add mirascope

khuyentran1401 · May 7, 2024 · 85446bd · 85446bd
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diff --git a/Chapter2/typing.ipynb b/Chapter2/typing.ipynb
@@ -738,7 +738,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.11.6"
   },
   "toc": {
    "base_numbering": 1,

diff --git a/Chapter5/llm.ipynb b/Chapter5/llm.ipynb
@@ -244,6 +244,105 @@
    "source": [
     "[Link to Outlines](https://github.com/outlines-dev/outlines)."
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ff519c06",
+   "metadata": {},
+   "source": [
+    "### Mirascope: Extract Structured Data Extraction From LLM Outputs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dc12a009",
+   "metadata": {
+    "tags": [
+     "hide-cell"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "!pip install mirascope"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0ea9cc6f",
+   "metadata": {},
+   "source": [
+    "Large Language Models (LLMs) are powerful at producing human-like text, but their outputs lack structure, which can limit their usefulness in many practical applications that require organized data.\n",
+    "\n",
+    "Mirascope offers a solution by enabling the extraction of structured information from LLM outputs reliably.\n",
+    "\n",
+    "The following code uses Mirascope to extract meeting details such as topic, date, time, and participants."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "03c7cfb0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "\n",
+    "\n",
+    "os.environ[\"OPENAI_API_KEY\"] = \"YOUR_API_KEY\"\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "79f19428",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "topic='Upcoming product launch' date='June 15th' time='3 PM' participants=['John', 'Sarah', 'Mike']\n"
+     ]
+    }
+   ],
+   "source": [
+    "from typing import List, Type\n",
+    "from pydantic import BaseModel\n",
+    "from mirascope.openai import OpenAIExtractor\n",
+    "\n",
+    "\n",
+    "class MeetingDetails(BaseModel):\n",
+    "    topic: str\n",
+    "    date: str\n",
+    "    time: str\n",
+    "    participants: List[str]\n",
+    "\n",
+    "\n",
+    "class MeetingExtractor(OpenAIExtractor[MeetingDetails]):\n",
+    "    extract_schema: Type[MeetingDetails] = MeetingDetails\n",
+    "    prompt_template = \"\"\"\n",
+    "    Extract the meeting details from the following description:\n",
+    "    {description}\n",
+    "    \"\"\"\n",
+    "\n",
+    "    description: str\n",
+    "\n",
+    "\n",
+    "# Example usage:\n",
+    "description = \"Discuss the upcoming product launch on June 15th at 3 PM with John, Sarah, and Mike.\"\n",
+    "meeting_details = MeetingExtractor(description=description).extract()\n",
+    "assert isinstance(meeting_details, MeetingDetails)\n",
+    "print(meeting_details)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "641d2dd5",
+   "metadata": {},
+   "source": [
+    "[Link to Mirascope](https://bit.ly/4bkciv3)."
+   ]
   }
  ],
  "metadata": {

