feat: Added SambaNova support

examples/.env.example

@@ -3,4 +3,5 @@
 TOOLHOUSE_API_KEY=
 OPENAI_API_KEY=
 ANTHROPIC_API_KEY=
-GROQCLOUD_API_KEY=
+GROQCLOUD_API_KEY=
+SAMBANOVA_API_KEY=

examples/sample_run_local_tools_sambanova.py

@@ -0,0 +1,67 @@
+"""Sambanova Sample"""
+import os
+from typing import List
+from dotenv import load_dotenv
+from openai import OpenAI
+from toolhouse import Toolhouse
+
+#  Make sure to set up the .env file according to the .env.example file.
+load_dotenv()
+
+TH_API_KEY = os.getenv("TOOLHOUSE_API_KEY")
+SAMBANOVA_API_KEY = os.getenv("SAMBANOVA_API_KEY")
+
+
+local_tools = [
+    {'type': 'function',
+     'function':
+         {
+             'name': 'hello',
+             'description': 'The user receives a customized hello message from a city and returns it to the user.',
+             'parameters': {
+                 'type': 'object',
+                 'properties': {
+                     'city': {'type': 'string', 'description': 'The city where you are from'}
+                 }},
+             'required': ['city']
+         }}]
+
+# Initialize Toolhouse with the OpenAI provider
+th = Toolhouse(api_key=TH_API_KEY, provider="openai")
+th.set_metadata("id", "fabio")
+th.set_metadata("timezone", 5)
+
+
+@th.register_local_tool("hello")
+def hello_tool(city: str):
+    """Return a Hello message from a specific city."""
+    return f"Hello from {city}!!!"
+
+
+client = OpenAI(
+    api_key=SAMBANOVA_API_KEY,
+    base_url="https://api.sambanova.ai/v1/",
+)
+
+messages: List = [{
+    "role": "user",
+    "content":
+        "Can I get a hello from Rome?"
+    }]
+
+response = client.chat.completions.create(
+    model='Meta-Llama-3.1-405B-Instruct',
+    messages=messages,
+    tools=th.get_tools() + local_tools # Retrieve tools installed from Toolhouse
+)
+
+# Run the tools using the Toolhouse client with the created message
+messages += th.run_tools(response)
+
+response = client.chat.completions.create(
+            model='Meta-Llama-3.1-405B-Instruct',
+            messages=messages,
+            tools=th.get_tools() + local_tools # Retrieve tools installed from Toolhouse
+        )
+
+print(response.choices[0].message.content)

examples/sample_run_local_tools_sambanova_stream.py

@@ -0,0 +1,65 @@
+"""SambaNova Sample"""
+
+import os
+from typing import List
+from dotenv import load_dotenv
+from openai import OpenAI
+from toolhouse import Toolhouse # Import the Toolhouse SDK
+from toolhouse.models.Stream import ToolhouseStreamStorage # Import the Toolhouse Stream Storage
+
+#  Make sure to set up the .env file according to the .env.example file.
+load_dotenv()
+
+TH_API_KEY = os.getenv("TOOLHOUSE_API_KEY")
+SAMBANOVA_API_KEY = os.getenv("SAMBANOVA_API_KEY")
+
+client = OpenAI(
+    api_key=SAMBANOVA_API_KEY,
+    base_url="https://api.sambanova.ai/v1/",
+)
+
+local_tools = [
+    {
+        "type": "function",
+        "function": {
+            "name": "hello",
+            "description": "The user receives a customized hello message from a city and returns it to the user.",
+            "parameters": {
+                "type": "object",
+                "properties": {"city": {"type": "string", "description": "The city where you are from"}},
+            },
+            "required": ["city"],
+        },
+    }
+]
+
+# Initialize Toolhouse with the OpenAI provider
+th = Toolhouse(api_key=TH_API_KEY, provider="openai")
+th.set_metadata("id", "fabio")
+th.set_metadata("timezone", 5)
+
+
+@th.register_local_tool("hello")
+def hello_tool(city: str):
+    """Return a Hello message from a specific city."""
+    return f"Hello from {city}!!!"
+
+
+messages: List = [{"role": "user", "content": "Can I get a hello from Rome?"}]
+
+
+stream = client.chat.completions.create(
+    model="Meta-Llama-3.3-70B-Instruct", messages=messages, tools=th.get_tools() + local_tools, stream=True # Retrieve tools installed from Toolhouse
+)
+
+# Use the stream and save blocks
+stream_storage = ToolhouseStreamStorage()
+for block in stream:  # pylint: disable=E1133
+    print(block)
+    stream_storage.add(block)
+
+# Run the tools using the Toolhouse client with the created message
+messages += th.run_tools(stream_storage)
+
+response = client.chat.completions.create(model="Meta-Llama-3.3-70B-Instruct", messages=messages, tools=th.get_tools() + local_tools) # Retrieve tools installed from Toolhouse
+print(response.choices[0].message.content)

