Merge pull request #12 from autogen-ai/website-updates

Updated repo links
autogenhub · Aug 25, 2024 · 20d83bb · 20d83bb
2 parents 22072b3 + b765d01
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diff --git a/notebook/Async_human_input.ipynb b/notebook/Async_human_input.ipynb
diff --git a/notebook/agentchat_cost_token_tracking.ipynb b/notebook/agentchat_cost_token_tracking.ipynb
@@ -4,17 +4,6 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "<a href=\"https://colab.research.google.com/github/microsoft/autogen/blob/main/notebook/oai_client_cost.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "Copyright (c) Microsoft Corporation. All rights reserved. \n",
-    "\n",
-    "Licensed under the MIT License.\n",
-    "\n",
     "# Usage tracking with AutoGen\n",
     "## 1. Use AutoGen's OpenAIWrapper for cost estimation\n",
     "The `OpenAIWrapper` from `autogen` tracks token counts and costs of your API calls. Use the `create()` method to initiate requests and `print_usage_summary()` to retrieve a detailed usage report, including total cost and token usage for both cached and actual requests.\n",
@@ -539,6 +528,12 @@
   }
  ],
  "metadata": {
+  "front_matter": {
+   "description": "cost calculation",
+   "tags": [
+    "cost"
+   ]
+  },
   "kernelspec": {
    "display_name": "msft",
    "language": "python",

diff --git a/notebook/agentchat_dalle_and_gpt4v.ipynb b/notebook/agentchat_dalle_and_gpt4v.ipynb
@@ -620,6 +620,13 @@
   }
  ],
  "metadata": {
+  "front_matter": {
+    "description": "Multimodal agent chat with DALL-E and GPT-4v.",
+    "tags": [
+        "multimodal",
+        "gpt-4v"
+    ]
+  },
   "kernelspec": {
    "display_name": "Python 3 (ipykernel)",
    "language": "python",

diff --git a/notebook/agentchat_function_call_code_writing.ipynb b/notebook/agentchat_function_call_code_writing.ipynb
@@ -983,9 +983,8 @@
   "front_matter": {
    "description": "Equip your agent with functions that can efficiently implement features into your software application.",
    "tags": [
-    "function call",
     "code generation",
-    "tool use",
+    "tool/function",
     "software engineering"
    ]
   },

diff --git a/notebook/agentchat_guidance.ipynb b/notebook/agentchat_guidance.ipynb
@@ -303,6 +303,13 @@
   }
  ],
  "metadata": {
+  "front_matter": {
+    "description": "Constrained responses via guidance.",
+    "tags": [
+        "guidance",
+        "JSON"
+    ]
+  },
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",

diff --git a/notebook/agentchat_human_feedback.ipynb b/notebook/agentchat_human_feedback.ipynb
@@ -1,13 +1,5 @@
 {
  "cells": [
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "<a href=\"https://colab.research.google.com/github/microsoft/autogen/blob/main/notebook/agentchat_human_feedback.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
-   ]
-  },
   {
    "attachments": {},
    "cell_type": "markdown",
@@ -377,6 +369,13 @@
   }
  ],
  "metadata": {
+  "front_matter": {
+    "description": "Code generation, execution, debugging and human feedback.",
+    "tags": [
+        "human",
+        "code generation"
+    ]
+  },
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",

diff --git a/notebook/agentchat_inception_function.ipynb b/notebook/agentchat_inception_function.ipynb
@@ -307,6 +307,13 @@
   }
  ],
  "metadata": {
+  "front_matter": {
+    "description": "Function Inception: Enable AutoGen agents to update/remove functions during conversations.",
+    "tags": [
+        "function inception",
+        "tool/function"
+    ]
+  },
   "kernelspec": {
    "display_name": "Python 3 (ipykernel)",
    "language": "python",

diff --git a/notebook/agentchat_langchain.ipynb b/notebook/agentchat_langchain.ipynb
@@ -1,16 +1,5 @@
 {
  "cells": [
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "id": "ae1f50ec",
-   "metadata": {
-    "id": "ae1f50ec"
-   },
-   "source": [
-    "<a href=\"https://colab.research.google.com/github/microsoft/autogen/blob/main/notebook/agentchat_langchain.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
-   ]
-  },
   {
    "attachments": {},
    "cell_type": "markdown",
@@ -688,6 +677,13 @@
   }
  ],
  "metadata": {
+  "front_matter": {
+    "description": "Use Langchain tools.",
+    "tags": [
+        "langchain",
+        "tool/function"
+    ]
+  },
   "colab": {
    "provenance": []
   },