diff --git a/docs/Chapter5/llm.html b/docs/Chapter5/llm.html
@@ -514,6 +514,7 @@ <h2> Contents </h2>
                 <ul class="visible nav section-nav flex-column">
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#simplify-llm-integration-with-magentic-s-prompt-decorator">6.16.1. Simplify LLM Integration with Magentic’s @prompt Decorator</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#outlines-ensuring-consistent-outputs-from-language-models">6.16.2. Outlines: Ensuring Consistent Outputs from Language Models</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#mirascope-extract-structured-data-extraction-from-llm-outputs">6.16.3. Mirascope: Extract Structured Data Extraction From LLM Outputs</a></li>
 </ul>
             </nav>
         </div>
@@ -660,6 +661,74 @@ <h2><span class="section-number">6.16.2. </span>Outlines: Ensuring Consistent Ou
 </div>
 <p><a class="reference external" href="https://github.com/outlines-dev/outlines">Link to Outlines</a>.</p>
 </section>
+<section id="mirascope-extract-structured-data-extraction-from-llm-outputs">
+<h2><span class="section-number">6.16.3. </span>Mirascope: Extract Structured Data Extraction From LLM Outputs<a class="headerlink" href="#mirascope-extract-structured-data-extraction-from-llm-outputs" title="Permalink to this heading">#</a></h2>
+<div class="cell tag_hide-cell docutils container">
+<details class="hide above-input">
+<summary aria-label="Toggle hidden content">
+<span class="collapsed">Show code cell content</span>
+<span class="expanded">Hide code cell content</span>
+</summary>
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="o">!</span>pip<span class="w"> </span>install<span class="w"> </span>mirascope
+</pre></div>
+</div>
+</div>
+</details>
+</div>
+<p>Large Language Models (LLMs) are powerful at producing human-like text, but their outputs lack structure, which can limit their usefulness in many practical applications that require organized data.</p>
+<p>Mirascope offers a solution by enabling the extraction of structured information from LLM outputs reliably.</p>
+<p>The following code uses Mirascope to extract meeting details such as topic, date, time, and participants.</p>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span> <span class="nn">os</span>
+
+
+<span class="n">os</span><span class="o">.</span><span class="n">environ</span><span class="p">[</span><span class="s2">&quot;OPENAI_API_KEY&quot;</span><span class="p">]</span> <span class="o">=</span> <span class="s2">&quot;YOUR_API_KEY&quot;</span>
+</pre></div>
+</div>
+</div>
+</div>
+<div class="cell docutils container">
+<div class="cell_input docutils container">
+<div class="highlight-ipython3 notranslate"><div class="highlight"><pre><span></span><span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">List</span><span class="p">,</span> <span class="n">Type</span>
+<span class="kn">from</span> <span class="nn">pydantic</span> <span class="kn">import</span> <span class="n">BaseModel</span>
+<span class="kn">from</span> <span class="nn">mirascope.openai</span> <span class="kn">import</span> <span class="n">OpenAIExtractor</span>
+
+
+<span class="k">class</span> <span class="nc">MeetingDetails</span><span class="p">(</span><span class="n">BaseModel</span><span class="p">):</span>
+    <span class="n">topic</span><span class="p">:</span> <span class="nb">str</span>
+    <span class="n">date</span><span class="p">:</span> <span class="nb">str</span>
+    <span class="n">time</span><span class="p">:</span> <span class="nb">str</span>
+    <span class="n">participants</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="nb">str</span><span class="p">]</span>
+
+
+<span class="k">class</span> <span class="nc">MeetingExtractor</span><span class="p">(</span><span class="n">OpenAIExtractor</span><span class="p">[</span><span class="n">MeetingDetails</span><span class="p">]):</span>
+    <span class="n">extract_schema</span><span class="p">:</span> <span class="n">Type</span><span class="p">[</span><span class="n">MeetingDetails</span><span class="p">]</span> <span class="o">=</span> <span class="n">MeetingDetails</span>
+    <span class="n">prompt_template</span> <span class="o">=</span> <span class="s2">&quot;&quot;&quot;</span>
+<span class="s2">    Extract the meeting details from the following description:</span>
+<span class="s2">    </span><span class="si">{description}</span>
+<span class="s2">    &quot;&quot;&quot;</span>
+
+    <span class="n">description</span><span class="p">:</span> <span class="nb">str</span>
+
+
+<span class="c1"># Example usage:</span>
+<span class="n">description</span> <span class="o">=</span> <span class="s2">&quot;Discuss the upcoming product launch on June 15th at 3 PM with John, Sarah, and Mike.&quot;</span>
+<span class="n">meeting_details</span> <span class="o">=</span> <span class="n">MeetingExtractor</span><span class="p">(</span><span class="n">description</span><span class="o">=</span><span class="n">description</span><span class="p">)</span><span class="o">.</span><span class="n">extract</span><span class="p">()</span>
+<span class="k">assert</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">meeting_details</span><span class="p">,</span> <span class="n">MeetingDetails</span><span class="p">)</span>
+<span class="nb">print</span><span class="p">(</span><span class="n">meeting_details</span><span class="p">)</span>
+</pre></div>
+</div>
+</div>
+<div class="cell_output docutils container">
+<div class="output stream highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>topic=&#39;Upcoming product launch&#39; date=&#39;June 15th&#39; time=&#39;3 PM&#39; participants=[&#39;John&#39;, &#39;Sarah&#39;, &#39;Mike&#39;]
+</pre></div>
+</div>
+</div>
+</div>
+<p><a class="reference external" href="https://bit.ly/4bkciv3">Link to Mirascope</a>.</p>
+</section>
 </section>
 
