feat(backend): add support for v0 by Vercel models and credentials (#10641)

## Summary
This PR adds support for v0 by Vercel's Model API to the AutoGPT
platform, enabling users to leverage v0's framework-aware AI models
optimized for React and Next.js code generation.

v0 provides OpenAI-compatible endpoints with models specifically trained
for frontend development, making them ideal for generating UI components
and web applications.

### Changes 🏗️

#### Backend Changes
- **Added v0 Provider**: Added `V0 = "v0"` to `ProviderName` enum in
`/backend/backend/integrations/providers.py`
- **Added v0 Models**: Added three v0 models to `LlmModel` enum in
`/backend/backend/blocks/llm.py`:
- `V0_1_5_MD = "v0-1.5-md"` - Everyday tasks and UI generation (128K
context, 64K output)
- `V0_1_5_LG = "v0-1.5-lg"` - Advanced reasoning (512K context, 64K
output)
  - `V0_1_0_MD = "v0-1.0-md"` - Legacy model (128K context, 64K output)
- **Implemented v0 Provider**: Added v0 support in `llm_call()` function
using OpenAI-compatible client with base URL `https://api.v0.dev/v1`
- **Added Credentials Support**: Created `v0_credentials` in
`/backend/backend/integrations/credentials_store.py` with UUID
`c4e6d1a0-3b5f-4789-a8e2-9b123456789f`
- **Cost Configuration**: Added model costs in
`/backend/backend/data/block_cost_config.py`:
  - v0-1.5-md: 1 credit
  - v0-1.5-lg: 2 credits
  - v0-1.0-md: 1 credit

#### Configuration Changes
- **Settings**: Added `v0_api_key` field to `Secrets` class in
`/backend/backend/util/settings.py`
- **Environment Variables**: Added `V0_API_KEY=` to
`/backend/.env.default`

### Features
- ✅ Full OpenAI-compatible API support
- ✅ Tool/function calling support
- ✅ JSON response format support
- ✅ Framework-aware completions optimized for React/Next.js
- ✅ Large context windows (up to 512K tokens)
- ✅ Integrated with platform credit system

### Checklist 📋

#### For code changes:
- [x] I have clearly listed my changes in the PR description
- [x] I have made a test plan
- [x] I have tested my changes according to the test plan:
  <!-- Put your test plan here: -->
- [x] Run existing block tests to ensure no regressions: `poetry run
pytest backend/blocks/test/test_block.py`
  - [x] Verify AITextGeneratorBlock works with v0 models
  - [x] Confirm all model metadata is correctly configured
  - [x] Validate cost configuration is properly set up
  - [x] Check that v0_credentials has a valid UUID4

#### For configuration changes:
- [x] `.env.example` is updated or already compatible with my changes
  - Added `V0_API_KEY=` to `/backend/.env.default`
- [x] `docker-compose.yml` is updated or already compatible with my
changes
  - No changes needed - uses existing environment variable patterns
- [x] I have included a list of my configuration changes in the PR
description (under **Changes**)

### Configuration Requirements
Users need to:
1. Obtain a v0 API key from [v0.app](https://v0.app) (requires Premium
or Team plan)
2. Add `V0_API_KEY=your-api-key` to their `.env` file

### API Documentation
- v0 API Docs: https://v0.app/docs/api
- Model API Docs: https://v0.app/docs/api/model

### Testing
All existing tests pass with the new v0 integration:
```bash
poetry run pytest backend/blocks/test/test_block.py::test_available_blocks -k "AITextGeneratorBlock" -xvs
# Result: PASSED
```

autogpt_platform/backend/.env.default

@@ -55,6 +55,7 @@ ANTHROPIC_API_KEY=
 GROQ_API_KEY=
 LLAMA_API_KEY=
 AIML_API_KEY=
+V0_API_KEY=
 OPEN_ROUTER_API_KEY=
 NVIDIA_API_KEY=
 

autogpt_platform/backend/backend/blocks/llm.py

@@ -37,6 +37,7 @@ LLMProviderName = Literal[
     ProviderName.OPENAI,
     ProviderName.OPEN_ROUTER,
     ProviderName.LLAMA_API,
+    ProviderName.V0,
 ]
 AICredentials = CredentialsMetaInput[LLMProviderName, Literal["api_key"]]
 
@@ -155,6 +156,10 @@ class LlmModel(str, Enum, metaclass=LlmModelMeta):
     LLAMA_API_LLAMA4_MAVERICK = "Llama-4-Maverick-17B-128E-Instruct-FP8"
     LLAMA_API_LLAMA3_3_8B = "Llama-3.3-8B-Instruct"
     LLAMA_API_LLAMA3_3_70B = "Llama-3.3-70B-Instruct"
+    # v0 by Vercel models
+    V0_1_5_MD = "v0-1.5-md"
+    V0_1_5_LG = "v0-1.5-lg"
+    V0_1_0_MD = "v0-1.0-md"
 
