique().tolist()\n", - "# len(articles)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "345f9840-2d43-4231-a063-09e7f390bb31", - "metadata": {}, - "outputs": [], - "source": [ - "import datetime\n", - "\n", - "UserData = lambda about, metadata, name, **kwargs: {\n", - " \"about\": about,\n", - " \"metadata\": metadata,\n", - " \"name\": name,\n", - "}\n", - "\n", - "user_data = [\n", - " UserData(\n", - " id=\"f2e900fd-c7b4-424b-b71d-d75d4a6d7692\",\n", - " created_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 371884, tzinfo=datetime.timezone.utc\n", - " ),\n", - " updated_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 371885, tzinfo=datetime.timezone.utc\n", - " ),\n", - " about=\"\",\n", - " metadata={\n", - " \"age\": 73,\n", - " \"city\": \"Springfield\",\n", - " \"entity_likes\": \"{Others=51, Sean Payton=2, LeBron James=2, Kyle Busch=12, Matt Eberflus=1, Tony Stewart=19, Dale Earnhardt Jr=6, Usain Bolt=1, Ronda Rousey=1, Khabib=1, Jim Harbaugh=1, Denny Hamlin=8, Bubba Wallace=6, Dana White=1, Michael Jordan=9, Patrick Mahomes=2}\",\n", - " \"latest_sport_read\": \"nascar\",\n", - " \"ppid\": \"nnqkt17143103131230f7ff7d9f6ca\",\n", - " \"sports_likes\": \"{ufc=3, nba active=3, uss=1, nascar=98, nfl active=15, college football=3}\",\n", - " \"state\": \"IL\",\n", - " \"top_entity\": \"Tony Stewart\",\n", - " \"top_sources\": \"discover\",\n", - " \"top_sport\": \"nascar\",\n", - " },\n", - " name=\"user_12976\",\n", - " ),\n", - " UserData(\n", - " id=\"4950ec58-2a5c-45da-887a-27799672a3d8\",\n", - " created_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 362493, tzinfo=datetime.timezone.utc\n", - " ),\n", - " updated_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 362494, tzinfo=datetime.timezone.utc\n", - " ),\n", - " about=\"\",\n", - " metadata={\n", - " \"age\": 28,\n", - " \"city\": \"Pensacola\",\n", - " \"entity_likes\": \"{Tara Davis Woodhall=2, Dan Quinn=2, Elaine Thompson=1, Shaquille ONeal=5, Bronny James=2, Caitlin Clark=6, Chennedy Carter=2, Sydney McLaughlin=1, ShaCarri Richardson=14, Dawn Staley=2, Gabby Thomas=3, Deion Sanders=62, Noah Lyles=10, Simone Biles=13, Others=118, Serena Williams=2, LeBron James=2, Quincy Wilson=1, Rebeca Andrade=1, Angel Reese=2, Usain Bolt=4, Michael Jordan=4, Floyd Mayweather=2, Patrick Mahomes=5}\",\n", - " \"latest_sport_read\": \"nba\",\n", - " \"ppid\": \"7tvpm1710440006185f5ec40de54bf\",\n", - " \"sports_likes\": \"{wnba=11, ufc=1, nba active=10, uss=58, boxing=2, nba legends=8, nfl active=9, nba=1, college football=163, tennis=3}\",\n", - " \"state\": \"FL\",\n", - " \"top_entity\": \"Deion Sanders\",\n", - " \"top_sources\": \"discover\",\n", - " \"top_sport\": \"college football\",\n", - " },\n", - " name=\"user_12975\",\n", - " ),\n", - " UserData(\n", - " id=\"c844b69d-72bc-4bc1-8beb-edbb26ba0619\",\n", - " created_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 353159, tzinfo=datetime.timezone.utc\n", - " ),\n", - " updated_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 353159, tzinfo=datetime.timezone.utc\n", - " ),\n", - " about=\"\",\n", - " metadata={\n", - " \"age\": 44,\n", - " \"city\": \"Canton\",\n", - " \"entity_likes\": \"{Tara Davis Woodhall=1, Dan Quinn=2, Elaine Thompson=1, Shaquille ONeal=10, Sean Payton=1, Tom Brady=1, Caitlin Clark=10, Sydney McLaughlin=9, ShaCarri Richardson=27, Gabby Thomas=5, Deion Sanders=16, Noah Lyles=7, Simone Biles=2, Breanna Stewart=1, Others=65, Serena Williams=6, LeBron James=14, Quincy Wilson=2, Sabrina Ionescu=2, Angel Reese=5, Erriyon Knighton=1, Shericka Jackson=2, Usain Bolt=3, Hezley Rivera=1, Dana White=1, Michael Jordan=7, Candace Parker=2, Patrick Mahomes=2}\",\n", - " \"latest_sport_read\": \"nfl\",\n", - " \"ppid\": \"c66581710732168012f4dec26d05e8\",\n", - " \"sports_likes\": \"{wnba=14, ufc=1, nba active=21, uss=70, boxing=6, nba legends=27, nfl active=15, nfl legends=1, college football=42, tennis=9}\",\n", - " \"state\": \"OH\",\n", - " \"top_entity\": \"ShaCarri Richardson\",\n", - " \"top_sources\": \"discover\",\n", - " \"top_sport\": \"uss\",\n", - " },\n", - " name=\"user_12974\",\n", - " ),\n", - " UserData(\n", - " id=\"4795faad-93ee-4f50-94f7-bafe62d47bc1\",\n", - " created_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 343759, tzinfo=datetime.timezone.utc\n", - " ),\n", - " updated_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 343759, tzinfo=datetime.timezone.utc\n", - " ),\n", - " about=\"\",\n", - " metadata={\n", - " \"age\": 58,\n", - " \"city\": \"Tulsa\",\n", - " \"entity_likes\": \"{Dale Earnhardt Jr=9, Others=54, Jordan Chiles=1, Denny Hamlin=8, Kyle Busch=13, Tony Stewart=27, Michael Jordan=7, Michael Phelps=1, Simone Biles=1}\",\n", - " \"latest_sport_read\": \"nascar\",\n", - " \"ppid\": \"l5t7w1709681830793f7f665e6157a\",\n", - " \"sports_likes\": \"{nba legends=1, uss=3, nascar=116, others=1}\",\n", - " \"state\": \"OK\",\n", - " \"top_entity\": \"Tony Stewart\",\n", - " \"top_sources\": \"discover\",\n", - " \"top_sport\": \"nascar\",\n", - " },\n", - " name=\"user_12973\",\n", - " ),\n", - " UserData(\n", - " id=\"9e11ac42-5c54-4e75-a363-aabd91358c28\",\n", - " created_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 334396, tzinfo=datetime.timezone.utc\n", - " ),\n", - " updated_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 334397, tzinfo=datetime.timezone.utc\n", - " ),\n", - " about=\"\",\n", - " metadata={\n", - " \"age\": 44,\n", - " \"city\": \"Wilton Manors\",\n", - " \"entity_likes\": \"{Dale Earnhardt Jr=8, Others=58, Kyle Busch=9, Denny Hamlin=9, Tony Stewart=20, Bubba Wallace=5, Michael Jordan=3, Patrick Mahomes=2}\",\n", - " \"latest_sport_read\": \"nascar\",\n", - " \"ppid\": \"fnpdj17097029293234deb46e2583a\",\n", - " \"sports_likes\": \"{nfl active=2, uss=1, nascar=111}\",\n", - " \"state\": \"FL\",\n", - " \"top_entity\": \"Tony Stewart\",\n", - " \"top_sources\": \"discover\",\n", - " \"top_sport\": \"nascar\",\n", - " },\n", - " name=\"user_12972\",\n", - " ),\n", - " UserData(\n", - " id=\"9be35edc-467f-41bd-acb3-320aa5ecffcf\",\n", - " created_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 324930, tzinfo=datetime.timezone.utc\n", - " ),\n", - " updated_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 324931, tzinfo=datetime.timezone.utc\n", - " ),\n", - " about=\"\",\n", - " metadata={\n", - " \"age\": 72,\n", - " \"city\": \"Maryville\",\n", - " \"entity_likes\": \"{Others=54, Bill Belichick=1, Kyle Busch=15, Tony Stewart=23, Caitlin Clark=2, Dale Earnhardt Jr=15, Olivia Dunne=2, Denny Hamlin=8, Bubba Wallace=2, Michael Jordan=7, Simone Biles=3, Patrick Mahomes=10}\",\n", - " \"latest_sport_read\": \"nascar\",\n", - " \"ppid\": \"5r6np1711468788752e89901959a1c\",\n", - " \"sports_likes\": \"{wnba=3, nfl active=11, uss=5, nascar=122, others=1}\",\n", - " \"state\": \"TN\",\n", - " \"top_entity\": \"Tony Stewart\",\n", - " \"top_sources\": \"discover\",\n", - " \"top_sport\": \"nascar\",\n", - " },\n", - " name=\"user_12971\",\n", - " ),\n", - " UserData(\n", - " id=\"6b9a9c0b-a1c6-45eb-9085-41e83e3d12e2\",\n", - " created_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 315598, tzinfo=datetime.timezone.utc\n", - " ),\n", - " updated_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 315599, tzinfo=datetime.timezone.utc\n", - " ),\n", - " about=\"\",\n", - " metadata={\n", - " \"age\": 45,\n", - " \"city\": \"Captain Cook\",\n", - " \"entity_likes\": \"{Dale Earnhardt Jr=10, Others=42, Kyle Busch=8, Denny Hamlin=6, Tony Stewart=23, Bubba Wallace=4, Michael Jordan=10}\",\n", - " \"latest_sport_read\": \"nascar\",\n", - " \"ppid\": \"tlwvs17162229474718d60903eaf36\",\n", - " \"sports_likes\": \"{nascar=103}\",\n", - " \"state\": \"HI\",\n", - " \"top_entity\": \"Tony Stewart\",\n", - " \"top_sources\": \"discover\",\n", - " \"top_sport\": \"nascar\",\n", - " },\n", - " name=\"user_12970\",\n", - " ),\n", - " UserData(\n", - " id=\"60df090e-cb0d-4d56-a5cd-bcf7162dbbd4\",\n", - " created_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 306010, tzinfo=datetime.timezone.utc\n", - " ),\n", - " updated_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 306011, tzinfo=datetime.timezone.utc\n", - " ),\n", - " about=\"\",\n", - " metadata={\n", - " \"age\": 50,\n", - " \"city\": \"Wagram\",\n", - " \"entity_likes\": \"{Others=50, Shaquille ONeal=2, LeBron James=3, Kyle Busch=9, Tony Stewart=5, Caitlin Clark=2, Dale Earnhardt Jr=6, Deion Sanders=17, Jim Harbaugh=4, Denny Hamlin=4, Bubba Wallace=4, Michael Jordan=17}\",\n", - " \"latest_sport_read\": \"nba\",\n", - " \"ppid\": \"8wgxh17023089742317e2410af281a\",\n", - " \"sports_likes\": \"{wnba=3, nba active=8, wwe=3, nascar=52, nba legends=12, nfl active=3, nfl legends=1, college football=40, others=1}\",\n", - " \"state\": \"NC\",\n", - " \"top_entity\": \"Deion Sanders\",\n", - " \"top_sources\": \"discover\",\n", - " \"top_sport\": \"nascar\",\n", - " },\n", - " name=\"user_12969\",\n", - " ),\n", - " UserData(\n", - " id=\"b3a5d5d5-01f1-499f-af3e-0e0047bb4d58\",\n", - " created_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 296415, tzinfo=datetime.timezone.utc\n", - " ),\n", - " updated_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 296415, tzinfo=datetime.timezone.utc\n", - " ),\n", - " about=\"\",\n", - " metadata={\n", - " \"age\": 55,\n", - " \"city\": \"Marion\",\n", - " \"entity_likes\": \"{Dale Earnhardt Jr=7, Others=63, Kyle Busch=38, Denny Hamlin=14, Tony Stewart=21, Bubba Wallace=11, Michael Jordan=5}\",\n", - " \"latest_sport_read\": \"nascar\",\n", - " \"ppid\": \"5mhq817108288806914ea2e8046bff\",\n", - " \"sports_likes\": \"{nfl active=1, nascar=157, others=1}\",\n", - " \"state\": \"NC\",\n", - " \"top_entity\": \"Kyle Busch\",\n", - " \"top_sources\": \"facebook\",\n", - " \"top_sport\": \"nascar\",\n", - " },\n", - " name=\"user_12968\",\n", - " ),\n", - " UserData(\n", - " id=\"639c741c-6f6a-4c87-be70-e980b412f332\",\n", - " created_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 