v31.7.0 (#138)

Author: truemagic-coder

README.md

@@ -88,6 +88,7 @@ Smart workflows are as easy as combining your tools and prompts.
 * [OpenAI](https://openai.com) - AI Model Provider
 * [Grok](https://x.ai) - Alternative AI Model Provider (optional)
 * [Groq](https://groq.com) - Alternative AI Model Provider (optional)
+* [Cerebras](https://cerebras.ai) - Alternative AI Model Provider (optional)
 * [MongoDB](https://mongodb.com) - Conversational History (optional)
 * [Zep Cloud](https://getzep.com) - Conversational Memory (optional)
 * [Pinecone](https://pinecone.io) - Knowledge Base (optional)
@@ -607,6 +608,40 @@ config = {
 - ✅ Structured outputs (via Instructor TOOLS_STRICT and JSON modes)
 - ✅ Native JSON mode
 
+### Cerebras
+
+Solana Agent supports using Cerebras as an alternative to OpenAI. When Cerebras is configured, it will be used for all LLM operations except embeddings, TTS, and STT (which still require OpenAI).
+
+**Note:** Grok takes priority over Groq, Groq takes priority over Cerebras, and Cerebras takes priority over OpenAI. If multiple are present, the highest priority provider will be used.
+
+```python
+config = {
+    "cerebras": {
+        "api_key": "your-cerebras-api-key",
+        "base_url": "https://api.cerebras.ai/v1",  # Optional, defaults to https://api.cerebras.ai/v1
+        "model": "gpt-oss-120b"  # Optional, defaults to gpt-oss-120b
+    },
+    # You can still include OpenAI for embeddings, TTS, and STT
+    "openai": {
+        "api_key": "your-openai-api-key"
+    },
+    "agents": [
+        {
+            "name": "research_specialist",
+            "instructions": "You are an expert researcher.",
+            "specialization": "Research",
+        }
+    ],
+}
+```
+
+**Verified Capabilities:**
+- ✅ Chat completions
+- ✅ Streaming responses
+- ✅ Function calling/Tool usage
+- ✅ Structured outputs (via Instructor TOOLS_STRICT and JSON modes)
+- ✅ Native JSON mode
+
 ### Business Alignment
 
 ```python

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "solana-agent"
-version = "31.6.0"
+version = "31.7.0"
 description = "AI Agents for Solana"
 authors = ["Bevan Hunt <[email protected]>"]
 license = "MIT"

solana_agent/adapters/openai_adapter.py

@@ -65,7 +65,7 @@ def __init__(
         self.api_key = api_key
         self.base_url = base_url
 
-        # Create client with base_url if provided (for Grok/Groq support)
+        # Create client with base_url if provided (for Grok/Groq/Cerebras support)
         if base_url:
             self.client = AsyncOpenAI(api_key=api_key, base_url=base_url)
         else:
@@ -85,9 +85,9 @@ def __init__(
                 logger.error(f"Failed to configure Logfire: {e}")
                 self.logfire = False
 
-        # Use provided model or defaults (for Grok/Groq or OpenAI)
+        # Use provided model or defaults (for Grok/Groq/Cerebras or OpenAI)
         if model:
-            # Custom model provided (e.g., from Grok or Groq config)
+            # Custom model provided (e.g., from Grok, Groq, or Cerebras config)
             self.parse_model = model
             self.text_model = model
             self.vision_model = model

solana_agent/factories/agent_factory.py

@@ -104,8 +104,8 @@ def create_from_config(config: Dict[str, Any]) -> QueryService:  # pragma: no co
         else:
             db_adapter = None
 
-        # Determine which LLM provider to use (Grok, Groq, or OpenAI)
-        # Priority: grok > groq > openai
+        # Determine which LLM provider to use (Grok, Groq, Cerebras, or OpenAI)
+        # Priority: grok > groq > cerebras > openai
         llm_api_key = None
         llm_base_url = None
         llm_model = None
@@ -122,6 +122,13 @@ def create_from_config(config: Dict[str, Any]) -> QueryService:  # pragma: no co
             )
             llm_model = config["groq"].get("model", "openai/gpt-oss-120b")
             logger.info(f"Using Groq as LLM provider with model: {llm_model}")
+        elif "cerebras" in config and "api_key" in config["cerebras"]:
+            llm_api_key = config["cerebras"]["api_key"]
+            llm_base_url = config["cerebras"].get(
+                "base_url", "https://api.cerebras.ai/v1"
+            )
+            llm_model = config["cerebras"].get("model", "gpt-oss-120b")
+            logger.info(f"Using Cerebras as LLM provider with model: {llm_model}")
         elif "openai" in config and "api_key" in config["openai"]:
             llm_api_key = config["openai"]["api_key"]
             llm_base_url = None  # Use default OpenAI endpoint
@@ -132,7 +139,7 @@ def create_from_config(config: Dict[str, Any]) -> QueryService:  # pragma: no co
                 logger.info("Using OpenAI as LLM provider")
         else:
             raise ValueError(
-                "Either OpenAI, Grok, or Groq API key is required in config."
