Use genai.protos instead of google.ai.generativelanguage (#192)

* Use genai.protos instead of google.ai.generativelanguage * fix links * lint * genai.GenerateContent* -> genai.protos.GenerateContent* * Fix import --------- Co-authored-by: Mark McDonald <macd@google.com>
google-gemini · Jun 7, 2024 · b4d0067 · b4d0067
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diff --git a/examples/Anomaly_detection_with_embeddings.ipynb b/examples/Anomaly_detection_with_embeddings.ipynb
@@ -90,7 +90,6 @@
         "import seaborn as sns\n",
         "\n",
         "import google.generativeai as genai\n",
-        "import google.ai.generativelanguage as glm\n",
         "\n",
         "# Used to securely store your API key\n",
         "from google.colab import userdata\n",

diff --git a/examples/Classify_text_with_embeddings.ipynb b/examples/Classify_text_with_embeddings.ipynb
@@ -90,7 +90,6 @@
         "import pandas as pd\n",
         "\n",
         "import google.generativeai as genai\n",
-        "import google.ai.generativelanguage as glm\n",
         "\n",
         "from google.colab import userdata\n",
         "\n",

diff --git a/examples/Search_reranking_using_embeddings.ipynb b/examples/Search_reranking_using_embeddings.ipynb
@@ -720,7 +720,7 @@
         "In the chat history you can see all 4 steps:\n",
         "\n",
         "1. The user sent the query.\n",
-        "2. The model replied with a `glm.FunctionCall` calling the `wikipedia_search` with a number of relevant searches.\n",
+        "2. The model replied with a `genai.protos.FunctionCall` calling the `wikipedia_search` with a number of relevant searches.\n",
         "3. Because you set `enable_automatic_function_calling=True` when creating the `genai.ChatSession`, it  executed the search function and returned the list of article summaries to the model.\n",
         "4. Folliwing the instructions in the prompt, the model generated a final answer based on those summaries.\n"
       ]
@@ -743,17 +743,6 @@
         "If you want to understand what happened behind the scenes, this section executes the `FunctionCall` manually to demonstrate."
       ]
     },
-    {
-      "cell_type": "code",
-      "execution_count": 11,
-      "metadata": {
-        "id": "6Q4p-zSP7ZBs"
-      },
-      "outputs": [],
-      "source": [
-        "import google.ai.generativelanguage as glm # for lower level code"
-      ]
-    },
     {
       "cell_type": "code",
       "execution_count": 12,
@@ -970,9 +959,9 @@
       ],
       "source": [
         "response = chat.send_message(\n",
-        "    glm.Content(\n",
-        "      parts=[glm.Part(\n",
-        "          function_response = glm.FunctionResponse(\n",
+        "    genai.protos.Content(\n",
+        "      parts=[genai.protos.Part(\n",
+        "          function_response = genai.protos.FunctionResponse(\n",
         "            name='wikipedia_search',\n",
         "            response={'result': summaries}\n",
         "          )\n",

diff --git a/examples/Talk_to_documents_with_embeddings.ipynb b/examples/Talk_to_documents_with_embeddings.ipynb
@@ -99,7 +99,6 @@
         "import pandas as pd\n",
         "\n",
         "import google.generativeai as genai\n",
-        "import google.ai.generativelanguage as glm\n",
         "\n",
         "# Used to securely store your API key\n",
         "from google.colab import userdata\n",

diff --git a/quickstarts/Counting_Tokens.ipynb b/quickstarts/Counting_Tokens.ipynb
@@ -308,7 +308,7 @@
               "        tools=None,\n",
               "        system_instruction=None,\n",
               "    ),\n",
-              "    history=[glm.Content({'parts': [{'text': 'Hi my name is Bob'}], 'role': 'user'}), glm.Content({'parts': [{'text': 'Hi Bob!'}], 'role': 'model'})]\n",
+              "    history=[genai.protos.Content({'parts': [{'text': 'Hi my name is Bob'}], 'role': 'user'}), genai.protos.Content({'parts': [{'text': 'Hi Bob!'}], 'role': 'model'})]\n",
               ")"
             ]
           },

