Migrate to PydanticAI for LLM and summary agents#59
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Replaces direct OpenAI SDK usage with PydanticAI Agent, enabling configurable LLM providers (OpenAI, Anthropic) via a provider:model string format. Renames openai_api_key → embeddings_api_key, adds explicit llm_api_key and llm_model config fields. Adds structured SummaryOutput type and tests for ConversationEngine and KnowledgeManager. Closes #58
- Install requirements-dev.txt to get pytest-asyncio - Explicitly install pydantic-ai>=1.0.0 with -U to upgrade opentelemetry packages past the version pinned by chromadb
Missing '; python_version >= "3.13"' marker caused CI failure on Python 3.10.
chromadb pins opentelemetry-exporter-otlp-proto-common==1.32.0 which lacks _create_exp_backoff_generator required by pydantic-ai.
…r otel packages grpc 1.32.0 imports _create_exp_backoff_generator from proto-common but that function only exists in newer versions. Must upgrade all otel packages together. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
…lemetry Pin pydantic-ai>=1.0.0 in requirements.in and recompile both requirements files so opentelemetry packages are consistently at 1.39.1 — compatible with both chromadb and pydantic-ai/logfire. Removes the version-upgrade workaround from the CI workflow.
numpy 2.4.x and other dependencies require Python >=3.11.
langchain 1.x removed langchain.vectorstores.base, langchain.embeddings.base, and langchain.text_splitter — updating those imports is a separate task.
Bump requires-python to >=3.13 to match dev/CI environment. Populate dependencies to mirror requirements.in so pip install -e . works correctly.
wolfdancer
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Jun 17, 2026
Reconcile the Slack bot with the PydanticAI migration (#59): - SlackBotConfig: replace openai_api_key with embeddings_api_key / llm_api_key / llm_model, matching DiscordBotConfig (read by Innie/Topic). - slack_bot.py: Innie() now takes only outie_config (no api_key arg). - Add slack-bolt to pyproject dependencies (was only in requirements). - Update slack_config.example.yaml and Slack tests for the new fields. - Reconcile CLAUDE.md to cover both platforms and the PydanticAI engine. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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Summary
Agent, enabling configurable LLM providers (OpenAI, Anthropic) viaprovider:modelstring format (e.g."anthropic:claude-sonnet-4-6")openai_api_key→embeddings_api_key, adds explicitllm_api_keyandllm_modelconfig fields so embeddings and chat LLM can be configured independentlySummaryOutputPydantic model for knowledge manager summaries, withsummary,key_points, andsuggested_titlefieldstests/test_conversation_engine.pyandtests/test_knowledge_manager.pyusing PydanticAI'sTestModelfor fast, dependency-free testingTest plan
pytestpasses all tests including new async tests forConversationEngineandKnowledgeManagerllm_model: "openai:gpt-4o")llm_model: "anthropic:claude-sonnet-4-6")config.yamlupdated to new field names (embeddings_api_key,llm_api_key,llm_model)Closes #58