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Update plugins (#135)
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real_agents/plugins_agent/plugins/ABCmouse/__init__.py

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{
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"id": "plugin-c6175037-25c5-4b97-a2b7-828a016be2f8",
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"domain": "ai.abcmouse.com",
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"namespace": "ABCmouse",
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"status": "approved",
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"manifest": {
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"schema_version": "v1",
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"name_for_model": "ABCmouse",
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"name_for_human": "ABCmouse",
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"description_for_model": "Assistant uses the ABCmouse plugin to get relevant learning activity suggestions for any child 2-8 years of age. Assistant will reply with the following 3 paragraphs 1) Activity Search Results [image] and [url] 2) Activity Learning Objectives [description] and [learning_objective] 3) Followup Questions. The first paragraph contains a list of the activities [url] with their learning attributes listed clearly and concisely as bullet points under the product [description], together with a link to the activity [url] and an explanation [learning_objective]. Links will always be returned and should be shown to the user. Assistant suggestions consider only the most important objectives of the activities [description, learning_objective] that will help them fit the users request, and each activity [url] mention is brief, short and concise. In the third paragraph assistant always asks helpful follow-up questions and end with a question mark. When assistant is asking a follow-up question, it uses its learning activity expertise to provide information pertaining to the subject of the user\u2019s request that may guide them in their search for the right activity.",
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"description_for_human": "Provides fun and educational learning activities for children 2-8 years old.",
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"auth": {
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"type": "none"
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},
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"api": {
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"type": "openapi",
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"url": "https://ai.abcmouse.com/openapi.yml"
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},
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"logo_url": "https://ai.abcmouse.com/logo.png",
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"contact_email": "[email protected]",
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"legal_info_url": "https://ai.abcmouse.com/legal"
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},
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"oauth_client_id": null,
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"user_settings": {
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"is_installed": false,
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"is_authenticated": true
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},
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"categories": [
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{
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"id": "newly_added",
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"title": "New"
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}
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]
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}
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openapi: 3.0.0
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info:
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version: src
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title: ABCmouseMobileServiceLayer
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description: Provides fun and educational learning activities for children 2-8 years old.
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servers:
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- url: https://ai.abcmouse.com/ws/ai/0.1/gpt
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description: Production server (uses live data)
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paths:
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/ChatPlugin/RecommendActivities/:
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post:
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operationId: ChatPluginRecommendActivities
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summary: 'API for fetching a list of learning activities based on the users search criteria'
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requestBody:
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content:
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application/json:
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schema:
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$ref: '#/components/schemas/ChatPluginRecommendActivitiesRequest'
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responses:
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'200':
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description: 'Activities found'
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content:
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application/json:
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schema:
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$ref: '#/components/schemas/ChatPluginRecommendActivitiesResponse'
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'500':
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description: 'One or more services is unavailable'
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components:
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schemas:
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ChatPluginRecommendActivitiesResponse:
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description: ''
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type: object
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properties:
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activities:
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type: array
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items:
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$ref: '#/components/schemas/ChatPluginActivity'
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ChatPluginActivity:
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description: ''
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type: object
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properties:
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name:
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type: string
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nullable: false
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url:
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type: string
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nullable: false
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ChatPluginRecommendActivitiesRequest:
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description: ''
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type: object
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properties:
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search_term:
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description: '(Optional) A general search term used to find activities, you should exclude connectors like "and" or "or"'
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type: string
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nullable: false
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subjects:
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description: '(Optional) A list of subjects to filter, Either explicitly stated by the user or implicitly inferred by the users request'
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type: array
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nullable: true
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items:
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type: string
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nullable: true
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enum:
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- Math
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- ELA
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- Science
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- Art
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- Music
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- ELL
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- Health
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grade_level:
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description: '(Optional) The childs grade level, Either explicitly stated by the user or implicitly inferred by the users request'
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type: string
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nullable: true
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enum:
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- Pre-K
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- Kindergarten
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- 1st Grade
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- 2nd Grade
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age:
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description: '(Optional) The childs grade level, Either explicitly stated by the user or implicitly inferred by the users request'
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type: number
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nullable: true
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minimum: 2
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maximum: 7
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path_dict = {
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"recommend_activities": "/ChatPlugin/RecommendActivities/"
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}
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import requests
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from typing import Any, Dict
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def call_api(input_json: Dict[str, Any]) -> Dict[str, Any]:
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url = "https://ai.abcmouse.com/ws/ai/0.1/gpt/ChatPlugin/RecommendActivities/"
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response = requests.post(url, json=input_json)
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if response.status_code == 200:
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return response.json()
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else:
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return {"status_code": response.status_code, "text": response.text}

