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Changelog

All notable changes to this project will be documented in this file.

[0.12.8] - 2026-03-12

Fixed

  • Vertex AI v1/v1beta1 bug: Model.parse("vertex_ai:gemini-2.5-pro-preview-06-05") with GOOGLE_CLOUD_PROJECT set was storing a hardcoded v1 URL in model.base_url, causing the provider's v1beta1 selection logic to be bypassed. Preview models now correctly use v1beta1 at request time.

Added

  • Vertex AI input validation: Project ID and region from environment variables are now validated with helpful error messages instead of producing opaque DNS/HTTP errors.
  • GOOGLE_CLOUD_LOCATION support: Added as a fallback for GOOGLE_CLOUD_REGION, consistent with other Google Cloud libraries and tooling.
  • Multi-region example script: examples/providers/vertex_ai_multi_region.exs

[0.12.7] - 2026-03-10

Fixed

  • Vertex AI model routing: Fixed build_request_params/3 not including the "model" key in the params map, causing chat/2 and chat_stream/2 to always fall back to "gemini-2.0-flash" regardless of the requested model.
  • Vertex AI 404 on preview models: Use v1beta1 API version for preview and experimental models (e.g., gemini-3.1-pro-preview). The v1 endpoint returns 404 for these models.

Added

  • Nous.Providers.VertexAI.api_version_for_model/1 — returns "v1beta1" for preview/experimental models, "v1" for stable models.
  • Nous.Providers.VertexAI.endpoint/3 now accepts an optional model name to select the correct API version.
  • Debug logging for Vertex AI request URLs.

[0.12.6] - 2026-03-07

Added

  • Auto-update memory: Nous.Plugins.Memory can now automatically reflect on conversations and update memories after each run — no explicit tool calls needed. Enable with auto_update_memory: true in memory_config. Configurable reflection model, frequency, and context limits.
    • New after_run/3 callback in Nous.Plugin behaviour — runs once after the entire agent run completes. Wired into both AgentRunner.run/3 and run_with_context/3.
    • Nous.Plugin.run_after_run/4 helper for executing the hook across all plugins
    • New config options: :auto_update_memory, :auto_update_every, :reflection_model, :reflection_max_tokens, :reflection_max_messages, :reflection_max_memories
    • New example: examples/memory/auto_update.exs

[0.12.5] - 2026-03-06

Added

  • Vertex AI provider: Nous.Providers.VertexAI for accessing Gemini models through Google Cloud Vertex AI. Supports enterprise features (VPC-SC, CMEK, regional endpoints, IAM).
    • Three auth modes: app config Goth (config :nous, :vertex_ai, goth: MyApp.Goth), per-model Goth (default_settings: %{goth: MyApp.Goth}), or direct access token (api_key / VERTEX_AI_ACCESS_TOKEN)
    • Bearer token auth via api_key option, VERTEX_AI_ACCESS_TOKEN env var, or Goth integration
    • Goth integration ({:goth, "~> 1.4", optional: true}) for automatic service account token management — reuse existing Goth processes from PubSub, etc.
    • URL auto-construction from GOOGLE_CLOUD_PROJECT and GOOGLE_CLOUD_REGION env vars
    • Nous.Providers.VertexAI.endpoint/2 helper to build endpoint URLs
    • Reuses existing Gemini message format, response parsing, and stream normalization
    • Model string: "vertex_ai:gemini-2.0-flash"

[0.12.2] - 2026-03-04

Fixed

  • Gemini streaming: Fixed streaming responses returning 0 events. The Gemini streamGenerateContent endpoint returns a JSON array (application/json) by default, not Server-Sent Events. Instead of forcing SSE via alt=sse query parameter, added a pluggable stream parser to Nous.Providers.HTTP.

Added

  • Nous.Providers.HTTP.JSONArrayParser — stream buffer parser for JSON array responses. Extracts complete JSON objects from a streaming [{...},{...},...] response by tracking {} nesting depth while respecting string literals and escape sequences.
  • :stream_parser option on HTTP.stream/4 — accepts any module implementing parse_buffer/1 with the same {events, remaining_buffer} contract as SSE parsing. Defaults to the existing SSE parser. Enables any provider with a non-SSE streaming format to plug in a custom parser.

[0.12.0] - 2026-02-28

Added

  • Memory System: Persistent memory for agents with hybrid text + vector search, temporal decay, importance weighting, and flexible scoping.