diff --git a/quickstarts/Function_calling.ipynb b/quickstarts/Function_calling.ipynb
@@ -128,7 +128,7 @@
       "source": [
         "To use function calling, pass a list of functions to the `tools` parameter when creating a [`GenerativeModel`](https://ai.google.dev/api/python/google/generativeai/GenerativeModel). The model uses the function name, docstring, parameters, and parameter type annotations to decide if it needs the function to best answer a prompt.\n",
         "\n",
-        "> Important: The SDK converts function parameter type annotations to a format the API understands (`glm.FunctionDeclaration`). The API only supports a limited selection of parameter types, and the Python SDK's automatic conversion only supports a subset of that: `AllowedTypes = int | float | bool | str | list['AllowedTypes'] | dict`"
+        "> Important: The SDK converts function parameter type annotations to a format the API understands (`genai.protos.FunctionDeclaration`). The API only supports a limited selection of parameter types, and the Python SDK's automatic conversion only supports a subset of that: `AllowedTypes = int | float | bool | str | list['AllowedTypes'] | dict`"
       ]
     },
     {
@@ -278,13 +278,13 @@
       "source": [
         "However, by examining the chat history, you can see the flow of the conversation and how function calls are integrated within it.\n",
         "\n",
-        "The `ChatSession.history` property stores a chronological record of the conversation between the user and the Gemini model. Each turn in the conversation is represented by a [`glm.Content`](https://ai.google.dev/api/python/google/ai/generativelanguage/Content) object, which contains the following information:\n",
+        "The `ChatSession.history` property stores a chronological record of the conversation between the user and the Gemini model. Each turn in the conversation is represented by a [`genai.protos.Content`](https://ai.google.dev/api/python/google/generativeai/protos/Content) object, which contains the following information:\n",
         "\n",
         "*   **Role**: Identifies whether the content originated from the \"user\" or the \"model\".\n",
-        "*   **Parts**: A list of [`glm.Part`](https://ai.google.dev/api/python/google/ai/generativelanguage/Part) objects that represent individual components of the message. With a text-only model, these parts can be:\n",
+        "*   **Parts**: A list of [`genai.protos.Part`](https://ai.google.dev/api/python/google/generativeai/protos/Part) objects that represent individual components of the message. With a text-only model, these parts can be:\n",
         "    *   **Text**: Plain text messages.\n",
-        "    *   **Function Call** ([`glm.FunctionCall`](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall)): A request from the model to execute a specific function with provided arguments.\n",
-        "    *   **Function Response** ([`glm.FunctionResponse`](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionResponse)): The result returned by the user after executing the requested function.\n",
+        "    *   **Function Call** ([`genai.protos.FunctionCall`](https://ai.google.dev/api/python/google/generativeai/protos/FunctionCall)): A request from the model to execute a specific function with provided arguments.\n",
+        "    *   **Function Response** ([`genai.protos.FunctionResponse`](https://ai.google.dev/api/python/google/generativeai/protos/FunctionResponse)): The result returned by the user after executing the requested function.\n",
         "\n",
         " In the previous example with the mittens calculation, the history shows the following sequence:\n",
         "\n",
@@ -350,7 +350,7 @@
         "id": "9610f3465a69"
       },
       "source": [
-        "For more control, you can process [`glm.FunctionCall`](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall) requests from the model yourself. This would be the case if:\n",
+        "For more control, you can process [`genai.protos.FunctionCall`](https://ai.google.dev/api/python/google/generativeai/protos/FunctionCall) requests from the model yourself. This would be the case if:\n",
         "\n",
         "- You use a `ChatSession` with the default `enable_automatic_function_calling=False`.\n",
         "- You use `GenerativeModel.generate_content` (and manage the chat history yourself)."
@@ -560,16 +560,15 @@
         }
       ],
       "source": [
-        "import google.ai.generativelanguage as glm\n",
         "from google.protobuf.struct_pb2 import Struct\n",
         "\n",
         "# Put the result in a protobuf Struct\n",
         "s = Struct()\n",
         "s.update({\"result\": result})\n",
         "\n",
         "# Update this after https://github.com/google/generative-ai-python/issues/243\n",
-        "function_response = glm.Part(\n",
