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feat: add GLM-4.5 and OpenAI gpt-oss models to Fireworks provider #6784

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Merged
merged 2 commits into from
Aug 7, 2025
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feat: add GLM-4.5 and OpenAI gpt-oss models to Fireworks provider #6784

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7798016
feat: add GLM-4.5 and OpenAI gpt-oss models to Fireworks provider
roomote Aug 7, 2025
0b3acf0
fix: update GLM-4.5 model IDs to use p instead of hyphen
roomote Aug 7, 2025
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44 changes: 44 additions & 0 deletions 44 packages/types/src/providers/fireworks.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -6,6 +6,10 @@ export type FireworksModelId =
| "accounts/fireworks/models/qwen3-coder-480b-a35b-instruct"
| "accounts/fireworks/models/deepseek-r1-0528"
| "accounts/fireworks/models/deepseek-v3"
| "accounts/fireworks/models/glm-4p5"
| "accounts/fireworks/models/glm-4p5-air"
| "accounts/fireworks/models/gpt-oss-20b"
| "accounts/fireworks/models/gpt-oss-120b"

export const fireworksDefaultModelId: FireworksModelId = "accounts/fireworks/models/kimi-k2-instruct"

Expand Down Expand Up @@ -58,4 +62,44 @@ export const fireworksModels = {
description:
"A strong Mixture-of-Experts (MoE) language model with 671B total parameters with 37B activated for each token from Deepseek. Note that fine-tuning for this model is only available through contacting fireworks at https://fireworks.ai/company/contact-us.",
},
"accounts/fireworks/models/glm-4p5": {
maxTokens: 16384,
contextWindow: 128000,
supportsImages: false,
supportsPromptCache: false,
inputPrice: 0.55,
outputPrice: 2.19,
description:
"Z.ai GLM-4.5 with 355B total parameters and 32B active parameters. Features unified reasoning, coding, and intelligent agent capabilities.",
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The descriptions are good, but could we add more technical details? For example, mentioning that GLM models use MoE architecture or specific optimization techniques would help users choose the right model.

},
"accounts/fireworks/models/glm-4p5-air": {
maxTokens: 16384,
contextWindow: 128000,
supportsImages: false,
supportsPromptCache: false,
inputPrice: 0.55,
outputPrice: 2.19,
description:
"Z.ai GLM-4.5-Air with 106B total parameters and 12B active parameters. Features unified reasoning, coding, and intelligent agent capabilities.",
},
"accounts/fireworks/models/gpt-oss-20b": {
maxTokens: 16384,
contextWindow: 128000,
supportsImages: false,
supportsPromptCache: false,
inputPrice: 0.07,
outputPrice: 0.3,
description:
"OpenAI gpt-oss-20b: Compact model for local/edge deployments. Optimized for low-latency and resource-constrained environments with chain-of-thought output, adjustable reasoning, and agentic workflows.",
},
"accounts/fireworks/models/gpt-oss-120b": {
maxTokens: 16384,
contextWindow: 128000,
supportsImages: false,
supportsPromptCache: false,
inputPrice: 0.15,
outputPrice: 0.6,
description:
"OpenAI gpt-oss-120b: Production-grade, general-purpose model that fits on a single H100 GPU. Features complex reasoning, configurable effort, full chain-of-thought transparency, and supports function calling, tool use, and structured outputs.",
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The description mentions function calling and tool use support. Should we consider adding a boolean to the model info for clarity, similar to how we have ?

},
} as const satisfies Record<string, ModelInfo>
84 changes: 84 additions & 0 deletions 84 src/api/providers/__tests__/fireworks.spec.ts
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Expand Up @@ -179,6 +179,90 @@ describe("FireworksHandler", () => {
)
})

it("should return GLM-4.5 model with correct configuration", () => {
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While the configuration tests are thorough, could we add tests that verify these models actually work with the API? Even mock tests simulating API responses would increase confidence that the integration works correctly.

const testModelId: FireworksModelId = "accounts/fireworks/models/glm-4p5"
const handlerWithModel = new FireworksHandler({
apiModelId: testModelId,
fireworksApiKey: "test-fireworks-api-key",
})
const model = handlerWithModel.getModel()
expect(model.id).toBe(testModelId)
expect(model.info).toEqual(
expect.objectContaining({
maxTokens: 16384,
contextWindow: 128000,
supportsImages: false,
supportsPromptCache: false,
inputPrice: 0.55,
outputPrice: 2.19,
description: expect.stringContaining("Z.ai GLM-4.5 with 355B total parameters"),
}),
)
})

it("should return GLM-4.5-Air model with correct configuration", () => {
const testModelId: FireworksModelId = "accounts/fireworks/models/glm-4p5-air"
const handlerWithModel = new FireworksHandler({
apiModelId: testModelId,
fireworksApiKey: "test-fireworks-api-key",
})
const model = handlerWithModel.getModel()
expect(model.id).toBe(testModelId)
expect(model.info).toEqual(
expect.objectContaining({
maxTokens: 16384,
contextWindow: 128000,
supportsImages: false,
supportsPromptCache: false,
inputPrice: 0.55,
outputPrice: 2.19,
description: expect.stringContaining("Z.ai GLM-4.5-Air with 106B total parameters"),
}),
)
})

it("should return gpt-oss-20b model with correct configuration", () => {
const testModelId: FireworksModelId = "accounts/fireworks/models/gpt-oss-20b"
const handlerWithModel = new FireworksHandler({
apiModelId: testModelId,
fireworksApiKey: "test-fireworks-api-key",
})
const model = handlerWithModel.getModel()
expect(model.id).toBe(testModelId)
expect(model.info).toEqual(
expect.objectContaining({
maxTokens: 16384,
contextWindow: 128000,
supportsImages: false,
supportsPromptCache: false,
inputPrice: 0.07,
outputPrice: 0.3,
description: expect.stringContaining("OpenAI gpt-oss-20b: Compact model for local/edge deployments"),
}),
)
})

it("should return gpt-oss-120b model with correct configuration", () => {
const testModelId: FireworksModelId = "accounts/fireworks/models/gpt-oss-120b"
const handlerWithModel = new FireworksHandler({
apiModelId: testModelId,
fireworksApiKey: "test-fireworks-api-key",
})
const model = handlerWithModel.getModel()
expect(model.id).toBe(testModelId)
expect(model.info).toEqual(
expect.objectContaining({
maxTokens: 16384,
contextWindow: 128000,
supportsImages: false,
supportsPromptCache: false,
inputPrice: 0.15,
outputPrice: 0.6,
description: expect.stringContaining("OpenAI gpt-oss-120b: Production-grade, general-purpose model"),
}),
)
})

it("completePrompt method should return text from Fireworks API", async () => {
const expectedResponse = "This is a test response from Fireworks"
mockCreate.mockResolvedValueOnce({ choices: [{ message: { content: expectedResponse } }] })
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