Merge pull request #42 from nextcloud/feat/add-new-providers

Feat: add new providers

lib/change_tone.py

@@ -0,0 +1,39 @@
+# SPDX-FileCopyrightText: 2024 Nextcloud GmbH and Nextcloud contributors
+# SPDX-License-Identifier: AGPL-3.0-or-later
+"""A chain that changes the tone of a text
+"""
+
+from typing import Any
+
+from langchain.prompts import PromptTemplate
+from langchain.schema.prompt_template import BasePromptTemplate
+from langchain_core.runnables import Runnable
+
+class ChangeToneProcessor():
+
+    runnable: Runnable
+
+    """
+    A topics chain
+    """
+    system_prompt: str = "You're an AI assistant tasked with rewriting the text given to you by the user in another tone."
+    user_prompt: BasePromptTemplate = PromptTemplate(
+            input_variables=["text", "tone"],
+            template="""Reformulate the following text in a " {tone} " tone in its original language without mentioning the language. Output only the reformulation, nothing else, no introductory sentence. Here is the text:
+
+"
+{text}
+"
+
+Output only the reformulated text, nothing else. Do not add an introductory sentence.
+"""
+    )
+
+    def __init__(self, runnable: Runnable):
+        self.runnable = runnable
+
+
+    def __call__(self, inputs: dict[str,Any],
+        ) -> dict[str, Any]:
+            output = self.runnable.invoke({"user_prompt": self.user_prompt.format_prompt(text=inputs['input'], tone=inputs['tone']), "system_prompt": self.system_prompt})
+            return {'output': output}

lib/main.py

@@ -15,7 +15,7 @@
 from fastapi import FastAPI
 from nc_py_api import AsyncNextcloudApp, NextcloudApp, NextcloudException
 from nc_py_api.ex_app import LogLvl, persistent_storage, run_app, set_handlers
-from nc_py_api.ex_app.providers.task_processing import TaskProcessingProvider
+from nc_py_api.ex_app.providers.task_processing import TaskProcessingProvider, ShapeEnumValue
 
 models_to_fetch = {
     "https://huggingface.co/bartowski/Meta-Llama-3.1-8B-Instruct-GGUF/resolve/4f0c246f125fc7594238ebe7beb1435a8335f519/Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf": { "save_path": os.path.join(persistent_storage(), "Meta-Llama-3.1-8B-Instruct-Q4_K_M.gguf") },
@@ -123,6 +123,15 @@ async def enabled_handler(enabled: bool, nc: AsyncNextcloudApp) -> str:
                     name="Local Large language Model: " + model,
                     task_type=task,
                     expected_runtime=30,
+                     input_shape_enum_values= {
+                            "tone": [
+                                ShapeEnumValue(name= "Friendlier", value= "friendlier"),
+                                ShapeEnumValue(name= "More formal", value= "more formal"),
+                                ShapeEnumValue(name= "Funnier", value= "funnier"),
+                                ShapeEnumValue(name= "More casual", value= "more casual"),
+                                ShapeEnumValue(name= "More urgent", value= "more urgent"),
+                            ],
+                        } if task == "core:text2text:changetone" else {}
                 )
                 await nc.providers.task_processing.register(provider)
                 print(f"Registered {task_processor_name}", flush=True)

lib/proofread.py

@@ -0,0 +1,40 @@
+# SPDX-FileCopyrightText: 2024 Nextcloud GmbH and Nextcloud contributors
+# SPDX-License-Identifier: AGPL-3.0-or-later
+"""A chain to proofread a text
+"""
+
+from typing import Any
+from langchain.prompts import PromptTemplate
+from langchain.schema.prompt_template import BasePromptTemplate
+from langchain_core.runnables import Runnable
+
+
+class ProofreadProcessor:
+    """
+    A proofreading chain
+    """
+    system_prompt: str = "You're an AI assistant tasked with proofreading the text given to you by the user."
+    user_prompt: BasePromptTemplate = PromptTemplate(
+        input_variables=["text"],
+        template="""
+Detect all grammar and spelling mistakes of the following text in its original language. Output only the list of mistakes in bullet points.
+
+"
+{text}
+"
+
+Give me the list of all mistakes in the above text in its original language. Do not output the language. Output only the list in bullet points, nothing else, no introductory or explanatory text.
+        """
+    )
+
+    runnable: Runnable
+
+    def __init__(self, runnable: Runnable):
+        self.runnable = runnable
+
+    def __call__(
+            self,
+            inputs: dict[str, Any],
+    ) -> dict[str, Any]:
+        output = self.runnable.invoke({"user_prompt": self.user_prompt.format_prompt(text=inputs['input']), "system_prompt": self.system_prompt})
+        return {'output': output}

lib/task_processors.py

@@ -16,6 +16,8 @@
 from chat import ChatProcessor
 from free_prompt import FreePromptProcessor
 from headline import HeadlineProcessor
+from proofread import ProofreadProcessor
+from change_tone import ChangeToneProcessor
 from chatwithtools import ChatWithToolsProcessor
 from topics import TopicsProcessor
 from summarize import SummarizeProcessor
@@ -132,5 +134,8 @@ def generate_task_processors_for_model(file_name, task_processors):
     # chains[model_name + ":core:text2text:reformulation"] = lambda: ReformulateChain(llm_chain=llm_chain(), chunk_size=chunk_size)
     task_processors[model_name + ":core:text2text"] = lambda: FreePromptProcessor(generate_llm_chain(file_name))
     task_processors[model_name + ":core:text2text:chat"] = lambda: ChatProcessor(generate_chat_chain(file_name))
+    task_processors[model_name + ":core:text2text:proofread"] = lambda: ProofreadProcessor(generate_llm_chain(file_name))
+    task_processors[model_name + ":core:text2text:changetone"] = lambda: ChangeToneProcessor(generate_llm_chain(file_name))
     task_processors[model_name + ":core:text2text:chatwithtools"] = lambda: ChatWithToolsProcessor(generate_chat_chain(file_name))
+
     # chains[model_name + ":core:contextwrite"] = lambda: ContextWriteChain(llm_chain=llm_chain())