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0.1.5.0

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agenticmem

A Python client for the AgenticMem API

Published27 Jan 2026
Direct dependencies9
Transitive dependenciesNot calculated

README

Version 0.1.5.0 documentation

/user_profiler/agenticmem/agenticmem_client

Description: Python SDK for remote async access to AgenticMem API

Main Entry Points

  • Client: agenticmem/client.py - AgenticMemClient
  • Utils: agenticmem/client_utils.py - Helper utilities

Purpose

  1. Remote API access - Async SDK for applications to call AgenticMem backend
  2. Authentication - Handle login and Bearer token management
  3. Type-safe interface - Auto-parsing responses into Pydantic models

API Methods

Authentication:

  • login(email, password) - Get auth token

Publishing:

  • publish_interaction(request_id, user_id, interactions, source, agent_version) - Publish interactions (triggers profile/feedback/evaluation)

Profiles:

  • search_profiles(request) - Semantic search
  • get_profiles(request) - Get all for user
  • get_all_profiles(limit, status_filter) - Get all profiles across all users
  • delete_profile(user_id, profile_id, search_query) - Delete profiles
  • get_profile_change_log() - Get history
  • rerun_profile_generation(request) - Regenerate profiles from interactions

Interactions:

  • search_interactions(request) - Semantic search
  • get_interactions(request) - Get all for user
  • delete_interaction(user_id, interaction_id) - Delete interaction

Requests:

  • get_requests(request) - Get request groups with associated interactions
  • delete_request(request_id) - Delete a request and its interactions
  • delete_request_group(request_group) - Delete all requests in a group

Feedback:

  • get_raw_feedbacks(request) - Raw feedback from interactions
  • add_raw_feedback(request) - Add raw feedback directly to storage
  • get_feedbacks(request) - Aggregated feedback with status
  • rerun_feedback_generation(request) - Regenerate feedback for agent version
  • run_feedback_aggregation(request) - Aggregate raw feedbacks into insights

Evaluation:

  • get_agent_success_evaluation_results(request) - Get agent success evaluation results

Configuration:

  • set_config(config) - Update org config (extractors, evaluators, storage)
  • get_config() - Get current config

Architecture Pattern

  • All async - Uses aiohttp for HTTP requests
  • Type-safe - Pydantic models from agenticmem_commons
  • Auto-parsing - Responses → Pydantic models
  • Flexible input - Accepts Pydantic models or dicts
  • Bearer auth - Automatic token handling

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Declared dependencies 9

Native requirements
9 direct targetsNot calculated transitive count
Package / targetRequirementRelationship
requests
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Distribution files

2 collected
agenticmem-0.1.5.0-py3-none-any.whl

bdist_wheel · 11.72 KB · Python py3

Source file
agenticmem-0.1.5.0.tar.gz

sdist · 11.12 KB · Python source

Source file

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Observed since 20 Oct, 22:17 UTC

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package_version:bedf820501e93298d41c87e9555e777bfe36e4fe7cf6c70b07e73e96145bc7ba

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