     <script type="text/x-thebe-config">
@@ -727,6 +796,7 @@ <h2><span class="section-number">6.16.2. </span>Outlines: Ensuring Consistent Ou
     <ul class="visible nav section-nav flex-column">
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#simplify-llm-integration-with-magentic-s-prompt-decorator">6.16.1. Simplify LLM Integration with Magentic’s @prompt Decorator</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#outlines-ensuring-consistent-outputs-from-language-models">6.16.2. Outlines: Ensuring Consistent Outputs from Language Models</a></li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#mirascope-extract-structured-data-extraction-from-llm-outputs">6.16.3. Mirascope: Extract Structured Data Extraction From LLM Outputs</a></li>
 </ul>
   </nav></div>
 

diff --git a/docs/_sources/Chapter2/typing.ipynb b/docs/_sources/Chapter2/typing.ipynb
@@ -738,7 +738,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.6"
+   "version": "3.11.6"
   },
   "toc": {
    "base_numbering": 1,

diff --git a/docs/_sources/Chapter5/llm.ipynb b/docs/_sources/Chapter5/llm.ipynb
@@ -244,6 +244,105 @@
    "source": [
     "[Link to Outlines](https://github.com/outlines-dev/outlines)."
    ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ff519c06",
+   "metadata": {},
+   "source": [
+    "### Mirascope: Extract Structured Data Extraction From LLM Outputs"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "dc12a009",
+   "metadata": {
+    "tags": [
+     "hide-cell"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "!pip install mirascope"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "0ea9cc6f",
+   "metadata": {},
+   "source": [
+    "Large Language Models (LLMs) are powerful at producing human-like text, but their outputs lack structure, which can limit their usefulness in many practical applications that require organized data.\n",
+    "\n",
+    "Mirascope offers a solution by enabling the extraction of structured information from LLM outputs reliably.\n",
+    "\n",
+    "The following code uses Mirascope to extract meeting details such as topic, date, time, and participants."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "03c7cfb0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "\n",
+    "\n",
+    "os.environ[\"OPENAI_API_KEY\"] = \"YOUR_API_KEY\"\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "79f19428",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "topic='Upcoming product launch' date='June 15th' time='3 PM' participants=['John', 'Sarah', 'Mike']\n"
+     ]
+    }
+   ],
+   "source": [
+    "from typing import List, Type\n",
+    "from pydantic import BaseModel\n",
+    "from mirascope.openai import OpenAIExtractor\n",
+    "\n",
+    "\n",
+    "class MeetingDetails(BaseModel):\n",
+    "    topic: str\n",
+    "    date: str\n",
+    "    time: str\n",
+    "    participants: List[str]\n",
+    "\n",
+    "\n",
+    "class MeetingExtractor(OpenAIExtractor[MeetingDetails]):\n",
+    "    extract_schema: Type[MeetingDetails] = MeetingDetails\n",
+    "    prompt_template = \"\"\"\n",
+    "    Extract the meeting details from the following description:\n",
+    "    {description}\n",
+    "    \"\"\"\n",
+    "\n",
+    "    description: str\n",
+    "\n",
+    "\n",
+    "# Example usage:\n",
+    "description = \"Discuss the upcoming product launch on June 15th at 3 PM with John, Sarah, and Mike.\"\n",
+    "meeting_details = MeetingExtractor(description=description).extract()\n",
+    "assert isinstance(meeting_details, MeetingDetails)\n",
+    "print(meeting_details)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "641d2dd5",
+   "metadata": {},
+   "source": [
+    "[Link to Mirascope](https://bit.ly/4bkciv3)."
+   ]
   }
  ],
  "metadata": {

diff --git a/docs/searchindex.js b/docs/searchindex.js