examples/sample_sambanova_openai_client.py

@@ -0,0 +1,44 @@
+"""SambaNova on OpenAI Client Sample"""
+import os
+from typing import List
+from dotenv import load_dotenv
+from openai import OpenAI
+from toolhouse import Toolhouse # Import the Toolhouse SDK
+
+#  Make sure to set up the .env file according to the .env.example file.
+load_dotenv()
+
+TH_API_KEY = os.getenv("TOOLHOUSE_API_KEY")
+SAMBANOVA_API_KEY = os.getenv("SAMBANOVA_API_KEY")
+
+client = OpenAI(
+    api_key=SAMBANOVA_API_KEY,
+    base_url="https://api.sambanova.ai/v1/"
+)
+
+# Initialize Toolhouse with the OpenAI provider
+th = Toolhouse(api_key=TH_API_KEY, provider="openai")
+
+messages: List = [{
+    "role": "user",
+    "content":
+        "Scrape data from https://docs.sambanova.ai/cloud/docs/get-started/overview and tell me what SambaNova Cloud is."
+}]
+
+response = client.chat.completions.create(
+    model='Meta-Llama-3.3-70B-Instruct',
+    messages=messages,
+    # Retrieve tools installed from Toolhouse
+    tools=th.get_tools()
+)
+
+# Run the tools using the Toolhouse client with the created message
+messages += th.run_tools(response)
+
+response = client.chat.completions.create(
+            model="Meta-Llama-3.3-70B-Instruct",
+            messages=messages,
+            # Retrieve tools installed from Toolhouse
+            tools=th.get_tools()
+        )
+print(response.choices[0].message.content)

examples/sample_sambanova_openai_client_stream.py

@@ -0,0 +1,52 @@
+"""SambaNova on OpenAI Sample"""
+import os
+from typing import List
+from dotenv import load_dotenv
+from openai import OpenAI
+from toolhouse import Toolhouse # Import the Toolhouse SDK
+from toolhouse.models.Stream import ToolhouseStreamStorage
+
+#  Make sure to set up the .env file according to the .env.example file.
+load_dotenv()
+
+TH_API_KEY = os.getenv("TOOLHOUSE_API_KEY")
+SAMBANOVA_API_KEY = os.getenv("SAMBANOVA_API_KEY")
+
+client = OpenAI(
+    api_key=SAMBANOVA_API_KEY,
+    base_url="https://api.sambanova.ai/v1/",
+)
+
+# Initialize Toolhouse with the OpenAI provider
+th = Toolhouse(api_key=TH_API_KEY, provider="openai")
+
+messages: List = [{
+    "role": "user",
+    "content":
+        "Generate code to calculate the Fibonacci sequence to 100." "Execute it and give me the result"
+}]
+
+stream = client.chat.completions.create(
+    model='Meta-Llama-3.1-405B-Instruct',
+    messages=messages,
+    # Retrieve tools installed from Toolhouse
+    tools=th.get_tools(),
+    stream=True
+)
+
+# Use the stream and save blocks
+stream_storage = ToolhouseStreamStorage()
+for block in stream:  # pylint: disable=E1133
+    print(block)
+    stream_storage.add(block)
+
+# Run the tools using the Toolhouse client with the created message
+messages += th.run_tools(stream_storage)
+
+response = client.chat.completions.create(
+            model="Meta-Llama-3.1-405B-Instruct",
+            messages=messages,
+            # Retrieve tools installed from Toolhouse
+            tools=th.get_tools()
+        )
+print(response.choices[0].message.content)