{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "akavFAooMPDD"
      },
      "source": [
        "# Build a GitHub Issue Resolver Agent\n",
        "\n",
        "In this recipe, we'll create a **GitHub Issue Resolver Agent with Anthropic Claude 4 Sonnet**. Given an issue URL, the agent will:  \n",
        "\n",
        "- Fetch and parse the issue description and comments  \n",
        "- Identify the relevant repository, directories, and files  \n",
        "- Retrieve and process file content  \n",
        "- Determine the next steps for resolution and post them as a comment  \n",
        "\n",
        "For this, we'll use the new [Agent](https://docs.haystack.deepset.ai/docs/agent) component. **`Agent`** is a Haystack component that implements a tool-calling functionality with provider-agnostic chat model support. We can use `Agent` either as a standalone component or within a pipeline.\n",
        "\n",
        "Here's what our **GitHub Issue Resolver Pipeline** looks like:"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xnIFhkWki8uR"
      },
      "source": [
        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      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "LKHtQv50Pdy_"
      },
      "source": [
        "## Install dependencies"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "8jbGvWWa_ARY"
      },
      "outputs": [],
      "source": [
        "!pip install anthropic-haystack github-haystack -q"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "UPq0Eq21_UI2"
      },
      "outputs": [],
      "source": [
        "import os\n",
        "from getpass import getpass\n",
        "from typing import List\n",
        "\n",
        "from haystack import logging, Document,Pipeline\n",
        "from haystack.components.agents import Agent\n",
        "from haystack.components.builders import ChatPromptBuilder\n",
        "from haystack.dataclasses import ChatMessage\n",
        "from haystack.tools.from_function import tool\n",
        "from haystack_integrations.components.generators.anthropic.chat.chat_generator import AnthropicChatGenerator"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "0b46lytcAr42"
      },
      "outputs": [],
      "source": [
        "logger = logging.getLogger(__name__)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "gFCDExiSdfQc"
      },
      "source": [
        "## Initialize a `GitHubIssueViewer` component\n",
        "The `GitHubIssueViewer` component takes a GitHub issue URL and returns a list of Haystack documents. The first document contains the main issue content, while the subsequent documents contain the issue comments."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "7USRQHDncL9T",
        "outputId": "4fd3907f-de53-4389-d19a-12a3ba0bd06f"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "[Document(id=401aeab38ff82756caddcf20be6191917e0a8d262347f4acc2adb24869c842e9, content: '**Is your feature request related to a problem? Please describe.**\n",
              " Most of our components require so...', meta: {'type': 'issue', 'title': 'Proposal to make input variables to `PromptBuilder` and `ChatPromptBuilder` required by default', 'number': 8903, 'state': 'closed', 'created_at': '2025-02-21T14:03:22Z', 'updated_at': '2025-03-21T14:53:27Z', 'author': 'sjrl', 'url': 'https://github.com/deepset-ai/haystack/issues/8903'}),\n",
              " Document(id=463748463715f2c4f988273caf73d5006e5a95beeecd04c91a142fa93ce78354, content: 'Old related issue: https://github.com/deepset-ai/haystack/issues/7441', meta: {'type': 'comment', 'issue_number': 8903, 'created_at': '2025-02-21T14:07:54Z', 'updated_at': '2025-02-21T14:07:54Z', 'author': 'anakin87', 'url': 'https://github.com/deepset-ai/haystack/issues/8903#issuecomment-2674648879'}),\n",
              " Document(id=d7eb9351f9c74a0d8eac616bfc92f97e06bdb6276c54b3e6ec437e3fc7378cb2, content: '@sjrl with the new run-logic released in 2.10 the component will not always trigger anymore. It need...', meta: {'type': 'comment', 'issue_number': 8903, 'created_at': '2025-02-21T21:32:12Z', 'updated_at': '2025-02-21T21:32:12Z', 'author': 'mathislucka', 'url': 'https://github.com/deepset-ai/haystack/issues/8903#issuecomment-2675585679'}),\n",
              " Document(id=1c5ea7c3f07f3db061bf2169b11d59ea675bd8269b7168598e88f5a072ed3a5e, content: '@mathislucka thanks for the additional info. I'll need to talk with @ju-gu again about how exactly h...', meta: {'type': 'comment', 'issue_number': 8903, 'created_at': '2025-02-24T07:02:02Z', 'updated_at': '2025-02-24T07:02:02Z', 'author': 'sjrl', 'url': 'https://github.com/deepset-ai/haystack/issues/8903#issuecomment-2677577510'}),\n",
