Merge branch 'main' into main

examples/rag/omniparse.py

@@ -0,0 +1,64 @@
+import asyncio
+
+from metagpt.config2 import config
+from metagpt.const import EXAMPLE_DATA_PATH
+from metagpt.logs import logger
+from metagpt.rag.parsers import OmniParse
+from metagpt.rag.schema import OmniParseOptions, OmniParseType, ParseResultType
+from metagpt.utils.omniparse_client import OmniParseClient
+
+TEST_DOCX = EXAMPLE_DATA_PATH / "omniparse/test01.docx"
+TEST_PDF = EXAMPLE_DATA_PATH / "omniparse/test02.pdf"
+TEST_VIDEO = EXAMPLE_DATA_PATH / "omniparse/test03.mp4"
+TEST_AUDIO = EXAMPLE_DATA_PATH / "omniparse/test04.mp3"
+
+
+async def omniparse_client_example():
+    client = OmniParseClient(base_url=config.omniparse.base_url)
+
+    # docx
+    with open(TEST_DOCX, "rb") as f:
+        file_input = f.read()
+    document_parse_ret = await client.parse_document(file_input=file_input, bytes_filename="test_01.docx")
+    logger.info(document_parse_ret)
+
+    # pdf
+    pdf_parse_ret = await client.parse_pdf(file_input=TEST_PDF)
+    logger.info(pdf_parse_ret)
+
+    # video
+    video_parse_ret = await client.parse_video(file_input=TEST_VIDEO)
+    logger.info(video_parse_ret)
+
+    # audio
+    audio_parse_ret = await client.parse_audio(file_input=TEST_AUDIO)
+    logger.info(audio_parse_ret)
+
+
+async def omniparse_example():
+    parser = OmniParse(
+        api_key=config.omniparse.api_key,
+        base_url=config.omniparse.base_url,
+        parse_options=OmniParseOptions(
+            parse_type=OmniParseType.PDF,
+            result_type=ParseResultType.MD,
+            max_timeout=120,
+            num_workers=3,
+        ),
+    )
+    ret = parser.load_data(file_path=TEST_PDF)
+    logger.info(ret)
+
+    file_paths = [TEST_DOCX, TEST_PDF]
+    parser.parse_type = OmniParseType.DOCUMENT
+    ret = await parser.aload_data(file_path=file_paths)
+    logger.info(ret)
+
+
+async def main():
+    await omniparse_client_example()
+    await omniparse_example()
+
+
+if __name__ == "__main__":
+    asyncio.run(main())

examples/rag/rag_search.py

@@ -2,7 +2,7 @@
 
 import asyncio
 
-from examples.rag_pipeline import DOC_PATH, QUESTION
+from examples.rag.rag_pipeline import DOC_PATH, QUESTION
 from metagpt.logs import logger
 from metagpt.rag.engines import SimpleEngine
 from metagpt.roles import Sales

