mirror of
https://github.com/microsoft/autogen.git
synced 2025-12-27 15:09:41 +00:00
Add codespell to pre-commit hooks and fix spelling of existing files (#1161)
* fixed spelling, minor errors and reformatted using black * polishing * added codespell to pre-commit hooks, fixed a number of spelling errors and a few minor bugs in the code * update autogen library version in notebooks * update autogen library version in notebooks * update autogen library version in notebooks * update autogen library version in notebooks * update autogen library version in notebooks
This commit is contained in:
Davor Runje
GitHub
parent
295b8355f1
commit
8f065e06e4
@ -31,3 +31,15 @@ repos:
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hooks:
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- id: ruff
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args: ["--fix"]
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- repo: https://github.com/codespell-project/codespell
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rev: v2.2.6
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hooks:
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- id: codespell
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args: ["-L", "ans,linar,nam,"]
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exclude: |
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(?x)^(
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pyproject.toml |
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website/static/img/ag.svg |
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website/yarn.lock |
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notebook/.*
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)$
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@ -694,7 +694,7 @@ class ConversableAgent(Agent):
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tool_responses = message.get("tool_responses", [])
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if tool_responses:
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all_messages += tool_responses
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# tool role on the parent message means the content is just concatentation of all of the tool_responses
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# tool role on the parent message means the content is just concatenation of all of the tool_responses
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if message.get("role") != "tool":
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all_messages.append({key: message[key] for key in message if key != "tool_responses"})
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else:
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@ -1682,7 +1682,7 @@ class ConversableAgent(Agent):
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RuntimeError: if the LLM config is not set up before registering a function.
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"""
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# name can be overwriten by the parameter, by default it is the same as function name
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# name can be overwritten by the parameter, by default it is the same as function name
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if name:
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func._name = name
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elif not hasattr(func, "_name"):
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@ -1746,7 +1746,7 @@ class ConversableAgent(Agent):
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ValueError: if the function description is not provided and not propagated by a previous decorator.
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"""
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# name can be overwriten by the parameter, by default it is the same as function name
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# name can be overwritten by the parameter, by default it is the same as function name
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if name:
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func._name = name
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elif not hasattr(func, "_name"):
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@ -261,7 +261,7 @@ def config_list_from_models(
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"""
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Get a list of configs for API calls with models specified in the model list.
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This function extends `config_list_openai_aoai` by allowing to clone its' out for each fof the models provided.
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This function extends `config_list_openai_aoai` by allowing to clone its' out for each of the models provided.
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Each configuration will have a 'model' key with the model name as its value. This is particularly useful when
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all endpoints have same set of models.
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@ -1,183 +1,188 @@
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{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"provenance": [],
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"toc_visible": true
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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}
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},
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 26,
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"execution_count": 1,
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"metadata": {
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"id": "tLIs1YRdr8jM",
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"colab": {
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"base_uri": "https://localhost:8080/"
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},
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"id": "tLIs1YRdr8jM",
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"outputId": "909c1c70-1a22-4e9d-b7f4-a40e2d737fb0"
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},
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"outputs": [
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{
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"output_type": "stream",
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Requirement already satisfied: pyautogen==0.2.0 in /usr/local/lib/python3.10/dist-packages (0.2.0)\n",
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"Defaulting to user installation because normal site-packages is not writeable\n",
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||||
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"Requirement already satisfied: exceptiongroup>=1.0.2 in /home/vscode/.local/lib/python3.10/site-packages (from anyio<5,>=3.5.0->openai>=1.3->pyautogen>=0.2.3) (1.2.0)\n",
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"Requirement already satisfied: httpcore==1.* in /home/vscode/.local/lib/python3.10/site-packages (from httpx<1,>=0.23.0->openai>=1.3->pyautogen>=0.2.3) (1.0.2)\n",
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"Requirement already satisfied: h11<0.15,>=0.13 in /home/vscode/.local/lib/python3.10/site-packages (from httpcore==1.*->httpx<1,>=0.23.0->openai>=1.3->pyautogen>=0.2.3) (0.14.0)\n",
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"Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/site-packages (from requests>=2.26.0->tiktoken->pyautogen>=0.2.3) (3.3.2)\n",
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"Requirement already satisfied: urllib3<3,>=1.21.1 in /home/vscode/.local/lib/python3.10/site-packages (from requests>=2.26.0->tiktoken->pyautogen>=0.2.3) (1.26.18)\n",
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||||
"Defaulting to user installation because normal site-packages is not writeable\n",
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"Requirement already satisfied: tokenizers>=0.13.2 in /home/vscode/.local/lib/python3.10/site-packages (from chromadb) (0.15.0)\n",
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"Requirement already satisfied: googleapis-common-protos~=1.52 in /home/vscode/.local/lib/python3.10/site-packages (from opentelemetry-exporter-otlp-proto-grpc>=1.2.0->chromadb) (1.62.0)\n",
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"Requirement already satisfied: opentelemetry-proto==1.22.0 in /home/vscode/.local/lib/python3.10/site-packages (from opentelemetry-exporter-otlp-proto-grpc>=1.2.0->chromadb) (1.22.0)\n",
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"Requirement already satisfied: opentelemetry-semantic-conventions==0.43b0 in /home/vscode/.local/lib/python3.10/site-packages (from opentelemetry-instrumentation-fastapi>=0.41b0->chromadb) (0.43b0)\n",
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"Requirement already satisfied: opentelemetry-util-http==0.43b0 in /home/vscode/.local/lib/python3.10/site-packages (from opentelemetry-instrumentation-fastapi>=0.41b0->chromadb) (0.43b0)\n",
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"Requirement already satisfied: setuptools>=16.0 in /usr/local/lib/python3.10/site-packages (from opentelemetry-instrumentation==0.43b0->opentelemetry-instrumentation-fastapi>=0.41b0->chromadb) (69.0.2)\n",
|
||||
"Requirement already satisfied: wrapt<2.0.0,>=1.0.0 in /usr/local/lib/python3.10/site-packages (from opentelemetry-instrumentation==0.43b0->opentelemetry-instrumentation-fastapi>=0.41b0->chromadb) (1.16.0)\n",
