Support vision input for Planner

README.md

@@ -23,6 +23,7 @@ Unlike many agent frameworks that only track the chat history with LLMs in text,
 
 
 ## 🆕 News
+- 📅2025-03-13: TaskWeaver now supports vision input for the Planner role. Please check the [vision input](https://microsoft.github.io/TaskWeaver/blog/vision) for more details.👀
 - 📅2025-01-16: TaskWeaver has been enhanced with an experimental role called [Recepta](https://microsoft.github.io/TaskWeaver/blog/reasoning) for its reasoning power.🧠
 - 📅2024-12-23: TaskWeaver has been integrated with the [AgentOps](https://microsoft.github.io/TaskWeaver/docs/observability) for better observability and monitoring.🔍
 - 📅2024-09-13: We introduce the shared memory to store information that is shared between the roles in TaskWeaver. Please check the [memory](https://microsoft.github.io/TaskWeaver/docs/memory) for more details.🧠
@@ -31,7 +32,7 @@ Unlike many agent frameworks that only track the chat history with LLMs in text,
 - 📅2024-05-07: We have added two blog posts on [Evaluating a LLM agent](https://microsoft.github.io/TaskWeaver/blog/evaluation) and [Adding new roles to TaskWeaver](https://microsoft.github.io/TaskWeaver/blog/role) in the documentation.📝
 - 📅2024-03-28: TaskWeaver now offers all-in-one Docker image, providing a convenient one-stop experience for users. Please check the [docker](https://microsoft.github.io/TaskWeaver/docs/usage/docker) for more details.🐳
 - 📅2024-03-27: TaskWeaver now switches to `container` mode by default for code execution. Please check the [code execution](https://microsoft.github.io/TaskWeaver/docs/code_execution) for more details.🐳
-- 📅2024-03-07: TaskWeaver now supports configuration of different LLMs for various components, such as the Planner and CodeInterpreter. Please check the [multi-llm](https://microsoft.github.io/TaskWeaver/docs/llms/multi-llm) for more details.🔗
+<!-- - 📅2024-03-07: TaskWeaver now supports configuration of different LLMs for various components, such as the Planner and CodeInterpreter. Please check the [multi-llm](https://microsoft.github.io/TaskWeaver/docs/llms/multi-llm) for more details.🔗 -->
 <!-- - 📅2024-03-04: TaskWeaver now supports a [container](https://microsoft.github.io/TaskWeaver/docs/code_execution) mode, which provides a more secure environment for code execution.🐳 -->
 <!-- - 📅2024-02-28: TaskWeaver now offers a [CLI-only](https://microsoft.github.io/TaskWeaver/docs/advanced/cli_only) mode, enabling users to interact seamlessly with the Command Line Interface (CLI) using natural language.📟 -->
 <!-- - 📅2024-02-01: TaskWeaver now has a plugin [document_retriever](https://github.com/microsoft/TaskWeaver/blob/main/project/plugins/README.md#document_retriever) for RAG based on a knowledge base.📚 -->
@@ -43,7 +44,8 @@ Unlike many agent frameworks that only track the chat history with LLMs in text,
 <!-- - 📅2023-12-21: TaskWeaver now supports a number of LLMs, such as LiteLLM, Ollama, Gemini, and QWen🎈.) -->
 <!-- - 📅2023-12-21: TaskWeaver Website is now [available]&#40;https://microsoft.github.io/TaskWeaver/&#41; with more documentations.) -->
 <!-- - 📅2023-12-12: A simple UI demo is available in playground/UI folder, try it [here](https://microsoft.github.io/TaskWeaver/docs/usage/webui)! -->
-<!-- - 📅2023-11-30: TaskWeaver is released on GitHub🎈.  -->
+- ......
+- 📅2023-11-30: TaskWeaver is released on GitHub🎈.  
 
