feat(llm): Support for Google Gemini LLMs and Embeddings (#1965)

* Support for Google Gemini LLMs and Embeddings

Initial support for Gemini, enables usage of Google LLMs and embedding models (see settings-gemini.yaml)

Install via
poetry install --extras "llms-gemini embeddings-gemini"

Notes:
* had to bump llama-index-core to later version that supports Gemini
* poetry --no-update did not work: Gemini/llama_index seem to require more (transient) updates to make it work...

* fix: crash when gemini is not selected

* docs: add gemini llm

---------

Co-authored-by: Javier Martinez <javiermartinezalvarez98@gmail.com>

fern/docs/pages/manual/llms.mdx

@@ -199,3 +199,36 @@ Navigate to http://localhost:8001 to use the Gradio UI or to http://localhost:80
 For a fully private setup on Intel GPUs (such as a local PC with an iGPU, or discrete GPUs like Arc, Flex, and Max), you can use [IPEX-LLM](https://github.com/intel-analytics/ipex-llm).
 
 To deploy Ollama and pull models using IPEX-LLM, please refer to [this guide](https://ipex-llm.readthedocs.io/en/latest/doc/LLM/Quickstart/ollama_quickstart.html). Then, follow the same steps outlined in the [Using Ollama](#using-ollama) section to create a `settings-ollama.yaml` profile and run the private-GPT server.
+
+### Using Gemini
+
+If you cannot run a local model (because you don't have a GPU, for example) or for testing purposes, you may
+decide to run PrivateGPT using Gemini as the LLM and Embeddings model. In addition, you will benefit from
+multimodal inputs, such as text and images, in a very large contextual window.
+
+In order to do so, create a profile `settings-gemini.yaml` with the following contents:
+
+```yaml
+llm:
+  mode: gemini
+
+embedding:
+  mode: gemini
+
+gemini:
+  api_key: <your_gemini_api_key>                # You could skip this configuration and use the GEMINI_API_KEY env var instead
+  model: <gemini_model_to_use>                  # Optional model to use. Default is models/gemini-pro"
+  embedding_model: <gemini_embeddings_to_use>   # Optional model to use. Default is "models/embedding-001"
+```
+
+And run PrivateGPT loading that profile you just created:
+
+`PGPT_PROFILES=gemini make run`
+
+or
+
+`PGPT_PROFILES=gemini poetry run python -m private_gpt`
+
+When the server is started it will print a log *Application startup complete*.
+Navigate to http://localhost:8001 to use the Gradio UI or to http://localhost:8001/docs (API section) to try the API.
+

poetry.lock

@@ -1363,6 +1363,66 @@ smb = ["smbprotocol"]
 ssh = ["paramiko"]
 tqdm = ["tqdm"]
 
