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Access Kimi, MiniMax, GLM, DeepSeek, and GPT-OSS models through the Fireworks AI API","maintainers":[{"name":"monotykamary","email":"tom81094@gmail.com"}],"readme":"<div align=\"center\">\n\n# 🎆 pi-fireworks-provider\n\n**31+ models through [Fireworks AI](https://fireworks.ai/)**\n\n_Kimi, MiniMax, GLM, DeepSeek, GPT-OSS — via Fireworks AI's Anthropic Messages and OpenAI-compatible endpoints for [pi](https://github.com/earendil-works/pi-coding-agent)._\n\n[![pi extension](https://img.shields.io/badge/pi-extension-blueviolet)](https://github.com/earendil-works/pi-coding-agent)\n[![license](https://img.shields.io/badge/license-MIT-blue)](./LICENSE)\n\n</div>\n\n## Pi 1.0 compatibility\n\nTested with Pi **1.0.0**. Host-provided packages remain wildcard peers; development uses exact SDK pins.\nRun `bun run test:pi` for offline manifest, catalog, lifecycle and streaming checks. To test an installed host, set `PI1_HOST_PACKAGE` to its package directory; add `PI1_HOST_ENTRY=bundle` for its bundled CLI runtime. The probe stubs all network requests and never uses a live provider endpoint.\n\n---\n\n## Features\n\n- **53+ AI Models** including Kimi K2.5, MiniMax M2.5, GLM 4.5/4.7/5, DeepSeek V3.1/V3.2, DeepSeek V4 Flash, and GPT-OSS\n- **Dual API support** via Fireworks AI's Anthropic Messages and OpenAI-compatible completions endpoints (per-model routing, matching pi core's Fireworks provider)\n- **Service tiers** — toggle Fireworks `priority` vs `standard` per request on supported models (with priority pricing reflected in cost tracking), via a keybinding, `/fireworks-tier`, and a footer status area\n- **Preserved thinking** — toggle Fireworks' `reasoning_history: \"preserved\"` so prior assistant reasoning is retained across turns (better multi-turn recall; uses more tokens), via the `/fireworks-settings` panel, with a model-select notification. Applied only on models whose documented support includes `\"preserved\"` (Kimi K2.6/K2.7, GLM 5.2/4.7, …); interleaved-only models like DeepSeek V4 and MiniMax M2 keep their default. Matches neuralwatt/makora's settings-only UX, adapted to Fireworks' global `reasoning_history` knob\n- **Logit bias** — set an OpenAI-style `logit_bias` map (token ID → -100..100) via a nested `/fireworks-settings` panel (add / edit / delete arbitrary token IDs), sent on every Fireworks OpenAI-completions request; persisted to `~/.pi/agent/extensions/fireworks.json`\n- **Settings panel** — `/fireworks-settings` (TUI) to configure preserved thinking, logit bias, service tier, and display preferences; persisted to `~/.pi/agent/extensions/fireworks.json`\n- **Cost Tracking** with per-model pricing for budget management\n- **Reasoning Models** support for advanced reasoning capabilities\n- **Vision Support** for image-capable models\n\n## Installation\n\n### Option 1: Using `pi install` (Recommended)\n\nInstall directly from GitHub:\n\n```bash\npi install https://github.com/monotykamary/pi-fireworks-provider\n```\n\nThen set your API key and run pi:\n```bash\n# Recommended: add to auth.json\n# See Authentication section below\n\n# Or set as environment variable\nexport FIREWORKS_API_KEY=your-api-key-here\n\npi\n```\n\n### Option 2: Manual Clone\n\n1. Clone this repository:\n   ```bash\n   git clone https://github.com/monotykamary/pi-fireworks-provider.git\n   cd pi-fireworks-provider\n   ```\n\n2. Set your Fireworks API key:\n   ```bash\n   # Recommended: add to auth.json\n   # See Authentication section below\n\n   # Or set as environment variable\n   export FIREWORKS_API_KEY=your-api-key-here\n   ```\n\n3. Run pi with the extension:\n   ```bash\n   pi -e /path/to/pi-fireworks-provider\n   ```\n\n## Available Models\n\n| Model | Type | Context | Max Tokens | Input Cost | Output Cost |\n|-------|------|---------|------------|------------|-------------|\n| DeepSeek V3.1 | Text | 164K | 164K | $0.56 | $1.68 |\n| DeepSeek V3.2 | Text | 164K | 160K | $0.56 | $1.68 |\n| DeepSeek V4 Flash | Text | 1.0M | 384K | $0.14 | $0.28 |\n| DeepSeek