    • Nous.Memory.Entry — memory entry struct with type (semantic/episodic/procedural), importance, evergreen flag, and scoping fields (agent_id, session_id, user_id, namespace)
    • Nous.Memory.Store — storage behaviour with 8 callbacks (init, store, fetch, delete, update, search_text, search_vector, list)
    • Nous.Memory.Store.ETS — zero-dep in-memory backend with Jaro-distance text search
    • Nous.Memory.Store.SQLite — SQLite + FTS5 backend (requires exqlite)
    • Nous.Memory.Store.DuckDB — DuckDB + FTS + vector backend (requires duckdbex)
    • Nous.Memory.Store.Muninn — Tantivy BM25 text search backend (requires muninn)
    • Nous.Memory.Store.Zvec — HNSW vector search backend (requires zvec)
    • Nous.Memory.Store.Hybrid — combines Muninn + Zvec for maximum retrieval quality
    • Nous.Memory.Scoring — pure functions for Reciprocal Rank Fusion, temporal decay, composite scoring
    • Nous.Memory.Search — hybrid search orchestrator (text + vector → RRF merge → decay → composite score)
    • Nous.Memory.Embedding — embedding provider behaviour with pluggable implementations
    • Nous.Memory.Embedding.Bumblebee — local on-device embeddings via Bumblebee + EXLA (Qwen 0.6B default)
    • Nous.Memory.Embedding.OpenAI — OpenAI text-embedding-3-small provider
    • Nous.Memory.Embedding.Local — generic local endpoint (Ollama, vLLM, LMStudio)
    • Nous.Memory.Tools — agent tools: remember, recall, forget
    • Nous.Plugins.Memory — plugin with auto-injection of relevant memories, configurable search scope and injection strategy
    • 6 example scripts in examples/memory/ (basic ETS, Bumblebee, SQLite, DuckDB, Hybrid, cross-agent)
    • 62 new tests across 6 test files

  • Graceful degradation: No embedding provider = keyword-only search. No optional deps = Store.ETS with Jaro matching. The core memory system has zero additional dependencies.

[0.11.3] - 2026-02-26

Fixed

  • Anthropic and Gemini streaming: Added missing Nous.StreamNormalizer.Anthropic and Nous.StreamNormalizer.Gemini modules. These were referenced in Provider.default_stream_normalizer/0 but never created, causing runtime crashes when streaming with Anthropic or Gemini providers.

Added

  • Nous.StreamNormalizer.Anthropic — normalizes Anthropic SSE events (content_block_delta, message_delta, content_block_start for tool use, thinking deltas, error events)
  • Nous.StreamNormalizer.Gemini — normalizes Gemini SSE events (candidates array with text parts, functionCall, finishReason mapping)
  • 42 tests for both new stream normalizers

[0.11.0] - 2026-02-20

Added

  • Structured Output Mode: Agents return validated, typed data instead of raw strings. Inspired by instructor_ex.

    • Nous.OutputSchema core module: JSON schema generation, provider settings dispatch, parsing and validation
    • use Nous.OutputSchema macro with @llm_doc attribute for schema-level LLM documentation
    • validate_changeset/1 optional callback for custom Ecto validation rules
    • Validation retry loop: failed outputs are sent back to the LLM with error details (max_retries option)
    • System prompt augmentation with schema instructions

  • Output Type Variants:

    • Ecto schema modules — full JSON schema + changeset validation
    • Schemaless Ecto types (%{name: :string, age: :integer}) — lightweight, no module needed
    • Raw JSON schema maps (string keys) — passed through as-is
    • {:regex, pattern} — regex-constrained output (vLLM/SGLang)
    • {:grammar, ebnf} — EBNF grammar-constrained output (vLLM)
    • {:choice, choices} — choice-constrained output (vLLM/SGLang)

  • Provider Modes: Controls how structured output is enforced per-provider

    • :auto (default) — picks best mode for the provider
    • :json_schema — response_format with strict JSON schema (OpenAI, vLLM, SGLang, Gemini)
    • :tool_call — synthetic tool with tool_choice (Anthropic default)
    • :json — response_format: json_object (OpenAI-compatible)
    • :md_json — prompt-only enforcement with markdown fence + stop token (all providers)

  • Provider Passthrough: response_format, guided_json, guided_regex, guided_grammar, guided_choice, json_schema, regex, generationConfig now passed through in build_request_params

  • New Files:

    • lib/nous/output_schema.ex — core module
    • lib/nous/output_schema/validator.ex — behaviour definition
    • lib/nous/output_schema/use_macro.ex — use Nous.OutputSchema macro
    • docs/guides/structured_output.md — comprehensive guide
    • examples/14_structured_output.exs — example script with 5 patterns
    • test/nous/output_schema_test.exs — 42 unit tests
    • test/nous/structured_output_integration_test.exs — 16 integration tests
    • test/eval/agents/structured_output_test.exs — 3 LLM integration tests