 
 ## 💥 Highlights
@@ -68,7 +70,6 @@ We are looking forward to your contributions to make TaskWeaver better.
 - [ ] Support for prompt template management
 - [ ] Better plugin experiences, such as displaying updates or stopping in the middle of running the plugin and user confirmation before running the plugin
 - [ ] Async interaction with LLMs
-- [ ] Support for vision input for Roles such as the Planner and CodeInterpreter
 - [ ] Support for remote code execution
 
 

taskweaver/chat/console/chat.py

@@ -498,7 +498,7 @@ def _reset_session(self, first_session: bool = False):
             self.session.stop()
             self.session = self.app.get_session()
 
-        self._system_message("--- new session starts ---")
+        self._system_message("--- new session started ---")
         self._assistant_message(
             "I am TaskWeaver, an AI assistant. To get started, could you please enter your request?",
         )

taskweaver/code_interpreter/code_interpreter/code_generator.py

@@ -251,7 +251,7 @@ def compose_conversation(
                     # for code correction
                     user_message += self.user_message_head_template.format(
                         FEEDBACK=format_code_feedback(post),
-                        MESSAGE=f"{post.get_attachment(AttachmentType.revise_message)[0]}",
+                        MESSAGE=f"{post.get_attachment(AttachmentType.revise_message)[0].content}",
                     )
 
                     assistant_message = self.post_translator.post_to_raw_text(

taskweaver/code_interpreter/code_interpreter_cli_only/code_interpreter_cli_only.py

@@ -60,9 +60,12 @@ def reply(
             prompt_log_path=prompt_log_path,
         )
 
-        code = post_proxy.post.get_attachment(type=AttachmentType.reply_content)[0]
+        code = post_proxy.post.get_attachment(type=AttachmentType.reply_content)[0].content
         if len(code) == 0:
-            post_proxy.update_message(post_proxy.post.get_attachment(type=AttachmentType.thought)[0], is_end=True)
+            post_proxy.update_message(
+                post_proxy.post.get_attachment(type=AttachmentType.thought)[0].content,
+                is_end=True,
+            )
             return post_proxy.end()
 
         code_to_exec = "! " + code

taskweaver/code_interpreter/code_interpreter_plugin_only/code_interpreter_plugin_only.py

@@ -78,7 +78,7 @@ def reply(
             return post_proxy.end()
 
         functions = json.loads(
-            post_proxy.post.get_attachment(type=AttachmentType.function)[0],
+            post_proxy.post.get_attachment(type=AttachmentType.function)[0].content,
         )
         if len(functions) > 0:
             code: List[str] = []

taskweaver/ext_role/image_reader/image_reader.py

@@ -0,0 +1,113 @@
+import base64
+import json
+import os.path
+from mimetypes import guess_type
+
+from injector import inject
+
+from taskweaver.llm import LLMApi, format_chat_message
+from taskweaver.logging import TelemetryLogger
+from taskweaver.memory import Memory, Post
+from taskweaver.memory.attachment import AttachmentType
+from taskweaver.module.event_emitter import SessionEventEmitter
+from taskweaver.module.tracing import Tracing
+from taskweaver.role import Role
+from taskweaver.role.role import RoleConfig, RoleEntry
+from taskweaver.session import SessionMetadata
+
+
+# Function to encode a local image into data URL
+def local_image_to_data_url(image_path):
+    # Guess the MIME type of the image based on the file extension
+    mime_type, _ = guess_type(image_path)
+    if mime_type is None:
+        mime_type = "application/octet-stream"  # Default MIME type if none is found
+
+    # Read and encode the image file
+    with open(image_path, "rb") as image_file:
+        base64_encoded_data = base64.b64encode(image_file.read()).decode("utf-8")
+
+    # Construct the data URL
+    return f"data:{mime_type};base64,{base64_encoded_data}"
+
+
+class ImageReaderConfig(RoleConfig):
+    def _configure(self):
+        pass
+
+
+class ImageReader(Role):
+    @inject
+    def __init__(
+        self,
+        config: ImageReaderConfig,
+        logger: TelemetryLogger,
+        tracing: Tracing,
+        event_emitter: SessionEventEmitter,
+        role_entry: RoleEntry,
+        llm_api: LLMApi,
+        session_metadata: SessionMetadata,
+    ):
+        super().__init__(config, logger, tracing, event_emitter, role_entry)
+
+        self.llm_api = llm_api
+        self.session_metadata = session_metadata
+
+    def reply(self, memory: Memory, **kwargs: ...) -> Post:
+        rounds = memory.get_role_rounds(
+            role=self.alias,
+            include_failure_rounds=False,
+        )
+
+        # obtain the query from the last round
+        last_post = rounds[-1].post_list[-1]
+
+        post_proxy = self.event_emitter.create_post_proxy(self.alias)
+
+        post_proxy.update_send_to(last_post.send_from)
+
+        input_message = last_post.message
+        prompt = (
+            f"Input message: {input_message}.\n"
+            "\n"
+            "Your response should be a JSON object with the key 'image_url' and the value as the image path. "
+            "For example, {'image_url': 'c:/images/image.jpg'} or {'image_url': 'http://example.com/image.jpg'}. "
+            "Do not add any additional information in the response or wrap the JSON with ```json and ```."
+        )
+
+        response = self.llm_api.chat_completion(
+            messages=[
+                format_chat_message(
+                    role="system",
+                    message="Your task is to read the image path from the message.",
+                ),
+                format_chat_message(
+                    role="user",
+                    message=prompt,
+                ),
+            ],
+        )
+
+        image_url = json.loads(response["content"])["image_url"]
+        if image_url.startswith("http"):
+            image_content = image_url
+            attachment_message = f"Image from {image_url}."
+        else:
+            if os.path.isabs(image_url):
+                image_content = local_image_to_data_url(image_url)
+            else:
+                image_content = local_image_to_data_url(os.path.join(self.session_metadata.execution_cwd, image_url))
+            attachment_message = f"Image from {image_url} encoded as a Base64 data URL."
+
+        post_proxy.update_attachment(
+            message=attachment_message,
+            type=AttachmentType.image_url,
+            extra={"image_url": image_content},
+            is_end=True,
+        )
+
+        post_proxy.update_message(
+            "I have read the image path from the message. The image is attached below.",
+        )
+
+        return post_proxy.end()