286775, tzinfo=datetime.timezone.utc\n", - " ),\n", - " updated_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 286775, tzinfo=datetime.timezone.utc\n", - " ),\n", - " about=\"\",\n", - " metadata={\n", - " \"age\": 45,\n", - " \"city\": \"Arcanum\",\n", - " \"entity_likes\": \"{Others=115, Dan Quinn=1, Shaquille ONeal=1, LeBron James=1, Kyle Busch=16, Tony Stewart=27, Angel Reese=1, Tiger Woods=3, Dale Earnhardt Jr=32, ShaCarri Richardson=1, Jim Harbaugh=5, Denny Hamlin=17, Bubba Wallace=7, Michael Jordan=10, Patrick Mahomes=5}\",\n", - " \"latest_sport_read\": \"nascar\",\n", - " \"ppid\": \"6b9rp1699808086600c15fdce82da2\",\n", - " \"sports_likes\": \"{wnba=1, golf=31, nba active=2, uss=1, nascar=192, nba legends=2, nfl active=9, college football=4}\",\n", - " \"state\": \"OH\",\n", - " \"top_entity\": \"Dale Earnhardt Jr\",\n", - " \"top_sources\": \"discover\",\n", - " \"top_sport\": \"nascar\",\n", - " },\n", - " name=\"user_12967\",\n", - " ),\n", - " UserData(\n", - " id=\"83a88deb-b918-4b16-88cc-c8cc37883f12\",\n", - " created_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 277434, tzinfo=datetime.timezone.utc\n", - " ),\n", - " updated_at=datetime.datetime(\n", - " 2024, 10, 9, 10, 44, 23, 277435, tzinfo=datetime.timezone.utc\n", - " ),\n", - " about=\"\",\n", - " metadata={\n", - " \"age\": 64,\n", - " \"city\": \"Taneytown\",\n", - " \"entity_likes\": \"{Dan Quinn=2, Shaquille ONeal=4, Sean Payton=1, Joe Rogan=4, Caitlin Clark=5, Chennedy Carter=2, ShaCarri Richardson=4, Alex Rodriguez=2, Ronda Rousey=1, Khabib=3, Olivia Dunne=2, Deion Sanders=5, Jon Jones=2, Noah Lyles=2, Simone Biles=2, Breanna 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presence_penalty=0.0, repetition_penalty=1.0, temperature=1.1, top_p=0.95), instructions=[], metadata={}, model='gpt-4o', name='Poem Emailer'), Agent(id='512de8a6-c5db-4434-914a-937976c326a9', created_at=datetime.datetime(2024, 10, 4, 23, 41, 13, 339146, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 4, 23, 41, 13, 339146, tzinfo=datetime.timezone.utc), about='hello', default_settings=DefaultSettings(frequency_penalty=0.0, length_penalty=1.0, min_p=0.01, presence_penalty=0.0, repetition_penalty=1.0, temperature=0.7, top_p=0.95), instructions=[], metadata={'a': 1}, model='o1-mini', name='hello'), Agent(id='9752eff3-eb17-4814-9f96-c52fb7955255', created_at=datetime.datetime(2024, 10, 1, 17, 56, 57, 112682, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 1, 17, 56, 57, 112684, tzinfo=datetime.timezone.utc), about='An agent that helps users of the Reclaim app verify their ownership of their data and reclaim their data from third-party providers.', default_settings=DefaultSettings(frequency_penalty=0.0, length_penalty=1.0, min_p=0.01, presence_penalty=0.0, repetition_penalty=1.0, temperature=0.7, top_p=0.95), instructions=[], metadata={}, model='gpt-4o', name='Reclaimer Agent'), Agent(id='3bb7bf64-70e3-40aa-be42-fc76299a4729', created_at=datetime.datetime(2024, 10, 1, 17, 56, 28, 525591, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 1, 17, 56, 28, 525592, tzinfo=datetime.timezone.utc), about='An agent that helps users of the Reclaim app verify their ownership of their data and reclaim their data from third-party providers.', default_settings=DefaultSettings(frequency_penalty=0.0, length_penalty=1.0, min_p=0.01, presence_penalty=0.0, repetition_penalty=1.0, temperature=0.7, top_p=0.95), instructions=[], metadata={}, model='gpt-4o', name='Reclaimer Agent'), Agent(id='0274f724-3465-4436-86ff-950b73e47267', created_at=datetime.datetime(2024, 10, 1, 17, 55, 37, 429487, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 1, 17, 55, 37, 429487, tzinfo=datetime.timezone.utc), about='An agent that helps users of the Reclaim app verify their ownership of their data and reclaim their data from third-party providers.', default_settings=DefaultSettings(frequency_penalty=0.0, length_penalty=1.0, min_p=0.01, presence_penalty=0.0, repetition_penalty=1.0, temperature=0.7, top_p=0.95), instructions=[], metadata={}, model='gpt-4o', name='Reclaimer Agent'), Agent(id='68c0ac2b-b355-466e-9db6-fe0689dc1453', created_at=datetime.datetime(2024, 10, 1, 17, 49, 44, 347786, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 1, 17, 49, 44, 347786, tzinfo=datetime.timezone.utc), about='An agent that helps users of the Reclaim app verify their ownership of their data and reclaim their data from third-party providers.', default_settings=DefaultSettings(frequency_penalty=0.0, length_penalty=1.0, min_p=0.01, presence_penalty=0.0, repetition_penalty=1.0, temperature=0.7, top_p=0.95), instructions=[], metadata={}, model='gpt-4o', name='Reclaimer Agent'), Agent(id='65e0dac5-5ef5-427a-aa43-512d0bd21f4d', created_at=datetime.datetime(2024, 10, 1, 17, 48, 13, 731758, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 1, 17, 48, 13, 731759, tzinfo=datetime.timezone.utc), about='An agent that helps users of the Reclaim app verify their ownership of their data and reclaim their data from third-party providers.', default_settings=DefaultSettings(frequency_penalty=0.0, length_penalty=1.0, min_p=0.01, presence_penalty=0.0, repetition_penalty=1.0, temperature=0.7, top_p=0.95), instructions=[], metadata={}, model='gpt-4o', name='Reclaimer Agent')])" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client.agents.list()" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "29d282de", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "SyncOffsetPagination[User](items=[User(id='221e8088-e17e-40f4-982e-6883bdb711e9', created_at=datetime.datetime(2024, 10, 5, 18, 23, 28, 109991, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 5, 18, 23, 28, 109992, tzinfo=datetime.timezone.utc), about='', metadata={'user_ppid': 'xyz'}, name='Diwank'), User(id='2b4e4f91-36d8-4f5c-a3e2-4190b4482df8', created_at=datetime.datetime(2024, 10, 5, 18, 9, 10, 732144, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 5, 18, 9, 10, 732145, tzinfo=datetime.timezone.utc), about='', metadata={'ppid': 'xyz'}, name='Diwank')])" - ] - }, - "execution_count": 17, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client.users.list()" - ] - }, - { - "cell_type": "markdown", - "id": "c96f5022", - "metadata": {}, - "source": [ - "## Agent with title lib" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "5de0f61b", - "metadata": {}, - "outputs": [], - "source": [ - "# Defining the agent\n", - "name = \"NewsLibraryAgent\"\n", - "about = \"It is used to manage a library of news article titles and their related data\"\n", - "default_settings = {\n", - " \"temperature\": 0.6,\n", - " \"top_p\": 0.9,\n", - " \"min_p\": 0.05,\n", - " \"presence_penalty\": 0.2,\n", - " \"frequency_penalty\": 0.2,\n", - " \"length_penalty\": 1.0,\n", - "}\n", - "\n", - "\n", - "# Create the agent\n", - "agent = client.agents.create_or_update(\n", - " agent_id=\"847b03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " name=name,\n", - " about=about,\n", - " model=\"gpt-4o\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "0392d3c6", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ResourceCreated(id='602641f5-29cb-4895-886f-d4db4ba47d8e', created_at=datetime.datetime(2024, 10, 9, 10, 45, 39, 700109, tzinfo=datetime.timezone.utc), jobs=['78251ce4-9199-49e6-a5de-f52e3cc1b537'])" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client.agents.docs.create(\n", - " agent_id=\"847d03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " title=\"NewsTitles\",\n", - " content=articles[:25000],\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "id": "fa817293", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "DocSearchResponse(docs=[], time=1.0753483772277832)" - ] - }, - "execution_count": 49, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client.agents.docs.search(\n", - " agent_id=\"847b03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " text=\"nascar-news-kyle-busch-denny-hamlin-brad-keselowski-fans-beef-over-their-superstars-filling-the-void-in-nascar-left-by-legendary-cup-champ\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "id": "4fb0e0be", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "SyncOffsetPagination[Doc](items=[])" - ] - }, - "execution_count": 50, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client.agents.docs.list(agent_id=\"847b03b1-856a-4ae1-a1f5-ad994ba5c87d\")" - ] - }, - { - "cell_type": "markdown", - "id": "c9c08542", - "metadata": {}, - "source": [ - "## User Creation" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "e0e70ef0", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|██████████████████████████████████████████████████████████████████████████████| 100/100 [00:00<00:00, 394.98it/s]\n" - ] - } - ], - "source": [ - "for i in tqdm(range(len(user_data))):\n", - " client.users.create(\n", - " name=f\"user_{i}\",\n", - " metadata={\n", - " \"ppid\": str(user_data[i][\"metadata\"][\"ppid\"]), # Ensure it's a native int\n", - " \"age\": int(user_data[i][\"metadata\"][\"age\"]), # Ensure it's a native int\n", - " \"state\": str(\n", - " user_data[i][\"metadata\"][\"state\"]\n", - " ), # Convert to string if not already\n", - " \"city\": str(\n", - " user_data[i][\"metadata\"][\"city\"]\n", - " ), # Convert to string if not already\n", - " \"sports_likes\": str(\n", - " user_data[i][\"metadata\"][\"sports_likes\"]\n", - " ), # Convert to string or json serializable format\n", - " \"entity_likes\": str(\n", - " user_data[i][\"metadata\"][\"entity_likes\"]\n", - " ), # Same as above\n", - " \"top_sport\": str(user_data[i][\"metadata\"][\"top_sport\"]),\n", - " \"top_entity\": str(user_data[i][\"metadata\"][\"top_entity\"]),\n", - " \"latest_sport_read\": str(user_data[i][\"metadata\"][\"latest_sport_read\"]),\n", - " \"top_sources\": str(user_data[i][\"metadata\"][\"top_sources\"]),\n", - " },\n", - " )" - ] - }, - { - "cell_type": "markdown", - "id": "15531cc5", - "metadata": {}, - "source": [ - "## Profiler " - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "48589b59", - "metadata": {}, - "outputs": [], - "source": [ - "# Defining the agent\n", - "name = \"ProfilerAgent\"\n", - "about = \"It is used to create/update the profile of the user\"\n", - "default_settings = {\n", - " \"temperature\": 0.9,\n", - " \"top_p\": 0.9,\n", - " \"min_p\": 0.05,\n", - " \"presence_penalty\": 0.2,\n", - " \"frequency_penalty\": 0.2,\n", - " \"length_penalty\": 1.0,\n", - " \"max_tokens\": 250,\n", - "}\n", - "\n", - "\n", - "# Create the agent\n", - "agent = client.agents.create_or_update(\n", - " agent_id=\"844e03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " name=name,\n", - " about=about,\n", - " model=\"gpt-4o\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "23649eeb", - "metadata": {}, - "outputs": [], - "source": [ - "# The profiler workflow\n", - "task_def = yaml.safe_load(\"\"\"\n", - "name: generate_update_persona\n", - "\n", - "# Define the input schema for the workflow\n", - "input_schema:\n", - " type: object\n", - " properties:\n", - " user_ppid:\n", - " type: string\n", - " articles_read:\n", - " type: array\n", - " items:\n", - " type: string\n", - " required:\n", - " - user_ppid\n", - " - articles_read\n", - "\n", - "# Define the tools that are going to be used in the workflow\n", - "tools:\n", - " - name: get_user_from_ppid\n", - " description: Get a user from the user ppid\n", - " system:\n", - " resource: user\n", - " operation: list\n", - " \n", - " - name: list_user_docs\n", - " description: List the user docs\n", - " system:\n", - " resource: user\n", - " subresource: doc\n", - " operation: list\n", - "\n", - " - name: create_user_doc\n", - " description: Create a user doc\n", - " system:\n", - " resource: user\n", - " subresource: doc\n", - " operation: create\n", - "\n", - "main:\n", - " # Get the user from the ppid using metadata_filter (returns a list)\n", - " - tool: get_user_from_ppid\n", - " arguments:\n", - " limit: \"1\"\n", - " metadata_filter:\n", - " ppid: inputs[0]['user_ppid']\n", - "\n", - " # Unwrap the list to get the user\n", - " - evaluate:\n", - " user: _[0]\n", - "\n", - "\n", - " # Get the user persona document using metadata_filter (returns a list)\n", - " - tool: list_user_docs\n", - " arguments:\n", - " user_id: _['user']['id']\n", - " limit: \"1\"\n", - " sort_by: \"'created_at'\"\n", - " direction: \"'desc'\"\n", - "\n", - " # Get the doc if it exists\n", - " - evaluate:\n", - " doc: _[0] if len(_) > 0 else {}\n", - "\n", - "\n", - " # Get the user persona from the doc if the doc exists\n", - " - evaluate:\n", - " user_persona: _['doc'].get('content', \"\")\n", - "\n", - "\n", - " # Create the user persona using the prompt step\n", - " - prompt:\n", - " - role: user\n", - " content: You are an expert at creating user profile based on data. Write the user persona based on {{_['user_persona']}} + {{inputs[2]['user']['metadata']}} + {{inputs[0]['articles_read']}}\n", - " unwrap: true\n", - " \n", - " # Create a new persona document\n", - " - tool: create_user_doc\n", - " arguments:\n", - " user_id: inputs[2]['user']['id']\n", - " data:\n", - " title: \"'User Persona Document'\"\n", - " # metadata:\n", - " # user_persona: true\n", - " content: _\n", - "\"\"\")" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "9b211a93", - "metadata": {}, - "outputs": [], - "source": [ - "# Creating/Updating a task\n", - "task = client.tasks.create_or_update(\n", - " task_id=\"813a03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " agent_id=\"844e03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " **task_def,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "beb8fca8", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|█████████████████████████████████████████████████████████████████████████████████| 10/10 [00:00<00:00, 16.50it/s]\n" - ] - } - ], - "source": [ - "for i in tqdm(range(10)): # range(len(user_data))):\n", - " ppid = str(user_data[i][\"metadata\"][\"ppid\"])\n", - " # filtered_df1 = df1[df1['ppid'] == ppid ]\n", - "\n", - " # if not filtered_df1.empty:\n", - " # Creating an Execution\n", - " execution = client.executions.create(\n", - " task_id=\"813a03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " input={\n", - " \"user_ppid\": ppid,\n", - " \"articles_read\": [\n", - " \"nascar-news-they-didnt-wait-for-tony-stewart\",\n", - " \"nfl-ncaa-news-privilege-to-love-travis-hunters\",\n", - " \"nascar-news-stuck-in-a-thirty-million-hole-dal\",\n", - " \"nascar-news-that-shouldnt-take-away-my-playoff\",\n", - " \"nascar-news-kyle-busch-denny-hamlin-brad-kesel\",\n", - " ],\n", - " },\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": 55, - "id": "31b8fc47", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ResourceCreated(id='8e69fbc6-7f10-4067-9b81-4b2015508628', created_at=datetime.datetime(2024, 10, 9, 12, 5, 56, 176543, tzinfo=datetime.timezone.utc), jobs=['6b78a7ea-4703-47a0-9b0c-13111f018586'])" - ] - }, - "execution_count": 55, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "execution" - ] - }, - { - "cell_type": "code", - "execution_count": 56, - "id": "316b33ae", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "SyncOffsetPagination[Transition](items=[])" - ] - }, - "execution_count": 56, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client.executions.transitions.list(execution_id=\"8e69fbc6-7f10-4067-9b81-4b2015508628\")" - ] - }, - { - "cell_type": "markdown", - "id": "07b9042e", - "metadata": {}, - "source": [ - "## Recommendation" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "id": "0dc2b395", - "metadata": {}, - "outputs": [], - "source": [ - "# Defining the agent\n", - "name = \"TitleRecommender\"\n", - "about = \"It is used to recommend the title recommendation for the user\"\n", - "default_settings = {\n", - " \"temperature\": 0.9,\n", - " \"top_p\": 0.9,\n", - " \"min_p\": 0.05,\n", - " \"presence_penalty\": 0.2,\n", - " \"frequency_penalty\": 0.2,\n", - " \"length_penalty\": 1.0,\n", - " \"max_tokens\": 250,\n", - "}\n", - "\n", - "# Create the agent\n", - "agent = client.agents.create_or_update(\n", - " agent_id=\"865e03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " name=name,\n", - " about=about,\n", - " model=\"gpt-4o\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 58, - "id": "c102054e", - "metadata": {}, - "outputs": [], - "source": [ - "for docs in client.agents.docs.list(agent_id=\"847b03b1-856a-4ae1-a1f5-ad994ba5c87d\"):\n", - " client.agents.docs.delete(\n", - " agent_id=\"847b03b1-856a-4ae1-a1f5-ad994ba5c87d\", doc_id=docs.id\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "id": "ead8d197", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(168, 1)" - ] - }, - "execution_count": 59, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df2 = pd.read_csv(\"new_titles.csv\")\n", - "df2.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "id": "b9b839c7", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|█████████████████████████████████████████| 168/168 [00:47<00:00, 3.52it/s]\n" - ] - } - ], - "source": [ - "for i in tqdm(range(len(df2))):\n", - " title = df2.iloc[i][\"post_name\"]\n", - "\n", - " client.agents.docs.create(\n", - " agent_id=\"847b03b1-856a-4ae1-a1f5-ad994ba5c87d\", title=title, content=title\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": 80, - "id": "b9d230e6", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "SyncOffsetPagination[Doc](items=[])" - ] - }, - "execution_count": 80, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client.agents.docs.list(agent_id=\"847b03b1-856a-4ae1-a1f5-ad994ba5c87d\")" - ] - }, - { - "cell_type": "markdown", - "id": "06a417bd", - "metadata": {}, - "source": [ - "1. Delete all the docs of libraryAgents \n", - "\n", - "2. Create new docs for each article with title=headline and content=headline with new batch of article which you are going to recommend\n", - "\n", - "\n", - "3. Get the user_persona\n", - "\n", - "\n", - "4. Ranking based on cosine similarity \n", - "5. Pick 5 articles for this users out of 50 \n", - "6. Recommend the newsletter title based on this articles " - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "id": "ca518cbb", - "metadata": {}, - "outputs": [], - "source": [ - "# The profiler workflow\n", - "task_def1 = yaml.safe_load(\"\"\"\n", - "\n", - "name: recommend news articles\n", - "\n", - "input_schema:\n", - " type: object\n", - " properties:\n", - " user_ppid:\n", - " type: string\n", - " \n", - "tools:\n", - " - name: get_user_from_ppid\n", - " description: Get a user from the user ppid\n", - " system:\n", - " resource: user\n", - " operation: list\n", - "\n", - " - name: get_user_docs\n", - " description: Get user docs\n", - " system:\n", - " resource: user\n", - " subresource: doc\n", - " operation: list\n", - " \n", - " - name : search_agent_docs\n", - " description: Get agent docs\n", - " system: \n", - " resource: agent\n", - " subresource: doc\n", - " operation: search \n", - " \n", - "main:\n", - " # Get the user from the ppid using metadata_filter (returns a list)\n", - " - tool: get_user_from_ppid\n", - " arguments:\n", - " limit: \"1\"\n", - " metadata_filter:\n", - " ppid: inputs[0]['user_ppid']\n", - "\n", - " # Unwrap the list to get the user\n", - " - evaluate:\n", - " user: _[0]\n", - "\n", - " - tool: get_user_docs\n", - " arguments:\n", - " user_id: _.user.id\n", - " limit: \"1\"\n", - " sort_by: \"'created_at'\"\n", - " direction: \"'desc'\"\n", - "\n", - " #user persona will always be available here\n", - " - evaluate:\n", - " user_embedding: _[0].embeddings\n", - " persona: _[0].content\n", - "\n", - " #Embedding similarity it will rank the docs\n", - " - tool: search_agent_docs\n", - " arguments:\n", - " vector: _.user_embedding\n", - " agent_id: \"'847b03b1-856a-4ae1-a1f5-ad994ba5c87d'\"\n", - "\n", - " #not sure how to evaluate news_titles\n", - " - evaluate:\n", - " top_titles: \"{{ [doc['title'] for doc in _['docs'][:50]] }}\"\n", - "\n", - " - prompt: \n", - " - role: user\n", - " content: Which of these {{_.top_titles}} do you think the user will like. Rank them according to the users' \n", - " persona {{inputs[2].biodata}} and give me the top 5 as valid yaml\n", - " unwrap: true\n", - " \n", - " - evaluate:\n", - " titles: load_yaml(_)\n", - " \n", - " - prompt: \n", - " - role: user\n", - " content: based on these 5 news {{_.titles}} and users' persona {{inputs[2].biodata}}, draft a catchy newsletter title.