-        "    function_response=glm.FunctionResponse(name=\"find_theaters\", response=s)\n",
+        "function_response = genai.protos.Part(\n",
+        "    function_response=genai.protos.FunctionResponse(name=\"find_theaters\", response=s)\n",
         ")\n",
         "\n",
         "# Build the message history\n",
@@ -709,8 +708,6 @@
         }
       ],
       "source": [
-        "import google.ai.generativelanguage as glm\n",
-        "\n",
         "# Simulate the responses from the specified tools.\n",
         "responses = {\n",
         "    \"power_disco_ball\": True,\n",
@@ -720,7 +717,7 @@
         "\n",
         "# Build the response parts.\n",
         "response_parts = [\n",
-        "    glm.Part(function_response=glm.FunctionResponse(name=fn, response={\"result\": val}))\n",
+        "    genai.protos.Part(function_response=genai.protos.FunctionResponse(name=fn, response={\"result\": val}))\n",
         "    for fn, val in responses.items()\n",
         "]\n",
         "\n",
@@ -746,13 +743,13 @@
         "Useful API references:\n",
         "\n",
         "- The [genai.GenerativeModel](https://ai.google.dev/api/python/google/generativeai/GenerativeModel) class\n",
-        "  - Its [GenerativeModel.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) method builds a [glm.GenerateContentRequest](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentRequest) behind the scenes.\n",
-        "    - The request's `.tools` field contains a list of 1 [glm.Tool](https://ai.google.dev/api/python/google/ai/generativelanguage/Tool) object.\n",
-        "    - The tool's `function_declarations` attribute contains a list of [FunctionDeclarations](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionDeclaration) objects.\n",
-        "- The [response](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse) may contain a [glm.FunctionCall](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall), in `response.candidates[0].contents.parts[0]`.\n",
-        "- if `enable_automatic_function_calling` is set the [genai.ChatSession](https://ai.google.dev/api/python/google/generativeai/ChatSession) executes the call, and sends back the [glm.FunctionResponse](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionResponse).\n",
-        "- In response to a [FunctionCall](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionCall) the model always expects a [FunctionResponse](https://ai.google.dev/api/python/google/ai/generativelanguage/FunctionResponse).\n",
-        "- If you reply manually using [chat.send_message](https://ai.google.dev/api/python/google/generativeai/ChatSession#send_message) or [model.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) remember thart the API is stateless you have to send the whole conversation history (a list of [content](https://ai.google.dev/api/python/google/ai/generativelanguage/Content) objects), not just the last one containing the `FunctionResponse`."
+        "  - Its [GenerativeModel.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) method builds a [genai.protos.GenerateContentRequest](https://ai.google.dev/api/python/google/generativeai/protos/GenerateContentRequest) behind the scenes.\n",
+        "    - The request's `.tools` field contains a list of 1 [genai.protos.Tool](https://ai.google.dev/api/python/google/generativeai/protos/Tool) object.\n",
+        "    - The tool's `function_declarations` attribute contains a list of [FunctionDeclarations](https://ai.google.dev/api/python/google/generativeai/protos/FunctionDeclaration) objects.\n",
+        "- The [response](https://ai.google.dev/api/python/google/generativeai/protos/GenerateContentResponse) may contain a [genai.protos.FunctionCall](https://ai.google.dev/api/python/google/generativeai/protos/FunctionCall), in `response.candidates[0].contents.parts[0]`.\n",
+        "- if `enable_automatic_function_calling` is set the [genai.ChatSession](https://ai.google.dev/api/python/google/generativeai/ChatSession) executes the call, and sends back the [genai.protos.FunctionResponse](https://ai.google.dev/api/python/google/generativeai/protos/FunctionResponse).\n",
+        "- In response to a [FunctionCall](https://ai.google.dev/api/python/google/generativeai/protos/FunctionCall) the model always expects a [FunctionResponse](https://ai.google.dev/api/python/google/generativeai/protos/FunctionResponse).\n",
+        "- If you reply manually using [chat.send_message](https://ai.google.dev/api/python/google/generativeai/ChatSession#send_message) or [model.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) remember thart the API is stateless you have to send the whole conversation history (a list of [content](https://ai.google.dev/api/python/google/generativeai/protos/Content) objects), not just the last one containing the `FunctionResponse`."
       ]
     }
   ],