diff --git a/notebook/agentchat_lmm_gpt-4v.ipynb b/notebook/agentchat_lmm_gpt-4v.ipynb
@@ -1138,7 +1138,7 @@
  ],
  "metadata": {
   "front_matter": {
-   "description": "In AutoGen, leveraging multimodal models can be done through two different methodologies: MultimodalConversableAgent and VisionCapability.",
+   "description": "Leveraging multimodal models through two different methodologies: MultimodalConversableAgent and VisionCapability.",
    "tags": [
     "multimodal",
     "gpt-4v"

diff --git a/notebook/agentchat_lmm_llava.ipynb b/notebook/agentchat_lmm_llava.ipynb
@@ -859,6 +859,13 @@
   }
  ],
  "metadata": {
+  "front_matter": {
+   "description": "Leveraging multimodal models like llava.",
+   "tags": [
+    "multimodal",
+    "llava"
+   ]
+  },
   "kernelspec": {
    "display_name": "Python 3 (ipykernel)",
    "language": "python",

diff --git a/notebook/agentchat_oai_assistant_function_call.ipynb b/notebook/agentchat_oai_assistant_function_call.ipynb
@@ -278,7 +278,7 @@
    "description": "This Jupyter Notebook demonstrates how to leverage OSS Insight (Open Source Software Insight) for advanced GitHub data analysis by defining `Function calls` in AutoGen for the OpenAI Assistant.",
    "tags": [
     "OpenAI Assistant",
-    "function call"
+    "function/tool"
    ]
   },
   "kernelspec": {

diff --git a/notebook/agentchat_oai_assistant_groupchat.ipynb b/notebook/agentchat_oai_assistant_groupchat.ipynb
@@ -482,7 +482,7 @@
  ],
  "metadata": {
   "front_matter": {
-   "description": "This Jupyter Notebook demonstrates how to use the GPTAssistantAgent in AutoGen's group chat mode, enabling collaborative task performance through automated chat with agents powered by LLMs, tools, or humans.",
+   "description": "Use GPTAssistantAgent in group chat.",
    "tags": [
     "OpenAI Assistant",
     "group chat"

diff --git a/notebook/agentchat_oai_assistant_retrieval.ipynb b/notebook/agentchat_oai_assistant_retrieval.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## RAG OpenAI Assistants in AutoGen\n",
+    "# RAG OpenAI Assistants in AutoGen\n",
     "\n",
     "This notebook shows an example of the [`GPTAssistantAgent`](https://github.com/microsoft/autogen/blob/main/autogen/agentchat/contrib/gpt_assistant_agent.py#L16C43-L16C43) with retrieval augmented generation. `GPTAssistantAgent` is an experimental AutoGen agent class that leverages the [OpenAI Assistant API](https://platform.openai.com/docs/assistants/overview) for conversational capabilities,  working with\n",
     "`UserProxyAgent` in AutoGen."
@@ -112,6 +112,13 @@
   }
  ],
  "metadata": {
+  "front_matter": {
+   "description": "OpenAI Assistant with retrieval augmentation.",
+   "tags": [
+    "RAG",
+    "OpenAI Assistant"
+   ]
+  },
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",

diff --git a/notebook/agentchat_oai_assistant_twoagents_basic.ipynb b/notebook/agentchat_oai_assistant_twoagents_basic.ipynb
@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "## OpenAI Assistants in AutoGen\n",
+    "# OpenAI Assistants in AutoGen\n",
     "\n",
     "This notebook shows a very basic example of the [`GPTAssistantAgent`](https://github.com/microsoft/autogen/blob/main/autogen/agentchat/contrib/gpt_assistant_agent.py#L16C43-L16C43), which is an experimental AutoGen agent class that leverages the [OpenAI Assistant API](https://platform.openai.com/docs/assistants/overview) for conversational capabilities,  working with\n",
     "`UserProxyAgent` in AutoGen."
@@ -185,6 +185,12 @@
   }
  ],
  "metadata": {
+  "front_matter": {
+   "description": "Two-agent chat with OpenAI assistants.",
+   "tags": [
+    "OpenAI Assistant"
+   ]
+  },
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",