+                "Either OpenAI, Grok, Groq, or Cerebras API key is required in config."
             )
 
         if "logfire" in config:
@@ -210,10 +217,10 @@ def create_from_config(config: Dict[str, Any]) -> QueryService:  # pragma: no co
         )
 
         # Create routing service
-        # Use Grok/Groq model if configured, otherwise check for OpenAI routing_model override
+        # Use Grok/Groq/Cerebras model if configured, otherwise check for OpenAI routing_model override
         routing_model = llm_model  # Use the same model as the main LLM by default
         if not routing_model:
-            # Fall back to OpenAI routing_model config if no Grok/Groq model
+            # Fall back to OpenAI routing_model config if no Grok/Groq/Cerebras model
             routing_model = (
                 config.get("openai", {}).get("routing_model")
                 if isinstance(config.get("openai"), dict)

solana_agent/services/routing.py

@@ -39,7 +39,7 @@ def __init__(
         if model:
             self.model = model
         elif base_url:
-            # Using custom provider (e.g., Grok or Groq) but no model specified - use provider's default
+            # Using custom provider (e.g., Grok, Groq, or Cerebras) but no model specified - use provider's default
             self.model = None  # Will use adapter's default
         else:
             # Using OpenAI - default to small, cheap model for routing

tests/unit/factories/test_agent_factory.py

@@ -250,6 +250,33 @@ def groq_with_logfire_config(groq_config):
     return config
 
 
+@pytest.fixture
+def cerebras_config():
+    """Config with Cerebras as the LLM provider."""
+    return {
+        "cerebras": {
+            "api_key": "test-cerebras-key",
+            "base_url": "https://api.cerebras.ai/v1",
+            "model": "gpt-oss-120b",
+        },
+        "agents": [
+            {
+                "name": "test_agent",
+                "instructions": "You are a test agent.",
+                "specialization": "Testing",
+            }
+        ],
+    }
+
+
+@pytest.fixture
+def cerebras_with_logfire_config(cerebras_config):
+    """Config with Cerebras and Logfire enabled."""
+    config = deepcopy(cerebras_config)
+    config["logfire"] = {"api_key": "test-logfire-key"}
+    return config
+
+
 @pytest.fixture
 def openai_with_model_config():
     """Config with OpenAI and a custom model specified."""
@@ -339,10 +366,10 @@ def test_create_from_config_minimal(
 
     def test_missing_openai_section(self, config_missing_openai_section):
         """Test factory creation when the entire openai section is missing."""