              " Document(id=3994326a4e33ee897938e8cff215d6e407d63d9b800fa088df27aec2cb24ad03, content: '> PromptBuilder with documents (pipeline provided) and query (user provided) will trigger even if it...', meta: {'type': 'comment', 'issue_number': 8903, 'created_at': '2025-02-25T14:55:26Z', 'updated_at': '2025-02-25T14:55:26Z', 'author': 'ju-gu', 'url': 'https://github.com/deepset-ai/haystack/issues/8903#issuecomment-2682266205'}),\n",
              " Document(id=630987248d564b2a538b56a1bc2ada63f66d4d53031708b9c004bfc9e1bf9346, content: '> I think this can still cause problems as it can run before the correct input is created inside the...', meta: {'type': 'comment', 'issue_number': 8903, 'created_at': '2025-02-26T08:01:12Z', 'updated_at': '2025-02-26T08:01:12Z', 'author': 'mathislucka', 'url': 'https://github.com/deepset-ai/haystack/issues/8903#issuecomment-2684214013'}),\n",
              " Document(id=622bc0e5219da00bfcb908519611a649f7eaa28eebedb3c30ad90d66cc0191ab, content: '> for the PromptBuilder, and ChatPromptBuilder we set all Jinja2 variables as optional by default.\n",
              " \n",
              " ...', meta: {'type': 'comment', 'issue_number': 8903, 'created_at': '2025-03-11T10:11:54Z', 'updated_at': '2025-03-11T10:12:29Z', 'author': 'LastRemote', 'url': 'https://github.com/deepset-ai/haystack/issues/8903#issuecomment-2713495950'}),\n",
              " Document(id=22d69cc52cb789306cf54f56a568d1526cdfe766d42818d18f6fc7ec2f9163ad, content: '@sjrl and I decided that we don't want to make breaking changes to the current behavior of the `Prom...', meta: {'type': 'comment', 'issue_number': 8903, 'created_at': '2025-03-21T14:53:24Z', 'updated_at': '2025-03-21T14:53:24Z', 'author': 'julian-risch', 'url': 'https://github.com/deepset-ai/haystack/issues/8903#issuecomment-2743603353'})]"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ],
      "source": [
        "from haystack_integrations.components.connectors.github import GitHubIssueViewer\n",
        "issue_viewer = GitHubIssueViewer()\n",
        "issue_viewer.run(url=\"https://github.com/deepset-ai/haystack/issues/8903\")[\"documents\"]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "zGn-cPpnWJlR"
      },
      "source": [
        "## Initialize a `GitHubRepoViewer` Tool\n",
        "\n",
        "This tool retrieves content from a GitHub repository based on a given `repo` and `path`:\n",
        "\n",
        "- If the `path` points to a **directory**, it returns a list of Documents—one per item—where each document contains the item's name (file or directory) along with full path and metadata in `Document.meta`.  \n",
        "- If the `path` points to a **file**, it returns a single Document containing the file content, with full path and metadata in `Document.meta`.  \n",
        "- If an **error** occurs, it returns a single Document with the error message, and `Document.meta` includes `type=\"error\"`.  "
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "Sl8-gsYQ_j29"
      },
      "outputs": [],
      "source": [
        "from haystack_integrations.tools.github import GitHubRepoViewerTool\n",
        "github_repo_viewer_tool = GitHubRepoViewerTool()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0iWVWZCZZEl3"
      },
      "source": [
        "## Mocked `GitHubIssueCommenter` Tool from a function\n",
        "\n",
        "With the [`@tool`](https://github.com/deepset-ai/haystack-experimental/blob/7e88f2a4e4310359e6c76a6ce8ff920d1bb841f7/haystack_experimental/tools/from_function.py#L137) decorator, we can easily convert a function into a tool, using its docstring as the description.\n",
        "\n",
        "Now, let's create a tool (a mockup) that allows the agent to write comments on GitHub issues. This tool will also serve as the agent's exit condition, signaling when it has completed its task.\n",
        "\n",
        "If you want, you can replace this mockup later with `GitHubIssueCommenterTool`. You will need a GitHub Personal Access Token to enable commenting on GitHub. The [GitHub-Haystack integration page](https://haystack.deepset.ai/integrations/github) has all the details."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "z06jlq2eAHkz"
      },
      "outputs": [],
      "source": [
        "@tool\n",
        "def write_github_comment(comment: str) -> str:\n",
        "    \"\"\"\n",
        "    Use this to create a comment on GitHub once you finished your exploration.\n",
        "    \"\"\"\n",
        "    return comment"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "68fgg6lAad1C"
      },