|
||||
"Requirement already satisfied: asgiref~=3.0 in /home/vscode/.local/lib/python3.10/site-packages (from opentelemetry-instrumentation-asgi==0.43b0->opentelemetry-instrumentation-fastapi>=0.41b0->chromadb) (3.7.2)\n",
|
||||
"Requirement already satisfied: monotonic>=1.5 in /home/vscode/.local/lib/python3.10/site-packages (from posthog>=2.4.0->chromadb) (1.6)\n",
|
||||
"Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/site-packages (from requests>=2.28->chromadb) (3.3.2)\n",
|
||||
"Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/site-packages (from requests>=2.28->chromadb) (3.6)\n",
|
||||
"Requirement already satisfied: huggingface_hub<1.0,>=0.16.4 in /home/vscode/.local/lib/python3.10/site-packages (from tokenizers>=0.13.2->chromadb) (0.20.2)\n",
|
||||
"Requirement already satisfied: click<9.0.0,>=7.1.1 in /usr/local/lib/python3.10/site-packages (from typer>=0.9.0->chromadb) (8.1.7)\n",
|
||||
"Requirement already satisfied: h11>=0.8 in /home/vscode/.local/lib/python3.10/site-packages (from uvicorn>=0.18.3->uvicorn[standard]>=0.18.3->chromadb) (0.14.0)\n",
|
||||
"Requirement already satisfied: httptools>=0.5.0 in /home/vscode/.local/lib/python3.10/site-packages (from uvicorn[standard]>=0.18.3->chromadb) (0.6.1)\n",
|
||||
"Requirement already satisfied: python-dotenv>=0.13 in /home/vscode/.local/lib/python3.10/site-packages (from uvicorn[standard]>=0.18.3->chromadb) (1.0.0)\n",
|
||||
"Requirement already satisfied: uvloop!=0.15.0,!=0.15.1,>=0.14.0 in /home/vscode/.local/lib/python3.10/site-packages (from uvicorn[standard]>=0.18.3->chromadb) (0.19.0)\n",
|
||||
"Requirement already satisfied: watchfiles>=0.13 in /home/vscode/.local/lib/python3.10/site-packages (from uvicorn[standard]>=0.18.3->chromadb) (0.21.0)\n",
|
||||
"Requirement already satisfied: websockets>=10.4 in /home/vscode/.local/lib/python3.10/site-packages (from uvicorn[standard]>=0.18.3->chromadb) (12.0)\n",
|
||||
"Requirement already satisfied: cachetools<6.0,>=2.0.0 in /home/vscode/.local/lib/python3.10/site-packages (from google-auth>=1.0.1->kubernetes>=28.1.0->chromadb) (5.3.2)\n",
|
||||
"Requirement already satisfied: pyasn1-modules>=0.2.1 in /home/vscode/.local/lib/python3.10/site-packages (from google-auth>=1.0.1->kubernetes>=28.1.0->chromadb) (0.3.0)\n",
|
||||
"Requirement already satisfied: rsa<5,>=3.1.4 in /home/vscode/.local/lib/python3.10/site-packages (from google-auth>=1.0.1->kubernetes>=28.1.0->chromadb) (4.9)\n",
|
||||
"Requirement already satisfied: filelock in /home/vscode/.local/lib/python3.10/site-packages (from huggingface_hub<1.0,>=0.16.4->tokenizers>=0.13.2->chromadb) (3.13.1)\n",
|
||||
"Requirement already satisfied: fsspec>=2023.5.0 in /home/vscode/.local/lib/python3.10/site-packages (from huggingface_hub<1.0,>=0.16.4->tokenizers>=0.13.2->chromadb) (2023.12.2)\n",
|
||||
"Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.10/site-packages (from importlib-metadata<7.0,>=6.0->opentelemetry-api>=1.2.0->chromadb) (3.17.0)\n",
|
||||
"Requirement already satisfied: anyio<5,>=3.4.0 in /home/vscode/.local/lib/python3.10/site-packages (from starlette<0.33.0,>=0.29.0->fastapi>=0.95.2->chromadb) (4.2.0)\n",
|
||||
"Requirement already satisfied: humanfriendly>=9.1 in /home/vscode/.local/lib/python3.10/site-packages (from coloredlogs->onnxruntime>=1.14.1->chromadb) (10.0)\n",
|
||||
"Requirement already satisfied: mpmath>=0.19 in /home/vscode/.local/lib/python3.10/site-packages (from sympy->onnxruntime>=1.14.1->chromadb) (1.3.0)\n",
|
||||
"Requirement already satisfied: sniffio>=1.1 in /home/vscode/.local/lib/python3.10/site-packages (from anyio<5,>=3.4.0->starlette<0.33.0,>=0.29.0->fastapi>=0.95.2->chromadb) (1.3.0)\n",
|
||||
"Requirement already satisfied: exceptiongroup>=1.0.2 in /home/vscode/.local/lib/python3.10/site-packages (from anyio<5,>=3.4.0->starlette<0.33.0,>=0.29.0->fastapi>=0.95.2->chromadb) (1.2.0)\n",
|
||||
"Requirement already satisfied: pyasn1<0.6.0,>=0.4.6 in /home/vscode/.local/lib/python3.10/site-packages (from pyasn1-modules>=0.2.1->google-auth>=1.0.1->kubernetes>=28.1.0->chromadb) (0.5.1)\n",
|
||||
"Defaulting to user installation because normal site-packages is not writeable\n",
|
||||
"Requirement already satisfied: sentence_transformers in /home/vscode/.local/lib/python3.10/site-packages (2.2.2)\n",
|
||||
"Requirement already satisfied: transformers<5.0.0,>=4.6.0 in /home/vscode/.local/lib/python3.10/site-packages (from sentence_transformers) (4.36.2)\n",
|
||||
"Requirement already satisfied: tqdm in /home/vscode/.local/lib/python3.10/site-packages (from sentence_transformers) (4.66.1)\n",
|
||||
"Requirement already satisfied: torch>=1.6.0 in /home/vscode/.local/lib/python3.10/site-packages (from sentence_transformers) (2.1.2)\n",
|
||||
"Requirement already satisfied: torchvision in /home/vscode/.local/lib/python3.10/site-packages (from sentence_transformers) (0.16.2)\n",
|
||||
"Requirement already satisfied: numpy in /home/vscode/.local/lib/python3.10/site-packages (from sentence_transformers) (1.26.3)\n",
|
||||
"Requirement already satisfied: scikit-learn in /home/vscode/.local/lib/python3.10/site-packages (from sentence_transformers) (1.3.2)\n",
|
||||
"Requirement already satisfied: scipy in /home/vscode/.local/lib/python3.10/site-packages (from sentence_transformers) (1.11.4)\n",
|
||||
"Requirement already satisfied: nltk in /home/vscode/.local/lib/python3.10/site-packages (from sentence_transformers) (3.8.1)\n",
|
||||
"Requirement already satisfied: sentencepiece in /home/vscode/.local/lib/python3.10/site-packages (from sentence_transformers) (0.1.99)\n",
|
||||
"Requirement already satisfied: huggingface-hub>=0.4.0 in /home/vscode/.local/lib/python3.10/site-packages (from sentence_transformers) (0.20.2)\n",
|
||||
"Requirement already satisfied: filelock in /home/vscode/.local/lib/python3.10/site-packages (from huggingface-hub>=0.4.0->sentence_transformers) (3.13.1)\n",
|
||||
"Requirement already satisfied: fsspec>=2023.5.0 in /home/vscode/.local/lib/python3.10/site-packages (from huggingface-hub>=0.4.0->sentence_transformers) (2023.12.2)\n",
|
||||
"Requirement already satisfied: requests in /usr/local/lib/python3.10/site-packages (from huggingface-hub>=0.4.0->sentence_transformers) (2.31.0)\n",
|
||||
"Requirement already satisfied: pyyaml>=5.1 in /usr/local/lib/python3.10/site-packages (from huggingface-hub>=0.4.0->sentence_transformers) (6.0.1)\n",
|
||||
"Requirement already satisfied: typing-extensions>=3.7.4.3 in /home/vscode/.local/lib/python3.10/site-packages (from huggingface-hub>=0.4.0->sentence_transformers) (4.9.0)\n",
|
||||
"Requirement already satisfied: packaging>=20.9 in /usr/local/lib/python3.10/site-packages (from huggingface-hub>=0.4.0->sentence_transformers) (23.2)\n",
|
||||
"Requirement already satisfied: sympy in /home/vscode/.local/lib/python3.10/site-packages (from torch>=1.6.0->sentence_transformers) (1.12)\n",
|
||||
"Requirement already satisfied: networkx in /home/vscode/.local/lib/python3.10/site-packages (from torch>=1.6.0->sentence_transformers) (3.2.1)\n",
|
||||
"Requirement already satisfied: jinja2 in /usr/local/lib/python3.10/site-packages (from torch>=1.6.0->sentence_transformers) (3.1.2)\n",
|
||||
"Requirement already satisfied: nvidia-cuda-nvrtc-cu12==12.1.105 in /home/vscode/.local/lib/python3.10/site-packages (from torch>=1.6.0->sentence_transformers) (12.1.105)\n",
|
||||
"Requirement already satisfied: nvidia-cuda-runtime-cu12==12.1.105 in /home/vscode/.local/lib/python3.10/site-packages (from torch>=1.6.0->sentence_transformers) (12.1.105)\n",
|
||||
"Requirement already satisfied: nvidia-cuda-cupti-cu12==12.1.105 in /home/vscode/.local/lib/python3.10/site-packages (from torch>=1.6.0->sentence_transformers) (12.1.105)\n",
|
||||
"Requirement already satisfied: nvidia-cudnn-cu12==8.9.2.26 in /home/vscode/.local/lib/python3.10/site-packages (from torch>=1.6.0->sentence_transformers) (8.9.2.26)\n",
|
||||
"Requirement already satisfied: nvidia-cublas-cu12==12.1.3.1 in /home/vscode/.local/lib/python3.10/site-packages (from torch>=1.6.0->sentence_transformers) (12.1.3.1)\n",
|
||||
"Requirement already satisfied: nvidia-cufft-cu12==11.0.2.54 in /home/vscode/.local/lib/python3.10/site-packages (from torch>=1.6.0->sentence_transformers) (11.0.2.54)\n",
|
||||
"Requirement already satisfied: nvidia-curand-cu12==10.3.2.106 in /home/vscode/.local/lib/python3.10/site-packages (from torch>=1.6.0->sentence_transformers) (10.3.2.106)\n",
|
||||
"Requirement already satisfied: nvidia-cusolver-cu12==11.4.5.107 in /home/vscode/.local/lib/python3.10/site-packages (from torch>=1.6.0->sentence_transformers) (11.4.5.107)\n",
|
||||
"Requirement already satisfied: nvidia-cusparse-cu12==12.1.0.106 in /home/vscode/.local/lib/python3.10/site-packages (from torch>=1.6.0->sentence_transformers) (12.1.0.106)\n",
|
||||
"Requirement already satisfied: nvidia-nccl-cu12==2.18.1 in /home/vscode/.local/lib/python3.10/site-packages (from torch>=1.6.0->sentence_transformers) (2.18.1)\n",
|
||||
"Requirement already satisfied: nvidia-nvtx-cu12==12.1.105 in /home/vscode/.local/lib/python3.10/site-packages (from torch>=1.6.0->sentence_transformers) (12.1.105)\n",
|
||||
"Requirement already satisfied: triton==2.1.0 in /home/vscode/.local/lib/python3.10/site-packages (from torch>=1.6.0->sentence_transformers) (2.1.0)\n",
|
||||
"Requirement already satisfied: nvidia-nvjitlink-cu12 in /home/vscode/.local/lib/python3.10/site-packages (from nvidia-cusolver-cu12==11.4.5.107->torch>=1.6.0->sentence_transformers) (12.3.101)\n",
|
||||