\n", - " unwrap: true\n", - " \n", - " - evaluate:\n", - " newsletter_title: _\n", - " titles: output[7].titles\n", - " \n", - "\"\"\")" - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "id": "12f688c6", - "metadata": {}, - "outputs": [], - "source": [ - "# Creating/Updating a task\n", - "task1 = client.tasks.create_or_update(\n", - " task_id=\"825a03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " agent_id=\"865e03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " **task_def1,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 76, - "id": "374f1b74", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " 21%|███████▌ | 2715/12977 [33:48<2:07:48, 1.34it/s]\n" - ] - }, - { - "ename": "KeyboardInterrupt", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m/var/folders/sm/rll592s91t375q5hbck24ptc0000gn/T/ipykernel_46728/1288718815.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;31m# Creating an Execution\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m execution = client.executions.create(\n\u001b[0m\u001b[1;32m 7\u001b[0m \u001b[0mtask_id\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0;34m'825a03b1-856a-4ae1-a1f5-ad994ba5c87d'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m input = {\n", - "\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/julep/resources/executions/executions.py\u001b[0m in \u001b[0;36mcreate\u001b[0;34m(self, task_id, input, error, metadata, output, extra_headers, extra_query, extra_body, timeout)\u001b[0m\n\u001b[1;32m 97\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mtask_id\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 98\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Expected a non-empty value for `task_id` but received {task_id!r}\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 99\u001b[0;31m return self._post(\n\u001b[0m\u001b[1;32m 100\u001b[0m \u001b[0;34mf\"/tasks/{task_id}/executions\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 101\u001b[0m body=maybe_transform(\n", - 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"\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/httpcore/_sync/http11.py\u001b[0m in \u001b[0;36m_receive_event\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 198\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 199\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mevent\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mh11\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mNEED_DATA\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 200\u001b[0;31m data = self._network_stream.read(\n\u001b[0m\u001b[1;32m 201\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mREAD_NUM_BYTES\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 202\u001b[0m )\n", - "\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/httpcore/_backends/sync.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, max_bytes, timeout)\u001b[0m\n\u001b[1;32m 26\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mmap_exceptions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexc_map\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 27\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msettimeout\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 28\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmax_bytes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 29\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 30\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbuffer\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mbytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mtyping\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mOptional\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mfloat\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/opt/anaconda3/lib/python3.9/ssl.py\u001b[0m in \u001b[0;36mrecv\u001b[0;34m(self, buflen, flags)\u001b[0m\n\u001b[1;32m 1225\u001b[0m \u001b[0;34m\"non-zero flags not allowed in calls to recv() on %s\"\u001b[0m \u001b[0;34m%\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1226\u001b[0m self.__class__)\n\u001b[0;32m-> 1227\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbuflen\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1228\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1229\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbuflen\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflags\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/opt/anaconda3/lib/python3.9/ssl.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, len, buffer)\u001b[0m\n\u001b[1;32m 1100\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sslobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbuffer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1101\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1102\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sslobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1103\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mSSLError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1104\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mSSL_ERROR_EOF\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msuppress_ragged_eofs\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mKeyboardInterrupt\u001b[0m: " - ] - } - ], - "source": [ - "execution_array = []\n", - "for i in tqdm(range(len(df))):\n", - " ppid = str(df.iloc[i][\"ppid\"])\n", - "\n", - " # Creating an Execution\n", - " execution = client.executions.create(\n", - " task_id=\"825a03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " input={\n", - " \"user_ppid\": ppid,\n", - " },\n", - " )\n", - " execution_array.append(execution.id)" - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "id": "e9873437", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['caed8408-235c-4a36-91fe-0559b91ece8d',\n", - " '909b976a-b5d4-40cb-8dd6-8a59d7e246d8',\n", - " '3519ee27-4e83-4ea4-9a25-e4f539eff630',\n", - " '5181be66-ca9d-4fba-a285-39345cb880ec',\n", - " 'b51178a4-b295-48dd-a482-55bdae34124c',\n", - " '6b78d6fb-335e-4fa0-bf1f-e8346bf938c1',\n", - " 'a01f11f8-8d97-4e83-b6cf-64f696247ef2',\n", - " 'b504190d-8be9-4f5e-be1a-8b5cf120e6a1',\n", - " '1f11e027-3456-4bc3-9e10-343bad92757a',\n", - 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" '43a726b6-b467-43c1-b168-a1d5f963a57e',\n", - " '045c30f3-a0b4-49af-a233-8273885d15f1',\n", - " '41c38def-db0d-4f44-ab29-2101f133f848',\n", - " '8bec378c-eda5-4f2a-b2e7-daca60856d18',\n", - " ...]" - ] - }, - "execution_count": 77, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "execution_array" - ] - }, - { - "cell_type": "code", - "execution_count": 82, - "id": "58aa4216", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "Execution(id='caed8408-235c-4a36-91fe-0559b91ece8d', created_at=datetime.datetime(2024, 10, 9, 12, 50, 58, 307650, tzinfo=datetime.timezone.utc), input={'user_ppid': 's7lm2170225005507862d53cc9cf54'}, status='queued', task_id='825a03b1-856a-4ae1-a1f5-ad994ba5c87d', updated_at=datetime.datetime(2024, 10, 9, 12, 50, 58, 307651, tzinfo=datetime.timezone.utc), error=None, metadata={}, output=None)" - ] - }, - "execution_count": 82, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client.executions.get(execution_id=\"caed8408-235c-4a36-91fe-0559b91ece8d\")" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1bc7efde", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.12.5" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/agents-api/notebooks/main-3.ipynb b/agents-api/notebooks/main-3.ipynb deleted file mode 100755 index 130489208..000000000 --- a/agents-api/notebooks/main-3.ipynb +++ /dev/null @@ -1,2000 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "36cdb647", - "metadata": {}, - "source": [ - "### Imports" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "469351b4", - "metadata": {}, - "outputs": [], - "source": [ - "from julep import Julep\n", - "import yaml\n", - "import pandas as pd\n", - "import uuid\n", - "from tqdm import tqdm" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "e226d8a8", - "metadata": {}, - "outputs": [], - "source": [ - "# Keys\n", - "api_key = \"eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzUxMiJ9.eyJleHAiOjE3Mjg1NTc3MDMsImlhdCI6MTcyODUxNDUwNCwic3ViIjoiMDAwMDAwMDAtMDAwMC0wMDAwLTAwMDAtMDAwMDAwMDAwMDAwIn0.WVCaBdSDKI6brYiZyd8ceSjKwGxKHiUcGYl2Mg3Xnr074MTM7YDMQ7leNI_c-_opc518PNPMhfrhO5_xo39MGQ\"\n", - "environment = \"local_multi_tenant\"" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "d3ae8ee1", - "metadata": {}, - "outputs": [], - "source": [ - "client = Julep(api_key=api_key, environment=environment)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "a9be17de", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(12977, 10)" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df = pd.read_csv(\"power_users.csv\")\n", - "df.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "fde31169", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(1458105, 2)" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df1 = pd.read_csv(\"titles_10k.csv\")\n", - "df1.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "c914cc2d", - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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ppidtitles
0zt2xx1676756313616f61fc06ce607nascar-news-kyle-busch-denny-hamlin-brad-kesel...
19ngxq16741971295637bda693f1856nascar-news-that-shouldnt-take-away-my-playoff...
29ngxq16741971295637bda693f1856nascar-news-stuck-in-a-thirty-million-hole-dal...
3t4ft9170231166061272d670d94e26nfl-ncaa-news-privilege-to-love-travis-hunters...
46z9qx1711142742381f25789ebd3f0nascar-news-they-didnt-wait-for-tony-stewart-r...