+[[package]]
+name = "google-ai-generativelanguage"
+version = "0.6.4"
+description = "Google Ai Generativelanguage API client library"
+optional = true
+python-versions = ">=3.7"
+files = [
+    {file = "google-ai-generativelanguage-0.6.4.tar.gz", hash = "sha256:1750848c12af96cb24ae1c3dd05e4bfe24867dc4577009ed03e1042d8421e874"},
+    {file = "google_ai_generativelanguage-0.6.4-py3-none-any.whl", hash = "sha256:730e471aa549797118fb1c88421ba1957741433ada575cf5dd08d3aebf903ab1"},
+]
+
+[package.dependencies]
+google-api-core = {version = ">=1.34.1,<2.0.dev0 || >=2.11.dev0,<3.0.0dev", extras = ["grpc"]}
+google-auth = ">=2.14.1,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0dev"
+proto-plus = ">=1.22.3,<2.0.0dev"
+protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<5.0.0dev"
+
+[[package]]
+name = "google-api-core"
+version = "2.19.1"
+description = "Google API client core library"
+optional = true
+python-versions = ">=3.7"
+files = [
+    {file = "google-api-core-2.19.1.tar.gz", hash = "sha256:f4695f1e3650b316a795108a76a1c416e6afb036199d1c1f1f110916df479ffd"},
+    {file = "google_api_core-2.19.1-py3-none-any.whl", hash = "sha256:f12a9b8309b5e21d92483bbd47ce2c445861ec7d269ef6784ecc0ea8c1fa6125"},
+]
+
+[package.dependencies]
+google-auth = ">=2.14.1,<3.0.dev0"
+googleapis-common-protos = ">=1.56.2,<2.0.dev0"
+grpcio = {version = ">=1.49.1,<2.0dev", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""}
+grpcio-status = {version = ">=1.49.1,<2.0.dev0", optional = true, markers = "python_version >= \"3.11\" and extra == \"grpc\""}
+proto-plus = ">=1.22.3,<2.0.0dev"
+protobuf = ">=3.19.5,<3.20.0 || >3.20.0,<3.20.1 || >3.20.1,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<6.0.0.dev0"
+requests = ">=2.18.0,<3.0.0.dev0"
+
+[package.extras]
+grpc = ["grpcio (>=1.33.2,<2.0dev)", "grpcio (>=1.49.1,<2.0dev)", "grpcio-status (>=1.33.2,<2.0.dev0)", "grpcio-status (>=1.49.1,<2.0.dev0)"]
+grpcgcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
+grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
+
+[[package]]
+name = "google-api-python-client"
+version = "2.136.0"
+description = "Google API Client Library for Python"
+optional = true
+python-versions = ">=3.7"
+files = [
+    {file = "google-api-python-client-2.136.0.tar.gz", hash = "sha256:161c722c8864e7ed39393e2b7eea76ef4e1c933a6a59f9d7c70409b6635f225d"},
+    {file = "google_api_python_client-2.136.0-py2.py3-none-any.whl", hash = "sha256:5a554c8b5edf0a609b905d89d7ced82e8f6ac31da1e4d8d5684ef63dbc0e49f5"},
+]
+
+[package.dependencies]
+google-api-core = ">=1.31.5,<2.0.dev0 || >2.3.0,<3.0.0.dev0"
+google-auth = ">=1.32.0,<2.24.0 || >2.24.0,<2.25.0 || >2.25.0,<3.0.0.dev0"
+google-auth-httplib2 = ">=0.2.0,<1.0.0"
+httplib2 = ">=0.19.0,<1.dev0"
+uritemplate = ">=3.0.1,<5"
+
 [[package]]
 name = "google-auth"
 version = "2.25.2"
@@ -1386,6 +1446,44 @@ pyopenssl = ["cryptography (>=38.0.3)", "pyopenssl (>=20.0.0)"]
 reauth = ["pyu2f (>=0.1.5)"]
 requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 
+[[package]]
+name = "google-auth-httplib2"
+version = "0.2.0"
+description = "Google Authentication Library: httplib2 transport"
+optional = true
+python-versions = "*"
+files = [
+    {file = "google-auth-httplib2-0.2.0.tar.gz", hash = "sha256:38aa7badf48f974f1eb9861794e9c0cb2a0511a4ec0679b1f886d108f5640e05"},
+    {file = "google_auth_httplib2-0.2.0-py2.py3-none-any.whl", hash = "sha256:b65a0a2123300dd71281a7bf6e64d65a0759287df52729bdd1ae2e47dc311a3d"},
+]
+
+[package.dependencies]
+google-auth = "*"
+httplib2 = ">=0.19.0"
+
+[[package]]
+name = "google-generativeai"
+version = "0.5.4"
+description = "Google Generative AI High level API client library and tools."
+optional = true
+python-versions = ">=3.9"
+files = [
+    {file = "google_generativeai-0.5.4-py3-none-any.whl", hash = "sha256:036d63ee35e7c8aedceda4f81c390a5102808af09ff3a6e57e27ed0be0708f3c"},
+]
+
+[package.dependencies]
+google-ai-generativelanguage = "0.6.4"
+google-api-core = "*"
+google-api-python-client = "*"
+google-auth = ">=2.15.0"
+protobuf = "*"
+pydantic = "*"
+tqdm = "*"
+typing-extensions = "*"
+
+[package.extras]
+dev = ["Pillow", "absl-py", "black", "ipython", "nose2", "pandas", "pytype", "pyyaml"]
+
 [[package]]
 name = "googleapis-common-protos"
 version = "1.62.0"
@@ -1602,6 +1700,22 @@ files = [
 [package.extras]
 protobuf = ["grpcio-tools (>=1.60.0)"]
 
