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kollabor-ai

kollabor-ai is the model/provider layer for Kollabor.

It owns profile loading, provider creation, prompt rendering, context services, conversation/session helpers, token/cost accounting, and response parsing. The CLI, engine, and agent runtime should use this package instead of talking directly to provider SDKs.

Current Role

  • Normalize provider access across Anthropic, OpenAI, OpenAI Responses, Azure OpenAI, Gemini, OpenRouter, and custom OpenAI-compatible endpoints.
  • Load, validate, and resolve LLM profiles, including environment-variable and OAuth-backed credentials.
  • Render system prompts and <trender> prompt fragments.
  • Parse streaming text, thinking/reasoning blocks, and tool-call deltas.
  • Track conversation logs, session names, branch names, pricing, and context service metadata.

Architecture

Module Responsibility
api_communication_service.py high-level LLM request/streaming service
providers/ provider configs, adapters, registry, errors, transformers
profile_manager.py profile model, config/env resolution, persistence
profile_validator.py profile field validation and connection checks
prompt_renderer.py dynamic prompt rendering and <trender> support
system_prompt_builder.py assembled system prompt construction
response_parser.py / response_processor.py response and tool-call parsing
streaming_thinking_parser.py streamed thinking/reasoning extraction
conversation_manager.py / conversation_logger.py history and raw logs
context_service/ context ledger, file tracking, hash utilities, hub bridge
pricing_registry.py / cost_calculator.py model pricing and usage costs
session_naming.py / session_parser.py session metadata helpers

Usage

from kollabor_ai import APICommunicationService, LLMProfile


class DictConfig:
    def __init__(self, values):
        self.values = values

    def get(self, key, default=None):
        return self.values.get(key, default)


profile = LLMProfile(
    name="default",
    provider="anthropic",
    model="claude-3-5-sonnet-20241022",
    api_key="${ANTHROPIC_API_KEY}",
)

api = APICommunicationService(
    config=DictConfig({"kollabor.llm.enable_streaming": True}),
    raw_conversations_dir=".kollab/raw",
    profile=profile,
)

await api.initialize()
text = await api.call_llm([{"role": "user", "content": "hello"}])

Known Gaps

  • ProviderRegistry currently caches singleton instances by provider type, so callers that need strict per-profile isolation must be careful until the registry is keyed by full provider configuration or sessions create their own providers.
  • LLMProfile.to_dict() includes resolved API keys when present; API layers must explicitly redact profile dictionaries before returning them to clients.
  • Provider behavior is still partly normalized by convention. Tool-call, thinking, usage, and stop-reason contracts need broader cross-provider tests.
  • Prompt rendering can execute dynamic includes; callers must sanitize user-controlled prompts before rendering.

Roadmap

Phase 1: Provider isolation and safety

  • Key provider instances by full provider config or create session-scoped providers for clients that need isolation.
  • Add a redacted profile view helper for API/UI use.
  • Expand provider conformance tests for streaming tool calls, thinking content, token usage, and error classification.

Phase 2: Contract cleanup

  • Make public service constructors and adapter boundaries easier to use outside the CLI orchestration layer.
  • Document the canonical message/tool-call schema expected by every provider.
  • Keep provider-specific transformers behind stable package APIs.

Phase 3: Context and cost maturity

  • Document the context-service ledger and hub bridge as first-class APIs.
  • Add pricing registry refresh/versioning guidance.
  • Add stronger diagnostics for context-window and max-token decisions.

Development

Targeted validation examples:

python -m py_compile packages/kollabor-ai/src/kollabor_ai/*.py
python -m pytest tests/unit/llm tests/unit/test_context_service_hub_bridge.py -q

Dependencies

  • pydantic >= 2.0
  • aiohttp >= 3.10
  • httpx >= 0.27
  • openai >= 1.0

License

MIT

Metadata

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