\n", - "
" - ], - "text/plain": [ - " ppid \\\n", - "0 zt2xx1676756313616f61fc06ce607 \n", - "1 9ngxq16741971295637bda693f1856 \n", - "2 9ngxq16741971295637bda693f1856 \n", - "3 t4ft9170231166061272d670d94e26 \n", - "4 6z9qx1711142742381f25789ebd3f0 \n", - "\n", - " titles \n", - "0 nascar-news-kyle-busch-denny-hamlin-brad-kesel... \n", - "1 nascar-news-that-shouldnt-take-away-my-playoff... \n", - "2 nascar-news-stuck-in-a-thirty-million-hole-dal... \n", - "3 nfl-ncaa-news-privilege-to-love-travis-hunters... \n", - "4 nascar-news-they-didnt-wait-for-tony-stewart-r... " - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df1.head()" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "b602a821", - "metadata": { - "scrolled": true - }, - "outputs": [ - { - "data": { - "text/plain": [ - "35382" - ] - }, - "execution_count": 7, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "articles = df1[\"titles\"].unique().tolist()\n", - "len(articles)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "2ffd5dcd", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "SyncOffsetPagination[Agent](items=[Agent(id='844e03b1-856a-4ae1-a1f5-ad994ba5c87d', created_at=datetime.datetime(2024, 10, 7, 9, 47, 0, 832657, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 7, 9, 47, 0, 831949, tzinfo=datetime.timezone.utc), about='It is used to create/update the profile of the user', default_settings=DefaultSettings(frequency_penalty=0.0, length_penalty=1.0, min_p=0.01, presence_penalty=0.0, repetition_penalty=1.0, temperature=0.7, top_p=0.95), instructions=[], metadata={}, model='gpt-4o', name='ProfilerAgent'), Agent(id='847d03b1-856a-4ae1-a1f5-ad994ba5c87d', created_at=datetime.datetime(2024, 10, 7, 9, 33, 49, 146318, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 7, 9, 33, 49, 145422, tzinfo=datetime.timezone.utc), about='It is used to manage a library of news article titles and their related data', default_settings=DefaultSettings(frequency_penalty=0.0, length_penalty=1.0, min_p=0.01, presence_penalty=0.0, repetition_penalty=1.0, temperature=0.7, top_p=0.95), instructions=[], metadata={}, model='gpt-4o', name='NewsLibraryAgent'), Agent(id='847b03b1-856a-4ae1-a1f5-ad994ba5c87d', created_at=datetime.datetime(2024, 10, 4, 12, 18, 0, 503478, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 5, 10, 3, 54, 42636, tzinfo=datetime.timezone.utc), about='It is used to manage a library of news article titles and their related data', default_settings=DefaultSettings(frequency_penalty=0.0, length_penalty=1.0, min_p=0.01, presence_penalty=0.0, repetition_penalty=1.0, temperature=0.7, top_p=0.95), instructions=[], metadata={}, model='gpt-4o', name='NewsLibraryAgent')])" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client.agents.list()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "29d282de", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "SyncOffsetPagination[User](items=[])" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client.users.list()" - ] - }, - { - "cell_type": "markdown", - "id": "c96f5022", - "metadata": {}, - "source": [ - "## Agent with title lib" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "5de0f61b", - "metadata": {}, - "outputs": [], - "source": [ - "# Defining the agent\n", - "name = \"NewsLibraryAgent\"\n", - "about = \"It is used to manage a library of news article titles and their related data\"\n", - "default_settings = {\n", - " \"temperature\": 0.6,\n", - " \"top_p\": 0.9,\n", - " \"min_p\": 0.05,\n", - " \"presence_penalty\": 0.2,\n", - " \"frequency_penalty\": 0.2,\n", - " \"length_penalty\": 1.0,\n", - "}\n", - "\n", - "\n", - "# Create the agent\n", - "agent = client.agents.create_or_update(\n", - " agent_id=\"847b03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " name=name,\n", - " about=about,\n", - " model=\"gpt-4o\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "0392d3c6", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ResourceCreated(id='602641f5-29cb-4895-886f-d4db4ba47d8e', created_at=datetime.datetime(2024, 10, 9, 10, 45, 39, 700109, tzinfo=datetime.timezone.utc), jobs=['78251ce4-9199-49e6-a5de-f52e3cc1b537'])" - ] - }, - "execution_count": 18, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client.agents.docs.create(\n", - " agent_id=\"847d03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " title=\"NewsTitles\",\n", - " content=articles[:25000],\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 49, - "id": "fa817293", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "DocSearchResponse(docs=[], time=1.0753483772277832)" - ] - }, - "execution_count": 49, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client.agents.docs.search(\n", - " agent_id=\"847b03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " text=\"nascar-news-kyle-busch-denny-hamlin-brad-keselowski-fans-beef-over-their-superstars-filling-the-void-in-nascar-left-by-legendary-cup-champ\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 50, - "id": "4fb0e0be", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "SyncOffsetPagination[Doc](items=[])" - ] - }, - "execution_count": 50, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client.agents.docs.list(agent_id=\"847b03b1-856a-4ae1-a1f5-ad994ba5c87d\")" - ] - }, - { - "cell_type": "markdown", - "id": "c9c08542", - "metadata": {}, - "source": [ - "## User Creation" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "e0e70ef0", - "metadata": {}, - "outputs": [], - "source": [ - "for i in tqdm(range(len(df))):\n", - " client.users.create(\n", - " name=f\"user_{i}\",\n", - " metadata={\n", - " \"ppid\": str(df.iloc[i][\"ppid\"]), # Ensure it's a native int\n", - " \"age\": int(df.iloc[i][\"enrich_age\"]), # Ensure it's a native int\n", - " \"state\": str(\n", - " df.iloc[i][\"enrich_state\"]\n", - " ), # Convert to string if not already\n", - " \"city\": str(df.iloc[i][\"enrich_city\"]), # Convert to string if not already\n", - " \"sports_likes\": str(\n", - " df.iloc[i][\"sports_with_visit_count\"]\n", - " ), # Convert to string or json serializable format\n", - " \"entity_likes\": str(df.iloc[i][\"entity_with_visit_count\"]), # Same as above\n", - " \"top_sport\": str(df.iloc[i][\"top_sport\"]),\n", - " \"top_entity\": str(df.iloc[i][\"top_entity\"]),\n", - " \"latest_sport_read\": str(df.iloc[i][\"latest_sport_read\"]),\n", - " \"top_sources\": str(df.iloc[i][\"top_sources\"]),\n", - " },\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "564aeb3e", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "SyncOffsetPagination[User](items=[User(id='f2e900fd-c7b4-424b-b71d-d75d4a6d7692', created_at=datetime.datetime(2024, 10, 9, 10, 44, 23, 371884, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 23, 371885, tzinfo=datetime.timezone.utc), about='', metadata={'age': 73, 'city': 'Springfield', 'entity_likes': '{Others=51, Sean Payton=2, LeBron James=2, Kyle Busch=12, Matt Eberflus=1, Tony Stewart=19, Dale Earnhardt Jr=6, Usain Bolt=1, Ronda Rousey=1, Khabib=1, Jim Harbaugh=1, Denny Hamlin=8, Bubba Wallace=6, Dana White=1, Michael Jordan=9, Patrick Mahomes=2}', 'latest_sport_read': 'nascar', 'ppid': 'nnqkt17143103131230f7ff7d9f6ca', 'sports_likes': '{ufc=3, nba active=3, uss=1, nascar=98, nfl active=15, college football=3}', 'state': 'IL', 'top_entity': 'Tony Stewart', 'top_sources': 'discover', 'top_sport': 'nascar'}, name='user_12976'), User(id='4950ec58-2a5c-45da-887a-27799672a3d8', created_at=datetime.datetime(2024, 10, 9, 10, 44, 23, 362493, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 23, 362494, tzinfo=datetime.timezone.utc), about='', metadata={'age': 28, 'city': 'Pensacola', 'entity_likes': '{Tara Davis Woodhall=2, Dan Quinn=2, Elaine Thompson=1, Shaquille ONeal=5, Bronny James=2, Caitlin Clark=6, Chennedy Carter=2, Sydney McLaughlin=1, ShaCarri Richardson=14, Dawn Staley=2, Gabby Thomas=3, Deion 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name='user_12895'), User(id='8d194f69-3bca-41a8-a050-37194b7ddc8c', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 604267, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 604268, tzinfo=datetime.timezone.utc), about='', metadata={'age': 69, 'city': 'Greenville', 'entity_likes': '{Others=79, Dan Quinn=1, Sean Payton=1, LeBron James=3, Kelsey Plum=1, Kyle Busch=15, Tony Stewart=12, Tiger Woods=2, Michael Phelps=1, Dale Earnhardt Jr=14, ShaCarri Richardson=2, Gabby Thomas=1, Jim Harbaugh=2, Deion Sanders=1, Denny Hamlin=7, Bubba Wallace=4, Michael Jordan=9}', 'latest_sport_read': 'nascar', 'ppid': 'xb96z1703264290857ca12bb3353d3', 'sports_likes': '{wnba=2, golf=8, nba active=9, uss=4, nascar=114, nba legends=1, nfl active=8, college football=9}', 'state': 'SC', 'top_entity': 'Kyle Busch', 'top_sources': 'discover', 'top_sport': 'nascar'}, name='user_12894'), User(id='415d81aa-3cb0-423f-b311-b107835d742e', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 594949, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 594949, tzinfo=datetime.timezone.utc), about='', metadata={'age': 59, 'city': 'Chattanooga', 'entity_likes': '{Others=43, Tara Davis Woodhall=1, Elaine Thompson=1, Shaquille ONeal=12, Serena Williams=14, LeBron James=6, Rebeca Andrade=1, Angel Reese=1, Bronny James=1, Caitlin Clark=1, Sydney McLaughlin=3, Shericka Jackson=2, ShaCarri Richardson=37, Gabby Thomas=2, Steph Curry=1, Michael Jordan=3, Noah Lyles=5, Simone Biles=19, Patrick Mahomes=4}', 'latest_sport_read': 'nfl', 'ppid': 'rm86f17130090035802efab297fd58', 'sports_likes': '{wnba=2, nba active=17, uss=76, nba legends=24, nfl active=13, nba=2, college football=2, tennis=21}', 'state': 'TN', 'top_entity': 'ShaCarri Richardson', 'top_sources': 'discover', 'top_sport': 'uss'}, name='user_12893'), User(id='887645d9-016e-44f0-b6da-366f96e9ac44', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 585637, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 585637, tzinfo=datetime.timezone.utc), about='', metadata={'age': 72, 'city': 'Greenville', 'entity_likes': '{Dale Earnhardt Jr=16, Others=69, Kyle Busch=8, Denny Hamlin=8, Tony Stewart=15, Bubba Wallace=1, Michael Jordan=6}', 'latest_sport_read': 'nascar', 'ppid': '29q4g169967093544713c35215f36e', 'sports_likes': '{nascar=123}', 'state': 'SC', 'top_entity': 'Dale Earnhardt Jr', 'top_sources': 'internal link', 'top_sport': 'nascar'}, name='user_12892'), User(id='b98a3e74-2e4f-409f-acce-9762b14aad64', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 576229, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 576230, tzinfo=datetime.timezone.utc), about='', metadata={'age': 57, 'city': 'Pine Bush', 'entity_likes': '{Others=57, Shaquille ONeal=7, Jakob Ingerbrigtsen=1, Serena Williams=9, LeBron James=7, Rebeca Andrade=1, Tiger Woods=2, Caitlin Clark=2, Michael Phelps=1, ShaCarri Richardson=5, Dawn Staley=1, Gabby Thomas=2, Christian Coleman=1, Deion Sanders=9, Michael Jordan=4, Noah Lyles=4, Simone Biles=4, Patrick Mahomes=1, Breanna Stewart=1}', 'latest_sport_read': 'nba', 'ppid': '5qj79171104912391278a511b5bf51', 