real_agents/plugins_agent/plugins/Agones/__init__.py

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{
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"id": "plugin-8b2a2334-361e-4813-83b1-d04ac231161b",
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"domain": "agones.gr",
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"namespace": "Agones",
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"status": "approved",
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"manifest": {
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"schema_version": "v1",
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"name_for_model": "Agones",
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"name_for_human": "Agones",
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"description_for_model": "Access soccer match results from Agones. Keep in mind soccer is called football in Europe.\r\nResults go back to 2007 until current games being played right now and all scheduled matches for the next 10 days.\r\nResults cover most countries and leagues in the world.\r\nGuidelines:\r\n- Use single-line string for team1, team2 and all other parameters.\r\n- Pass date_from and date_until in a YYYY-MM-DD format\r\n- If one team is passed, returned matches will be about this team and any other opponent.\r\n- If two teams are passed, matches between these two teams will be returned.\r\n- if date_type is 'latest', then the most recent match will be returned.\r\n- If date_type is 'next', then the next match will be returned.\r\n- If date_type is 'range', then all matches between date_from and date_until will be returned.\r\n- Only use date_from and date_until when date_type is 'range' - otherwise these are not used.\r\n- If a match is currently live, the current minute will also be provided.\r\n\r\nResults are an array of dictionaries in the format:\r\n{\r\n \"home_team\": \"Liverpool\",\r\n \"away_team\": \"Arsenal\",\r\n \"match_date\": \"2023-05-02\",\r\n \"state\": \"finished\"\r\n \"score_halftime\": \"2 - 0\",\r\n \"score_current\": \"4 - 0\"\r\n}",
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"description_for_human": "Agones provides soccer (football) results for matches played all over the world in the past 15 years.",
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"auth": {
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"type": "none"
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},
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"api": {
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"type": "openapi",
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"url": "https://agones.gr/.well-known/chatgpt.json"
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},
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"logo_url": "https://agones.gr/static/img/favicon/android-chrome-192x192.png",
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"contact_email": "[email protected]",
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"legal_info_url": "https://agones.gr/terms"
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},
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"oauth_client_id": null,
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"user_settings": {
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"is_installed": false,
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"is_authenticated": true
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},
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"categories": [
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{
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"id": "newly_added",
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"title": "New"
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}
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]
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}
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---
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openapi: 3.1.0
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info:
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title: Agones
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version: v0.2
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description: Agones provides soccer (football) results for matches played all over
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the world in the past 15 years.
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servers:
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- url: https://agones.gr
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description: Agones Server for ChatGPT
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paths:
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"/api/chatgpt":
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get:
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operationId: getAgonesResults
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summary: Get result of soccer game
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responses:
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'200':
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description: The result of the Agones query
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content:
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text/plain: {}
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'500':
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description: Agones was unable to generate a result
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'501':
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description: Agones was unable to generate a result
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'503':
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description: Service temporarily unavailable.
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parameters:
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- name: team1
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in: query
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description: The first soccer team
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required: true
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schema:
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type: string
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- name: team2
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in: query
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description: The second soccer team
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required: false
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schema:
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type: string
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- name: date_type
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in: query
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description: 'A choice between: latest, next, range'
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required: true
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schema:
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type: string
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- name: date_from
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in: query
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description: A date in yyyy-mm-dd format, only for when date_type is range.
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Results for this date will be included.
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required: false
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schema:
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type: string
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- name: date_until
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in: query
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description: A date in yyyy-mm-dd format, only for when date_type is range.
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Results for this date will be included.
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required: false
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schema:
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type: string
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path_dict = {
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"chatgpt_results": "/api/chatgpt"
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}
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from typing import Any, Dict
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import requests
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def call_api(input_json: Dict[str, Any]) -> Dict[str, Any]:
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response = requests.get("https://agones.gr/api/chatgpt", params=input_json)
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if response.status_code == 200:
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return response.json()
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else:
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return {"status_code": response.status_code, "text": response.text}