V4 Flash 0731 | Text | 1.0M | 384K | $0.22 | $0.66 |\n| DeepSeek V4 Flash Vision Exp | Text + Image | 1.0M | 384K | $0.22 | $0.66 |\n| DeepSeek V4 Pro | Text | 1.0M | 384K | $1.74 | $3.48 |\n| DeepSeek V4 Pro (router) | Text | 1.0M | 384K | $1.74 | $3.48 |\n| DeepSeek V4 Pro 0813 | Text | 1.0M | 384K | $1.32 | $3.96 |\n| DeepSeek V4.1 Flash | Text + Image | 1.0M | 384K | $0.22 | $0.66 |\n| Ember-1 | Text + Image | 1.0M | 0 | — | — |\n| Gemma 4 26B A4B IT | Text + Image | 262K | 33K | — | — |\n| Gemma 4 31B IT | Text + Image | 262K | 33K | — | — |\n| GLM 4.5 | Text | 131K | 131K | $0.55 | $2.19 |\n| GLM 4.5 Air | Text | 131K | 131K | $0.22 | $0.88 |\n| GLM 4.7 | Text | 203K | 198K | $0.60 | $2.20 |\n| GLM 5 | Text | 203K | 131K | $1.00 | $3.20 |\n| GLM 5 Fast | Text | 203K | 131K | $1.00 | $3.20 |\n| GLM 5.1 | Text | 203K | 131K | $1.40 | $4.40 |\n| GLM 5.1 Fast | Text | 203K | 131K | $2.80 | $8.80 |\n| GLM 5.2 | Text | 1.0M | 131K | $1.40 | $4.40 |\n| GLM 5.2 Fast | Text | 1.0M | 131K | $2.10 | $6.60 |\n| GLM 5.3 | Text | 1.0M | 131K | $1.40 | $4.40 |\n| GLM 5.3 Flash | Text + Image | 1.0M | 131K | $0.15 | $0.50 |\n| GPT OSS 120B | Text | 131K | 33K | $0.15 | $0.60 |\n| GPT OSS 20B | Text | 131K | 33K | $0.07 | $0.30 |\n| Inkling | Text + Image | 1.0M | 262K | $1.00 | $4.05 |\n| Kimi K2 Instruct | Text | 131K | 16K | $1.00 | $3.00 |\n| Kimi K2 Thinking | Text | 262K | 256K | $0.60 | $2.50 |\n| Kimi K2.5 | Text + Image | 262K | 256K | $0.60 | $3.00 |\n| Kimi K2.5 Fast (router) | Text + Image | 262K | 256K | $0.60 | $3.00 |\n| Kimi K2.6 | Text + Image | 262K | 262K | $0.95 | $4.00 |\n| Kimi K2.6 (router) | Text + Image | 262K | 262K | $0.95 | $4.00 |\n| Kimi K2.6 Fast | Text + Image | 262K | 262K | $2.00 | $8.00 |\n| Kimi K2.6 Turbo | Text + Image | 262K | 262K | $2.00 | $8.00 |\n| Kimi K2.7 Code | Text + Image | 262K | 262K | $0.95 | $4.00 |\n| Kimi K2.7 Code Fast | Text + Image | 262K | 262K | $1.90 | $8.00 |\n| Kimi K3 | Text + Image | 1.0M | 131K | $3.00 | $15.00 |\n| Kimi K3 Fast | Text + Image | 1.0M | 131K | $4.50 | $22.50 |\n| Llama 3.3 70B Instruct | Text | 131K | 4K | $0.90 | $0.90 |\n| MiniMax M2.7 (router) | Text | 204K | 131K | $0.30 | $1.20 |\n| MiniMax-M2.1 | Text | 197K | 200K | $0.30 | $1.20 |\n| MiniMax-M2.5 | Text | 197K | 197K | $0.30 | $1.20 |\n| MiniMax-M2.7 | Text | 197K | 197K | $0.30 | $1.20 |\n| MiniMax-M3 | Text + Image | 512K | 512K | $0.30 | $1.20 |\n| Muse Glimmer 30B | Text + Image | 131K | 131K | $0.35 | $1.50 |\n| Nemotron 3.5 Lightning 30B A3B | Text | 262K | 262K | $0.05 | $0.20 |\n| NVIDIA Nemotron 3 Ultra NVFP4 | Text | 262K | 66K | $0.60 | $2.40 |\n| Qwen 3.7 Plus | Text + Image | 262K | 66K | $0.40 | $1.60 |\n| Qwen3 8B | Text | 41K | 41K | $0.20 | $0.20 |\n| Qwen3 VL 30B A3B Instruct | Text + Image | 262K | 33K | $0.50 | $0.50 |\n| Qwen3 VL 30B A3B Thinking | Text + Image | 262K | 33K | $0.50 | $0.50 |\n| Qwen3.8 Max | Text | 262K | 131K | $2.00 | $6.00 |\n| Qwen3.8-2.4T-A95B | Text | 262K | 131K | — | — |\n*Costs are per million tokens. Prices subject to change - check [fireworks.ai](https://fireworks.ai) for current pricing.*\n\n## Service Tiers\n\nFireworks exposes a `service_tier` request field (`standard` | `priority`) on its chat-completions endpoint. The **priority** tier trades higher per-token pricing for higher throughput / lower latency. This is orthogonal to the `-fast`/`-turbo` router model IDs (which are separate models) — service tiers apply to the base models below.\n\n| Model | Priority Uncached Input | Priority Cached Input | Priority Output |\n| --- | --- | --- | --- |\n| GLM 5.2 | $1.75/M | $0.175/M | $5.5/M |\n| Kimi K2.7 Code | $1.43/M | $0.29/M | $6/M |\n| Minimax M3 | $0.45/M | $0.09/M | $1.8/M |\n| DeepSeek V4 Pro | $2.61/M | $0.218/M | $5.22/M |\n| Kimi K2.6 | $1.5/M | $0.22/M | $6/M |\n| MiniMax M2.7 | $0.45/M | $0.09/M | $1.8/M |\n| GLM 5.1 | $2.1/M | $0.39/M | $6.6/M |\n| GPT OSS 120B | $0.18/M | $0.018/M | $0.72/M |\n| DeepSeek V4 Flash | $0.21/M | $0.045/M | $0.42/M |\n\n*Priority pricing is roughly 1.2–1.5× the standard rate. `cacheWrite` is not tiered.