"Requirement already satisfied: regex!=2019.12.17 in /home/vscode/.local/lib/python3.10/site-packages (from transformers<5.0.0,>=4.6.0->sentence_transformers) (2023.12.25)\n",
|
||||
"Requirement already satisfied: tokenizers<0.19,>=0.14 in /home/vscode/.local/lib/python3.10/site-packages (from transformers<5.0.0,>=4.6.0->sentence_transformers) (0.15.0)\n",
|
||||
"Requirement already satisfied: safetensors>=0.3.1 in /home/vscode/.local/lib/python3.10/site-packages (from transformers<5.0.0,>=4.6.0->sentence_transformers) (0.4.1)\n",
|
||||
"Requirement already satisfied: click in /usr/local/lib/python3.10/site-packages (from nltk->sentence_transformers) (8.1.7)\n",
|
||||
"Requirement already satisfied: joblib in /home/vscode/.local/lib/python3.10/site-packages (from nltk->sentence_transformers) (1.3.2)\n",
|
||||
"Requirement already satisfied: threadpoolctl>=2.0.0 in /home/vscode/.local/lib/python3.10/site-packages (from scikit-learn->sentence_transformers) (3.2.0)\n",
|
||||
"Requirement already satisfied: pillow!=8.3.*,>=5.3.0 in /home/vscode/.local/lib/python3.10/site-packages (from torchvision->sentence_transformers) (10.2.0)\n",
|
||||
"Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.10/site-packages (from jinja2->torch>=1.6.0->sentence_transformers) (2.1.3)\n",
|
||||
"Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/site-packages (from requests->huggingface-hub>=0.4.0->sentence_transformers) (3.3.2)\n",
|
||||
"Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/site-packages (from requests->huggingface-hub>=0.4.0->sentence_transformers) (3.6)\n",
|
||||
"Requirement already satisfied: urllib3<3,>=1.21.1 in /home/vscode/.local/lib/python3.10/site-packages (from requests->huggingface-hub>=0.4.0->sentence_transformers) (1.26.18)\n",
|
||||
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/site-packages (from requests->huggingface-hub>=0.4.0->sentence_transformers) (2023.11.17)\n",
|
||||
"Requirement already satisfied: mpmath>=0.19 in /home/vscode/.local/lib/python3.10/site-packages (from sympy->torch>=1.6.0->sentence_transformers) (1.3.0)\n",
|
||||
"Defaulting to user installation because normal site-packages is not writeable\n",
|
||||
"Requirement already satisfied: tiktoken in /home/vscode/.local/lib/python3.10/site-packages (0.5.2)\n",
|
||||
"Requirement already satisfied: regex>=2022.1.18 in /home/vscode/.local/lib/python3.10/site-packages (from tiktoken) (2023.12.25)\n",
|
||||
"Requirement already satisfied: requests>=2.26.0 in /usr/local/lib/python3.10/site-packages (from tiktoken) (2.31.0)\n",
|
||||
"Requirement already satisfied: charset-normalizer<4,>=2 in /usr/local/lib/python3.10/site-packages (from requests>=2.26.0->tiktoken) (3.3.2)\n",
|
||||
"Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.10/site-packages (from requests>=2.26.0->tiktoken) (3.6)\n",
|
||||
"Requirement already satisfied: urllib3<3,>=1.21.1 in /home/vscode/.local/lib/python3.10/site-packages (from requests>=2.26.0->tiktoken) (1.26.18)\n",
|
||||
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.10/site-packages (from requests>=2.26.0->tiktoken) (2023.11.17)\n",
|
||||
"Defaulting to user installation because normal site-packages is not writeable\n",
|
||||
"Requirement already satisfied: pypdf in /home/vscode/.local/lib/python3.10/site-packages (3.17.4)\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"!pip install pyautogen==0.2.0\n",
|
||||
"!pip install \"pyautogen>=0.2.3\"\n",
|
||||
"!pip install chromadb\n",
|
||||
"!pip install sentence_transformers\n",
|
||||
"!pip install tiktoken\n",
|
||||
@ -186,19 +191,24 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "yU8zQPetsW28"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from autogen import AssistantAgent\n",
|
||||
"from autogen.agentchat.contrib.retrieve_user_proxy_agent import RetrieveUserProxyAgent\n",
|
||||
"from autogen.agentchat.user_proxy_agent import UserProxyAgent"
|
||||
],
|
||||
"metadata": {
|
||||
"id": "yU8zQPetsW28"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": []
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "R2ITRFQisgzI"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from typing import Callable, Dict, Optional, Union, List, Tuple, Any\n",
|
||||
"import asyncio\n",
|
||||
@ -255,15 +265,15 @@
|
||||
" await super().a_receive(message, sender, request_reply, silent)\n",
|
||||
"\n",
|
||||
"\n"
|
||||
],
|
||||
"metadata": {
|
||||
"id": "R2ITRFQisgzI"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": []
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"id": "2v_DhqBFuA1O"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def create_llm_config(model, temperature, seed):\n",
|
||||
" config_list = [\n",
|
||||
@ -280,18 +290,11 @@
|
||||
" }\n",
|
||||
"\n",
|
||||
" return llm_config\n"
|
||||
],
|
||||
"metadata": {
|
||||
"id": "2v_DhqBFuA1O"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": []
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"!pip install nest-asyncio"
|
||||
],
|
||||
"execution_count": null,
|
||||
"metadata": {
|
||||
"colab": {
|
||||
"base_uri": "https://localhost:8080/"
|
||||
@ -299,53 +302,29 @@
|
||||
"id": "yHIUO2CiwfIp",
|
||||
"outputId": "79ceccca-f91c-4dde-9e21-1f2129cdc1a8"
|
||||
},
|
||||
"execution_count": null,
|
||||
"outputs": [
|
||||
{
|
||||
"output_type": "stream",
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Requirement already satisfied: nest-asyncio in /usr/local/lib/python3.10/dist-packages (1.5.8)\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"!pip install nest-asyncio"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"source": [
|
||||
"import nest_asyncio\n",
|
||||
"nest_asyncio.apply()\n",
|
||||
"\n",
|
||||
"async def main():\n",
|
||||
" boss = CustomisedUserProxyAgent(\n",
|
||||
" name=\"boss\",\n",
|
||||
" human_input_mode=\"ALWAYS\",\n",
|
||||
" max_consecutive_auto_reply=0,\n",
|
||||
" code_execution_config=False,\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
" assistant = CustomisedAssistantAgent(\n",
|
||||
" name=\"assistant\",\n",
|
||||
" system_message=\"You will provide some agenda, and I will create questions for an interview meeting.Everytime when you generate question then you have to ask user for feedback and if user provides the feedback then you have to incorporate that feedback and generate new set of questions and if user don't want to update then terminate the process and exit\",\n",
|
||||
" llm_config=create_llm_config(\"gpt-4\", \"0.4\", \"23\"),\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
" await boss.a_initiate_chat(\n",
|
||||
" assistant,\n",
|
||||
" message=\"Resume Review, Technical Skills Assessment, Project Discussion, Job Role Expectations, Closing Remarks.\",\n",
|
||||
" n_results=3,\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
"await main()"
|
||||
],
|
||||
"execution_count": 25,
|
||||
"metadata": {
|
||||
"id": "ywFsRNMDteaH",
|
||||
"colab": {
|
||||
"base_uri": "https://localhost:8080/"
|
||||
},
|
||||
"id": "ywFsRNMDteaH",
|
||||
"outputId": "5716adad-de80-4595-eec9-523b1f1cd313"
|
||||
},
|
||||
"execution_count": 25,
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
@ -370,7 +349,57 @@
|
||||
"Provide feedback to assistant. Press enter to skip and use auto-reply, or type 'exit' to end the conversation: exit\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"import nest_asyncio\n",
|
||||
"nest_asyncio.apply()\n",
|
||||
"\n",
|
||||
"async def main():\n",
|
||||
" boss = CustomisedUserProxyAgent(\n",
|
||||
" name=\"boss\",\n",
|
||||
" human_input_mode=\"ALWAYS\",\n",
|
||||
" max_consecutive_auto_reply=0,\n",
|
||||
" code_execution_config=False,\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
" assistant = CustomisedAssistantAgent(\n",
|
||||
" name=\"assistant\",\n",
|
||||
" system_message=\"You will provide some agenda, and I will create questions for an interview meeting. Every time when you generate question then you have to ask user for feedback and if user provides the feedback then you have to incorporate that feedback and generate new set of questions and if user don't want to update then terminate the process and exit\",\n",
|
||||
" llm_config=create_llm_config(\"gpt-4\", \"0.4\", \"23\"),\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
" await boss.a_initiate_chat(\n",
|
||||
" assistant,\n",
|
||||
" message=\"Resume Review, Technical Skills Assessment, Project Discussion, Job Role Expectations, Closing Remarks.\",\n",
|
||||
" n_results=3,\n",
|
||||
" )\n",
|
||||
"\n",
|
||||
"await main()"
|
||||
]
|
||||
}
|
||||
]
|
||||
],
|
||||
"metadata": {
|
||||
"colab": {
|
||||
"provenance": [],
|
||||
"toc_visible": true
|
||||
},
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.10.13"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 0
|
||||
}
|
||||
|
||||
@ -117,7 +117,7 @@
|
||||
"source": [
|
||||
"## Construct agents for MathChat\n",
|
||||
"\n",
|
||||
"We start by initialzing the `AssistantAgent` and `MathUserProxyAgent`. The system message needs to be set to \"You are a helpful assistant.\" for MathChat. The detailed instructions are given in the user message. Later we will use the `MathUserProxyAgent.generate_init_message` to combine the instructions and a math problem for an initial message to be sent to the LLM assistant."
|
||||
"We start by initializing the `AssistantAgent` and `MathUserProxyAgent`. The system message needs to be set to \"You are a helpful assistant.\" for MathChat. The detailed instructions are given in the user message. Later we will use the `MathUserProxyAgent.generate_init_message` to combine the instructions and a math problem for an initial message to be sent to the LLM assistant."
