Add Azure OpenAI docs

guidance/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "0.0.60"
+__version__ = "0.0.61"
 
 import types
 import sys

guidance/llms/__init__.py

@@ -1,8 +1,7 @@
-from ._openai import OpenAI
+from ._openai import OpenAI, MSALOpenAI, AzureOpenAI
 from ._transformers import Transformers
 from ._mock import Mock
 from ._llm import LLM, LLMSession, SyncSession
-from ._azure_openai import AzureOpenAI
 from ._deep_speed import DeepSpeed
 from . import transformers
 from . import caches

guidance/llms/_openai.py

@@ -553,3 +553,83 @@ async def __call__(self, prompt, stop=None, stop_regex=None, temperature=None, n
             return [llm_cache[key]]
 
         return llm_cache[key]
+
+
+import os
+import atexit
+import json
+import platformdirs
+from ._openai import OpenAI
+
+class AzureOpenAI(OpenAI):
+    def __init__(self, *args, **kwargs):
+        raise NotImplementedError("The AzureOpenAI class has been merged with the OpenAI class for Azure usage. Please use the OpenAI class instead: https://guidance.readthedocs.io/en/latest/example_notebooks/api_examples/llms/OpenAI.html")
+
+class MSALOpenAI(OpenAI):
+    """ Microsoft Authentication Library (MSAL) OpenAI style integration.
+
+    Warning: This class is not finalized and may change in the future.
+    """
+
+    llm_name: str = "azure_openai"
+
+    def __init__(self, model=None, client_id=None, authority=None, caching=True, max_retries=5, max_calls_per_min=60, token=None,
+                 endpoint=None, scopes=None, temperature=0.0, chat_mode="auto"):
+
+
+        assert endpoint is not None, "An endpoint must be specified!"
+
+        # build a standard OpenAI LLM object
+        super().__init__(
+            model=model, caching=caching, max_retries=max_retries, max_calls_per_min=max_calls_per_min,
+            token=token, endpoint=endpoint, temperature=temperature, chat_mode=chat_mode
+        )
+
+        self.client_id = client_id
+        self.authority = authority
+        self.scopes = scopes
+
+        from msal import PublicClientApplication, SerializableTokenCache
+        self._token_cache = SerializableTokenCache()
+        self._token_cache_path = os.path.join(platformdirs.user_cache_dir("guidance"), "_azure_openai.token")
+        self._app = PublicClientApplication(client_id=self.client_id, authority=self.authority, token_cache=self._token_cache)
+        if os.path.exists(self._token_cache_path):
+            self._token_cache.deserialize(open(self._token_cache_path, 'r').read())
+
+        self._rest_headers["X-ModelType"] = self.model_name
+
+    @property
+    def token(self):
+        return self._get_token()
+    @token.setter
+    def token(self, value):
+        pass # ignored for now
+
+    def _get_token(self):
+        accounts = self._app.get_accounts()
+        result = None
+
+        if accounts:
+            # Assuming the end user chose this one
+            chosen = accounts[0]
+
+            # Now let's try to find a token in cache for this account
+            result = self._app.acquire_token_silent(self.scopes, account=chosen)
+
+        if not result:
+            # So no suitable token exists in cache. Let's get a new one from AAD.
+            flow = self._app.initiate_device_flow(scopes=self.scopes)
+
+            if "user_code" not in flow:
+                raise ValueError(
+                    "Fail to create device flow. Err: %s" % json.dumps(flow, indent=4))
+
+            print(flow["message"])
+
+            result = self._app.acquire_token_by_device_flow(flow)
+
+            # save the aquired token
+            with open(self._token_cache_path, "w") as f:
+                f.write(self._token_cache.serialize())
+
+        return result["access_token"]

notebooks/api_examples/llms/OpenAI.ipynb

@@ -0,0 +1,109 @@
+{
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# `OpenAI` API examples\n",
+    "\n",
+    "This notebook contains examples of how to use the `OpenAI` LLM."
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Basic OpenAI usage"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div id=\"guidance-stop-button-836b0e69-9215-48a7-be0f-33edbb2a754b\" style=\"cursor: pointer; margin: 0px; display: none; float: right; padding: 3px; border-radius: 4px 4px 4px 4px; border: 0px solid rgba(127, 127, 127, 1); padding-left: 10px; padding-right: 10px; font-size: 13px; background-color: rgba(127, 127, 127, 0.25);\">Stop program</div><div id=\"guidance-content-836b0e69-9215-48a7-be0f-33edbb2a754b\"><pre style='margin: 0px; padding: 0px; padding-left: 8px; margin-left: -8px; border-radius: 0px; border-left: 1px solid rgba(127, 127, 127, 0.2); white-space: pre-wrap; font-family: ColfaxAI, Arial; font-size: 15px; line-height: 23px;'>My favorite flavor is<span style='background-color: rgba(0, 165, 0, 0.25); opacity: 1.0; display: inline;' title='{{gen &#x27;flavor&#x27; max_tokens=10 stop=&quot;.&quot;}}'> chocolate</span></pre></div>\n",
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+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import guidance\n",
+    "\n",
+    "# this relies on the environment variable OPENAI_API_KEY being set\n",
+    "llm = guidance.llms.OpenAI('text-davinci-003')\n",
+    "\n",
+    "program = guidance(\"\"\"My favorite flavor is{{gen 'flavor' max_tokens=10 stop=\".\"}}\"\"\", llm=llm)\n",
+    "program()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Basic Azure OpenAI usage"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import guidance\n",
+    "\n",
+    "# here we explicitly pass in the API key\n",
+    "llm = guidance.llms.OpenAI(\n",
+    "    'text-davinci-003',\n",
+    "    api_type='azure',\n",
+    "    api_key='sk-...',\n",
+    "    api_base='https://example-endpoint.openai.azure.com',\n",
+    "    api_version='2023-05-15',\n",
+    "    deployment_id='...'\n",
+    ")\n",
+    "\n",
+    "program = guidance(\"\"\"My favorite flavor is{{gen 'flavor' max_tokens=10 stop=\".\"}}\"\"\", llm=llm)\n",
+    "program()"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "<hr style=\"height: 1px; opacity: 0.5; border: none; background: #cccccc;\">\n",
+    "<div style=\"text-align: center; opacity: 0.5\">Have an idea for more helpful examples? Pull requests that add to this documentation notebook are encouraged!</div>"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "adatest",
+   "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": "3.10.4"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}