diff --git a/quickstarts/Safety.ipynb b/quickstarts/Safety.ipynb
@@ -131,7 +131,7 @@
         "\n",
         "Pick the prompt you want to use to test the safety filters settings. An examples could be `Write a list of 5 very rude things that I might say to the universe after stubbing my toe in the dark` which was previously tested and trigger the `HARM_CATEGORY_HARASSMENT` and `HARM_CATEGORY_DANGEROUS_CONTENT` categories.\n",
         "\n",
-        "The result returned by the [Model.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) method is a [genai.GenerateContentResponse](https://ai.google.dev/api/python/google/generativeai/types/GenerateContentResponse)."
+        "The result returned by the [Model.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) method is a [genai.protos.GenerateContentResponse](https://ai.google.dev/api/python/google/generativeai/types/GenerateContentResponse)."
       ]
     },
     {
@@ -402,13 +402,13 @@
         "\n",
         "* They can also be passed on each request to [GenerativeModel.generate_content](https://ai.google.dev/api/python/google/generativeai/GenerativeModel#generate_content) or [ChatSession.send_message](https://ai.google.dev/api/python/google/generativeai/ChatSession?hl=en#send_message).\n",
         "\n",
-        "- The [genai.GenerateContentResponse](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse) returns [SafetyRatings](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetyRating) for the prompt in the [GenerateContentResponse.prompt_feedback](https://ai.google.dev/api/python/google/ai/generativelanguage/GenerateContentResponse/PromptFeedback), and for each [Candidate](https://ai.google.dev/api/python/google/ai/generativelanguage/Candidate) in the `safety_ratings` attribute.\n",
+        "- The [genai.protos.GenerateContentResponse](https://ai.google.dev/api/python/google/generativeai/protos/GenerateContentResponse) returns [SafetyRatings](https://ai.google.dev/api/python/google/generativeai/protos/SafetyRating) for the prompt in the [GenerateContentResponse.prompt_feedback](https://ai.google.dev/api/python/google/generativeai/protos/GenerateContentResponse/PromptFeedback), and for each [Candidate](https://ai.google.dev/api/python/google/generativeai/protos/Candidate) in the `safety_ratings` attribute.\n",
         "\n",
-        "- A [glm.SafetySetting](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetySetting)  contains: [glm.HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) and a [glm.HarmBlockThreshold](https://ai.google.dev/api/python/google/generativeai/types/HarmBlockThreshold)\n",
+        "- A [genai.protos.SafetySetting](https://ai.google.dev/api/python/google/generativeai/protos/SafetySetting)  contains: [genai.protos.HarmCategory](https://ai.google.dev/api/python/google/generativeai/protos/HarmCategory) and a [genai.protos.HarmBlockThreshold](https://ai.google.dev/api/python/google/generativeai/types/HarmBlockThreshold)\n",
         "\n",
-        "- A [glm.SafetyRating](https://ai.google.dev/api/python/google/ai/generativelanguage/SafetyRating) contains a [HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) and a [HarmProbability](https://ai.google.dev/api/python/google/generativeai/types/HarmProbability)\n",
+        "- A [genai.protos.SafetyRating](https://ai.google.dev/api/python/google/generativeai/protos/SafetyRating) contains a [HarmCategory](https://ai.google.dev/api/python/google/generativeai/protos/HarmCategory) and a [HarmProbability](https://ai.google.dev/api/python/google/generativeai/types/HarmProbability)\n",
         "\n",
-        "The [glm.HarmCategory](https://ai.google.dev/api/python/google/ai/generativelanguage/HarmCategory) enum includes both the categories for PaLM and Gemini models.\n",
+        "The [genai.protos.HarmCategory](https://ai.google.dev/api/python/google/generativeai/protos/HarmCategory) enum includes both the categories for PaLM and Gemini models.\n",
         "\n",
         "- When specifying enum values the SDK will accept the enum values themselves, or their integer or string representations.\n",
         "\n",