Changed

  • Nous.Agent struct gains structured_output keyword list field (mode, max_retries)
  • Nous.Types.output_type expanded with schemaless, raw JSON schema, and guided mode tuples
  • Nous.AgentRunner injects structured output settings, augments system prompt, handles validation retries
  • Nous.Agents.BasicAgent.extract_output/2 routes through OutputSchema.parse_and_validate/2
  • Nous.Agents.ReActAgent.extract_output/2 validates final_answer against output_type
  • Provider build_request_params/3 passes through structured output parameters

[0.10.1] - 2026-02-14

Changed

  • Sub-Agent plugin unified: Merged ParallelSubAgent into Nous.Plugins.SubAgent

    • Single plugin now provides both delegate_task (single) and spawn_agents (parallel) tools
    • system_prompt/2 callback injects orchestration guidance including available templates
    • Templates accept %Nous.Agent{} structs (recommended) or config maps (legacy)
    • Parallel execution via Task.Supervisor.async_stream_nolink
    • Configurable concurrency (parallel_max_concurrency, default: 5) and timeout (parallel_timeout, default: 120s)
    • Graceful partial failure: crashed/timed-out sub-agents don't block others

  • New Example: examples/13_sub_agents.exs

    • Template-based sub-agents using Nous.Agent.new/2 structs
    • Parallel execution with inline model config
    • Direct programmatic invocation bypassing the LLM

[0.10.0] - 2026-02-14

Added

  • Plugin System: Composable agent extensions via Nous.Plugin behaviour

    • Callbacks: init/2, tools/2, system_prompt/2, before_request/3, after_response/3
    • Add plugins: [MyPlugin] to any agent for cross-cutting concerns
    • AgentRunner iterates plugins at each stage of the execution loop

  • Human-in-the-Loop (HITL): Approval workflows for sensitive tool calls

    • requires_approval: true on Nous.Tool struct
    • approval_handler on Nous.Agent.Context for approve/edit/reject decisions
    • Nous.Plugins.HumanInTheLoop for per-tool configuration via deps

  • Sub-Agent System: Enable agents to delegate tasks to specialized child agents

    • Nous.Plugins.SubAgent provides delegate_task tool
    • Pre-configured agent templates via deps[:sub_agent_templates]
    • Isolated context per sub-agent with shared deps support

  • Conversation Summarization: Automatic context window management

    • Nous.Plugins.Summarization monitors token usage against configurable threshold
    • LLM-powered summarization with safe split points (never separates tool_call/tool_result pairs)
    • Error-resilient: keeps all messages if summarization fails

  • State Persistence: Save and restore agent conversation state

    • Nous.Agent.Context.serialize/1 and deserialize/1 for JSON-safe round-trips
    • Nous.Persistence behaviour with save/load/delete/list callbacks
    • Nous.Persistence.ETS reference implementation
    • Auto-save hooks on Nous.AgentServer

  • Enhanced Supervision: Production lifecycle management for agents

    • Nous.AgentRegistry for session-based process lookup via Registry
    • Nous.AgentDynamicSupervisor for on-demand agent creation/destruction
    • Configurable inactivity timeout on AgentServer (default: 5 minutes)
    • Added to application supervision tree

  • Dangling Tool Call Recovery: Resilient session resumption

    • Nous.Agent.Context.patch_dangling_tool_calls/1 injects synthetic results for interrupted tool calls
    • Called automatically when continuing from an existing context

  • PubSub Abstraction Layer: Unified Nous.PubSub module for all PubSub usage

    • Nous.PubSub wraps Phoenix.PubSub with graceful no-op fallback when unavailable
    • Application-level configuration via config :nous, pubsub: MyApp.PubSub
    • Topic builders: agent_topic/1, research_topic/1, approval_topic/1
    • Nous.Agent.Context gains pubsub and pubsub_topic fields (runtime-only, never serialized)
    • Nous.Agent.Callbacks.execute/3 now broadcasts via PubSub as a third channel alongside callbacks and notify_pid
    • AgentServer refactored to use Nous.PubSub — removes ad-hoc setup_pubsub_functions/0 and subscribe_fn/broadcast_fn from state
    • Research Coordinator broadcasts progress via PubSub when :session_id is provided
    • SubAgent plugin propagates parent's PubSub context to child agents

  • Async HITL Approval via PubSub: Nous.PubSub.Approval module

    • handler/1 builds an approval handler compatible with Nous.Plugins.HumanInTheLoop
    • Broadcasts {:approval_required, info} and blocks via receive for response
    • respond/4 sends approval decisions from external processes (e.g., LiveView)
    • Configurable timeout with :reject as default on expiry
    • Enables async approval workflows without synchronous I/O