taskweaver/ext_role/image_reader/image_reader.role.yaml

@@ -0,0 +1,5 @@
+alias: ImageReader
+module: taskweaver.ext_role.image_reader.image_reader.ImageReader
+intro : |-
+  - ImageReader is responsible for helping the Planner to read images.
+  - The input message must contain the image path, either local or remote.

taskweaver/llm/util.py

@@ -1,7 +1,9 @@
 from typing import Any, Dict, List, Literal, Optional, TypedDict, Union
 
 ChatMessageRoleType = Literal["system", "user", "assistant", "function"]
-ChatMessageType = Dict[Literal["role", "name", "content"], str]
+ChatContentType = Dict[Literal["type", "text", "image_url"], str | Dict[Literal["url"], str]]
+ChatMessageType = Dict[Literal["role", "name", "content"], str | List[ChatContentType]]
+
 PromptTypeSimple = List[ChatMessageType]
 
 
@@ -21,15 +23,43 @@ class PromptTypeWithTools(TypedDict):
     tools: Optional[List[PromptToolType]]
 
 
+def format_chat_message_content(
+    content_type: Literal["text", "image_url"],
+    content_value: str,
+) -> ChatContentType:
+    if content_type == "image_url":
+        return {
+            "type": content_type,
+            content_type: {
+                "url": content_value,
+            },
+        }
+    else:
+        return {
+            "type": content_type,
+            content_type: content_value,
+        }
+
+
 def format_chat_message(
     role: ChatMessageRoleType,
     message: str,
+    image_urls: Optional[List[str]] = None,
     name: Optional[str] = None,
 ) -> ChatMessageType:
-    msg: ChatMessageType = {
-        "role": role,
-        "content": message,
-    }
+    if not image_urls:
+        msg: ChatMessageType = {
+            "role": role,
+            "content": message,
+        }
+    else:
+        msg: ChatMessageType = {
+            "role": role,
+            "content": [
+                format_chat_message_content("text", message),
+            ]
+            + [format_chat_message_content("image_url", image) for image in image_urls],
+        }
     if name is not None:
         msg["name"] = name
     return msg

taskweaver/memory/attachment.py

@@ -47,6 +47,9 @@ class AttachmentType(Enum):
     # shared memory entry
     shared_memory_entry = "shared_memory_entry"
 
+    # vision input
+    image_url = "image_url"
+
 
 @dataclass
 class Attachment:

taskweaver/memory/post.py

@@ -87,9 +87,9 @@ def add_attachment(self, attachment: Attachment) -> None:
         """Add an attachment to the post."""
         self.attachment_list.append(attachment)
 
