Upgrade Assistant with ollama backend

README.md

@@ -193,17 +193,16 @@ t2t.Transformer.LANGUAGES
 import text2text as t2t
 asst = t2t.Assistant()
 
-#OpenAI Chat Completion API
+# Streaming example
 chat_history = [
     {"role": "user",  "content": "Hi"},
     {"role": "assistant", "content": "Hello, how are you?"},
     {"role": "user", "content": "What should I do today?"}
 ]
-num_tokens = asst.chat_completion_tokens(chat_history) #31
-print(num_tokens)
 
 result = asst.chat_completion(chat_history, stream=True) #{'role': 'assistant', 'content': '1. Make a list of things to be grateful for.\n2. Go outside and take a walk in nature.\n3. Practice mindfulness meditation.\n4. Connect with a loved one or friend.\n5. Do something kind for someone else.\n6. Engage in a creative activity like drawing or writing.\n7. Read an uplifting book or listen to motivational podcasts.'}
-print(result["content"])
+for chunk in result:
+  print(chunk['message']['content'], end='', flush=True)
 ```
 
 ### Tokenization

demos/Text2Text_Demos.ipynb

@@ -66,18 +66,16 @@
         "\n",
         "asst = t2t.Assistant()\n",
         "\n",
-        "#OpenAI Chat Completion API\n",
-        "\n",
+        "# Streaming example\n",
         "chat_history = [\n",
         "    {\"role\": \"user\",  \"content\": \"Hi\"},\n",
         "    {\"role\": \"assistant\", \"content\": \"Hello, how are you?\"},\n",
         "    {\"role\": \"user\", \"content\": \"What should I do today?\"}\n",
         "]\n",
-        "num_tokens = asst.chat_completion_tokens(chat_history) #31\n",
-        "print(num_tokens)\n",
         "\n",
         "result = asst.chat_completion(chat_history, stream=True) #{'role': 'assistant', 'content': '1. Make a list of things to be grateful for.\\n2. Go outside and take a walk in nature.\\n3. Practice mindfulness meditation.\\n4. Connect with a loved one or friend.\\n5. Do something kind for someone else.\\n6. Engage in a creative activity like drawing or writing.\\n7. Read an uplifting book or listen to motivational podcasts.'}\n",
-        "print(result[\"content\"])"
+        "for chunk in result:\n",
+        "  print(chunk['message']['content'], end='', flush=True)"
       ],
       "metadata": {
         "id": "VPMdUSy9YYRl"