  • Deep Research Agent: Autonomous multi-step research with citations

    • Nous.Research.run/2 public API with HITL checkpoints between iterations
    • Five-phase loop: plan → search → synthesize → evaluate → report
    • Nous.Research.Planner decomposes queries into searchable sub-questions
    • Nous.Research.Searcher runs parallel search agents per sub-question
    • Nous.Research.Synthesizer for deduplication, contradiction detection, gap analysis
    • Nous.Research.Reporter generates markdown reports with inline citations
    • Progress broadcasting via callbacks, notify_pid, and PubSub

  • New Research Tools:

    • Nous.Tools.WebFetch — URL content extraction with Floki HTML parsing
    • Nous.Tools.Summarize — LLM-powered text summarization focused on research queries
    • Nous.Tools.SearchScrape — Parallel fetch + summarize for multiple URLs
    • Nous.Tools.TavilySearch — Tavily AI search API integration
    • Nous.Tools.ResearchNotes — Structured finding/gap/contradiction tracking via ContextUpdate

  • New Dependencies:

    • floki ~> 0.36 (optional, for HTML content extraction)
    • phoenix_pubsub ~> 2.1 (test-only, for PubSub integration tests)

Changed

  • Nous.Agent struct now accepts plugins: [module()] option
  • Nous.Tool struct now accepts requires_approval: boolean() option
  • Nous.Agent.Context now includes approval_handler, pubsub, and pubsub_topic fields
  • Nous.AgentServer supports optional :name registration, :persistence backend, and uses Nous.PubSub (removed ad-hoc setup_pubsub_functions/0)
  • Nous.AgentServer :pubsub option now defaults to Nous.PubSub.configured_pubsub() instead of MyApp.PubSub
  • Nous.AgentRunner accepts :pubsub and :pubsub_topic options when building context
  • Application supervision tree includes AgentRegistry and AgentDynamicSupervisor

[0.9.0] - 2026-01-04

Added

  • Evaluation Framework: Production-grade testing and benchmarking for AI agents

    • Nous.Eval module for defining and running test suites
    • Nous.Eval.Suite for test suite management with YAML support
    • Nous.Eval.TestCase for individual test case definitions
    • Nous.Eval.Runner for sequential and parallel test execution
    • Nous.Eval.Metrics for collecting latency, token usage, and cost metrics
    • Nous.Eval.Reporter for console and JSON result reporting
    • A/B testing support with Nous.Eval.run_ab/2

  • Six Built-in Evaluators:

    • :exact_match - Strict string equality matching
    • :fuzzy_match - Jaro-Winkler similarity with configurable thresholds
    • :contains - Substring and regex pattern matching
    • :tool_usage - Tool call verification with argument validation
    • :schema - Ecto schema validation for structured outputs
    • :llm_judge - LLM-based quality assessment with custom rubrics

  • Optimization Engine: Automated parameter tuning for agents

    • Nous.Eval.Optimizer with three strategies: grid search, random search, Bayesian optimization
    • Support for float, integer, choice, and boolean parameter types
    • Early stopping on threshold achievement
    • Detailed trial history and best configuration reporting

  • New Mix Tasks:

    • mix nous.eval - Run evaluation suites with filtering, parallelism, and multiple output formats
    • mix nous.optimize - Parameter optimization with configurable strategies and metrics

  • New Dependency: yaml_elixir ~> 2.9 for YAML test suite parsing

Documentation

  • New comprehensive evaluation framework guide (docs/guides/evaluation.md)
  • Five new example scripts in examples/eval/:
    • 01_basic_evaluation.exs - Simple test execution
    • 02_yaml_suite.exs - Loading and running YAML suites
    • 03_optimization.exs - Parameter optimization workflows
    • 04_custom_evaluator.exs - Implementing custom evaluators
    • 05_ab_testing.exs - A/B testing configurations

[0.8.1] - 2025-12-31

Fixed

  • Fixed Usage struct not implementing Access behaviour for telemetry metrics
  • Fixed Task.shutdown/2 nil return case in AgentServer cancellation
  • Fixed tool call field access for OpenAI-compatible APIs (string vs atom keys)

Added

  • Vision/multimodal test suite with image fixtures (test/nous/vision_test.exs)
  • ContentPart test suite for image conversion utilities (test/nous/content_part_test.exs)
  • Multimodal message examples in conversation demo (examples/04_conversation.exs)

Changed

  • Updated docs to link examples to GitHub source files
  • Improved sidebar grouping in hexdocs

[0.8.0] - 2025-12-31

Added

  • Context Management: New Nous.Agent.Context struct for immutable conversation state, message history, and dependency injection. Supports context continuation between runs:

    {:ok, result1} = Nous.run(agent, "My name is Alice")
{:ok, result2} = Nous.run(agent, "What's my name?", context: result1.context)

  • Agent Behaviour: New Nous.Agent.Behaviour for implementing custom agents with lifecycle callbacks (init_context/2, build_messages/2, process_response/3, extract_output/2).