*\n\n**Switching tiers:**\n\n- **Keybinding:** `ctrl+shift+l` (default) toggles `standard` ↔ `priority` for the active supported model. No-op with an info notice for unsupported models.\n- **Command:** `/fireworks-tier standard|priority|toggle`.\n- **Status area:** a dim `tier: standard` / `tier: ⚡priority` line is shown in the footer for supported models while a Fireworks model is active.\n\nThe selection is persisted per session (survives `/reload` and resume). When `priority` is active, `service_tier: \"priority\"` is injected into every request and finalized cost is recomputed against the priority rates above.\n\n**Configuration** — `~/.pi/agent/extensions/fireworks.json` (created with defaults on first load):\n\n```json\n{\n  \"serviceTier\": {\n    \"default\": \"standard\",\n    \"keybinding\": \"ctrl+shift+l\",\n    \"display\": \"statusbar\"\n  },\n  \"preserveThinking\": {\n    \"default\": false\n  },\n  \"logitBias\": {\n    \"enabled\": false,\n    \"biases\": {}\n  }\n}\n```\n\n- `serviceTier.default` — tier used until you toggle (`standard` | `priority`).\n- `serviceTier.keybinding` — any [pi key format](https://github.com/earendil-works/pi-coding-agent/blob/main/docs/keybindings.md) (e.g. `ctrl+shift+l`, `ctrl+shift+k`). Requires `/reload` after changing. On macOS browser terminals (localterm), avoid `alt`/`ctrl+alt` (Option produces special chars) and `ctrl+shift+t/w/n/c/v` (browser/localterm tab + copy/paste shortcuts).\n- `serviceTier.display` — `statusbar` (footer status area) or `off` (hide the tier indicator).\n- `preserveThinking.default` — whether `reasoning_history: \"preserved\"` is injected (`true` | `false`, default `false`). Also settable via `/fireworks-settings`.\n- `logitBias.enabled` — whether the `logit_bias` map is sent on OpenAI-completions requests (`true` | `false`, default `false`). Also settable via `/fireworks-settings`.\n- `logitBias.biases` — a map of token ID (string) → bias (integer -100..100), e.g. `{\"123\": 5, \"456\": -100}`. Editable via the nested `/fireworks-settings` → *Logit bias* panel. -100 effectively bans the token; other values shift its logit additively before sampling.\n\n> **Note:** The OpenAI completions endpoint accepts `service_tier` directly (per Fireworks' API). The Anthropic Messages endpoint passes the top-level field through as an extra. If a supported Anthropic-routed model rejects it, file an issue so we can gate injection by API.\n\n## Preserved Thinking\n\nFireworks exposes a top-level `reasoning_history` request parameter. The only accepted value is `\"preserved\"`; omitting it (the default) means prior assistant reasoning is **stripped** from the model's context each turn. Setting `reasoning_history: \"preserved\"` makes Fireworks render prior assistant reasoning into the model's context, improving multi-turn recall at the cost of extra tokens. See [the Fireworks reasoning guide](https://docs.fireworks.ai/guides/reasoning#preserved-thinking).\n\nThis works on **both** transports — the OpenAI completions endpoint (assistant `reasoning_content` field) and the Anthropic Messages endpoint (assistant `thinking` content blocks, for which Fireworks returns a `signature` so pi-ai replays them). pi-ai already replays the reasoning field/block on prior assistant turns; this extension's only job is injecting the top-level `reasoning_history: \"preserved\"` flag that makes Fireworks honor it.\n\nUnlike neuralwatt/makora (which use per-model vLLM `chat_template_kwargs` flags like `preserve_thinking`/`clear_thinking`), Fireworks' knob is a single global parameter that applies to every reasoning model, so we expose it as one on/off toggle rather than a per-model submenu.\n\n**Toggle it:**\n\n- **`/fireworks-settings`** (TUI) → *Preserved thinking* → `on` / `off`. Takes effect immediately and persists as the default for future sessions.\n- A dim **model-select notification** tells you the current state when you switch to a Fireworks reasoning model (`Preserved thinking ON for …` / `… OFF for …`).