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -266,7 +266,7 @@
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# we set the prompt_type to \"python\", which is a simplied version of the default prompt.\n",
|
||||
"# we set the prompt_type to \"python\", which is a simplified version of the default prompt.\n",
|
||||
"math_problem = \"Problem: If $725x + 727y = 1500$ and $729x+ 731y = 1508$, what is the value of $x - y$ ?\"\n",
|
||||
"mathproxyagent.initiate_chat(assistant, problem=math_problem, prompt_type=\"python\")"
|
||||
]
|
||||
|
||||
@ -42,7 +42,7 @@
|
||||
"\n",
|
||||
"AutoGen requires `Python>=3.8`. To run this notebook example, please install the [retrievechat] option.\n",
|
||||
"```bash\n",
|
||||
"pip install \"pyautogen[retrievechat]~=0.2.0b5\" \"flaml[automl]\"\n",
|
||||
"pip install \"pyautogen[retrievechat]>=0.2.3\" \"flaml[automl]\"\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
@ -52,7 +52,7 @@
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# %pip install \"pyautogen[retrievechat]~=0.2.0b5\" \"flaml[automl]\""
|
||||
"# %pip install \"pyautogen[retrievechat]>=0.2.3\" \"flaml[automl]\""
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -143,7 +143,7 @@
|
||||
"source": [
|
||||
"## Construct agents for RetrieveChat\n",
|
||||
"\n",
|
||||
"We start by initialzing the `RetrieveAssistantAgent` and `RetrieveUserProxyAgent`. The system message needs to be set to \"You are a helpful assistant.\" for RetrieveAssistantAgent. The detailed instructions are given in the user message. Later we will use the `RetrieveUserProxyAgent.generate_init_prompt` to combine the instructions and a retrieval augmented generation task for an initial prompt to be sent to the LLM assistant."
|
||||
"We start by initializing the `RetrieveAssistantAgent` and `RetrieveUserProxyAgent`. The system message needs to be set to \"You are a helpful assistant.\" for RetrieveAssistantAgent. The detailed instructions are given in the user message. Later we will use the `RetrieveUserProxyAgent.generate_init_prompt` to combine the instructions and a retrieval augmented generation task for an initial prompt to be sent to the LLM assistant."
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -198,7 +198,7 @@
|
||||
"# `task` indicates the kind of task we're working on. In this example, it's a `code` task.\n",
|
||||
"# `chunk_token_size` is the chunk token size for the retrieve chat. By default, it is set to `max_tokens * 0.6`, here we set it to 2000.\n",
|
||||
"# `custom_text_types` is a list of file types to be processed. Default is `autogen.retrieve_utils.TEXT_FORMATS`.\n",
|
||||
"# This only applies to files under the directories in `docs_path`. Explictly included files and urls will be chunked regardless of their types.\n",
|
||||
"# This only applies to files under the directories in `docs_path`. Explicitly included files and urls will be chunked regardless of their types.\n",
|
||||
"# In this example, we set it to [\"mdx\"] to only process markdown files. Since no mdx files are included in the `websit/docs`,\n",
|
||||
"# no files there will be processed. However, the explicitly included urls will still be processed.\n",
|
||||
"ragproxyagent = RetrieveUserProxyAgent(\n",
|
||||
@ -377,7 +377,7 @@
|
||||
"\n",
|
||||
"\n",
|
||||
"- `use_spark`: boolean, default=False | Whether to use spark to run the training in parallel spark jobs. This can be used to accelerate training on large models and large datasets, but will incur more overhead in time and thus slow down training in some cases. GPU training is not supported yet when use_spark is True. For Spark clusters, by default, we will launch one trial per executor. However, sometimes we want to launch more trials than the number of executors (e.g., local mode). In this case, we can set the environment variable `FLAML_MAX_CONCURRENT` to override the detected `num_executors`. The final number of concurrent trials will be the minimum of `n_concurrent_trials` and `num_executors`.\n",
|
||||
"- `n_concurrent_trials`: int, default=1 | The number of concurrent trials. When n_concurrent_trials > 1, FLAML performes parallel tuning.\n",
|
||||
"- `n_concurrent_trials`: int, default=1 | The number of concurrent trials. When n_concurrent_trials > 1, FLAML performs parallel tuning.\n",
|
||||
"- `force_cancel`: boolean, default=False | Whether to forcely cancel Spark jobs if the search time exceeded the time budget. Spark jobs include parallel tuning jobs and Spark-based model training jobs.\n",
|
||||
"\n",
|
||||
"An example code snippet for using parallel Spark jobs:\n",
|
||||
@ -669,7 +669,7 @@
|
||||
"\n",
|
||||
"\n",
|
||||
"- `use_spark`: boolean, default=False | Whether to use spark to run the training in parallel spark jobs. This can be used to accelerate training on large models and large datasets, but will incur more overhead in time and thus slow down training in some cases. GPU training is not supported yet when use_spark is True. For Spark clusters, by default, we will launch one trial per executor. However, sometimes we want to launch more trials than the number of executors (e.g., local mode). In this case, we can set the environment variable `FLAML_MAX_CONCURRENT` to override the detected `num_executors`. The final number of concurrent trials will be the minimum of `n_concurrent_trials` and `num_executors`.\n",
|
||||
"- `n_concurrent_trials`: int, default=1 | The number of concurrent trials. When n_concurrent_trials > 1, FLAML performes parallel tuning.\n",
|
||||
"- `n_concurrent_trials`: int, default=1 | The number of concurrent trials. When n_concurrent_trials > 1, FLAML performs parallel tuning.\n",
|
||||
"- `force_cancel`: boolean, default=False | Whether to forcely cancel Spark jobs if the search time exceeded the time budget. Spark jobs include parallel tuning jobs and Spark-based model training jobs.\n",
|
||||
"\n",
|
||||
"An example code snippet for using parallel Spark jobs:\n",
|
||||
@ -922,7 +922,7 @@
|
||||
"\n",
|
||||
"\n",
|
||||
"- `use_spark`: boolean, default=False | Whether to use spark to run the training in parallel spark jobs. This can be used to accelerate training on large models and large datasets, but will incur more overhead in time and thus slow down training in some cases. GPU training is not supported yet when use_spark is True. For Spark clusters, by default, we will launch one trial per executor. However, sometimes we want to launch more trials than the number of executors (e.g., local mode). In this case, we can set the environment variable `FLAML_MAX_CONCURRENT` to override the detected `num_executors`. The final number of concurrent trials will be the minimum of `n_concurrent_trials` and `num_executors`.\n",
|
||||
"- `n_concurrent_trials`: int, default=1 | The number of concurrent trials. When n_concurrent_trials > 1, FLAML performes parallel tuning.\n",
|
||||
"- `n_concurrent_trials`: int, default=1 | The number of concurrent trials. When n_concurrent_trials > 1, FLAML performs parallel tuning.\n",
|
||||
"- `force_cancel`: boolean, default=False | Whether to forcely cancel Spark jobs if the search time exceeded the time budget. Spark jobs include parallel tuning jobs and Spark-based model training jobs.\n",
|
||||
"\n",
|
||||
"An example code snippet for using parallel Spark jobs:\n",
|
||||
@ -1224,7 +1224,7 @@
|
||||
"\n",
|
||||
"\n",
|
||||
"- `use_spark`: boolean, default=False | Whether to use spark to run the training in parallel spark jobs. This can be used to accelerate training on large models and large datasets, but will incur more overhead in time and thus slow down training in some cases. GPU training is not supported yet when use_spark is True. For Spark clusters, by default, we will launch one trial per executor. However, sometimes we want to launch more trials than the number of executors (e.g., local mode). In this case, we can set the environment variable `FLAML_MAX_CONCURRENT` to override the detected `num_executors`. The final number of concurrent trials will be the minimum of `n_concurrent_trials` and `num_executors`.\n",
|
||||
"- `n_concurrent_trials`: int, default=1 | The number of concurrent trials. When n_concurrent_trials > 1, FLAML performes parallel tuning.\n",
|
||||
"- `n_concurrent_trials`: int, default=1 | The number of concurrent trials. When n_concurrent_trials > 1, FLAML performs parallel tuning.\n",
|
||||
"- `force_cancel`: boolean, default=False | Whether to forcely cancel Spark jobs if the search time exceeded the time budget. Spark jobs include parallel tuning jobs and Spark-based model training jobs.\n",
|
||||
"\n",
|
||||
"An example code snippet for using parallel Spark jobs:\n",
|
||||
@ -1638,7 +1638,7 @@
|
||||
"\n",
|
||||
"\n",
|
||||
"- `use_spark`: boolean, default=False | Whether to use spark to run the training in parallel spark jobs. This can be used to accelerate training on large models and large datasets, but will incur more overhead in time and thus slow down training in some cases. GPU training is not supported yet when use_spark is True. For Spark clusters, by default, we will launch one trial per executor. However, sometimes we want to launch more trials than the number of executors (e.g., local mode). In this case, we can set the environment variable `FLAML_MAX_CONCURRENT` to override the detected `num_executors`. The final number of concurrent trials will be the minimum of `n_concurrent_trials` and `num_executors`.\n",
