Merge pull request #46 from jhakulin/main

o1-assistant configuration

config/o1_assistant_assistant_config.yaml

@@ -0,0 +1,52 @@
+name: o1_assistant
+instructions: |-
+  ### Pre-requisites for processing
+  - You will get user input in the form of a question or prompt.
+  - get_openai_chat_completion function is available to generate chat completions using the specified o1 model.
+
+  ### Requirements
+  1. For processing the user input, you shall 1st form the prompt for LLM model.
+  2. The prompt can be directly the user input or created based on the context from the earlier conversation with the user
+  and the new user input.
+  3. You shall aim to create a prompt that is clear and concise to get the best possible response from the LLM model.
+  4. Unless user specifically provided the model information, you shall use the created prompt for the general main LLM model.
+  5. Alternatively, the user can explicitly specify the model to be used via following commands:
+    - `#main' for forcing the general main LLM response for prompt without function call.
+    - `#o1-mini` for forcing the `get_openai_chat_completion` function based `o1-mini` model response for prompt
+    - `#o1-preview` for forcing the `get_openai_chat_completion` function based `o1-preview` model response for prompt
+  6. If user provided image as input, you shall convert the image to text and use the text as prompt for LLM model.
+model: gpt-4o
+assistant_id: 
+file_references: []
+tool_resources:
+  code_interpreter:
+    files: {}
+  file_search:
+    vector_stores: []
+functions:
+- type: function
+  function:
+    name: get_openai_chat_completion
+    module: azure.ai.assistant.functions.llm_functions
+    description: Generates a chat completion for the given prompt using the prompt
+      and specified model.
+    parameters:
+      type: object
+      properties:
+        prompt:
+          type: string
+          description: The prompt for which the chat completion is to be generated.
+        model:
+          type: string
+          description: The model to use for generating the chat completion.
+      required:
+      - prompt
+      - model
+file_search: false
+code_interpreter: false
+output_folder_path: ''
+ai_client_type: OPEN_AI
+assistant_type: assistant
+completion_settings: null
+assistant_role: user
+config_folder: null

config/system_function_specs.json

@@ -234,5 +234,55 @@
                 ]
             }
         }
+    },
+    {
+        "type": "function",
+        "function": {
+            "name": "get_openai_chat_completion",
+            "module": "azure.ai.assistant.functions.llm_functions",
+            "description": "Generates a chat completion for the given prompt using the prompt and specified model.",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "prompt": {
+                        "type": "string",
+                        "description": "The prompt for which the chat completion is to be generated."
+                    },
+                    "model": {
+                        "type": "string",
+                        "description": "The model to use for generating the chat completion."
+                    }
+                },
+                "required": [
+                    "prompt",
+                    "model"
+                ]
+            }
+        }
+    },
+    {
+        "type": "function",
+        "function": {
+            "name": "get_azure_openai_chat_completion",
+            "module": "azure.ai.assistant.functions.llm_functions",
+            "description": "Generates a chat completion for the given prompt using the prompt and specified model.",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "prompt": {
+                        "type": "string",
+                        "description": "The prompt for which the chat completion is to be generated."
+                    },
+                    "model": {
+                        "type": "string",
+                        "description": "The model to use for generating the chat completion."
+                    }
+                },
+                "required": [
+                    "prompt",
+                    "model"
+                ]
+            }
+        }
     }
 ]

requirements.txt

@@ -1,5 +1,5 @@
 # Assistant middleware from GitHub Release
-https://github.com/Azure-Samples/azureai-assistant-tool/releases/download/v0.4.4-alpha/azure_ai_assistant-0.4.4a1-py3-none-any.whl
+https://github.com/Azure-Samples/azureai-assistant-tool/releases/download/v0.4.5-alpha/azure_ai_assistant-0.4.5a1-py3-none-any.whl
 
 # GUI Framework
 PySide6

sdk/azure-ai-assistant/azure/ai/assistant/_version.py

@@ -6,4 +6,4 @@
 # Changes may cause incorrect behavior and will be lost if the code is regenerated.
 # --------------------------------------------------------------------------
 
-VERSION = "0.4.4a1"
+VERSION = "0.4.5a1"