      "source": [
        "## Create the \"Issue Resolver Agent\" with Tools  \n",
        "\n",
        "To initialize the agent, we need:  \n",
        "1. A list of tools (✅)   \n",
        "2. A chat generator  \n",
        "3. A system prompt\n",
        "\n",
        "We'll start by creating the `ChatGenerator`. In this example, we'll use the [AnthropicChatGenerator](https://docs.haystack.deepset.ai/docs/anthropicchatgenerator) with the `claude-sonnet-4-20250514` model."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hRokrzuWAJQ8",
        "outputId": "486db630-14de-4e9a-c68c-158d7f6bde26"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Anthropic Key: ··········\n"
          ]
        }
      ],
      "source": [
        "os.environ[\"ANTHROPIC_API_KEY\"] = getpass(\"Anthropic Key: \")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "0-xtxYIsalW5"
      },
      "outputs": [],
      "source": [
        "chat_generator = AnthropicChatGenerator(model=\"claude-sonnet-4-20250514\", generation_kwargs={\"max_tokens\": 8000})"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qnA_Jp3YvNZW"
      },
      "source": [
        "In this example, we'll use a pre-defined system prompt, guiding the agent to analyze GitHub issues, explore the repository for relevant files, and generate a detailed comment with resolution steps. Of course, you can use your own custom prompt instead."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "kM3GfuqUAYYQ",
        "outputId": "da816d51-35d3-4b2c-ae41-ad440e533eca",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "The assistant is Haystack-Agent, created by deepset.\n",
            "Haystack-Agent helps developers to develop soft...\n"
          ]
        }
      ],
      "source": [
        "from haystack_integrations.prompts.github import SYSTEM_PROMPT\n",
        "print(SYSTEM_PROMPT[:100]+\"...\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "i3bLwb7aam4q"
      },
      "source": [
        "Finally, we create the agent using `chat_generator`, `SYSTEM_PROMPT`, and `tools`. We set `exit_conditions=[\"write_github_comment\"]` to ensure the agent stops once the `write_github_comment` tool is used. For `state_schema`, we define `{\"documents\": {\"type\": List[Document]}}`, allowing the agent to accumulate documents retrieved from tools, such as `github_repo_viewer_tool`."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "id": "XKCWxjxSANAW"
      },
      "outputs": [],
      "source": [
        "issue_resolver_agent = Agent(\n",
        "    chat_generator=chat_generator,\n",
        "    system_prompt=SYSTEM_PROMPT,\n",
        "    tools=[github_repo_viewer_tool, write_github_comment],\n",
        "    exit_conditions=[\"write_github_comment\"],\n",
        "    state_schema={\"documents\": {\"type\": List[Document]}},\n",
        ")"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "> 💡 Tip: You can pass the built-in `print_streaming_chunk` or your custom function to `Agent` to enable streaming and see the tool calls and results in real time.\n",
        "\n",
        "```python\n",
        "from haystack.components.generators.utils import print_streaming_chunk\n",
        "\n",
        "issue_resolver_agent = Agent(\n",
        "    chat_generator=chat_generator,\n",
        "    system_prompt=SYSTEM_PROMPT,\n",
        "    tools=[github_repo_viewer_tool, write_github_comment],\n",
        "    exit_conditions=[\"write_github_comment\"],\n",
        "    state_schema={\"documents\": {\"type\": List[Document]}},\n",
        "    streaming_callback=print_streaming_chunk\n",
        ")\n",
        "```"
      ],
      "metadata": {
        "id": "so39oUarxPSP"
      }
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WsewUUUreVon"
      },
      "source": [
        "## Construct the Issue Resolver Pipeline  \n",
        "\n",
        "With all components in place, we can now assemble the issue resolver pipeline."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KU_vu0yPATJj",
        "outputId": "72313bd9-631a-40d9-bd16-9c0cbe22d306"
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "<haystack.core.pipeline.pipeline.Pipeline object at 0x7c205115ab90>\n",
              "🚅 Components\n",
              "  - issue_viewer: GitHubIssueViewer\n",
              "  - issue_builder: ChatPromptBuilder\n",
              "  - issue_resolver_agent: Agent\n",
              "🛤️ Connections\n",
              "  - issue_viewer.documents -> issue_builder.documents (List[Document])\n",
              "  - issue_builder.prompt -> issue_resolver_agent.messages (List[ChatMessage])"
            ]
          },