'sports_likes': '{wnba=1, golf=4, nba active=23, uss=25, nascar=1, boxing=2, nba legends=13, nfl active=2, college football=23, tennis=25}', 'state': 'NY', 'top_entity': 'Deion Sanders', 'top_sources': 'discover', 'top_sport': 'tennis'}, name='user_12891'), User(id='25361cf3-8fd6-4fe9-b185-499a39c32283', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 566985, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 566986, tzinfo=datetime.timezone.utc), about='', metadata={'age': 55, 'city': 'Ellenville', 'entity_likes': '{Jake Paul=1, Others=69, Shaquille ONeal=2, Serena Williams=1, Joe Rogan=11, LeBron James=3, Tiger Woods=5, Mike Tyson=7, Caitlin Clark=2, Dale Earnhardt Jr=1, ShaCarri Richardson=9, Ronda Rousey=2, Khabib=5, Olivia Dunne=3, Lewis Hamilton=1, Deion Sanders=11, Dana White=22, Michael Jordan=3, Conor McGregor=11, Floyd Mayweather=1, Simone Biles=4, Patrick Mahomes=14}', 'latest_sport_read': 'ufc', 'ppid': '5zxzj170290682376491751d4720a4', 'sports_likes': '{wnba=1, golf=9, ufc=81, nba active=5, uss=19, nascar=1, boxing=10, nba legends=4, nfl active=19, college football=37, tennis=2}', 'state': 'NY', 'top_entity': 'Dana White', 'top_sources': 'discover', 'top_sport': 'ufc'}, name='user_12890'), User(id='55d34803-538f-4af5-b871-10ea948a42e7', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 557641, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 557641, tzinfo=datetime.timezone.utc), about='', metadata={'age': 36, 'city': 'Pearland', 'entity_likes': '{Others=75, Tara Davis Woodhall=1, Elaine Thompson=1, Shaquille ONeal=3, Serena Williams=7, Sean Payton=6, LeBron James=8, Quincy Wilson=1, Rebeca Andrade=1, Angel Reese=6, Bronny James=1, Caitlin Clark=10, Chennedy Carter=1, Sydney McLaughlin=4, ShaCarri Richardson=35, Dawn Staley=2, Gabby Thomas=6, Jordan Chiles=4, Olivia Dunne=1, Deion Sanders=36, Derek Jeter=1, Noah Lyles=4, Simone Biles=17}', 'latest_sport_read': 'nba', 'ppid': '5l9kj1711045407182bd7c7cd074a1', 'sports_likes': '{wnba=10, mlb=1, nba active=17, uss=84, boxing=2, nba legends=12, nfl active=10, nfl legends=1, nba=1, college football=79, tennis=14}', 'state': 'TX', 'top_entity': 'Deion Sanders', 'top_sources': 'discover', 'top_sport': 'uss'}, name='user_12889'), User(id='fad0bc2d-c3b6-4f2a-acc8-f6774e354cdc', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 548274, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 548274, tzinfo=datetime.timezone.utc), about='', metadata={'age': 55, 'city': 'Bridgewater', 'entity_likes': '{Dale Earnhardt Jr=12, Others=55, Denny Hamlin=8, Kyle Busch=10, Tony Stewart=13, Bubba Wallace=3, Michael Jordan=4, Caitlin Clark=1, Simone Biles=2, Patrick Mahomes=1}', 'latest_sport_read': 'nascar', 'ppid': 'dgxst1711018117632c449a2aa5282', 'sports_likes': '{wnba=1, uss=2, nascar=102, nfl active=2, college football=1, others=1}', 'state': 'NJ', 'top_entity': 'Tony Stewart', 'top_sources': 'discover', 'top_sport': 'nascar'}, name='user_12888'), User(id='1c26226e-3c4a-4765-aa71-597102368958', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 539118, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 539118, tzinfo=datetime.timezone.utc), about='', metadata={'age': 69, 'city': 'Brooklyn', 'entity_likes': '{Others=110, ShaCarri Richardson=1, Serena Williams=9, Lewis Hamilton=1, Jordan Chiles=1, Rebeca Andrade=1, Simone Biles=8}', 'latest_sport_read': 'tennis', 'ppid': 'wqjjb171124441117050f49b85cf1d', 'sports_likes': '{boxing=1, uss=21, tennis=109}', 'state': 'NY', 'top_entity': 'Serena Williams', 'top_sources': 'discover', 'top_sport': 'tennis'}, name='user_12887'), User(id='39fe3818-7ce2-4b5c-8192-ac2439d614f9', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 530030, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 530030, tzinfo=datetime.timezone.utc), about='', metadata={'age': 35, 'city': 'Silverdale', 'entity_likes': '{Others=16, Tara Davis Woodhall=1, Serena Williams=1, Joe Rogan=8, Fred Kerley=1, LeBron James=1, Sabrina Ionescu=1, Angel Reese=1, Caitlin Clark=3, Sydney McLaughlin=5, Shericka Jackson=4, ShaCarri Richardson=31, Gabby Thomas=3, Usain Bolt=1, Khabib=10, Jon Jones=3, Dana White=18, Conor McGregor=5, Noah Lyles=3, Floyd Mayweather=3, Simone Biles=4}', 'latest_sport_read': 'uss', 'ppid': '7vzkw17108581777680209740ccccd', 'sports_likes': '{wnba=2, ufc=53, nba active=2, uss=58, boxing=6, college football=2}', 'state': 'WA', 'top_entity': 'ShaCarri Richardson', 'top_sources': 'discover', 'top_sport': 'uss'}, name='user_12886'), User(id='578eb71c-3bfc-4ab5-bd3c-ee81bd08c9a1', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 520885, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 520885, tzinfo=datetime.timezone.utc), about='', metadata={'age': 47, 'city': 'Thornton', 'entity_likes': '{Others=58, Brittney Griner=1, Shaquille ONeal=2, LeBron James=1, Kyle Busch=17, Tony Stewart=16, Dale Earnhardt Jr=9, Khabib=1, Deion Sanders=5, Jim Harbaugh=1, Denny Hamlin=10, Bubba Wallace=6, Dana White=1, Michael Jordan=9, Noah Lyles=1, Patrick Mahomes=4}', 'latest_sport_read': 'nascar', 'ppid': 'bv8jw17032121894964bac073b7d43', 'sports_likes': '{wnba=1, golf=3, ufc=2, nba active=3, wwe=2, nascar=113, nba legends=3, nfl active=7, college football=8}', 'state': 'CO', 'top_entity': 'Kyle Busch', 'top_sources': 'discover', 'top_sport': 'nascar'}, name='user_12885'), User(id='2c534b8f-2958-4284-8d30-35d2f0fc043f', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 511805, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 511806, tzinfo=datetime.timezone.utc), about='', metadata={'age': 63, 'city': 'Chipley', 'entity_likes': '{Dale Earnhardt Jr=20, Others=90, Kyle Busch=26, Denny Hamlin=16, Tony Stewart=24, Bubba Wallace=9, Michael Jordan=4}', 'latest_sport_read': 'nascar', 'ppid': 'dcmnc17096841606166c29ab366683', 'sports_likes': '{nascar=187, others=2}', 'state': 'FL', 'top_entity': 'Kyle Busch', 'top_sources': 'discover', 'top_sport': 'nascar'}, name='user_12884'), User(id='f807c9ab-96a7-4c54-ba78-054ba479e33d', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 502403, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 502403, tzinfo=datetime.timezone.utc), about='', metadata={'age': 30, 'city': 'New Bedford', 'entity_likes': '{Others=52, Shaquille ONeal=1, Serena Williams=3, Kyle Busch=12, Tom Brady=1, Tony Stewart=16, Tiger Woods=1, Dale Earnhardt Jr=24, Denny Hamlin=8, Bubba Wallace=1, Michael Jordan=2, Derek Jeter=1, Patrick Mahomes=2}', 'latest_sport_read': 'nascar', 'ppid': '8bvjm170811436163550cef50a1f66', 'sports_likes': '{wnba=1, mlb=1, golf=3, ufc=1, nascar=109, nba legends=1, nfl active=3, nfl legends=1, tennis=4}', 'state': 'MA', 'top_entity': 'Dale Earnhardt Jr', 'top_sources': 'google search', 'top_sport': 'nascar'}, name='user_12883'), User(id='71e8aa48-3634-423f-909c-0bc2dc6d1e66', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 493226, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 493226, tzinfo=datetime.timezone.utc), about='', metadata={'age': 40, 'city': 'Bridgeport', 'entity_likes': '{Others=18, Tara Davis Woodhall=1, Elaine Thompson=2, Shaquille ONeal=5, Serena Williams=10, Fred Kerley=1, Rebeca Andrade=2, Jade Carey=2, Caitlin Clark=2, Michael Phelps=1, Sydney McLaughlin=1, Arnold Schwarzenegger=1, Shericka Jackson=1, ShaCarri Richardson=13, Gabby Thomas=3, Usain Bolt=10, Jordan Chiles=1, Deion Sanders=1, Michael Jordan=2, Noah Lyles=7, Simone Biles=28, Patrick Mahomes=1}', 'latest_sport_read': 'tennis', 'ppid': 'tq8dw1703205107273a4e3da9719be', 'sports_likes': '{soccer=1, wnba=1, uss=83, nba legends=7, nfl active=2, bodybuilding=1, college football=2, tennis=16}', 'state': 'CT', 'top_entity': 'Simone Biles', 'top_sources': 'discover', 'top_sport': 'uss'}, name='user_12882'), User(id='5134e56d-074b-492b-ba64-e5fd7c7fb6de', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 484121, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 484122, tzinfo=datetime.timezone.utc), about='', metadata={'age': 23, 'city': 'Lauderhill', 'entity_likes': '{Shaquille ONeal=2, Sean Payton=3, Joe Rogan=7, Shelly Ann Frazer Pryce=1, Kyle Busch=3, Tom Brady=1, Tony Stewart=3, Mike Tyson=6, Caitlin Clark=3, Femke Bol=2, Sydney McLaughlin=5, ShaCarri Richardson=4, Kishane Thompson=1, Gabby Thomas=1, Khabib=2, Jordan Chiles=2, Olivia Dunne=2, Deion Sanders=1, Noah Lyles=5, Simone Biles=3, Jake Paul=1, Others=42, Serena Williams=1, Tiger Woods=1, Dale Earnhardt Jr=4, Denny Hamlin=2, Dana White=2, Michael Jordan=1, Floyd Mayweather=3}', 'latest_sport_read': 'uss', 'ppid': 's8d29171287710911410e9f713f6af', 'sports_likes': '{golf=3, ufc=13, nba active=4, uss=29, nascar=26, boxing=11, nba legends=4, nfl active=14, nfl legends=3, college football=3, tennis=4}', 'state': 'FL', 'top_entity': 'Joe Rogan', 'top_sources': 'google news', 'top_sport': 'uss'}, name='user_12881'), User(id='b9139854-c314-4e81-bf89-306ea3ca7d28', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 474914, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 474914, tzinfo=datetime.timezone.utc), about='', metadata={'age': 39, 'city': 'Spokane Valley', 'entity_likes': '{Dale Earnhardt Jr=3, Others=33, Kyle Busch=23, Denny Hamlin=8, Tony Stewart=1, Bubba Wallace=4, Michael Jordan=1, Patrick Mahomes=64}', 'latest_sport_read': 'nfl', 'ppid': 'c9brb16993043699712fe8cbefcf65', 'sports_likes': '{nfl active=64, nfl=1, nascar=71, tennis=1}', 'state': 'WA', 'top_entity': 'Patrick Mahomes', 'top_sources': 'discover', 'top_sport': 'nascar'}, name='user_12880'), User(id='7612f7db-d1aa-4365-8728-a0e1d9ca0d77', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 465879, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 465880, tzinfo=datetime.timezone.utc), about='', metadata={'age': 78, 'city': 'Mahopac', 'entity_likes': '{Others=70, Shaquille ONeal=6, Serena Williams=20, LeBron James=8, Quincy Wilson=1, Rebeca Andrade=1, Bronny James=1, Sydney McLaughlin=2, ShaCarri Richardson=14, Gabby Thomas=5, Usain Bolt=2, Steph Curry=2, Michael Jordan=10, Noah Lyles=7}', 'latest_sport_read': 'tennis', 'ppid': 'xlsvl1709741308093663153187dbe', 'sports_likes': '{soccer=1, wnba=1, mlb=1, nba active=19, uss=37, nba legends=23, college football=2, others=1, tennis=64}', 'state': 'NY', 'top_entity': 'Serena Williams', 'top_sources': 'google search', 'top_sport': 'tennis'}, name='user_12879'), User(id='2c1af3fd-2fcb-42e6-b349-3321cd8c8915', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 456797, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 456798, tzinfo=datetime.timezone.utc), about='', metadata={'age': 56, 'city': 'Richmond', 'entity_likes': '{Dale Earnhardt Jr=27, Others=71, Deion Sanders=1, Jim Harbaugh=5, Denny Hamlin=11, Kyle Busch=39, Tony Stewart=23, Bubba Wallace=6, Michael Jordan=15, Patrick Mahomes=5}', 'latest_sport_read': 'nascar', 'ppid': '8hxdp169971023268921acc266a987', 'sports_likes': '{uss=1, nascar=186, nba legends=1, nfl active=6, college football=7, others=2}', 'state': 'VA', 'top_entity': 'Kyle