diff --git a/notebook/agentchat_planning.ipynb b/notebook/agentchat_planning.ipynb
@@ -1,13 +1,5 @@
 {
  "cells": [
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "<a href=\"https://colab.research.google.com/github/microsoft/autogen/blob/main/notebook/agentchat_planning.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
-   ]
-  },
   {
    "attachments": {},
    "cell_type": "markdown",
@@ -431,6 +423,13 @@
   }
  ],
  "metadata": {
+  "front_matter": {
+    "description": "Use planning agent in a function call.",
+    "tags": [
+        "planning",
+        "tool/function"
+    ]
+  },
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",

diff --git a/notebook/agentchat_sql_spider.ipynb b/notebook/agentchat_sql_spider.ipynb
@@ -294,6 +294,13 @@
   }
  ],
  "metadata": {
+  "front_matter": {
+    "description": "Natural language text to SQL query using the Spider text-to-SQL benchmark.",
+    "tags": [
+        "SQL",
+        "tool/function"
+    ]
+  },
   "kernelspec": {
    "display_name": ".venv",
    "language": "python",

diff --git a/notebook/agentchat_stream.ipynb b/notebook/agentchat_stream.ipynb
@@ -1,13 +1,5 @@
 {
  "cells": [
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "<a href=\"https://colab.research.google.com/github/microsoft/autogen/blob/main/notebook/agentchat_stream.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
-   ]
-  },
   {
    "attachments": {},
    "cell_type": "markdown",
@@ -370,6 +362,14 @@
   }
  ],
  "metadata": {
+  "front_matter": {
+    "description": "Automated continual learning from new data.",
+    "tags": [
+        "streaming",
+        "async",
+        "learning"
+    ]
+  },
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",

diff --git a/notebook/agentchat_surfer.ipynb b/notebook/agentchat_surfer.ipynb
@@ -39,7 +39,7 @@
     "\n",
     "It first looks for environment variable \"OAI_CONFIG_LIST\" which needs to be a valid json string. If that variable is not found, it then looks for a json file named \"OAI_CONFIG_LIST\". It filters the configs by models (you can filter by other keys as well).\n",
     "\n",
-    "The WebSurferAgent uses a combination of models. GPT-4 and GPT-3.5-turbo-16 are recommended.\n",
+    "The WebSurferAgent uses a combination of models. GPT-4 and GPT-3.5-turbo-16k are recommended.\n",
     "\n",
     "Your json config should look something like the following:\n",
     "```json\n",
@@ -604,6 +604,13 @@
   }
  ],
  "metadata": {
+  "front_matter": {
+    "description": "Browse the web with agents.",
+    "tags": [
+        "web",
+        "tool/function"
+    ]
+  },
   "kernelspec": {
    "display_name": "Python 3 (ipykernel)",
    "language": "python",

diff --git a/notebook/agentchat_teachable_oai_assistants.ipynb b/notebook/agentchat_teachable_oai_assistants.ipynb
@@ -1,13 +1,5 @@
 {
  "cells": [
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "<a href=\"https://colab.research.google.com/github/microsoft/autogen/blob/main/notebook/agentchat_teachability.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
-   ]
-  },
   {
    "attachments": {},
    "cell_type": "markdown",
@@ -1127,6 +1119,13 @@
   }
  ],
  "metadata": {
+  "front_matter": {
+    "description": "Teach OpenAI assistants.",
+    "tags": [
+        "teaching",
+        "OpenAI assistant"
+    ]
+  },
   "kernelspec": {
    "display_name": "flaml",
    "language": "python",

diff --git a/notebook/agentchat_two_users.ipynb b/notebook/agentchat_two_users.ipynb
@@ -1,13 +1,5 @@
 {
  "cells": [
-  {
-   "attachments": {},
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "<a href=\"https://colab.research.google.com/github/microsoft/autogen/blob/main/notebook/agentchat_two_users.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
-   ]
-  },
   {
    "attachments": {},
    "cell_type": "markdown",
@@ -493,6 +485,13 @@
   }
  ],
  "metadata": {
+  "front_matter": {
+    "description": "Involve multiple human users via function calls and nested chat.",
+    "tags": [
+        "human",
+        "tool/function"
+    ]
+  },
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",