-        # This should raise ValueError since OpenAI, Grok, or Groq API key is required
+        # This should raise ValueError since OpenAI, Grok, Groq, or Cerebras API key is required
         with pytest.raises(
             ValueError,
-            match="Either OpenAI, Grok, or Groq API key is required in config.",
+            match="Either OpenAI, Grok, Groq, or Cerebras API key is required in config.",
         ):
             SolanaAgentFactory.create_from_config(config_missing_openai_section)
 
@@ -1665,7 +1692,7 @@ def test_logfire_config_missing_openai_key(self, logfire_config_missing_openai):
         # Based on the current factory code, this should raise a ValueError
         with pytest.raises(
             ValueError,
-            match="Either OpenAI, Grok, or Groq API key is required in config.",
+            match="Either OpenAI, Grok, Groq, or Cerebras API key is required in config.",
         ):
             SolanaAgentFactory.create_from_config(logfire_config_missing_openai)
 
@@ -1874,6 +1901,89 @@ def test_create_groq_without_logfire(
         mock_query_service.assert_called_once()
         assert result == mock_query_instance
 
+    @patch("solana_agent.factories.agent_factory.MongoDBAdapter")
+    @patch("solana_agent.factories.agent_factory.OpenAIAdapter")
+    @patch("solana_agent.factories.agent_factory.AgentService")
+    @patch("solana_agent.factories.agent_factory.RoutingService")
+    @patch("solana_agent.factories.agent_factory.QueryService")
+    def test_create_cerebras_with_logfire(
+        self,
+        mock_query_service,
+        mock_routing_service,
+        mock_agent_service,
+        mock_openai_adapter,
+        mock_mongo_adapter,
+        cerebras_with_logfire_config,
+    ):
+        """Test creating services with Cerebras and Logfire configuration."""
+        # Setup mocks
+        mock_openai_instance = MagicMock()
+        mock_openai_adapter.return_value = mock_openai_instance
+        mock_agent_instance = MagicMock()
+        mock_agent_service.return_value = mock_agent_instance
+        mock_agent_instance.tool_registry.list_all_tools.return_value = []
+        mock_routing_instance = MagicMock()
+        mock_routing_service.return_value = mock_routing_instance
+        mock_query_instance = MagicMock()
+        mock_query_service.return_value = mock_query_instance
+
+        # Call the factory
+        result = SolanaAgentFactory.create_from_config(cerebras_with_logfire_config)
+
+        # Verify OpenAIAdapter was called with Cerebras config and logfire key
+        mock_openai_adapter.assert_called_once_with(
+            api_key="test-cerebras-key",
+            base_url="https://api.cerebras.ai/v1",
+            model="gpt-oss-120b",
+            logfire_api_key="test-logfire-key",
+        )
+        # Verify other services were called
+        mock_agent_service.assert_called_once()
+        mock_routing_service.assert_called_once()
+        mock_query_service.assert_called_once()
+        assert result == mock_query_instance
+
+    @patch("solana_agent.factories.agent_factory.MongoDBAdapter")
+    @patch("solana_agent.factories.agent_factory.OpenAIAdapter")
+    @patch("solana_agent.factories.agent_factory.AgentService")
+    @patch("solana_agent.factories.agent_factory.RoutingService")
+    @patch("solana_agent.factories.agent_factory.QueryService")
+    def test_create_cerebras_without_logfire(
+        self,
+        mock_query_service,
+        mock_routing_service,
+        mock_agent_service,
+        mock_openai_adapter,
+        mock_mongo_adapter,
+        cerebras_config,
+    ):
+        """Test creating services with Cerebras but no Logfire configuration."""
+        # Setup mocks
+        mock_openai_instance = MagicMock()
+        mock_openai_adapter.return_value = mock_openai_instance
+        mock_agent_instance = MagicMock()
+        mock_agent_service.return_value = mock_agent_instance
+        mock_agent_instance.tool_registry.list_all_tools.return_value = []
+        mock_routing_instance = MagicMock()
+        mock_routing_service.return_value = mock_routing_instance
+        mock_query_instance = MagicMock()
+        mock_query_service.return_value = mock_query_instance
+
+        # Call the factory
+        result = SolanaAgentFactory.create_from_config(cerebras_config)
+
+        # Verify OpenAIAdapter was called with Cerebras config but no logfire key
+        mock_openai_adapter.assert_called_once_with(
+            api_key="test-cerebras-key",
+            base_url="https://api.cerebras.ai/v1",
+            model="gpt-oss-120b",
+        )
+        # Verify other services were called
+        mock_agent_service.assert_called_once()
+        mock_routing_service.assert_called_once()
+        mock_query_service.assert_called_once()
+        assert result == mock_query_instance
+
     @patch("solana_agent.factories.agent_factory.MongoDBAdapter")
     @patch("solana_agent.factories.agent_factory.OpenAIAdapter")
     @patch("solana_agent.factories.agent_factory.AgentService")