examples/sk_agent.py

@@ -1,82 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-"""
-@Time    : 2023/9/13 12:36
-@Author  : femto Zheng
-@File    : sk_agent.py
-"""
-import asyncio
-
-from semantic_kernel.core_skills import FileIOSkill, MathSkill, TextSkill, TimeSkill
-from semantic_kernel.planning import SequentialPlanner
-
-# from semantic_kernel.planning import SequentialPlanner
-from semantic_kernel.planning.action_planner.action_planner import ActionPlanner
-
-from metagpt.actions import UserRequirement
-from metagpt.const import SKILL_DIRECTORY
-from metagpt.roles.sk_agent import SkAgent
-from metagpt.schema import Message
-from metagpt.tools.search_engine import SkSearchEngine
-
-
-async def main():
-    # await basic_planner_example()
-    # await action_planner_example()
-
-    # await sequential_planner_example()
-    await basic_planner_web_search_example()
-
-
-async def basic_planner_example():
-    task = """
-    Tomorrow is Valentine's day. I need to come up with a few date ideas. She speaks French so write it in French.
-    Convert the text to uppercase"""
-    role = SkAgent()
-
-    # let's give the agent some skills
-    role.import_semantic_skill_from_directory(SKILL_DIRECTORY, "SummarizeSkill")
-    role.import_semantic_skill_from_directory(SKILL_DIRECTORY, "WriterSkill")
-    role.import_skill(TextSkill(), "TextSkill")
-    # using BasicPlanner
-    await role.run(Message(content=task, cause_by=UserRequirement))
-
-
-async def sequential_planner_example():
-    task = """
-    Tomorrow is Valentine's day. I need to come up with a few date ideas. She speaks French so write it in French.
-    Convert the text to uppercase"""
-    role = SkAgent(planner_cls=SequentialPlanner)
-
-    # let's give the agent some skills
-    role.import_semantic_skill_from_directory(SKILL_DIRECTORY, "SummarizeSkill")
-    role.import_semantic_skill_from_directory(SKILL_DIRECTORY, "WriterSkill")
-    role.import_skill(TextSkill(), "TextSkill")
-    # using BasicPlanner
-    await role.run(Message(content=task, cause_by=UserRequirement))
-
-
-async def basic_planner_web_search_example():
-    task = """
-    Question: Who made the 1989 comic book, the film version of which Jon Raymond Polito appeared in?"""
-    role = SkAgent()
-
-    role.import_skill(SkSearchEngine(), "WebSearchSkill")
-    # role.import_semantic_skill_from_directory(skills_directory, "QASkill")
-
-    await role.run(Message(content=task, cause_by=UserRequirement))
-
-
-async def action_planner_example():
-    role = SkAgent(planner_cls=ActionPlanner)
-    # let's give the agent 4 skills
-    role.import_skill(MathSkill(), "math")
-    role.import_skill(FileIOSkill(), "fileIO")
-    role.import_skill(TimeSkill(), "time")
-    role.import_skill(TextSkill(), "text")
-    task = "What is the sum of 110 and 990?"
-    await role.run(Message(content=task, cause_by=UserRequirement))  # it will choose mathskill.Add
-
-
-if __name__ == "__main__":
-    asyncio.run(main())

examples/ui_with_chainlit/.gitignore

@@ -0,0 +1,3 @@
+*.chainlit
+chainlit.md
+.files

examples/ui_with_chainlit/README.md

@@ -0,0 +1,34 @@
+# MetaGPT in UI with Chainlit! 🤖
+
+- MetaGPT functionality in UI using Chainlit.
+- It also takes a **one line requirement** as input and outputs **user stories / competitive analysis / requirements / data structures / APIs / documents, etc.**, But `everything in UI`.
+
+## Install Chainlit
+
+- Setup initial MetaGPT config from [Main](../../README.md).
+
+```bash
+pip install chainlit
+```
+
+## Usage
+
+```bash
+chainlit run app.py
+```
+
+- Now go to: http://localhost:8000
+
+- Select,
+  - `Create a 2048 game`
+  - `Write a cli Blackjack Game`
+  - `Type your own message...`
+
+- It will run a metagpt software company.
+
+## To Setup with own application
+
+- We can change `Environment.run`, `Team.run`, `Role.run`, `Role._act`, `Action.run`.
+- In this code, changed `Environment.run`, as it was easier to do.
+- We will need to change `metagpt.logs.set_llm_stream_logfunc` to stream messages in UI with Chainlit Message.
+- To use at some other place we need to call `chainlit.Message(content="").send()` with content.