|
||||
"- `n_concurrent_trials`: int, default=1 | The number of concurrent trials. When n_concurrent_trials > 1, FLAML performes parallel tuning.\n",
|
||||
"- `n_concurrent_trials`: int, default=1 | The number of concurrent trials. When n_concurrent_trials > 1, FLAML performs parallel tuning.\n",
|
||||
"- `force_cancel`: boolean, default=False | Whether to forcely cancel Spark jobs if the search time exceeded the time budget. Spark jobs include parallel tuning jobs and Spark-based model training jobs.\n",
|
||||
"\n",
|
||||
"An example code snippet for using parallel Spark jobs:\n",
|
||||
@ -1891,7 +1891,7 @@
|
||||
"\n",
|
||||
"\n",
|
||||
"- `use_spark`: boolean, default=False | Whether to use spark to run the training in parallel spark jobs. This can be used to accelerate training on large models and large datasets, but will incur more overhead in time and thus slow down training in some cases. GPU training is not supported yet when use_spark is True. For Spark clusters, by default, we will launch one trial per executor. However, sometimes we want to launch more trials than the number of executors (e.g., local mode). In this case, we can set the environment variable `FLAML_MAX_CONCURRENT` to override the detected `num_executors`. The final number of concurrent trials will be the minimum of `n_concurrent_trials` and `num_executors`.\n",
|
||||
"- `n_concurrent_trials`: int, default=1 | The number of concurrent trials. When n_concurrent_trials > 1, FLAML performes parallel tuning.\n",
|
||||
"- `n_concurrent_trials`: int, default=1 | The number of concurrent trials. When n_concurrent_trials > 1, FLAML performs parallel tuning.\n",
|
||||
"- `force_cancel`: boolean, default=False | Whether to forcely cancel Spark jobs if the search time exceeded the time budget. Spark jobs include parallel tuning jobs and Spark-based model training jobs.\n",
|
||||
"\n",
|
||||
"An example code snippet for using parallel Spark jobs:\n",
|
||||
|
||||
@ -45,7 +45,7 @@
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# %pip install pyautogen~=0.2.0b4"
|
||||
"# %pip install pyautogen>=0.2.3"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -35,7 +35,7 @@
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"%%capture --no-stderr\n",
|
||||
"# %pip install \"pyautogen~=0.2.0b4\"\n",
|
||||
"# %pip install \"pyautogen>=0.2.3\"\n",
|
||||
"%pip install chess -U"
|
||||
]
|
||||
},
|
||||
|
||||
@ -549,7 +549,7 @@
|
||||
" compress_config={\n",
|
||||
" \"mode\": \"COMPRESS\",\n",
|
||||
" \"trigger_count\": 600, # set this to a large number for less frequent compression\n",
|
||||
" \"verbose\": True, # to allow printing of compression information: contex before and after compression\n",
|
||||
" \"verbose\": True, # to allow printing of compression information: context before and after compression\n",
|
||||
" \"leave_last_n\": 2,\n",
|
||||
" }\n",
|
||||
")\n",
|
||||
@ -835,7 +835,7 @@
|
||||
" code_execution_config={\"work_dir\": \"coding\"},\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"# define functions according to the function desription\n",
|
||||
"# define functions according to the function description\n",
|
||||
"from IPython import get_ipython\n",
|
||||
"\n",
|
||||
"def exec_python(cell):\n",
|
||||
|
||||
@ -17,7 +17,7 @@
|
||||
"source": [
|
||||
"### Before everything starts, install AutoGen with the `lmm` option\n",
|
||||
"```bash\n",
|
||||
"pip install \"pyautogen[lmm]~=0.2.0b4\"\n",
|
||||
"pip install \"pyautogen[lmm]>=0.2.3\"\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
@ -401,7 +401,7 @@
|
||||
"How to create a figure that is better in terms of color, shape, text (clarity), and other things.\n",
|
||||
"Reply with the following format:\n",
|
||||
"\n",
|
||||
"CIRITICS: the image needs to improve...\n",
|
||||
"CRITICS: the image needs to improve...\n",
|
||||
"PROMPT: here is the updated prompt!\n",
|
||||
"\n",
|
||||
"\"\"\",\n",
|
||||
@ -432,7 +432,7 @@
|
||||
" self.msg_to_critics = f\"\"\"Here is the prompt: {img_prompt}.\n",
|
||||
" Here is the figure <img result.png>.\n",
|
||||
" Now, critic and create a prompt so that DALLE can give me a better image.\n",
|
||||
" Show me both \"CIRITICS\" and \"PROMPT\"!\n",
|
||||
" Show me both \"CRITICS\" and \"PROMPT\"!\n",
|
||||
" \"\"\"\n",
|
||||
" self.send(message=self.msg_to_critics,\n",
|
||||
" recipient=self.critics,\n",
|
||||
@ -615,7 +615,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.9.16"
|
||||
"version": "3.10.13"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
||||
@ -36,7 +36,7 @@
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# %pip install \"pyautogen~=0.2.2\""
|
||||
"# %pip install \"pyautogen>=0.2.3\""
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -36,7 +36,7 @@
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# %pip install \"pyautogen~=0.2.2\""
|
||||
"# %pip install \"pyautogen>=0.2.3\""
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -222,7 +222,7 @@
|
||||
"\n",
|
||||
"- objects of the Pydantic BaseModel type are serialized to JSON.\n",
|
||||
"\n",
|
||||
"We can check the correctness of of function map by using `._origin` property of the wrapped funtion as follows:"
|
||||
"We can check the correctness of of function map by using `._origin` property of the wrapped function as follows:"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -33,26 +33,26 @@
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"%%capture --no-stderr\n",
|
||||
"# %pip install pyautogen~=0.2.0b6\n",
|
||||
"# %pip install \"pyautogen>=0.2.3\"\n",
|
||||
"%pip install networkX~=3.2.1\n",
|
||||
"%pip install matplotlib~=3.8.1"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"execution_count": 3,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"0.2.0b6\n"
|
||||
"0.2.3\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
@ -471,7 +471,7 @@
|
||||
" \n",
|
||||
" If you are the team leader, you should aggregate your team's total chocolate count to cooperate.\n",
|
||||
" Once the team leader know their team's tally, they can suggest another team leader for them to find their team tally, because we need all three team tallys to succeed.\n",
|
||||
" Use NEXT: to sugest the next speaker, e.g., NEXT: A0.\n",
|
||||
" Use NEXT: to suggest the next speaker, e.g., NEXT: A0.\n",
|
||||
" \n",
|
||||
" Once we have the total tally from all nine players, sum up all three teams' tally, then terminate the discussion using TERMINATE.\n",
|
||||
" \n",
|
||||
@ -777,7 +777,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.10.12"
|
||||
"version": "3.10.13"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
||||
@ -35,7 +35,7 @@
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"%%capture --no-stderr\n",
|
||||
"# %pip install pyautogen~=0.2.0b4"
|
||||
"# %pip install \"pyautogen>=0.2.3\""
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -22,7 +22,7 @@
|
||||
"\n",
|
||||
"AutoGen requires `Python>=3.8`. To run this notebook example, please install:\n",
|
||||
"```bash\n",
|
||||
"pip install \"pyautogen[retrievechat]~=0.2.0b5\"\n",
|
||||
"pip install \"pyautogen[retrievechat]>=0.2.3\"\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
@ -33,7 +33,7 @@
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"%%capture --no-stderr\n",
|
||||
"# %pip install \"pyautogen[retrievechat]~=0.2.0b5\""
|
||||
"# %pip install \"pyautogen[retrievechat]>=0.2.3\""
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -815,7 +815,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.10.12"
|
||||
"version": "3.10.13"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
||||
@ -33,7 +33,7 @@
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"%%capture --no-stderr\n",
|
||||
"# %pip install pyautogen~=0.2.0b4"
|
||||
"# %pip install \"pyautogen>=0.2.3\""
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -33,7 +33,7 @@
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"%%capture --no-stderr\n",
|
||||
"# %pip install pyautogen~=0.2.0b4"
|
||||
"# %pip install \"pyautogen>=0.2.3\""
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -50,7 +50,7 @@
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"%%capture --no-stderr\n",
|
||||
"# %pip install pyautogen~=0.2.0b4"
|
||||
"# %pip install \"pyautogen>=0.2.3\""
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -72,7 +72,7 @@
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"0.2.0b1\n"
|
||||
"0.2.3\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
||||
@ -45,7 +45,7 @@
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# %pip install pyautogen~=0.2.0b4"
|
||||
"# %pip install \"pyautogen>=0.2.3\""
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -47,7 +47,7 @@
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"%pip install \"pyautogen~=0.2.0b2\" Langchain"
|
||||
"%pip install \"pyautogen>=0.2.3\" Langchain"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -15,7 +15,7 @@
|
||||
"source": [
|
||||
"### Before everything starts, install AutoGen with the `lmm` option\n",
|
||||
"```bash\n",
|
||||
"pip install \"pyautogen[lmm]~=0.2.0b4\"\n",
|
||||
"pip install \"pyautogen[lmm]>=0.2.3\"\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
