first commit

README.md

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+# default_async_llm_extension_python
+
+<!-- brief introduction for the extension -->
+
+## Features
+
+<!-- main features introduction -->
+
+- xxx feature
+
+## API
+
+Refer to `api` definition in [manifest.json] and default values in [property.json](property.json).
+
+<!-- Additional API.md can be referred to if extra introduction needed -->
+
+## Development
+
+### Build
+
+<!-- build dependencies and steps -->
+
+### Unit test
+
+<!-- how to do unit test for the extension -->
+
+## Misc
+
+<!-- others if applicable -->

README.md.tent

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+# {{package_name}}
+
+<!-- brief introduction for the extension -->
+
+## Features
+
+<!-- main features introduction -->
+
+- xxx feature
+
+## API
+
+Refer to `api` definition in [manifest.json] and default values in [property.json](property.json).
+
+<!-- Additional API.md can be referred to if extra introduction needed -->
+
+## Development
+
+### Build
+
+<!-- build dependencies and steps -->
+
+### Unit test
+
+<!-- how to do unit test for the extension -->
+
+## Misc
+
+<!-- others if applicable -->

__init__.py

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+#
+# This file is part of TEN Framework, an open source project.
+# Licensed under the Apache License, Version 2.0.
+# See the LICENSE file for more information.
+#
+from . import addon

addon.py

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+#
+# This file is part of TEN Framework, an open source project.
+# Licensed under the Apache License, Version 2.0.
+# See the LICENSE file for more information.
+#
+from ten import (
+    Addon,
+    register_addon_as_extension,
+    TenEnv,
+)
+from .extension import DefaultAsyncLLMExtension
+
+
+@register_addon_as_extension("default_async_llm_extension_python")
+class DefaultAsyncLLMExtensionAddon(Addon):
+    def on_create_instance(self, ten_env: TenEnv, name: str, context) -> None:
+        ten_env.log_info("on_create_instance")
+        ten_env.on_create_instance_done(
+            DefaultAsyncLLMExtension(name), context)

addon.py.tent

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+#
+# This file is part of TEN Framework, an open source project.
+# Licensed under the Apache License, Version 2.0.
+# See the LICENSE file for more information.
+#
+from ten import (
+    Addon,
+    register_addon_as_extension,
+    TenEnv,
+)
+from .extension import {{class_name_prefix}}Extension
+
+
+@register_addon_as_extension("{{package_name}}")
+class {{class_name_prefix}}ExtensionAddon(Addon):
+    def on_create_instance(self, ten_env: TenEnv, name: str, context) -> None:
+        ten_env.log_info("on_create_instance")
+        ten_env.on_create_instance_done(
+            {{class_name_prefix}}Extension(name), context)

extension.py

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+#
+# This file is part of TEN Framework, an open source project.
+# Licensed under the Apache License, Version 2.0.
+# See the LICENSE file for more information.
+#
+from ten import AsyncTenEnv
+from ten_ai_base import (
+    AsyncLLMBaseExtension, LLMCallCompletionArgs, LLMDataCompletionArgs, LLMToolMetadata, BaseConfig
+)
+from dataclasses import dataclass
+
+
+@dataclass
+class DefaultAsyncLLMConfig(BaseConfig):
+    model: str = ""
+    # TODO: add extra config fields here
+
+
+class DefaultAsyncLLMExtension(AsyncLLMBaseExtension):
+    async def on_start(self, ten_env: AsyncTenEnv) -> None:
+        await super().on_start(ten_env)
+
+        # initialize configuration
+        self.config = DefaultAsyncLLMConfig.create(ten_env=ten_env)
+        ten_env.log_info(f"config: {self.config}")
+
+        """Implement this method to construct and start your resources."""
+        ten_env.log_debug("TODO: on_start")
+
+    async def on_stop(self, ten_env: AsyncTenEnv) -> None:
+        await super().on_stop(ten_env)
+
+        """Implement this method to stop and destruct your resources."""
+        ten_env.log_debug("TODO: on_stop")
+
+    async def on_call_chat_completion(self, ten_env: AsyncTenEnv, **kargs: LLMCallCompletionArgs) -> any:
+        """Called when a chat completion is requested by cmd call. Implement this method to process the chat completion."""
+        ten_env.log_debug("TODO: on_call_chat_completion")
+
+    async def on_data_chat_completion(self, ten_env: AsyncTenEnv, **kargs: LLMDataCompletionArgs) -> None:
+        """
+        Called when a chat completion is requested by data input. Implement this method to process the chat completion.
+        Note that this method is stream-based, and it should consider supporting local context caching.
+        """
+        ten_env.log_debug("TODO: on_data_chat_completion")
+
+    async def on_tools_update(self, ten_env: AsyncTenEnv, tool: LLMToolMetadata) -> None:
+        """Called when a new tool is registered. Implement this method to process the new tool."""
+        ten_env.log_debug("TODO: on_tools_update")