sdk/azure-ai-assistant/azure/ai/assistant/functions/llm_functions.py

@@ -0,0 +1,147 @@
+# Copyright (c) Microsoft. All rights reserved.
+# Licensed under the MIT license. See LICENSE.md file in the project root for full license information.
+
+from azure.ai.assistant.management.ai_client_factory import AIClientFactory, AIClientType
+from azure.ai.assistant.management.conversation_thread_client import ConversationThreadClient
+from azure.ai.assistant.management.message import ConversationMessage
+from azure.ai.assistant.management.logger_module import logger
+
+from typing import Dict, Any, List
+import json, copy
+
+
+def _initialize_clients(client_type):
+    try:
+        ai_client = AIClientFactory.get_instance().get_client(client_type)
+        thread_client = ConversationThreadClient.get_instance(client_type)
+        return ai_client, thread_client
+    except Exception as e:
+        error_message = f"Failed to initialize AI or thread client: {str(e)}"
+        logger.exception(error_message)
+        return None, None
+
+
+def _retrieve_and_parse_conversation(thread_client):
+    try:
+        thread_config = thread_client.get_config()
+        thread_id = thread_config.get_current_thread_id()
+        logger.info(f"retrieve_and_parse_conversation, thread_id: {thread_id}")
+
+        thread_name = thread_config.get_thread_name_by_id(thread_id)
+        # Retrieve max 10 last text messages from the conversation
+        conversation = thread_client.retrieve_conversation(
+            thread_name=thread_name, max_text_messages=10
+        )
+        messages = _parse_text_messages(conversation.messages)
+        return messages
+    except Exception as e:
+        error_message = f"Failed to retrieve or parse conversation: {str(e)}"
+        logger.exception(error_message)
+        return None
+
+
+def _generate_chat_completion(ai_client, model, messages):
+    logger.info(f"generate_chat_completion, messages: {messages}")
+    logger.info(f"generate_chat_completion, model: {model}")
+
+    try:
+        # Generate the chat completion
+        response = ai_client.chat.completions.create(
+            model=model,
+            messages=messages
+        )
+        logger.info(f"generate_chat_completion, response: {response}")
+
+        # Extract the content of the first choice
+        if response.choices and response.choices[0].message:
+            message_content = response.choices[0].message.content
+        else:
+            message_content = "No response"
+
+        return json.dumps({"result": message_content})
+    except Exception as e:
+        error_message = f"Failed to generate chat completion: {str(e)}"
+        logger.exception(error_message)
+        return json.dumps({"function_error": error_message})
+
+
+def _update_messages_with_prompt(messages : List[ConversationMessage], prompt):
+    updated_messages = copy.deepcopy(messages)
+
+    new_message = {
+        "role": "user",
+        "content": [{"type": "text", "text": prompt}]
+    }
+
+    if not updated_messages:
+        updated_messages.append(new_message)
+        return updated_messages
+
+    for message in reversed(updated_messages):
+        if message.get("role") == "user":
+            message["content"] = new_message["content"]
+            return updated_messages
+
+    # If no user message is found, append the new user message
+    updated_messages.append(new_message)
+
+    return updated_messages
+
+
+def _parse_text_messages(messages: List['ConversationMessage']) -> List[Dict[str, Any]]:
+    parsed_messages = []
+    for message in reversed(messages):
+        if message.text_message:
+            parsed_messages.append({
+                "role": message.role,
+                "content": [{"type": "text", "text": message.text_message.content}]
+            })
+    return parsed_messages
+
+
+def get_openai_chat_completion(prompt: str, model: str) -> str:
+    """
+    Generates a chat completion for the given prompt using the specified model.
+
+    :param prompt: The prompt for which the chat completion is to be generated.
+    :type prompt: str
+    :param model: The model to be used for generating the chat completion.
+    :type model: str
+
+    :return: JSON formatted string containing the result or an error message.
+    :rtype: str
+    """
+    ai_client, thread_client = _initialize_clients(AIClientType.OPEN_AI)
+    if not ai_client or not thread_client:
+        return json.dumps({"function_error": "Failed to initialize AI or thread client."})
+
+    messages = _retrieve_and_parse_conversation(thread_client)
+    if messages is None:
+        return json.dumps({"function_error": "Failed to retrieve or parse conversation."})
+
+    messages = _update_messages_with_prompt(messages, prompt)
+    return _generate_chat_completion(ai_client, model, messages)
+
+
+def get_azure_openai_chat_completion(prompt: str, model: str) -> str:
+    """
+    Generates a chat completion for the given prompt using the specified Azure OpenAI model.
+
+    :param prompt: The prompt for which the chat completion is to be generated.
+    :type prompt: str
+    :param model: The Azure OpenAI model to be used for generating the chat completion.
+    :type model: str
+
+    :return: JSON formatted string containing the result or an error message.
+    :rtype: str
+    """
+    ai_client, thread_client = _initialize_clients(AIClientType.AZURE_OPEN_AI)
+    if not ai_client or not thread_client:
+        return json.dumps({"function_error": "Failed to initialize Azure AI or thread client."})
+
+    messages = _retrieve_and_parse_conversation(thread_client)
+    if messages is None:
+        return json.dumps({"function_error": "Failed to retrieve or parse conversation."})
+
+    messages = _update_messages_with_prompt(messages, prompt)
+    return _generate_chat_completion(ai_client, model, messages)

sdk/azure-ai-assistant/azure/ai/assistant/functions/system_function_mappings.py

@@ -17,6 +17,11 @@
     find_files_by_extension_in_directory,
 )
 
+from azure.ai.assistant.functions.llm_functions import (
+    get_openai_chat_completion,
+    get_azure_openai_chat_completion,
+)
+
 # Statically defined system functions for fast reference
 system_functions = {
     "fetch_current_datetime": fetch_current_datetime,
@@ -30,5 +35,7 @@
     "find_all_folders_by_name_from_current_directory": find_all_folders_by_name_from_current_directory,
     "retrieve_current_directory_structure_subfolders": retrieve_current_directory_structure_subfolders,
     "find_files_by_name_in_directory": find_files_by_name_in_directory,
-    "find_files_by_extension_in_directory": find_files_by_extension_in_directory
+    "find_files_by_extension_in_directory": find_files_by_extension_in_directory,
+    "get_openai_chat_completion": get_openai_chat_completion,
+    "get_azure_openai_chat_completion": get_azure_openai_chat_completion,
 }