|
||||
@ -26,7 +26,7 @@
|
||||
"source": [
|
||||
"### Before everything starts, install AutoGen with the `lmm` option\n",
|
||||
"```bash\n",
|
||||
"pip install \"pyautogen[lmm]~=0.2.0b4\"\n",
|
||||
"pip install \"pyautogen[lmm]>=0.2.3\"\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
|
||||
@ -29,7 +29,7 @@
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"%%capture --no-stderr\n",
|
||||
"# %pip install \"pyautogen~=0.2.0b5"
|
||||
"# %pip install \"pyautogen>=0.2.3\""
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -71,7 +71,7 @@
|
||||
" \"question\"\n",
|
||||
" ]\n",
|
||||
" },\n",
|
||||
" \"description\": \"This is an API endpoint allowing users (analysts) to input question about GitHub in text format to retrieve the realted and structured data.\"\n",
|
||||
" \"description\": \"This is an API endpoint allowing users (analysts) to input question about GitHub in text format to retrieve the related and structured data.\"\n",
|
||||
"}\n",
|
||||
"\n",
|
||||
"def get_ossinsight(question):\n",
|
||||
|
||||
@ -15,7 +15,7 @@
|
||||
"\n",
|
||||
"AutoGen requires `Python>=3.8`. To run this notebook example, please install:\n",
|
||||
"```bash\n",
|
||||
"pip install \"pyautogen==0.2.0b5\"\n",
|
||||
"pip install \"pyautogen>=0.2.3\"\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
|
||||
@ -132,7 +132,7 @@
|
||||
" human_input_mode=\"NEVER\"\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"# When all is set, initate the chat.\n",
|
||||
"# When all is set, initiate the chat.\n",
|
||||
"user_proxy.initiate_chat(gpt_assistant, message=\"If $725x + 727y = 1500$ and $729x+ 731y = 1508$, what is the value of $x - y$ ?\")\n"
|
||||
]
|
||||
},
|
||||
@ -279,7 +279,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.10.12"
|
||||
"version": "3.10.13"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
||||
@ -45,7 +45,7 @@
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# %pip install pyautogen~=0.2.0b4 docker"
|
||||
"# %pip install \"pyautogen>=0.2.3\" docker"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -29,7 +29,7 @@
|
||||
"\n",
|
||||
"AutoGen requires `Python>=3.8`. To run this notebook example, please install the [retrievechat] option.\n",
|
||||
"```bash\n",
|
||||
"pip install \"pyautogen[retrievechat]~=0.2.0b5\" \"flaml[automl]\" \"qdrant_client[fastembed]\"\n",
|
||||
"pip install \"pyautogen[retrievechat]>=0.2.3\" \"flaml[automl]\" \"qdrant_client[fastembed]\"\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
@ -37,9 +37,162 @@
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Requirement already satisfied: pyautogen>=0.2.3 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from pyautogen[retrievechat]>=0.2.3) (0.2.3)\n",
|
||||
"Requirement already satisfied: flaml[automl] in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (2.1.1)\n",
|
||||
"Requirement already satisfied: qdrant_client[fastembed] in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (1.7.0)\n",
|
||||
"Requirement already satisfied: diskcache in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from pyautogen>=0.2.3->pyautogen[retrievechat]>=0.2.3) (5.6.3)\n",
|
||||
"Requirement already satisfied: openai>=1.3 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from pyautogen>=0.2.3->pyautogen[retrievechat]>=0.2.3) (1.6.1)\n",
|
||||
"Requirement already satisfied: pydantic<3,>=1.10 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from pyautogen>=0.2.3->pyautogen[retrievechat]>=0.2.3) (2.5.3)\n",
|
||||
"Requirement already satisfied: python-dotenv in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from pyautogen>=0.2.3->pyautogen[retrievechat]>=0.2.3) (1.0.0)\n",
|
||||
"Requirement already satisfied: termcolor in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from pyautogen>=0.2.3->pyautogen[retrievechat]>=0.2.3) (2.4.0)\n",
|
||||
"Requirement already satisfied: tiktoken in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from pyautogen>=0.2.3->pyautogen[retrievechat]>=0.2.3) (0.5.2)\n",
|
||||
"Requirement already satisfied: NumPy>=1.17.0rc1 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from flaml[automl]) (1.26.2)\n",
|
||||
"Requirement already satisfied: lightgbm>=2.3.1 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from flaml[automl]) (4.2.0)\n",
|
||||
"Requirement already satisfied: xgboost>=0.90 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from flaml[automl]) (2.0.3)\n",
|
||||
"Requirement already satisfied: scipy>=1.4.1 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from flaml[automl]) (1.11.4)\n",
|
||||
"Requirement already satisfied: pandas>=1.1.4 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from flaml[automl]) (2.1.4)\n",
|
||||
"Requirement already satisfied: scikit-learn>=0.24 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from flaml[automl]) (1.3.2)\n",
|
||||
"Requirement already satisfied: fastembed==0.1.1 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from qdrant_client[fastembed]) (0.1.1)\n",
|
||||
"Requirement already satisfied: grpcio>=1.41.0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from qdrant_client[fastembed]) (1.60.0)\n",
|
||||
"Requirement already satisfied: grpcio-tools>=1.41.0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from qdrant_client[fastembed]) (1.60.0)\n",
|
||||
"Requirement already satisfied: httpx>=0.14.0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from httpx[http2]>=0.14.0->qdrant_client[fastembed]) (0.26.0)\n",
|
||||
"Requirement already satisfied: portalocker<3.0.0,>=2.7.0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from qdrant_client[fastembed]) (2.8.2)\n",
|
||||
"Requirement already satisfied: urllib3<2.0.0,>=1.26.14 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from qdrant_client[fastembed]) (1.26.18)\n",
|
||||
"Requirement already satisfied: onnx<2.0,>=1.11 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from fastembed==0.1.1->qdrant_client[fastembed]) (1.15.0)\n",
|
||||
"Requirement already satisfied: onnxruntime<2.0,>=1.15 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from fastembed==0.1.1->qdrant_client[fastembed]) (1.16.3)\n",
|
||||
"Requirement already satisfied: requests<3.0,>=2.31 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from fastembed==0.1.1->qdrant_client[fastembed]) (2.31.0)\n",
|
||||
"Requirement already satisfied: tokenizers<0.14,>=0.13 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from fastembed==0.1.1->qdrant_client[fastembed]) (0.13.3)\n",
|
||||
"Requirement already satisfied: tqdm<5.0,>=4.65 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from fastembed==0.1.1->qdrant_client[fastembed]) (4.66.1)\n",
|
||||
"Requirement already satisfied: chromadb in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from pyautogen[retrievechat]>=0.2.3) (0.4.21)\n",
|
||||
"Requirement already satisfied: ipython in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from pyautogen[retrievechat]>=0.2.3) (8.19.0)\n",
|
||||
"Requirement already satisfied: pypdf in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from pyautogen[retrievechat]>=0.2.3) (3.17.4)\n",
|
||||
"Requirement already satisfied: sentence-transformers in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from pyautogen[retrievechat]>=0.2.3) (2.2.2)\n",
|
||||
"Requirement already satisfied: protobuf<5.0dev,>=4.21.6 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from grpcio-tools>=1.41.0->qdrant_client[fastembed]) (4.25.1)\n",
|
||||
"Requirement already satisfied: setuptools in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from grpcio-tools>=1.41.0->qdrant_client[fastembed]) (65.5.0)\n",
|
||||
"Requirement already satisfied: anyio in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from httpx>=0.14.0->httpx[http2]>=0.14.0->qdrant_client[fastembed]) (4.2.0)\n",
|
||||
"Requirement already satisfied: certifi in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from httpx>=0.14.0->httpx[http2]>=0.14.0->qdrant_client[fastembed]) (2023.11.17)\n",
|
||||
"Requirement already satisfied: httpcore==1.* in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from httpx>=0.14.0->httpx[http2]>=0.14.0->qdrant_client[fastembed]) (1.0.2)\n",
|
||||
"Requirement already satisfied: idna in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from httpx>=0.14.0->httpx[http2]>=0.14.0->qdrant_client[fastembed]) (3.6)\n",
|
||||
"Requirement already satisfied: sniffio in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from httpx>=0.14.0->httpx[http2]>=0.14.0->qdrant_client[fastembed]) (1.3.0)\n",
|
||||
"Requirement already satisfied: h11<0.15,>=0.13 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from httpcore==1.*->httpx>=0.14.0->httpx[http2]>=0.14.0->qdrant_client[fastembed]) (0.14.0)\n",
|
||||
"Requirement already satisfied: h2<5,>=3 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from httpx[http2]>=0.14.0->qdrant_client[fastembed]) (4.1.0)\n",
|
||||
"Requirement already satisfied: distro<2,>=1.7.0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from openai>=1.3->pyautogen>=0.2.3->pyautogen[retrievechat]>=0.2.3) (1.9.0)\n",
|
||||
"Requirement already satisfied: typing-extensions<5,>=4.7 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from openai>=1.3->pyautogen>=0.2.3->pyautogen[retrievechat]>=0.2.3) (4.9.0)\n",
|
||||