          "metadata": {},
          "execution_count": 19
        }
      ],
      "source": [
        "issue_viewer = GitHubIssueViewer()\n",
        "issue_template = \"\"\"\n",
        "Issue from: {{ url }}\n",
        "{% for document in documents %}\n",
        "{% if loop.index == 1 %}\n",
        "**Title: {{ document.meta.title }}**\n",
        "{% endif %}\n",
        "<issue-comment>\n",
        "{{document.content}}\n",
        "</issue-comment>\n",
        "{% endfor %}\n",
        "\"\"\"\n",
        "\n",
        "issue_builder = ChatPromptBuilder(template=[ChatMessage.from_user(issue_template)], required_variables=\"*\")\n",
        "\n",
        "issue_resolver = Pipeline()\n",
        "issue_resolver.add_component(\"issue_viewer\", issue_viewer)\n",
        "issue_resolver.add_component(\"issue_builder\", issue_builder)\n",
        "issue_resolver.add_component(\"issue_resolver_agent\", issue_resolver_agent)\n",
        "\n",
        "issue_resolver.connect(\"issue_viewer.documents\", \"issue_builder.documents\")\n",
        "issue_resolver.connect(\"issue_builder.prompt\", \"issue_resolver_agent.messages\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "obZtukiwMLve"
      },
      "source": [
        "## Let's Try Our Pipeline  \n",
        "\n",
        "Now, let's run the pipeline with an issue URL and see the agent in action."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "wmggtlTpDZb9"
      },
      "outputs": [],
      "source": [
        "issue_url = \"https://github.com/deepset-ai/haystack-core-integrations/issues/1819\"\n",
        "result = issue_resolver.run({\"url\": issue_url})"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "b8OURcK3MXcp"
      },
      "source": [
        "Let's see the comment generated by our pipeline to resolve the given issue."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 32,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "I8leArws9CzW",
        "outputId": "a4516f32-0622-48be-cc11-e59c8a9fce5f"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "# Implementation: Adding `component_info` Support to `AmazonBedrockChatGenerator`\n",
            "\n",
            "I've analyzed the codebase and the PR mentioned in the issue. Here's my proposed implementation to add `component_info` support to `AmazonBedrockChatGenerator`, following the same pattern used in the main Haystack repository.\n",
            "\n",
            "## Changes Required\n",
            "\n",
            "### 1. Update Imports in `utils.py`\n",
            "\n",
            "The `ComponentInfo` class needs to be imported:\n",
            "\n",
            "```python\n",
            "from haystack.dataclasses import (\n",
            "    AsyncStreamingCallbackT,\n",
            "    ChatMessage,\n",
            "    ChatRole,\n",
            "    ComponentInfo,  # Add this import\n",
            "    StreamingChunk,\n",
            "    SyncStreamingCallbackT,\n",
            "    ToolCall,\n",
            ")\n",
            "```\n",
            "\n",
            "### 2. Update `_convert_event_to_streaming_chunk` Function\n",
            "\n",
            "Modify the function signature to accept an optional `component_info` parameter and include it in all `StreamingChunk` creations:\n",
            "\n",
            "```python\n",
            "def _convert_event_to_streaming_chunk(\n",
            "    event: Dict[str, Any], \n",
            "    model: str, \n",
            "    component_info: Optional[ComponentInfo] = None\n",
            ") -> StreamingChunk:\n",
            "    \"\"\"\n",
            "    Convert a Bedrock streaming event to a Haystack StreamingChunk.\n",
            "\n",
            "    Handles different event types (contentBlockStart, contentBlockDelta, messageStop, metadata) and extracts relevant\n",
            "    information to create StreamingChunk objects in the same format used by Haystack's OpenAIChatGenerator.\n",
            "\n",
            "    :param event: Dictionary containing a Bedrock streaming event.\n",
            "    :param model: The model ID used for generation, included in chunk metadata.\n",
            "    :param component_info: An optional `ComponentInfo` object containing information about the component that\n",
            "        generated the chunk, such as the component name and type.\n",
            "    :returns: StreamingChunk object containing the content and metadata extracted from the event.\n",
            "    \"\"\"\n",
            "    # Initialize an empty StreamingChunk to return if no relevant event is found\n",