examples/ui_with_chainlit/app.py

@@ -0,0 +1,83 @@
+import chainlit as cl
+from init_setup import ChainlitEnv
+
+from metagpt.roles import (
+    Architect,
+    Engineer,
+    ProductManager,
+    ProjectManager,
+    QaEngineer,
+)
+from metagpt.team import Team
+
+
+# https://docs.chainlit.io/concepts/starters
+@cl.set_chat_profiles
+async def chat_profile() -> list[cl.ChatProfile]:
+    """Generates a chat profile containing starter messages which can be triggered to run MetaGPT
+
+    Returns:
+        list[chainlit.ChatProfile]: List of Chat Profile
+    """
+    return [
+        cl.ChatProfile(
+            name="MetaGPT",
+            icon="/public/MetaGPT-new-log.jpg",
+            markdown_description="It takes a **one line requirement** as input and outputs **user stories / competitive analysis / requirements / data structures / APIs / documents, etc.**, But `everything in UI`.",
+            starters=[
+                cl.Starter(
+                    label="Create a 2048 Game",
+                    message="Create a 2048 game",
+                    icon="/public/2048.jpg",
+                ),
+                cl.Starter(
+                    label="Write a cli Blackjack Game",
+                    message="Write a cli Blackjack Game",
+                    icon="/public/blackjack.jpg",
+                ),
+            ],
+        )
+    ]
+
+
+# https://docs.chainlit.io/concepts/message
+@cl.on_message
+async def startup(message: cl.Message) -> None:
+    """On Message in UI, Create a MetaGPT software company
+
+    Args:
+        message (chainlit.Message): message by chainlist
+    """
+    idea = message.content
+    company = Team(env=ChainlitEnv())
+
+    # Similar to software_company.py
+    company.hire(
+        [
+            ProductManager(),
+            Architect(),
+            ProjectManager(),
+            Engineer(n_borg=5, use_code_review=True),
+            QaEngineer(),
+        ]
+    )
+
+    company.invest(investment=3.0)
+    company.run_project(idea=idea)
+
+    await company.run(n_round=5)
+
+    workdir = company.env.context.git_repo.workdir
+    files = company.env.context.git_repo.get_files(workdir)
+    files = "\n".join([f"{workdir}/{file}" for file in files if not file.startswith(".git")])
+
+    await cl.Message(
+        content=f"""
+Codes can be found here:
+{files}
+
+---
+
+Total cost: `{company.cost_manager.total_cost}`
+"""
+    ).send()

examples/ui_with_chainlit/init_setup.py

@@ -0,0 +1,69 @@
+import asyncio
+
+import chainlit as cl
+
+from metagpt.environment import Environment
+from metagpt.logs import logger, set_llm_stream_logfunc
+from metagpt.roles import Role
+from metagpt.utils.common import any_to_name
+
+
+def log_llm_stream_chainlit(msg):
+    # Stream the message token into Chainlit UI.
+    cl.run_sync(chainlit_message.stream_token(msg))
+
+
+set_llm_stream_logfunc(func=log_llm_stream_chainlit)
+
+
+class ChainlitEnv(Environment):
+    """Chainlit Environment for UI Integration"""
+
+    async def run(self, k=1):
+        """处理一次所有信息的运行
+        Process all Role runs at once
+        """
+        for _ in range(k):
+            futures = []
+            for role in self.roles.values():
+                # Call role.run with chainlit configuration
+                future = self._chainlit_role_run(role=role)
+                futures.append(future)
+
+            await asyncio.gather(*futures)
+            logger.debug(f"is idle: {self.is_idle}")
+
+    async def _chainlit_role_run(self, role: Role) -> None:
+        """To run the role with chainlit config
+
+        Args:
+            role (Role): metagpt.role.Role
+        """
+        global chainlit_message
+        chainlit_message = cl.Message(content="")
+
+        message = await role.run()
+        # If message is from role._act() publish to UI.
+        if message is not None and message.content != "No actions taken yet":
+            # Convert a message from action node in json format
+            chainlit_message.content = await self._convert_message_to_markdownjson(message=chainlit_message.content)
+
+            # message content from which role and its action...
+            chainlit_message.content += f"---\n\nAction: `{any_to_name(message.cause_by)}` done by `{role._setting}`."
+
+            await chainlit_message.send()
+
+    # for clean view in UI
+    async def _convert_message_to_markdownjson(self, message: str) -> str:
+        """If the message is from MetaGPT Action Node output, then
+        convert it into markdown json for clear view in UI.
+
+        Args:
+            message (str): message by role._act
+
+        Returns:
+            str: message in mardown from
+        """
+        if message.startswith("[CONTENT]"):
+            return f"```json\n{message}\n```\n"
+        return message