-    def get_attachment(self, type: AttachmentType) -> List[Any]:
+    def get_attachment(self, type: AttachmentType) -> List[Attachment]:
         """Get all the attachments of the given type."""
-        return [attachment.content for attachment in self.attachment_list if attachment.type == type]
+        return [attachment for attachment in self.attachment_list if attachment.type == type]
 
     def del_attachment(self, type_list: List[AttachmentType]) -> None:
         """Delete all the attachments of the given type."""

taskweaver/planner/planner.py

@@ -133,6 +133,7 @@ def compose_conversation_for_prompt(
             for post in chat_round.post_list:
                 if post.send_from == self.alias:
                     if post.send_to == "User" or post.send_to in self.recipient_alias_set:
+                        # planner responses
                         planner_message = self.planner_post_translator.post_to_raw_text(
                             post=post,
                         )
@@ -144,47 +145,45 @@ def compose_conversation_for_prompt(
                         )
                     elif post.send_to == self.alias:
                         # self correction for planner response, e.g., format error/field check error
+                        # append the invalid response to chat history
                         conversation.append(
                             format_chat_message(
                                 role="assistant",
                                 message=post.get_attachment(
                                     type=AttachmentType.invalid_response,
-                                )[0],
+                                )[0].content,
                             ),
                         )
 
-                        # append the invalid response to chat history
+                        # append the self correction instruction message to chat history
                         conversation.append(
                             format_chat_message(
                                 role="user",
                                 message=self.format_message(
                                     role="User",
-                                    message=post.get_attachment(type=AttachmentType.revise_message)[0],
+                                    message=post.get_attachment(type=AttachmentType.revise_message)[0].content,
                                 ),
                             ),
                         )
-                        # append the self correction instruction message to chat history
-
                 else:
-                    if conv_init_message is not None:
-                        message = self.format_message(
-                            role=post.send_from,
-                            message=conv_init_message + "\n" + post.message,
-                        )
-                        conversation.append(
-                            format_chat_message(role="user", message=message),
-                        )
-                        conv_init_message = None
-                    else:
-                        conversation.append(
-                            format_chat_message(
-                                role="user",
-                                message=self.format_message(
-                                    role=post.send_from,
-                                    message=post.message,
-                                ),
+                    # messages from user or workers
+                    conversation.append(
+                        format_chat_message(
+                            role="user",
+                            message=self.format_message(
+                                role=post.send_from,
+                                message=post.message
+                                if conv_init_message is None
+                                else conv_init_message + "\n" + post.message,
                             ),
-                        )
+                            image_urls=[
+                                attachment.extra["image_url"]
+                                for attachment in post.get_attachment(type=AttachmentType.image_url)
+                            ],
+                        ),
+                    )
+
+                    conv_init_message = None
 
         return conversation
 

website/blog/authors.yml

@@ -0,0 +1,11 @@
+liqli:
+  name: Liqun Li
+  url: https://liqul.github.io
+  title: Principal Researcher
+  image_url: https://liqul.github.io/assets/logo_small_bw.png
+
+xu:
+  name: Xu Zhang
+  url: https://scholar.google.com/citations?user=bqXdMMMAAAAJ&hl=zh-CN
+  title: Senior Researcher
+  image_url: https://scholar.googleusercontent.com/citations?view_op=view_photo&user=bqXdMMMAAAAJ&citpid=3

website/blog/evaluation.md

@@ -1,4 +1,8 @@
-# How to evaluate a LLM agent?
+---
+title: How to evaluate a LLM agent?  
+authors: [liqli, xu]
+date: 2024-05-07  
+---
 
 ## The challenges
 It is nontrivial to evaluate the performance of a LLM agent. 

website/blog/experience.md

@@ -1,4 +1,8 @@
-# Experience selection
+---
+title: Experience Selection in TaskWeaver
+authors: liqli
+date: 2024-09-14
+---
 
 We have introduced the motivation of the `experience` module in [Experience](/docs/customization/experience) 
 and how to create a handcrafted experience in [Handcrafted Experience](/docs/customization/experience/handcrafted_experience).

website/blog/local_llm.md

@@ -1,4 +1,8 @@
-# Run TaskWeaver with Locally Deployed Not-that-Large Language Models
+---
+title: Run TaskWeaver with Locally Deployed Not-that-Large Language Models
+authors: liqli
+date: 2024-07-08
+---
 
 :::info
 The feature introduced in this blog post can cause incompatibility issue with the previous version of TaskWeaver