  • Dual Callback System: New Nous.Agent.Callbacks supporting both map-based callbacks and process messages:

    # Map callbacks
Nous.run(agent, "Hello", callbacks: %{
  on_llm_new_delta: fn _event, delta -> IO.write(delta) end
})

# Process messages (for LiveView)
Nous.run(agent, "Hello", notify_pid: self())

  • Module-Based Tools: New Nous.Tool.Behaviour for defining tools as modules with metadata/0 and execute/2 callbacks. Use Nous.Tool.from_module/2 to create tools from modules.

  • Tool Context Updates: New Nous.Tool.ContextUpdate struct allowing tools to modify context state:

    def my_tool(ctx, args) do
  {:ok, result, ContextUpdate.new() |> ContextUpdate.set(:key, value)}
end

  • Tool Testing Helpers: New Nous.Tool.Testing module with mock_tool/2, spy_tool/1, and test_context/1 for testing tool interactions.

  • Tool Validation: New Nous.Tool.Validator for JSON Schema validation of tool arguments.

  • Prompt Templates: New Nous.PromptTemplate for EEx-based prompt templates with variable substitution.

  • Built-in Agent Implementations: Nous.Agents.BasicAgent (default) and Nous.Agents.ReActAgent (reasoning with planning tools).

  • Structured Errors: New Nous.Errors module with MaxIterationsReached, ToolExecutionError, and ExecutionCancelled error types.

  • Enhanced Telemetry: New events for iterations (:iteration), tool timeouts (:tool_timeout), and context updates (:context_update).

Changed

  • Result Structure: Nous.run/3 now returns %{output: _, context: _, usage: _} instead of just output string.

  • Tool Function Signature: Tools now receive (ctx, args) instead of (args). The context provides access to ctx.deps for dependency injection.

  • Examples Modernized: Reduced from ~95 files to 21 files. Flattened directory structure from 4 levels to 2 levels. All examples updated to v0.8.0 API.

Removed

  • Removed deprecated provider modules: Nous.Providers.Gemini, Nous.Providers.Mistral, Nous.Providers.VLLM, Nous.Providers.SGLang.

  • Removed built-in tools: Nous.Tools.BraveSearch, Nous.Tools.DateTimeTools, Nous.Tools.StringTools, Nous.Tools.TodoTools. These can be implemented as custom tools.

  • Removed Nous.RunContext (replaced by Nous.Agent.Context).

  • Removed Nous.PromEx.Plugin (users can implement custom Prometheus metrics using telemetry events).

[0.7.2] - 2025-12-29

Fixed

  • Stream completion events: The [DONE] SSE event now properly emits a {:finish, "stop"} event instead of being silently discarded. This ensures stream consumers always receive a completion signal.

  • Documentation links: Fixed broken links in hexdocs documentation. Relative links to .exs example files now use absolute GitHub URLs so they work correctly on hexdocs.pm.

[0.7.1] - 2025-12-29

Changed

  • Make all provider dependencies optional: openai_ex, anthropix, and gemini_ex are now truly optional dependencies. Users only need to install the dependencies for the providers they use.

  • Runtime dependency checks: Provider modules now check for dependency availability at runtime instead of compile-time, allowing the library to compile without any provider-specific dependencies.

  • OpenAI message format: Messages are now returned as plain maps with string keys (%{"role" => "user", "content" => "Hi"}) instead of OpenaiEx.ChatMessage structs. This removes the compile-time dependency on openai_ex for message formatting.

Fixed

  • Fixed "anthropix dependency not available" errors that occurred when using the library in applications without anthropix installed.

  • Fixed compile-time errors that occurred when openai_ex was not present in the consuming application.

[0.7.0] - 2025-12-27

Initial public release with multi-provider LLM support:

  • OpenAI-compatible providers (OpenAI, Groq, OpenRouter, Ollama, LM Studio, vLLM)
  • Native Anthropic Claude support with extended thinking
  • Google Gemini support
  • Mistral AI support
  • Tool/function calling
  • Streaming support
  • ReAct agent implementation