Busch', 'top_sources': 'discover', 'top_sport': 'nascar'}, name='user_12878'), User(id='ab6ca560-aa18-4a77-a5dc-cf16df426b44', created_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 447731, tzinfo=datetime.timezone.utc), updated_at=datetime.datetime(2024, 10, 9, 10, 44, 22, 447732, tzinfo=datetime.timezone.utc), about='', metadata={'age': 81, 'city': 'Fishers', 'entity_likes': '{Others=35, Shaquille ONeal=10, Serena Williams=6, LeBron James=4, Tiger Woods=3, Caitlin Clark=6, Michael Phelps=1, Dawn Staley=1, Deion Sanders=1, Olivia Dunne=3, Michael Jordan=4, Simone Biles=17, Patrick Mahomes=30}', 'latest_sport_read': 'nfl', 'ppid': 'j6k481706464547054c3940b7e352e', 'sports_likes': '{soccer=4, wnba=6, golf=3, nba active=15, uss=24, nascar=1, nba legends=15, nfl active=37, nba=1, college football=8, tennis=7}', 'state': 'IN', 'top_entity': 'Patrick Mahomes', 'top_sources': 'discover', 'top_sport': 'nfl active'}, name='user_12877')])" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client.users.list()" - ] - }, - { - "cell_type": "markdown", - "id": "15531cc5", - "metadata": {}, - "source": [ - "## Profiler " - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "48589b59", - "metadata": {}, - "outputs": [], - "source": [ - "# Defining the agent\n", - "name = \"ProfilerAgent\"\n", - "about = \"It is used to create/update the profile of the user\"\n", - "default_settings = {\n", - " \"temperature\": 0.9,\n", - " \"top_p\": 0.9,\n", - " \"min_p\": 0.05,\n", - " \"presence_penalty\": 0.2,\n", - " \"frequency_penalty\": 0.2,\n", - " \"length_penalty\": 1.0,\n", - " \"max_tokens\": 250,\n", - "}\n", - "\n", - "\n", - "# Create the agent\n", - "agent = client.agents.create_or_update(\n", - " agent_id=\"844e03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " name=name,\n", - " about=about,\n", - " model=\"gpt-4o\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "id": "23649eeb", - "metadata": {}, - "outputs": [], - "source": [ - "# The profiler workflow\n", - "task_def = yaml.safe_load(\"\"\"\n", - "name: generate_update_persona\n", - "\n", - "# Define the input schema for the workflow\n", - "input_schema:\n", - " type: object\n", - " properties:\n", - " user_ppid:\n", - " type: string\n", - " articles_read:\n", - " type: array\n", - " items:\n", - " type: string\n", - " required:\n", - " - user_ppid\n", - " - articles_read\n", - "\n", - "# Define the tools that are going to be used in the workflow\n", - "tools:\n", - " - name: get_user_from_ppid\n", - " description: Get a user from the user ppid\n", - " system:\n", - " resource: user\n", - " operation: list\n", - " \n", - " - name: list_user_docs\n", - " description: List the user docs\n", - " system:\n", - " resource: user\n", - " subresource: doc\n", - " operation: list\n", - "\n", - " - name: create_user_doc\n", - " description: Create a user doc\n", - " system:\n", - " resource: user\n", - " subresource: doc\n", - " operation: create\n", - "\n", - "main:\n", - " # Get the user from the ppid using metadata_filter (returns a list)\n", - " - tool: get_user_from_ppid\n", - " arguments:\n", - " limit: \"1\"\n", - " metadata_filter:\n", - " ppid: inputs[0]['user_ppid']\n", - "\n", - " # Unwrap the list to get the user\n", - " - evaluate:\n", - " user: _[0]\n", - "\n", - "\n", - " # Get the user persona document using metadata_filter (returns a list)\n", - " - tool: list_user_docs\n", - " arguments:\n", - " user_id: _['user']['id']\n", - " limit: \"1\"\n", - " sort_by: \"'created_at'\"\n", - " direction: \"'desc'\"\n", - "\n", - " # Get the doc if it exists\n", - " - evaluate:\n", - " doc: _[0] if len(_) > 0 else {}\n", - "\n", - "\n", - " # Get the user persona from the doc if the doc exists\n", - " - evaluate:\n", - " user_persona: _['doc'].get('content', \"\")\n", - "\n", - "\n", - " # Create the user persona using the prompt step\n", - " - prompt:\n", - " - role: user\n", - " content: You are an expert at creating user profile based on data. Write the user persona based on {{_['user_persona']}} + {{inputs[2]['user']['metadata']}} + {{inputs[0]['articles_read']}}\n", - " unwrap: true\n", - " \n", - " # Create a new persona document\n", - " - tool: create_user_doc\n", - " arguments:\n", - " user_id: inputs[2]['user']['id']\n", - " data:\n", - " title: \"'User Persona Document'\"\n", - " # metadata:\n", - " # user_persona: true\n", - " content: _\n", - "\"\"\")" - ] - }, - { - "cell_type": "code", - "execution_count": 34, - "id": "9b211a93", - "metadata": {}, - "outputs": [], - "source": [ - "# Creating/Updating a task\n", - "task = client.tasks.create_or_update(\n", - " task_id=\"813a03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " agent_id=\"844e03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " **task_def,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "id": "beb8fca8", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|███████████████████████████████████| 12977/12977 [1:07:31<00:00, 3.20it/s]\n" - ] - } - ], - "source": [ - "for i in tqdm(range(len(df))):\n", - " ppid = str(df.iloc[i][\"ppid\"])\n", - " filtered_df1 = df1[df1[\"ppid\"] == ppid]\n", - "\n", - " if not filtered_df1.empty:\n", - " # Creating an Execution\n", - " execution = client.executions.create(\n", - " task_id=\"813a03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " input={\"user_ppid\": ppid, \"articles_read\": filtered_df1[\"titles\"].tolist()},\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": 55, - "id": "31b8fc47", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "ResourceCreated(id='8e69fbc6-7f10-4067-9b81-4b2015508628', created_at=datetime.datetime(2024, 10, 9, 12, 5, 56, 176543, tzinfo=datetime.timezone.utc), jobs=['6b78a7ea-4703-47a0-9b0c-13111f018586'])" - ] - }, - "execution_count": 55, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "execution" - ] - }, - { - "cell_type": "code", - "execution_count": 56, - "id": "316b33ae", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "SyncOffsetPagination[Transition](items=[])" - ] - }, - "execution_count": 56, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client.executions.transitions.list(execution_id=\"8e69fbc6-7f10-4067-9b81-4b2015508628\")" - ] - }, - { - "cell_type": "markdown", - "id": "07b9042e", - "metadata": {}, - "source": [ - "## Recommendation" - ] - }, - { - "cell_type": "code", - "execution_count": 57, - "id": "0dc2b395", - "metadata": {}, - "outputs": [], - "source": [ - "# Defining the agent\n", - "name = \"TitleRecommender\"\n", - "about = \"It is used to recommend the title recommendation for the user\"\n", - "default_settings = {\n", - " \"temperature\": 0.9,\n", - " \"top_p\": 0.9,\n", - " \"min_p\": 0.05,\n", - " \"presence_penalty\": 0.2,\n", - " \"frequency_penalty\": 0.2,\n", - " \"length_penalty\": 1.0,\n", - " \"max_tokens\": 250,\n", - "}\n", - "\n", - "# Create the agent\n", - "agent = client.agents.create_or_update(\n", - " agent_id=\"865e03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " name=name,\n", - " about=about,\n", - " model=\"gpt-4o\",\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 58, - "id": "c102054e", - "metadata": {}, - "outputs": [], - "source": [ - "for docs in client.agents.docs.list(agent_id=\"847b03b1-856a-4ae1-a1f5-ad994ba5c87d\"):\n", - " client.agents.docs.delete(\n", - " agent_id=\"847b03b1-856a-4ae1-a1f5-ad994ba5c87d\", doc_id=docs.id\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": 59, - "id": "ead8d197", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "(168, 1)" - ] - }, - "execution_count": 59, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "df2 = pd.read_csv(\"new_titles.csv\")\n", - "df2.shape" - ] - }, - { - "cell_type": "code", - "execution_count": 60, - "id": "b9b839c7", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|█████████████████████████████████████████| 168/168 [00:47<00:00, 3.52it/s]\n" - ] - } - ], - "source": [ - "for i in tqdm(range(len(df2))):\n", - " title = df2.iloc[i][\"post_name\"]\n", - "\n", - " client.agents.docs.create(\n", - " agent_id=\"847b03b1-856a-4ae1-a1f5-ad994ba5c87d\", title=title, content=title\n", - " )" - ] - }, - { - "cell_type": "code", - "execution_count": 80, - "id": "b9d230e6", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "SyncOffsetPagination[Doc](items=[])" - ] - }, - "execution_count": 80, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "client.agents.docs.list(agent_id=\"847b03b1-856a-4ae1-a1f5-ad994ba5c87d\")" - ] - }, - { - "cell_type": "markdown", - "id": "06a417bd", - "metadata": {}, - "source": [ - "1. Delete all the docs of libraryAgents \n", - "\n", - "2. Create new docs for each article with title=headline and content=headline with new batch of article which you are going to recommend\n", - "\n", - "\n", - "3. Get the user_persona\n", - "\n", - "\n", - "4. Ranking based on cosine similarity \n", - "5. Pick 5 articles for this users out of 50 \n", - "6. Recommend the newsletter title based on this articles " - ] - }, - { - "cell_type": "code", - "execution_count": 72, - "id": "ca518cbb", - "metadata": {}, - "outputs": [], - "source": [ - "# The profiler workflow\n", - "task_def1 = yaml.safe_load(\"\"\"\n", - "\n", - "name: recommend news articles\n", - "\n", - "input_schema:\n", - " type: object\n", - " properties:\n", - " user_ppid:\n", - " type: string\n", - " \n", - "tools:\n", - " - name: get_user_from_ppid\n", - " description: Get a user from the user ppid\n", - " system:\n", - " resource: user\n", - " operation: list\n", - "\n", - " - name: get_user_docs\n", - " description: Get user docs\n", - " system:\n", - " resource: user\n", - " subresource: doc\n", - " operation: list\n", - " \n", - " - name : search_agent_docs\n", - " description: Get agent docs\n", - " system: \n", - " resource: agent\n", - " subresource: doc\n", - " operation: search \n", - " \n", - "main:\n", - " # Get the user from the ppid using metadata_filter (returns a list)\n", - " - tool: get_user_from_ppid\n", - " arguments:\n", - " limit: \"1\"\n", - " metadata_filter:\n", - " ppid: inputs[0]['user_ppid']\n", - "\n", - " # Unwrap the list to get the user\n", - " - evaluate:\n", - " user: _[0]\n", - "\n", - " - tool: get_user_docs\n", - " arguments:\n", - " user_id: _.user.id\n", - " limit: \"1\"\n", - " sort_by: \"'created_at'\"\n", - " direction: \"'desc'\"\n", - "\n", - " #user persona will always be available here\n", - " - evaluate:\n", - " user_embedding: _[0].embeddings\n", - " persona: _[0].content\n", - "\n", - " #Embedding similarity it will rank the docs\n", - " - tool: search_agent_docs\n", - " arguments:\n", - " vector: _.user_embedding\n", - " agent_id: \"'847b03b1-856a-4ae1-a1f5-ad994ba5c87d'\"\n", - "\n", - " #not sure how to evaluate news_titles\n", - " - evaluate:\n", - " top_titles: \"{{ [doc['title'] for doc in _['docs'][:50]] }}\"\n", - "\n", - " - prompt: \n", - " - role: user\n", - " content: Which of these {{_.top_titles}} do you think the user will like. Rank them according to the users' \n", - " persona {{inputs[2].biodata}} and give me the top 5 as valid yaml\n", - " unwrap: true\n", - " \n", - " - evaluate:\n", - " titles: load_yaml(_)\n", - " \n", - " - prompt: \n", - " - role: user\n", - " content: based on these 5 news {{_.titles}} and users' persona {{inputs[2].biodata}}, draft a catchy newsletter title.