\n\nPreserved thinking is **off by default** to match pi core and Fireworks' default (stripped). There is intentionally no `/fireworks-preserve` command or keybinding — it's settings-panel-only, mirroring neuralwatt/makora.\n\n## Logit Bias\n\nFireworks' OpenAI-compatible completions endpoint accepts the standard OpenAI `logit_bias` parameter: a map of token ID → bias (integer -100..100), added to the token's logit before sampling. `-100` effectively bans the token; other values shift its likelihood up or down. See [the Fireworks chat-completions API reference](https://docs.fireworks.ai/api-reference/post-chatcompletions).\n\nThis extension forwards the map verbatim as the top-level `logit_bias` field on every Fireworks OpenAI-completions request when `logitBias.enabled` is `true` and the map is non-empty.\n\n**Important:** token IDs are **tokenizer-specific**. A token ID that biases one model correctly may be wrong for another (different vocabularies / tokenizers). You must compute token IDs against the exact tokenizer of the model you're calling — Fireworks uses each model's native tokenizer (Llama, Mistral, etc.). There's no per-tokenizer validation here; biasing a wrong ID silently does nothing (or worse, biases an unrelated token).\n\n**OpenAI-completions only.** `logit_bias` is injected only on the OpenAI-completions transport. Models routed via the Anthropic Messages transport (`api: \"anthropic-messages\"`, only set via a patch/custom model — the provider default is `openai-completions`) are skipped, since the Anthropic Messages API has no `logit_bias` equivalent.\n\n**Edit it:**\n\n- **`/fireworks-settings`** (TUI) → *Logit bias* → open the nested panel. A search `>` area at the top filters entries by token ID (type digits); `↑↓` move · `Enter` activate (toggle *Enabled* / edit a bias / start *Add token…*) · `d` delete the selected entry · `Esc` back. Add / edit use free-text entry (token ID = non-negative integer, bias = -100..100). Changes take effect immediately and persist.\n\nThe top-level *Logit bias* row shows a one-line summary (e.g. `3 entries · on`, `off`). Off by default; an empty map (or `enabled: false`) means nothing is sent.\n\n## Usage\n\nAfter loading the extension, use the `/model` command in pi to select your preferred model:\n\n```\n/model\n```\n\nThen select \"fireworks\" as the provider and choose from the available models.\n\n## Authentication\n\nThe Fireworks API key can be configured in multiple ways (resolved in this order):\n\n1. **`auth.json`** (recommended) — Add to `~/.pi/agent/auth.json`:\n   ```json\n   { \"fireworks\": { \"type\": \"api_key\", \"key\": \"your-api-key\" } }\n   ```\n   The `key` field supports literal values, env var names, and shell commands (prefix with `!`). See [pi's auth file docs](https://github.com/badlogic/pi-mono) for details.\n2. **Runtime override** — Use the `--api-key` CLI flag\n3. **Environment variable** — Set `FIREWORKS_API_KEY`\n\n## Environment Variables\n\n| Variable | Required | Description |\n|----------|----------|-------------|\n| `FIREWORKS_API_KEY` | No | Your Fireworks AI API key (fallback if not in auth.json) |\n\n## Configuration\n\nAdd to your pi configuration for automatic loading:\n\n```json\n{\n  \"extensions\": [\n    \"/path/to/pi-fireworks-provider\"\n  ]\n}\n```\n\n## Development\n\n```bash\npnpm install          # install dev tooling (vitest, knip, typescript)\npnpm test             # run the test suite (vitest)\npnpm run test:watch   # watch mode\npnpm run lint:dead    # dead-code / unused-export scan (knip)\npnpm run check        # typecheck (tsc) + tests + knip, all green or exit non-zero\n```\n\nTests live in `tests/` and stub the `@earendil-works/pi-coding-agent` / `@earendil-works/pi-tui` peer dependencies (see `tests/__mocks__/`) so they run without the real pi packages installed. A per-run temp dir is used for `~/.pi/agent` (via `PI_CODING_AGENT_DIR` in `tests/vitest.setup.ts`) so config/cache reads and writes never touch your real environment.\n\n## License\n\nMIT\n","readmeFilename":"README.md"}