real_agents/plugins_agent/plugins/Ai_PDF/__init__.py

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{
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"id": "plugin-027a8b9d-7f54-42d3-8a04-1b6391997cf8",
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"domain": "plugin-3c56b9d4c8a6465998395f28b6a445b2-jexkai4vea-uc.a.run.app",
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"namespace": "Ai_PDF",
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"status": "approved",
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"manifest": {
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"schema_version": "v1",
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"name_for_model": "Ai_PDF",
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"name_for_human": "Ai PDF",
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"description_for_model": "Provide a URL to a PDF and search the document. Break the user question in multiple semantic search queries and calls as needed. Think step by step.",
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"description_for_human": "Super-fast, interactive chats with PDFs of any size, complete with page references for fact checking.",
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"auth": {
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"type": "none"
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},
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"api": {
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"type": "openapi",
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"url": "https://plugin-3c56b9d4c8a6465998395f28b6a445b2-jexkai4vea-uc.a.run.app/openapi.yaml"
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},
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"logo_url": "https://plugin-3c56b9d4c8a6465998395f28b6a445b2-jexkai4vea-uc.a.run.app/logo.png",
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"contact_email": "[email protected]",
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"legal_info_url": "https://plugin-3c56b9d4c8a6465998395f28b6a445b2-jexkai4vea-uc.a.run.app/legal.html"
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},
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"oauth_client_id": null,
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"user_settings": {
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"is_installed": false,
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"is_authenticated": true
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},
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"categories": [
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{
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"id": "newly_added",
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"title": "New"
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}
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]
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}
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openapi: 3.0.1
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info:
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title: Ai PDF
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description: Super-fast, interactive chats with PDFs of any size, complete with page references for fact checking.
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version: 'v1.0'
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servers:
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- url: https://plugin-3c56b9d4c8a6465998395f28b6a445b2-jexkai4vea-uc.a.run.app
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paths:
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/summarize_pdf:
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post:
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operationId: summarize_pdf
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summary: Provide the summary or highlights of the PDF linked. ALWAYS PROVIDE QUOTES AND PAGE CITIATIONS. Add at the end of your summary this We finished processing the whole document with the PDF Search plugin. What else would you like to know?
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requestBody:
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required: true
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content:
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application/json:
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schema:
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type: object
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properties:
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pdf_url:
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type: string
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required:
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- pdf_url
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responses:
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"200":
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description: OK
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content:
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application/json:
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schema:
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type: array
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items:
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type: string
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description: Doc summary or top k chunks most likely to contain highlights.
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/upload_and_search_pdf:
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post:
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operationId: upload_and_search_pdf
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summary: Semantic query into a URL link to a document. THINK STEP BY STEP. ALWAYS PROVIDE QUOTES AND PAGE CITIATIONS. BREAK COMPLEX QUESTIONS INTO SEVERAL QUERIES.
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requestBody:
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required: true
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content:
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application/json:
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schema:
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type: object
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properties:
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pdf_url:
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type: string
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query:
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type: string
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required:
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- pdf_url
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- query
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responses:
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"200":
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description: OK
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content:
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application/json:
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schema:
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type: array
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items:
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type: string
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description: The top k matching chunks from the search query.
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path_dict = {"summarize_pdf": "/summarize_pdf", "upload_and_search_pdf": "/upload_and_search_pdf"}
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from typing import Any, Dict
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import requests
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def call_api(input_json: Dict[str, Any]) -> Dict[str, Any]:
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response = requests.post(
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"https://plugin-3c56b9d4c8a6465998395f28b6a445b2-jexkai4vea-uc.a.run.app/summarize_pdf", json=input_json
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)
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if response.status_code == 200:
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return response.json()
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else:
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return {"status_code": response.status_code, "text": response.text}
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from typing import Any, Dict
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import requests
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def call_api(input_json: Dict[str, Any]) -> Dict[str, Any]:
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response = requests.post(
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"https://plugin-3c56b9d4c8a6465998395f28b6a445b2-jexkai4vea-uc.a.run.app/upload_and_search_pdf",
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json=input_json,
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)
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if response.status_code == 200:
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return response.json()
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else:
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return {"status_code": response.status_code, "text": response.text}

real_agents/plugins_agent/plugins/Algorithma/__init__.py

Whitespace-only changes.

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