extension.py.tent

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+#
+# This file is part of TEN Framework, an open source project.
+# Licensed under the Apache License, Version 2.0.
+# See the LICENSE file for more information.
+#
+from ten import AsyncTenEnv
+from ten_ai_base import (
+    AsyncLLMBaseExtension, LLMCallCompletionArgs, LLMDataCompletionArgs, LLMToolMetadata, BaseConfig
+)
+from dataclasses import dataclass
+
+
+@dataclass
+class {{class_name_prefix}}Config(BaseConfig):
+    model: str = ""
+    # TODO: add extra config fields here
+
+
+class {{class_name_prefix}}Extension(AsyncLLMBaseExtension):
+    async def on_start(self, ten_env: AsyncTenEnv) -> None:
+        await super().on_start(ten_env)
+
+        # initialize configuration
+        self.config = {{class_name_prefix}}Config.create(ten_env=ten_env)
+        ten_env.log_info(f"config: {self.config}")
+
+        """Implement this method to construct and start your resources."""
+        ten_env.log_debug("TODO: on_start")
+
+    async def on_stop(self, ten_env: AsyncTenEnv) -> None:
+        await super().on_stop(ten_env)
+
+        """Implement this method to stop and destruct your resources."""
+        ten_env.log_debug("TODO: on_stop")
+
+    async def on_call_chat_completion(self, ten_env: AsyncTenEnv, **kargs: LLMCallCompletionArgs) -> any:
+        """Called when a chat completion is requested by cmd call. Implement this method to process the chat completion."""
+        ten_env.log_debug("TODO: on_call_chat_completion")
+
+    async def on_data_chat_completion(self, ten_env: AsyncTenEnv, **kargs: LLMDataCompletionArgs) -> None:
+        """
+        Called when a chat completion is requested by data input. Implement this method to process the chat completion.
+        Note that this method is stream-based, and it should consider supporting local context caching.
+        """
+        ten_env.log_debug("TODO: on_data_chat_completion")
+
+    async def on_tools_update(self, ten_env: AsyncTenEnv, tool: LLMToolMetadata) -> None:
+        """Called when a new tool is registered. Implement this method to process the new tool."""
+        ten_env.log_debug("TODO: on_tools_update")

manifest.json

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+{
+  "type": "extension",
+  "name": "default_async_llm_extension_python",
+  "version": "0.1.0",
+  "dependencies": [
+    {
+      "type": "system",
+      "name": "ten_ai_base",
+      "version": "0.1.0"
+    }
+  ],
+  "package": {
+    "include": [
+      "manifest.json",
+      "property.json",
+      "requirements.txt",
+      "**.tent",
+      "**.py",
+      "README.md"
+    ]
+  },
+  "api": {
+    "property": {
+      "model": {
+        "type": "string"
+      }
+    },
+    "cmd_in": [
+      {
+        "name": "tool_register",
+        "property": {
+          "tool": {
+            "type": "string"
+          }
+        },
+        "required": [
+          "tool"
+        ]
+      },
+      {
+        "name": "call_chat_completion",
+        "property": {
+          "messages": {
+            "type": "string"
+          },
+          "stream": {
+            "type": "bool"
+          }
+        },
+        "required": [
+          "messages"
+        ],
+        "result": {
+          "property": {
+            "text": {
+              "type": "string"
+            }
+          },
+          "required": [
+            "text"
+          ]
+        }
+      },
+      {
+        "name": "flush"
+      }
+    ],
+    "cmd_out": [
+      {
+        "name": "flush"
+      }
+    ],
+    "data_in": [
+      {
+        "name": "text_data",
+        "property": {
+          "text": {
+            "type": "string"
+          },
+          "is_final": {
+            "type": "bool"
+          }
+        },
+        "required": [
+          "text"
+        ]
+      }
+    ],
+    "data_out": [
+      {
+        "name": "text_data",
+        "property": {
+          "text": {
+            "type": "string"
+          },
+          "end_of_segment": {
+            "type": "bool"
+          }
+        },
+        "required": [
+          "text",
+          "end_of_segment"
+        ]
+      }
+    ]
+  }
+}