"Requirement already satisfied: python-dateutil>=2.8.2 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from pandas>=1.1.4->flaml[automl]) (2.8.2)\n",
|
||||
"Requirement already satisfied: pytz>=2020.1 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from pandas>=1.1.4->flaml[automl]) (2023.3.post1)\n",
|
||||
"Requirement already satisfied: tzdata>=2022.1 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from pandas>=1.1.4->flaml[automl]) (2023.4)\n",
|
||||
"Requirement already satisfied: annotated-types>=0.4.0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from pydantic<3,>=1.10->pyautogen>=0.2.3->pyautogen[retrievechat]>=0.2.3) (0.6.0)\n",
|
||||
"Requirement already satisfied: pydantic-core==2.14.6 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from pydantic<3,>=1.10->pyautogen>=0.2.3->pyautogen[retrievechat]>=0.2.3) (2.14.6)\n",
|
||||
"Requirement already satisfied: joblib>=1.1.1 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from scikit-learn>=0.24->flaml[automl]) (1.3.2)\n",
|
||||
"Requirement already satisfied: threadpoolctl>=2.0.0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from scikit-learn>=0.24->flaml[automl]) (3.2.0)\n",
|
||||
"Requirement already satisfied: chroma-hnswlib==0.7.3 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from chromadb->pyautogen[retrievechat]>=0.2.3) (0.7.3)\n",
|
||||
"Requirement already satisfied: fastapi>=0.95.2 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from chromadb->pyautogen[retrievechat]>=0.2.3) (0.108.0)\n",
|
||||
"Requirement already satisfied: uvicorn>=0.18.3 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from uvicorn[standard]>=0.18.3->chromadb->pyautogen[retrievechat]>=0.2.3) (0.25.0)\n",
|
||||
"Requirement already satisfied: posthog>=2.4.0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from chromadb->pyautogen[retrievechat]>=0.2.3) (3.1.0)\n",
|
||||
"Requirement already satisfied: pulsar-client>=3.1.0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from chromadb->pyautogen[retrievechat]>=0.2.3) (3.3.0)\n",
|
||||
"Requirement already satisfied: opentelemetry-api>=1.2.0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from chromadb->pyautogen[retrievechat]>=0.2.3) (1.22.0)\n",
|
||||
"Requirement already satisfied: opentelemetry-exporter-otlp-proto-grpc>=1.2.0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from chromadb->pyautogen[retrievechat]>=0.2.3) (1.22.0)\n",
|
||||
"Requirement already satisfied: opentelemetry-instrumentation-fastapi>=0.41b0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from chromadb->pyautogen[retrievechat]>=0.2.3) (0.43b0)\n",
|
||||
"Requirement already satisfied: opentelemetry-sdk>=1.2.0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from chromadb->pyautogen[retrievechat]>=0.2.3) (1.22.0)\n",
|
||||
"Requirement already satisfied: pypika>=0.48.9 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from chromadb->pyautogen[retrievechat]>=0.2.3) (0.48.9)\n",
|
||||
"Requirement already satisfied: overrides>=7.3.1 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from chromadb->pyautogen[retrievechat]>=0.2.3) (7.4.0)\n",
|
||||
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|
||||
"Requirement already satisfied: bcrypt>=4.0.1 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from chromadb->pyautogen[retrievechat]>=0.2.3) (4.1.2)\n",
|
||||
"Requirement already satisfied: typer>=0.9.0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from chromadb->pyautogen[retrievechat]>=0.2.3) (0.9.0)\n",
|
||||
"Requirement already satisfied: kubernetes>=28.1.0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from chromadb->pyautogen[retrievechat]>=0.2.3) (28.1.0)\n",
|
||||
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|
||||
"Requirement already satisfied: PyYAML>=6.0.0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from chromadb->pyautogen[retrievechat]>=0.2.3) (6.0.1)\n",
|
||||
"Requirement already satisfied: mmh3>=4.0.1 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from chromadb->pyautogen[retrievechat]>=0.2.3) (4.0.1)\n",
|
||||
"Requirement already satisfied: decorator in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from ipython->pyautogen[retrievechat]>=0.2.3) (5.1.1)\n",
|
||||
"Requirement already satisfied: jedi>=0.16 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from ipython->pyautogen[retrievechat]>=0.2.3) (0.19.1)\n",
|
||||
"Requirement already satisfied: matplotlib-inline in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from ipython->pyautogen[retrievechat]>=0.2.3) (0.1.6)\n",
|
||||
"Requirement already satisfied: prompt-toolkit<3.1.0,>=3.0.41 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from ipython->pyautogen[retrievechat]>=0.2.3) (3.0.43)\n",
|
||||
"Requirement already satisfied: pygments>=2.4.0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from ipython->pyautogen[retrievechat]>=0.2.3) (2.17.2)\n",
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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||||
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"Requirement already satisfied: deprecated>=1.2.6 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from opentelemetry-api>=1.2.0->chromadb->pyautogen[retrievechat]>=0.2.3) (1.2.14)\n",
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||||
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||||
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||||
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||||
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||||
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||||
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||||
"Requirement already satisfied: opentelemetry-util-http==0.43b0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from opentelemetry-instrumentation-fastapi>=0.41b0->chromadb->pyautogen[retrievechat]>=0.2.3) (0.43b0)\n",
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||||
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||||
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||||
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||||
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||||
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||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
"Requirement already satisfied: pyasn1-modules>=0.2.1 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from google-auth>=1.0.1->kubernetes>=28.1.0->chromadb->pyautogen[retrievechat]>=0.2.3) (0.3.0)\n",
|
||||
"Requirement already satisfied: rsa<5,>=3.1.4 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from google-auth>=1.0.1->kubernetes>=28.1.0->chromadb->pyautogen[retrievechat]>=0.2.3) (4.9)\n",
|
||||
"Requirement already satisfied: zipp>=0.5 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from importlib-metadata<7.0,>=6.0->opentelemetry-api>=1.2.0->chromadb->pyautogen[retrievechat]>=0.2.3) (3.17.0)\n",
|
||||
"Requirement already satisfied: humanfriendly>=9.1 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from coloredlogs->onnxruntime<2.0,>=1.15->fastembed==0.1.1->qdrant_client[fastembed]) (10.0)\n",
|
||||
"Requirement already satisfied: MarkupSafe>=2.0 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from jinja2->torch>=1.6.0->sentence-transformers->pyautogen[retrievechat]>=0.2.3) (2.1.3)\n",
|
||||
"Requirement already satisfied: mpmath>=0.19 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from sympy->onnxruntime<2.0,>=1.15->fastembed==0.1.1->qdrant_client[fastembed]) (1.3.0)\n",
|
||||
"Requirement already satisfied: pyasn1<0.6.0,>=0.4.6 in /workspaces/autogen/.venv-3.11/lib/python3.11/site-packages (from pyasn1-modules>=0.2.1->google-auth>=1.0.1->kubernetes>=28.1.0->chromadb->pyautogen[retrievechat]>=0.2.3) (0.5.1)\n",
|
||||
"Note: you may need to restart the kernel to use updated packages.\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# %pip install \"pyautogen[retrievechat]~=0.2.0b5\" \"flaml[automl]\" \"qdrant_client[fastembed]\""
|
||||
"%pip install \"pyautogen[retrievechat]>=0.2.3\" \"flaml[automl]\" \"qdrant_client[fastembed]\""
|
||||
]
|
||||
},
|
||||
{
|
||||
@ -153,7 +306,7 @@
|
||||
"source": [
|
||||
"## Construct agents for RetrieveChat\n",
|
||||
"\n",
|
||||
"We start by initialzing the `RetrieveAssistantAgent` and `QdrantRetrieveUserProxyAgent`. The system message needs to be set to \"You are a helpful assistant.\" for RetrieveAssistantAgent. The detailed instructions are given in the user message. Later we will use the `QdrantRetrieveUserProxyAgent.generate_init_prompt` to combine the instructions and a retrieval augmented generation task for an initial prompt to be sent to the LLM assistant.\n",
|
||||
"We start by initializing the `RetrieveAssistantAgent` and `QdrantRetrieveUserProxyAgent`. The system message needs to be set to \"You are a helpful assistant.\" for RetrieveAssistantAgent. The detailed instructions are given in the user message. Later we will use the `QdrantRetrieveUserProxyAgent.generate_init_prompt` to combine the instructions and a retrieval augmented generation task for an initial prompt to be sent to the LLM assistant.\n",
|
||||
"\n",
|
||||
"### You can find the list of all the embedding models supported by Qdrant [here](https://qdrant.github.io/fastembed/examples/Supported_Models/)."