\n", - " unwrap: true\n", - " \n", - " - evaluate:\n", - " newsletter_title: _\n", - " titles: output[7].titles\n", - " \n", - "\"\"\")" - ] - }, - { - "cell_type": "code", - "execution_count": 73, - "id": "12f688c6", - "metadata": {}, - "outputs": [], - "source": [ - "# Creating/Updating a task\n", - "task1 = client.tasks.create_or_update(\n", - " task_id=\"825a03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " agent_id=\"865e03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " **task_def1,\n", - ")" - ] - }, - { - "cell_type": "code", - "execution_count": 76, - "id": "374f1b74", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " 21%|███████▌ | 2715/12977 [33:48<2:07:48, 1.34it/s]\n" - ] - }, - { - "ename": "KeyboardInterrupt", - "evalue": "", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mKeyboardInterrupt\u001b[0m Traceback (most recent call last)", - "\u001b[0;32m/var/folders/sm/rll592s91t375q5hbck24ptc0000gn/T/ipykernel_46728/1288718815.py\u001b[0m in \u001b[0;36m\u001b[0;34m\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;31m# Creating an Execution\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m execution = client.executions.create(\n\u001b[0m\u001b[1;32m 7\u001b[0m \u001b[0mtask_id\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0;34m'825a03b1-856a-4ae1-a1f5-ad994ba5c87d'\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m input = {\n", - "\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/julep/resources/executions/executions.py\u001b[0m in \u001b[0;36mcreate\u001b[0;34m(self, task_id, input, error, metadata, output, extra_headers, extra_query, extra_body, timeout)\u001b[0m\n\u001b[1;32m 97\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mtask_id\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 98\u001b[0m \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34mf\"Expected a non-empty value for `task_id` but received {task_id!r}\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 99\u001b[0;31m return self._post(\n\u001b[0m\u001b[1;32m 100\u001b[0m \u001b[0;34mf\"/tasks/{task_id}/executions\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 101\u001b[0m body=maybe_transform(\n", - 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"\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/httpcore/_sync/connection_pool.py\u001b[0m in \u001b[0;36mhandle_request\u001b[0;34m(self, request)\u001b[0m\n\u001b[1;32m 260\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mShieldCancellation\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 261\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mresponse_closed\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstatus\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 262\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 263\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 264\u001b[0m \u001b[0;32mbreak\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/httpcore/_sync/connection_pool.py\u001b[0m in \u001b[0;36mhandle_request\u001b[0;34m(self, request)\u001b[0m\n\u001b[1;32m 243\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 244\u001b[0m \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 245\u001b[0;31m \u001b[0mresponse\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mconnection\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mhandle_request\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrequest\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 246\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mConnectionNotAvailable\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 247\u001b[0m \u001b[0;31m# The ConnectionNotAvailable exception is a special case, that\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - 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"\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/httpcore/_sync/http11.py\u001b[0m in \u001b[0;36mhandle_request\u001b[0;34m(self, request)\u001b[0m\n\u001b[1;32m 119\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mTrace\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"response_closed\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlogger\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrequest\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mtrace\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 120\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_response_closed\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 121\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 122\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 123\u001b[0m \u001b[0;31m# Sending the request...\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/httpcore/_sync/http11.py\u001b[0m in \u001b[0;36mhandle_request\u001b[0;34m(self, request)\u001b[0m\n\u001b[1;32m 97\u001b[0m \u001b[0mreason_phrase\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 98\u001b[0m \u001b[0mheaders\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 99\u001b[0;31m ) = self._receive_response_headers(**kwargs)\n\u001b[0m\u001b[1;32m 100\u001b[0m trace.return_value = (\n\u001b[1;32m 101\u001b[0m \u001b[0mhttp_version\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/httpcore/_sync/http11.py\u001b[0m in \u001b[0;36m_receive_response_headers\u001b[0;34m(self, request)\u001b[0m\n\u001b[1;32m 162\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 163\u001b[0m \u001b[0;32mwhile\u001b[0m \u001b[0;32mTrue\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 164\u001b[0;31m \u001b[0mevent\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_receive_event\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 165\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0misinstance\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mevent\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mh11\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mResponse\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 166\u001b[0m \u001b[0;32mbreak\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/httpcore/_sync/http11.py\u001b[0m in \u001b[0;36m_receive_event\u001b[0;34m(self, timeout)\u001b[0m\n\u001b[1;32m 198\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 199\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mevent\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0mh11\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mNEED_DATA\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 200\u001b[0;31m data = self._network_stream.read(\n\u001b[0m\u001b[1;32m 201\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mREAD_NUM_BYTES\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 202\u001b[0m )\n", - "\u001b[0;32m~/opt/anaconda3/lib/python3.9/site-packages/httpcore/_backends/sync.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, max_bytes, timeout)\u001b[0m\n\u001b[1;32m 26\u001b[0m \u001b[0;32mwith\u001b[0m \u001b[0mmap_exceptions\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexc_map\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 27\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msettimeout\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mtimeout\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 28\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sock\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmax_bytes\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 29\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 30\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mwrite\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbuffer\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mbytes\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mtimeout\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mtyping\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mOptional\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mfloat\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;34m->\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/opt/anaconda3/lib/python3.9/ssl.py\u001b[0m in \u001b[0;36mrecv\u001b[0;34m(self, buflen, flags)\u001b[0m\n\u001b[1;32m 1225\u001b[0m \u001b[0;34m\"non-zero flags not allowed in calls to recv() on %s\"\u001b[0m \u001b[0;34m%\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1226\u001b[0m self.__class__)\n\u001b[0;32m-> 1227\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbuflen\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1228\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1229\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrecv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mbuflen\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mflags\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;32m~/opt/anaconda3/lib/python3.9/ssl.py\u001b[0m in \u001b[0;36mread\u001b[0;34m(self, len, buffer)\u001b[0m\n\u001b[1;32m 1100\u001b[0m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sslobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mbuffer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1101\u001b[0m \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1102\u001b[0;31m \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_sslobj\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mlen\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 1103\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mSSLError\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1104\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0mSSL_ERROR_EOF\u001b[0m \u001b[0;32mand\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msuppress_ragged_eofs\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n", - "\u001b[0;31mKeyboardInterrupt\u001b[0m: " - ] - } - ], - "source": [ - "execution_array = []\n", - "for i in tqdm(range(len(df))):\n", - " ppid = str(df.iloc[i][\"ppid\"])\n", - "\n", - " # Creating an Execution\n", - " execution = client.executions.create(\n", - " task_id=\"825a03b1-856a-4ae1-a1f5-ad994ba5c87d\",\n", - " input={\n", - " \"user_ppid\": ppid,\n", - " },\n", - " )\n", - " execution_array.append(execution.id)" - ] - }, - { - "cell_type": "code", - "execution_count": 77, - "id": "e9873437", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "['caed8408-235c-4a36-91fe-0559b91ece8d',\n", - " '909b976a-b5d4-40cb-8dd6-8a59d7e246d8',\n", - " '3519ee27-4e83-4ea4-9a25-e4f539eff630',\n", - " '5181be66-ca9d-4fba-a285-39345cb880ec',\n", - " 'b51178a4-b295-48dd-a482-55bdae34124c',\n", - " '6b78d6fb-335e-4fa0-bf1f-e8346bf938c1',\n", - " 'a01f11f8-8d97-4e83-b6cf-64f696247ef2',\n", - " 'b504190d-8be9-4f5e-be1a-8b5cf120e6a1',\n", - " '1f11e027-3456-4bc3-9e10-343bad92757a',\n", - 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