            "    # (e.g. for messageStart and contentBlockStop)\n",
            "    streaming_chunk = StreamingChunk(\n",
            "        content=\"\", \n",
            "        component_info=component_info,  # Add component_info here\n",
            "        meta={\"model\": model, \"received_at\": datetime.now(timezone.utc).isoformat()}\n",
            "    )\n",
            "\n",
            "    if \"contentBlockStart\" in event:\n",
            "        # contentBlockStart always has the key \"contentBlockIndex\"\n",
            "        block_start = event[\"contentBlockStart\"]\n",
            "        block_idx = block_start[\"contentBlockIndex\"]\n",
            "        if \"start\" in block_start and \"toolUse\" in block_start[\"start\"]:\n",
            "            tool_start = block_start[\"start\"][\"toolUse\"]\n",
            "            streaming_chunk = StreamingChunk(\n",
            "                content=\"\",\n",
            "                component_info=component_info,  # Add component_info here\n",
            "                meta={\n",
            "                    \"model\": model,\n",
            "                    # This is always 0 b/c it represents the choice index\n",
            "                    \"index\": 0,\n",
            "                    # We follow the same format used in the OpenAIChatGenerator\n",
            "                    \"tool_calls\": [  # Optional[List[ChoiceDeltaToolCall]]\n",
            "                        {\n",
            "                            \"index\": block_idx,  # int\n",
            "                            \"id\": tool_start[\"toolUseId\"],  # Optional[str]\n",
            "                            \"function\": {  # Optional[ChoiceDeltaToolCallFunction]\n",
            "                                # Will accumulate deltas as string\n",
            "                                \"arguments\": \"\",  # Optional[str]\n",
            "                                \"name\": tool_start[\"name\"],  # Optional[str]\n",
            "                            },\n",
            "                            \"type\": \"function\",  # Optional[Literal[\"function\"]]\n",
            "                        }\n",
            "                    ],\n",
            "                    \"finish_reason\": None,\n",
            "                    \"received_at\": datetime.now(timezone.utc).isoformat(),\n",
            "                },\n",
            "            )\n",
            "\n",
            "    elif \"contentBlockDelta\" in event:\n",
            "        # contentBlockDelta always has the key \"contentBlockIndex\" and \"delta\"\n",
            "        block_idx = event[\"contentBlockDelta\"][\"contentBlockIndex\"]\n",
            "        delta = event[\"contentBlockDelta\"][\"delta\"]\n",
            "        # This is for accumulating text deltas\n",
            "        if \"text\" in delta:\n",
            "            streaming_chunk = StreamingChunk(\n",
            "                content=delta[\"text\"],\n",
            "                component_info=component_info,  # Add component_info here\n",
            "                meta={\n",
            "                    \"model\": model,\n",
            "                    # This is always 0 b/c it represents the choice index\n",
            "                    \"index\": 0,\n",
            "                    \"tool_calls\": None,\n",
            "                    \"finish_reason\": None,\n",
            "                    \"received_at\": datetime.now(timezone.utc).isoformat(),\n",
            "                },\n",
            "            )\n",
            "        # This only occurs when accumulating the arguments for a toolUse\n",
            "        # The content_block for this tool should already exist at this point\n",
            "        elif \"toolUse\" in delta:\n",
            "            streaming_chunk = StreamingChunk(\n",
            "                content=\"\",\n",
            "                component_info=component_info,  # Add component_info here\n",
            "                meta={\n",
            "                    \"model\": model,\n",
            "                    # This is always 0 b/c it represents the choice index\n",
            "                    \"index\": 0,\n",
            "                    \"tool_calls\": [  # Optional[List[ChoiceDeltaToolCall]]\n",
            "                        {\n",
            "                            \"index\": block_idx,  # int\n",
            "                            \"id\": None,  # Optional[str]\n",