+[[package]]
+name = "grpcio-status"
+version = "1.60.0"
+description = "Status proto mapping for gRPC"
+optional = true
+python-versions = ">=3.6"
+files = [
+    {file = "grpcio-status-1.60.0.tar.gz", hash = "sha256:f10e0b6db3adc0fdc244b71962814ee982996ef06186446b5695b9fa635aa1ab"},
+    {file = "grpcio_status-1.60.0-py3-none-any.whl", hash = "sha256:7d383fa36e59c1e61d380d91350badd4d12ac56e4de2c2b831b050362c3c572e"},
+]
+
+[package.dependencies]
+googleapis-common-protos = ">=1.5.5"
+grpcio = ">=1.60.0"
+protobuf = ">=4.21.6"
+
 [[package]]
 name = "grpcio-tools"
 version = "1.60.0"
@@ -1728,6 +1842,20 @@ http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
 trio = ["trio (>=0.22.0,<0.23.0)"]
 
+[[package]]
+name = "httplib2"
+version = "0.22.0"
+description = "A comprehensive HTTP client library."
+optional = true
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
+files = [
+    {file = "httplib2-0.22.0-py3-none-any.whl", hash = "sha256:14ae0a53c1ba8f3d37e9e27cf37eabb0fb9980f435ba405d546948b009dd64dc"},
+    {file = "httplib2-0.22.0.tar.gz", hash = "sha256:d7a10bc5ef5ab08322488bde8c726eeee5c8618723fdb399597ec58f3d82df81"},
+]
+
+[package.dependencies]
+pyparsing = {version = ">=2.4.2,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.0.2 || >3.0.2,<3.0.3 || >3.0.3,<4", markers = "python_version > \"3.0\""}
+
 [[package]]
 name = "httptools"
 version = "0.6.1"
@@ -2273,6 +2401,21 @@ llama-index-core = ">=0.10.11.post1,<0.11.0"
 llama-index-embeddings-openai = ">=0.1.3,<0.2.0"
 llama-index-llms-azure-openai = ">=0.1.3,<0.2.0"
 
+[[package]]
+name = "llama-index-embeddings-gemini"
+version = "0.1.8"
+description = "llama-index embeddings gemini integration"
+optional = true
+python-versions = "<4.0,>=3.9"
+files = [
+    {file = "llama_index_embeddings_gemini-0.1.8-py3-none-any.whl", hash = "sha256:b0afd99706cec2cf2f0c5e1f70675170777e82e96a7459f231da07c79408b469"},
+    {file = "llama_index_embeddings_gemini-0.1.8.tar.gz", hash = "sha256:ad02b23ea667c95607da1e534d5579de461895d1944560115a3601ac16f87793"},
+]
+
+[package.dependencies]
+google-generativeai = ">=0.5.2,<0.6.0"
+llama-index-core = ">=0.10.11.post1,<0.11.0"
+
 [[package]]
 name = "llama-index-embeddings-huggingface"
 version = "0.2.2"
@@ -2334,6 +2477,21 @@ httpx = "*"
 llama-index-core = ">=0.10.11.post1,<0.11.0"
 llama-index-llms-openai = ">=0.1.1,<0.2.0"
 
+[[package]]
+name = "llama-index-llms-gemini"
+version = "0.1.11"
+description = "llama-index llms gemini integration"
+optional = true
+python-versions = "<4.0,>=3.9"
+files = [
+    {file = "llama_index_llms_gemini-0.1.11-py3-none-any.whl", hash = "sha256:0031853d938875ba2975c2c92c40d6ac18b6dde1f0103cdee10bfc87d128fb34"},
+]
+
+[package.dependencies]
+google-generativeai = ">=0.5.2,<0.6.0"
+llama-index-core = ">=0.10.11.post1,<0.11.0"
+pillow = ">=10.2.0,<11.0.0"
+
 [[package]]
 name = "llama-index-llms-llama-cpp"
 version = "0.1.4"
@@ -3665,70 +3823,100 @@ numpy = "*"
 
 [[package]]
 name = "pillow"
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+version = "10.4.0"
 description = "Python Imaging Library (Fork)"
 optional = false
 python-versions = ">=3.8"
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+    {file = "pillow-10.4.0-pp39-pypy39_pp73-manylinux_2_28_x86_64.whl", hash = "sha256:f7baece4ce06bade126fb84b8af1c33439a76d8a6fd818970215e0560ca28c27"},
+    {file = "pillow-10.4.0-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:cfdd747216947628af7b259d274771d84db2268ca062dd5faf373639d00113a3"},
+    {file = "pillow-10.4.0.tar.gz", hash = "sha256:166c1cd4d24309b30d61f79f4a9114b7b2313d7450912277855ff5dfd7cd4a06"},
 ]
 