     @property
     def metadata(self) -> ModelMetadata:
@@ -280,6 +285,10 @@ MODEL_METADATA = {
     LlmModel.LLAMA_API_LLAMA4_MAVERICK: ModelMetadata("llama_api", 128000, 4028),
     LlmModel.LLAMA_API_LLAMA3_3_8B: ModelMetadata("llama_api", 128000, 4028),
     LlmModel.LLAMA_API_LLAMA3_3_70B: ModelMetadata("llama_api", 128000, 4028),
+    # v0 by Vercel models
+    LlmModel.V0_1_5_MD: ModelMetadata("v0", 128000, 64000),
+    LlmModel.V0_1_5_LG: ModelMetadata("v0", 512000, 64000),
+    LlmModel.V0_1_0_MD: ModelMetadata("v0", 128000, 64000),
 }
 
 for model in LlmModel:
@@ -700,6 +709,42 @@ async def llm_call(
             ),
             reasoning=None,
         )
+    elif provider == "v0":
+        tools_param = tools if tools else openai.NOT_GIVEN
+        client = openai.AsyncOpenAI(
+            base_url="https://api.v0.dev/v1",
+            api_key=credentials.api_key.get_secret_value(),
+        )
+
+        response_format = None
+        if json_format:
+            response_format = {"type": "json_object"}
+
+        parallel_tool_calls_param = get_parallel_tool_calls_param(
+            llm_model, parallel_tool_calls
+        )
+
+        response = await client.chat.completions.create(
+            model=llm_model.value,
+            messages=prompt,  # type: ignore
+            response_format=response_format,  # type: ignore
+            max_tokens=max_tokens,
+            tools=tools_param,  # type: ignore
+            parallel_tool_calls=parallel_tool_calls_param,
+        )
+
+        tool_calls = extract_openai_tool_calls(response)
+        reasoning = extract_openai_reasoning(response)
+
+        return LLMResponse(
+            raw_response=response.choices[0].message,
+            prompt=prompt,
+            response=response.choices[0].message.content or "",
+            tool_calls=tool_calls,
+            prompt_tokens=response.usage.prompt_tokens if response.usage else 0,
+            completion_tokens=response.usage.completion_tokens if response.usage else 0,
+            reasoning=reasoning,
+        )
     else:
         raise ValueError(f"Unsupported LLM provider: {provider}")
 

autogpt_platform/backend/backend/data/block_cost_config.py

@@ -46,6 +46,7 @@ from backend.integrations.credentials_store import (
     replicate_credentials,
     revid_credentials,
     unreal_credentials,
+    v0_credentials,
 )
 
 # =============== Configure the cost for each LLM Model call =============== #
@@ -122,6 +123,10 @@ MODEL_COST: dict[LlmModel, int] = {
     LlmModel.GEMINI_2_5_FLASH_LITE_PREVIEW: 1,
     LlmModel.GEMINI_2_0_FLASH_LITE: 1,
     LlmModel.DEEPSEEK_R1_0528: 1,
+    # v0 by Vercel models
+    LlmModel.V0_1_5_MD: 1,
+    LlmModel.V0_1_5_LG: 2,
+    LlmModel.V0_1_0_MD: 1,
 }
 
 for model in LlmModel:
@@ -211,6 +216,23 @@ LLM_COST = (
         for model, cost in MODEL_COST.items()
         if MODEL_METADATA[model].provider == "llama_api"
     ]
+    # v0 by Vercel Models
+    + [
+        BlockCost(
+            cost_type=BlockCostType.RUN,
+            cost_filter={
+                "model": model,
+                "credentials": {
+                    "id": v0_credentials.id,
+                    "provider": v0_credentials.provider,
+                    "type": v0_credentials.type,
+                },
+            },
+            cost_amount=cost,
+        )
+        for model, cost in MODEL_COST.items()
+        if MODEL_METADATA[model].provider == "v0"
+    ]
     # AI/ML Api Models
     + [
         BlockCost(

autogpt_platform/backend/backend/integrations/credentials_store.py

@@ -199,6 +199,14 @@ llama_api_credentials = APIKeyCredentials(
     expires_at=None,
 )
 
+v0_credentials = APIKeyCredentials(
+    id="c4e6d1a0-3b5f-4789-a8e2-9b123456789f",
+    provider="v0",
+    api_key=SecretStr(settings.secrets.v0_api_key),
+    title="Use Credits for v0 by Vercel",
+    expires_at=None,
+)
+
 DEFAULT_CREDENTIALS = [
     ollama_credentials,
     revid_credentials,
@@ -223,6 +231,8 @@ DEFAULT_CREDENTIALS = [
     smartlead_credentials,
     zerobounce_credentials,
     google_maps_credentials,
+    llama_api_credentials,
+    v0_credentials,
 ]
 
 

autogpt_platform/backend/backend/integrations/providers.py

@@ -48,6 +48,7 @@ class ProviderName(str, Enum):
     TWITTER = "twitter"
     TODOIST = "todoist"
     UNREAL_SPEECH = "unreal_speech"
+    V0 = "v0"
     ZEROBOUNCE = "zerobounce"
 
     @classmethod

autogpt_platform/backend/backend/util/settings.py

@@ -472,6 +472,7 @@ class Secrets(UpdateTrackingModel["Secrets"], BaseSettings):
     groq_api_key: str = Field(default="", description="Groq API key")
     open_router_api_key: str = Field(default="", description="Open Router API Key")
     llama_api_key: str = Field(default="", description="Llama API Key")
+    v0_api_key: str = Field(default="", description="v0 by Vercel API key")
 
     reddit_client_id: str = Field(default="", description="Reddit client ID")
     reddit_client_secret: str = Field(default="", description="Reddit client secret")