            "                            \"function\": {  # Optional[ChoiceDeltaToolCallFunction]\n",
            "                                # Will accumulate deltas as string\n",
            "                                \"arguments\": delta[\"toolUse\"].get(\"input\", \"\"),  # Optional[str]\n",
            "                                \"name\": None,  # Optional[str]\n",
            "                            },\n",
            "                            \"type\": \"function\",  # Optional[Literal[\"function\"]]\n",
            "                        }\n",
            "                    ],\n",
            "                    \"finish_reason\": None,\n",
            "                    \"received_at\": datetime.now(timezone.utc).isoformat(),\n",
            "                },\n",
            "            )\n",
            "\n",
            "    elif \"messageStop\" in event:\n",
            "        finish_reason = event[\"messageStop\"].get(\"stopReason\")\n",
            "        streaming_chunk = StreamingChunk(\n",
            "            content=\"\",\n",
            "            component_info=component_info,  # Add component_info here\n",
            "            meta={\n",
            "                \"model\": model,\n",
            "                # This is always 0 b/c it represents the choice index\n",
            "                \"index\": 0,\n",
            "                \"tool_calls\": None,\n",
            "                \"finish_reason\": finish_reason,\n",
            "                \"received_at\": datetime.now(timezone.utc).isoformat(),\n",
            "            },\n",
            "        )\n",
            "\n",
            "    elif \"metadata\" in event and \"usage\" in event[\"metadata\"]:\n",
            "        metadata = event[\"metadata\"]\n",
            "        streaming_chunk = StreamingChunk(\n",
            "            content=\"\",\n",
            "            component_info=component_info,  # Add component_info here\n",
            "            meta={\n",
            "                \"model\": model,\n",
            "                # This is always 0 b/c it represents the choice index\n",
            "                \"index\": 0,\n",
            "                \"tool_calls\": None,\n",
            "                \"finish_reason\": None,\n",
            "                \"received_at\": datetime.now(timezone.utc).isoformat(),\n",
            "                \"usage\": {\n",
            "                    \"prompt_tokens\": metadata[\"usage\"].get(\"inputTokens\", 0),\n",
            "                    \"completion_tokens\": metadata[\"usage\"].get(\"outputTokens\", 0),\n",
            "                    \"total_tokens\": metadata[\"usage\"].get(\"totalTokens\", 0),\n",
            "                },\n",
            "            },\n",
            "        )\n",
            "\n",
            "    return streaming_chunk\n",
            "```\n",
            "\n",
            "### 3. Update Streaming Response Parsing Functions\n",
            "\n",
            "Update both sync and async versions to create `ComponentInfo` and pass it to the conversion function:\n",
            "\n",
            "```python\n",
            "def _parse_streaming_response(\n",
            "    response_stream: EventStream,\n",
            "    streaming_callback: SyncStreamingCallbackT,\n",
            "    model: str,\n",
            "    component_info: Optional[ComponentInfo] = None,  # Add this parameter\n",
            ") -> List[ChatMessage]:\n",
            "    \"\"\"\n",
            "    Parse a streaming response from Bedrock.\n",
            "\n",
            "    :param response_stream: EventStream from Bedrock API\n",
            "    :param streaming_callback: Callback for streaming chunks\n",
            "    :param model: The model ID used for generation\n",
            "    :param component_info: An optional `ComponentInfo` object containing information about the component that\n",
            "        generated the chunk, such as the component name and type.\n",
            "    :return: List of ChatMessage objects\n",
            "    \"\"\"\n",
            "    chunks: List[StreamingChunk] = []\n",
            "    for event in response_stream:\n",
            "        streaming_chunk = _convert_event_to_streaming_chunk(\n",
            "            event=event, \n",
            "            model=model, \n",
            "            component_info=component_info  # Pass component_info here\n",
            "        )\n",
            "        streaming_callback(streaming_chunk)\n",
