Friday Chat

Terminal chat application for the Friday Framework.

Friday Chat provides the user-facing command-line chat experience built on the Friday runtime, memory, agent, LLM, transcript, and tools packages.

Install

pip install friday-chat==0.1.0a2

Run

friday-chat --help

Import Package

import friday_chat

Model Library Configuration

Friday Chat 0.1.0a2 uses one provider-independent model library for primary chat, extraction, passage routing, compaction, maintenance, embeddings, and smart-file processing. Copy both packaged examples into the same directory, rename the model library if desired, and keep its path relative to the runtime configuration file.

model_library:
  path: ./models-config.yaml
llm_pool:
  default_service: chat
  services:
    chat:
      profile: qwen38_chat_local
    extraction:
      profile: qwen36_chat_local
      generation_overrides:
        reasoning: {mode: disabled}
        sampling: {temperature: 0.0}
        max_tokens: 8000
embedding_pool:
  default_service: memory
  services:
    memory:
      profile: nomic_embedding_local
extraction:
  llm_service: extraction
embedding:
  embedding_service: memory

The referenced models-config.yaml stores reusable endpoint and model identity, but never a secret value:

schema: friday.model-library/v1
credentials:
  local_lmstudio:
    env: FRIDAY_LLM_API_KEY
endpoints:
  local_lmstudio:
    api_base: http://127.0.0.1:1234/v1
    provider: openai_compatible
    serving_engine: lm_studio
    default_credential: local_lmstudio
profiles:
  qwen38_chat_local:
    kind: chat
    endpoint: local_lmstudio
    dialect: openai_chat_completions
    model: openai/qwen3.8-27b-mlx
    model_target:
      model_id: qwen3.8-27b-mlx
      family: qwen3_8
      revision: replace-with-exact-served-revision

Export every credential selected by an enabled service before startup. The packaged example uses FRIDAY_LLM_API_KEY, FRIDAY_OPENROUTER_API_KEY, and FRIDAY_MOONSHOT_API_KEY. If you maintain a local .env, source it first; Friday Chat does not load .env files implicitly. For hosted providers, define a credential entry whose env names the provider key and select that credential from each least-privilege service binding. Never put the key itself in either YAML file.

Friday LLM provides the built-in normalized reasoning profile for LM Studio, OpenAI-compatible Chat Completions, and Qwen3.8. Other transports continue to work through compatibility behavior but are not automatically assigned that capability profile.

Provider-specific controls, when needed, use a bounded provider_options object with an explicit namespace. Arbitrary provider keyword dictionaries are not accepted. Prefer normalized generation fields when they express the same intent.

Legacy Compatibility

The former flat fields remain accepted through the 0.1.x compatibility window:

Legacy configurations without explicit targets retain their previous behavior and produce startup migration diagnostics. With explicit targets, flat fields are converted to typed generation controls. Equal flat and nested values are accepted with a diagnostic; contradictory values fail before provider I/O.

top_p and top_k were present in earlier Friday Chat YAML but were not forwarded by its legacy adapter. They become effective on the typed path. Wire emission proves forwarding, not that every endpoint behaviorally honors the setting.

License

MIT