|
||||
]
|
||||
@ -1079,7 +1232,7 @@
|
||||
"\n",
|
||||
"- `result_type_name` - A String to specify the name of the result type.\n",
|
||||
"- `cb_coef` - a string to specify the coefficient on the confidence bound.\n",
|
||||
"- `init_loss` - a float to specify the inital loss.\n",
|
||||
"- `init_loss` - a float to specify the initial loss.\n",
|
||||
"- `init_cb` - a float to specify the intial confidence bound.\n",
|
||||
"- `mode` - A string in ['min', 'max'] to specify the objective as\n",
|
||||
" minimization or maximization.\n",
|
||||
@ -1233,7 +1386,7 @@
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.10.12"
|
||||
"version": "3.11.2"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
|
||||
@ -45,7 +45,7 @@
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# %pip install pyautogen~=0.2.0b4"
|
||||
"# %pip install \"pyautogen>=0.2.3\""
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -24,7 +24,7 @@
|
||||
"\n",
|
||||
"AutoGen requires `Python>=3.8`. To run this notebook example, please install:\n",
|
||||
"```bash\n",
|
||||
"pip install \"pyautogen~=0.2.0b5\"\n",
|
||||
"pip install \"pyautogen>=0.2.3\"\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
@ -34,7 +34,7 @@
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# %pip install --quiet \"pyautogen~=0.2.0b5\""
|
||||
"# %pip install --quiet \"pyautogen>=0.2.3\""
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -44,7 +44,7 @@
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# %pip install pyautogen~=0.2.0b4"
|
||||
"# %pip install \"pyautogen>=0.2.3\""
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -45,7 +45,7 @@
|
||||
"# %pip install moviepy~=1.0.3\n",
|
||||
"# %pip install openai-whisper~=20230918\n",
|
||||
"# %pip install openai~=1.3.5\n",
|
||||
"# %pip install pyautogen~=0.2.0b4"
|
||||
"# %pip install \"pyautogen>=0.2.3\""
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -49,7 +49,7 @@
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# %pip install pyautogen~=0.2.0b4 docker"
|
||||
"# %pip install \"pyautogen>=0.2.3\" docker"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
File diff suppressed because one or more lines are too long
@ -233,7 +233,7 @@
|
||||
],
|
||||
"source": [
|
||||
"# Since cache is enabled, the same completion will be returned from cache, which will not incur any actual cost. \n",
|
||||
"# So acutal cost doesn't change but total cost doubles.\n",
|
||||
"# So actual cost doesn't change but total cost doubles.\n",
|
||||
"response = client.create(messages=messages, model=\"gpt-35-turbo-1106\", cache_seed=41)\n",
|
||||
"client.print_usage_summary()"
|
||||
]
|
||||
|
||||
@ -60,7 +60,7 @@
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# %pip install \"pyautogen~=0.2.0b4\""
|
||||
"# %pip install \"pyautogen>=0.2.3\""
|
||||
]
|
||||
},
|
||||
{
|
||||
|
||||
@ -180,7 +180,7 @@
|
||||
},
|
||||
"human_input_mode": "NEVER",
|
||||
"max_consecutive_auto_reply": 4,
|
||||
"system_message": "Your task is to ensure you generate a high quality visualization for the user. Your visualizations must follow best practices and you must articulate your reasoning for your choices. The visualization must not have grid or outline box. The visualization should have an APPROPRIATE ASPECT RATIO e..g rectangular for time series data. The title must be bold. Importantly, if THE CHART IS A LINE CHART, you MUST ADD ALINE OF BEST FIT and ADD TEXT ON THE SLOPE OF EACH LINE. Note that today's date is 12/10/2023. At each point, do your best to determine if the user's request has been addressed and if so, respond with a summary. The summary must be written as a coherent helpful response to the user request e.g. 'Sure, here is result to your request '. The summary MUST end with the word TERMINATE. If the user request is pleasantry or greeting, you should respond with a pleasantry or greeting and TERMINATE."
|
||||
"system_message": "Your task is to ensure you generate a high quality visualization for the user. Your visualizations must follow best practices and you must articulate your reasoning for your choices. The visualization must not have grid or outline box. The visualization should have an APPROPRIATE ASPECT RATIO e..g rectangular for time series data. The title must be bold. Importantly, if THE CHART IS A LINE CHART, you MUST ADD A LINE OF BEST FIT and ADD TEXT ON THE SLOPE OF EACH LINE. Note that today's date is 12/10/2023. At each point, do your best to determine if the user's request has been addressed and if so, respond with a summary. The summary must be written as a coherent helpful response to the user request e.g. 'Sure, here is result to your request '. The summary MUST end with the word TERMINATE. If the user request is pleasantry or greeting, you should respond with a pleasantry or greeting and TERMINATE."
|
||||
}
|
||||
},
|
||||
"type": "default"
|
||||
|
||||
@ -80,7 +80,7 @@ const SessionsView = ({}: any) => {
|
||||
const onSuccess = (data: any) => {
|
||||
if (data && data.status) {
|
||||
message.success(data.message);
|
||||
// console.log("sesssions", data);
|
||||
// console.log("sessions", data);
|
||||
setSessions(data.data);
|
||||
if (data.data && data.data.length === 0) {
|
||||
createSession();
|
||||
|
||||
@ -162,7 +162,7 @@ For the sake of brevity we will refer to this folder as the `DEST_FOLDER`.
|
||||
|
||||
The algorithm for populating the `DEST_FOLDER` is as follows:
|
||||
|
||||
1. Recursively copy the contents of `./incudes` to DEST_FOLDER. This folder contains all the basic starter files for running a scenario, including an ENV file which will set the Docker environment variables.
|
||||
1. Recursively copy the contents of `./includes` to DEST_FOLDER. This folder contains all the basic starter files for running a scenario, including an ENV file which will set the Docker environment variables.
|
||||
2. Append the OAI_CONFIG_LIST to the ENV file so that autogen may access these secrets.
|
||||
3. Recursively copy the scenario folder (if `template` in the json scenario definition points to a folder) to DEST_FOLDER. If the `template` instead points to a file, copy the file, but rename it to `scenario.py`
|
||||
4. Apply any templating, as outlined in the prior section.
|
||||
|
||||
@ -87,7 +87,7 @@ With AutoGen 0.2.2 onward, GroupChat instead relies on the description field. Wi
|
||||
```
|
||||
You are in a role play game. The following roles are available:
|
||||
|
||||
assitant: A helpful and general-purpose AI assistant that has strong language skills, Python skills, and Linux command line skills.
|
||||
assistant: A helpful and general-purpose AI assistant that has strong language skills, Python skills, and Linux command line skills.
|
||||
user_proxy: A user that can run Python code or input command line commands at a Linux terminal and report back the execution results.
|
||||
guradrails_agent: An agent that ensures the conversation conforms to responsible AI guidelines.
|
||||
|
||||
|
||||
@ -93,7 +93,7 @@ If you have problems with agents running `pip install` or get errors similar to
|
||||
|
||||
### Agents keep thanking each other when using `gpt-3.5-turbo`
|
||||
|
||||
When using `gpt-3.5-turbo` you may often encounter agents going into a "gratitude loop", meaning when they complete a task they will begin congratulating and thanking eachother in a continuous loop. This is a limitation in the performance of `gpt-3.5-turbo`, in contrast to `gpt-4` which has no problem remembering instructions. This can hinder the experimentation experience when trying to test out your own use case with cheaper models.
|
||||
When using `gpt-3.5-turbo` you may often encounter agents going into a "gratitude loop", meaning when they complete a task they will begin congratulating and thanking each other in a continuous loop. This is a limitation in the performance of `gpt-3.5-turbo`, in contrast to `gpt-4` which has no problem remembering instructions. This can hinder the experimentation experience when trying to test out your own use case with cheaper models.
|
||||
|
||||
A workaround is to add an additional termination notice to the prompt. This acts a "little nudge" for the LLM to remember that they need to terminate the conversation when their task is complete. You can do this by appending a string such as the following to your user input string:
|
||||
|
||||
|
||||
@ -48,7 +48,7 @@ specified with a JSON schema describing its parameters and their types. Writing
|
||||
is complex and error-prone and that is why AutoGen framework provides two high level function decorators for automatically generating such schema using type hints on standard Python datatypes
|
||||
or Pydantic models:
|
||||
|
||||
1. [`ConversableAgent.register_for_llm`](../reference/agentchat/conversable_agent#register_for_llm) is used to register the function as a Tool in the `llm_config` of a ConversableAgent. The ConversableAgent agent can propose execution of a registrated Tool, but the actual execution will be performed by a UserProxy agent.
|
||||
1. [`ConversableAgent.register_for_llm`](../reference/agentchat/conversable_agent#register_for_llm) is used to register the function as a Tool in the `llm_config` of a ConversableAgent. The ConversableAgent agent can propose execution of a registered Tool, but the actual execution will be performed by a UserProxy agent.
|
||||
|
||||
2. [`ConversableAgent.register_for_execution`](../reference/agentchat/conversable_agent#register_for_execution) is used to register the function in the `function_map` of a UserProxy agent.
|
||||
|
||||
|
||||
Loading…
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Reference in New Issue
Block a user