[goose-llm] add providerConfig param for exposed LLM functions (#2491)

bindings/python/usage.py

@@ -0,0 +1,133 @@
+import asyncio
+import os
+import time
+from goose_llm import (
+    Message, MessageContent, TextContent, ToolRequest, ToolResponse,
+    Role, ModelConfig, ToolApprovalMode,
+    create_tool_config, ExtensionConfig,
+    generate_session_name, generate_tooltip,
+    create_completion_request, completion
+)
+
+async def main():
+    now = int(time.time())
+
+    # 1) User sends a plain-text prompt
+    messages = [
+        Message(
+            role=Role.USER,
+            created=now,
+            content=[MessageContent.TEXT(TextContent(text="What is 7 x 6?"))]
+        ),
+
+        # 2) Assistant makes a tool request
+        Message(
+            role=Role.ASSISTANT,
+            created=now + 2,
+            content=[MessageContent.TOOL_REQ(ToolRequest(
+                id="calc1",
+                tool_call="""
+                    {
+                      "status": "success",
+                      "value": {
+                        "name": "calculator_extension__toolname",
+                        "arguments": {
+                          "operation": "multiply",
+                          "numbers": [7, 6]
+                        },
+                        "needsApproval": false
+                      }
+                    }
+                """
+            ))]
+        ),
+
+        # 3) User sends tool result
+        Message(
+            role=Role.USER,
+            created=now + 3,
+            content=[MessageContent.TOOL_RESP(ToolResponse(
+                id="calc1",
+                tool_result="""
+                    {
+                      "status": "success",
+                      "value": [
+                        {"type": "text", "text": "42"}
+                      ]
+                    }
+                """
+            ))]
+        )
+    ]
+
+    provider_name = "databricks"
+    provider_config = f'''{{
+        "host": "{os.environ.get("DATABRICKS_HOST")}",
+        "token": "{os.environ.get("DATABRICKS_TOKEN")}"
+    }}'''
+
+    print(f"Provider Name: {provider_name}")
+    print(f"Provider Config: {provider_config}")
+
+    session_name = await generate_session_name(provider_name, provider_config, messages)
+    print(f"\nSession Name: {session_name}")
+
+    tooltip = await generate_tooltip(provider_name, provider_config, messages)
+    print(f"\nTooltip: {tooltip}")
+
+    model_config = ModelConfig(
+        model_name="goose-gpt-4-1",
+        max_tokens=500,
+        temperature=0.1,
+        context_limit=4096,
+    )
+
+    calculator_tool = create_tool_config(
+        name="calculator",
+        description="Perform basic arithmetic operations",
+        input_schema="""
+            {
+                "type": "object",
+                "required": ["operation", "numbers"],
+                "properties": {
+                    "operation": {
+                        "type": "string",
+                        "enum": ["add", "subtract", "multiply", "divide"],
+                        "description": "The arithmetic operation to perform"
+                    },
+                    "numbers": {
+                        "type": "array",
+                        "items": { "type": "number" },
+                        "description": "List of numbers to operate on in order"
+                    }
+                }
+            }
+        """,
+        approval_mode=ToolApprovalMode.AUTO
+    )
+
+    calculator_extension = ExtensionConfig(
+        name="calculator_extension",
+        instructions="This extension provides a calculator tool.",
+        tools=[calculator_tool]
+    )
+
+    system_preamble = "You are a helpful assistant."
+    extensions = [calculator_extension]
+
+    req = create_completion_request(
+        provider_name,
+        provider_config,
+        model_config,
+        system_preamble,
+        messages,
+        extensions
+    )
+
+    resp = await completion(req)
+    print(f"\nCompletion Response:\n{resp.message}")
+    print(f"Msg content: {resp.message.content[0][0]}")
+
+
+if __name__ == "__main__":
+    asyncio.run(main())