            "        chunks.append(streaming_chunk)\n",
            "    replies = [_convert_streaming_chunks_to_chat_message(chunks=chunks)]\n",
            "    return replies\n",
            "\n",
            "\n",
            "async def _parse_streaming_response_async(\n",
            "    response_stream: EventStream,\n",
            "    streaming_callback: AsyncStreamingCallbackT,\n",
            "    model: str,\n",
            "    component_info: Optional[ComponentInfo] = None,  # Add this parameter\n",
            ") -> List[ChatMessage]:\n",
            "    \"\"\"\n",
            "    Parse a streaming response from Bedrock.\n",
            "\n",
            "    :param response_stream: EventStream from Bedrock API\n",
            "    :param streaming_callback: Callback for streaming chunks\n",
            "    :param model: The model ID used for generation\n",
            "    :param component_info: An optional `ComponentInfo` object containing information about the component that\n",
            "        generated the chunk, such as the component name and type.\n",
            "    :return: List of ChatMessage objects\n",
            "    \"\"\"\n",
            "    chunks: List[StreamingChunk] = []\n",
            "    async for event in response_stream:\n",
            "        streaming_chunk = _convert_event_to_streaming_chunk(\n",
            "            event=event, \n",
            "            model=model, \n",
            "            component_info=component_info  # Pass component_info here\n",
            "        )\n",
            "        await streaming_callback(streaming_chunk)\n",
            "        chunks.append(streaming_chunk)\n",
            "    replies = [_convert_streaming_chunks_to_chat_message(chunks=chunks)]\n",
            "    return replies\n",
            "```\n",
            "\n",
            "### 4. Update Chat Generator Import\n",
            "\n",
            "In `chat_generator.py`, add the `ComponentInfo` import:\n",
            "\n",
            "```python\n",
            "from haystack.dataclasses import ChatMessage, StreamingCallbackT, ComponentInfo, select_streaming_callback\n",
            "```\n",
            "\n",
            "### 5. Update Chat Generator Methods\n",
            "\n",
            "Update both `run` and `run_async` methods to create and pass `ComponentInfo`:\n",
            "\n",
            "```python\n",
            "# In the run method, update the streaming section:\n",
            "if callback:\n",
            "    response = self.client.converse_stream(**params)\n",
            "    response_stream: EventStream = response.get(\"stream\")\n",
            "    if not response_stream:\n",
            "        msg = \"No stream found in the response.\"\n",
            "        raise AmazonBedrockInferenceError(msg)\n",
            "    \n",
            "    # Create ComponentInfo from this component instance\n",
            "    component_info = ComponentInfo.from_component(self)\n",
            "    replies = _parse_streaming_response(response_stream, callback, self.model, component_info)\n",
            "else:\n",
            "    response = self.client.converse(**params)\n",
            "    replies = _parse_completion_response(response, self.model)\n",
            "\n",
            "# In the run_async method, update the streaming section:\n",
            "if callback:\n",
            "    response = await async_client.converse_stream(**params)\n",
            "    response_stream: EventStream = response.get(\"stream\")\n",
            "    if not response_stream:\n",
            "        msg = \"No stream found in the response.\"\n",
            "        raise AmazonBedrockInferenceError(msg)\n",
            "    \n",
            "    # Create ComponentInfo from this component instance\n",
            "    component_info = ComponentInfo.from_component(self)\n",
            "    replies = await _parse_streaming_response_async(response_stream, callback, self.model, component_info)\n",
            "else:\n",
            "    response = await async_client.converse(**params)\n",
            "    replies = _parse_completion_response(response, self.model)\n",
            "```\n",
            "\n",
            "## Testing\n",
            "\n",
            "The existing tests should continue to pass with these changes. The `ComponentInfo` will be automatically populated for streaming chunks, making the component information available to any streaming callback functions.\n",
            "\n",
            "You can test the implementation by running streaming inference and checking that `chunk.component_info` is properly populated:\n",
            "\n",
            "```python\n",
            "def test_streaming_callback(chunk):\n",
            "    assert chunk.component_info is not None\n",
            "    assert \"AmazonBedrockChatGenerator\" in chunk.component_info.type\n",
            "    # component name will be None unless the component is added to a pipeline with a specific name\n",
            "\n",
            "generator = AmazonBedrockChatGenerator(model=\"anthropic.claude-3-5-sonnet-20240620-v1:0\", streaming_callback=test_streaming_callback)\n",
            "```\n",
            "\n",
            "This implementation follows the exact same pattern as the OpenAI chat generator and ensures consistency across all chat generators in the Haystack ecosystem.\n"
          ]
        }
      ],
      "source": [
        "print(result[\"issue_resolver_agent\"][\"last_message\"].tool_call_result.result)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "collapsed": true,
        "id": "cjeH2bcnDdSf"
      },
      "outputs": [],
      "source": [
        "# Render it in markdown format\n",
        "from IPython.display import Markdown, display\n",
        "\n",
        "display(Markdown(\"# Comment from Agent\\n\\n\" + result[\"issue_resolver_agent\"][\"last_message\"].tool_call_result.result))"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xG-ICFhHKwYb"
      },
      "source": [
        "By checking other `messages`, you can observe the iterative process of our Issue Resolver Agent as it generates the GitHub comment, making tool calls and processing their results step by step."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Fbtj2CNcKv_D"
      },
      "outputs": [],
      "source": [
        "result[\"issue_resolver_agent\"][\"messages\"]"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "28BQn_KALovJ"
      },
      "source": [
        "We can also investigate the files our Agent looked at:"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 35,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "id": "-JfJ5K8RLoML",
        "outputId": "bc62811e-803f-45f9-8eb7-1fd5938ac402"
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Markdown object>"
            ],
            "text/markdown": "[https://github.com/deepset-ai/haystack-core-integrations/blob/main/integrations/amazon_bedrock/src/haystack_integrations/components/generators/amazon_bedrock/chat/chat_generator.py](https://github.com/deepset-ai/haystack-core-integrations/blob/main/integrations/amazon_bedrock/src/haystack_integrations/components/generators/amazon_bedrock/chat/chat_generator.py)"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Markdown object>"
            ],
            "text/markdown": "[https://github.com/deepset-ai/haystack-core-integrations/blob/main/integrations/amazon_bedrock/src/haystack_integrations/components/generators/amazon_bedrock/chat/utils.py](https://github.com/deepset-ai/haystack-core-integrations/blob/main/integrations/amazon_bedrock/src/haystack_integrations/components/generators/amazon_bedrock/chat/utils.py)"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Markdown object>"
            ],
            "text/markdown": "[https://github.com/deepset-ai/haystack/blob/main/haystack/dataclasses/streaming_chunk.py](https://github.com/deepset-ai/haystack/blob/main/haystack/dataclasses/streaming_chunk.py)"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Markdown object>"
            ],
            "text/markdown": "[https://github.com/deepset-ai/haystack/blob/main/haystack/components/generators/chat/openai.py](https://github.com/deepset-ai/haystack/blob/main/haystack/components/generators/chat/openai.py)"
          },
          "metadata": {}
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<IPython.core.display.Markdown object>"
            ],
            "text/markdown": "[https://github.com/deepset-ai/haystack-core-integrations/blob/main/integrations/amazon_bedrock/tests/test_chat_generator.py](https://github.com/deepset-ai/haystack-core-integrations/blob/main/integrations/amazon_bedrock/tests/test_chat_generator.py)"
          },
          "metadata": {}
        }
      ],
      "source": [
        "for document in result[\"issue_resolver_agent\"][\"documents\"]:\n",
        "    if document.meta[\"type\"] in [\"file_content\"]:\n",
        "        display(Markdown(f\"[{document.meta['url']}]({document.meta['url']})\"))"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": ".venv",
      "language": "python",
      "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": "3.13.3"
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}