 [package.extras]
-docs = ["furo", "olefile", "sphinx (>=2.4)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinx-removed-in", "sphinxext-opengraph"]
+docs = ["furo", "olefile", "sphinx (>=7.3)", "sphinx-copybutton", "sphinx-inline-tabs", "sphinxext-opengraph"]
+fpx = ["olefile"]
+mic = ["olefile"]
 tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "packaging", "pyroma", "pytest", "pytest-cov", "pytest-timeout"]
+typing = ["typing-extensions"]
+xmp = ["defusedxml"]
 
 [[package]]
 name = "platformdirs"
@@ -3820,6 +4008,23 @@ nodeenv = ">=0.11.1"
 pyyaml = ">=5.1"
 virtualenv = ">=20.10.0"
 
+[[package]]
+name = "proto-plus"
+version = "1.24.0"
+description = "Beautiful, Pythonic protocol buffers."
+optional = true
+python-versions = ">=3.7"
+files = [
+    {file = "proto-plus-1.24.0.tar.gz", hash = "sha256:30b72a5ecafe4406b0d339db35b56c4059064e69227b8c3bda7462397f966445"},
+    {file = "proto_plus-1.24.0-py3-none-any.whl", hash = "sha256:402576830425e5f6ce4c2a6702400ac79897dab0b4343821aa5188b0fab81a12"},
+]
+
+[package.dependencies]
+protobuf = ">=3.19.0,<6.0.0dev"
+
+[package.extras]
+testing = ["google-api-core (>=1.31.5)"]
+
 [[package]]
 name = "protobuf"
 version = "4.25.1"
@@ -5797,6 +6002,17 @@ files = [
     {file = "ujson-5.9.0.tar.gz", hash = "sha256:89cc92e73d5501b8a7f48575eeb14ad27156ad092c2e9fc7e3cf949f07e75532"},
 ]
 
+[[package]]
+name = "uritemplate"
+version = "4.1.1"
+description = "Implementation of RFC 6570 URI Templates"
+optional = true
+python-versions = ">=3.6"
+files = [
+    {file = "uritemplate-4.1.1-py2.py3-none-any.whl", hash = "sha256:830c08b8d99bdd312ea4ead05994a38e8936266f84b9a7878232db50b044e02e"},
+    {file = "uritemplate-4.1.1.tar.gz", hash = "sha256:4346edfc5c3b79f694bccd6d6099a322bbeb628dbf2cd86eea55a456ce5124f0"},
+]
+
 [[package]]
 name = "urllib3"
 version = "2.2.2"
@@ -6328,11 +6544,13 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
 
 [extras]
 embeddings-azopenai = ["llama-index-embeddings-azure-openai"]
+embeddings-gemini = ["llama-index-embeddings-gemini"]
 embeddings-huggingface = ["llama-index-embeddings-huggingface"]
 embeddings-ollama = ["llama-index-embeddings-ollama"]
 embeddings-openai = ["llama-index-embeddings-openai"]
 embeddings-sagemaker = ["boto3"]
 llms-azopenai = ["llama-index-llms-azure-openai"]
+llms-gemini = ["google-generativeai", "llama-index-llms-gemini"]
 llms-llama-cpp = ["llama-index-llms-llama-cpp"]
 llms-ollama = ["llama-index-llms-ollama"]
 llms-openai = ["llama-index-llms-openai"]
@@ -6348,4 +6566,4 @@ vector-stores-qdrant = ["llama-index-vector-stores-qdrant"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.11,<3.12"
-content-hash = "955caf907acef68af94fd63f287e2ba257f8721dcc8d7f371ab10f54d4980bd3"
+content-hash = "f2b0a0235b28c2a210e2d752e43ad6897e21863c3129f5ec629e93b4b32af32b"

private_gpt/components/embedding/embedding_component.py

@@ -99,6 +99,20 @@ class EmbeddingComponent:
                     azure_endpoint=azopenai_settings.azure_endpoint,
                     api_version=azopenai_settings.api_version,
                 )
+            case "gemini":
+                try:
+                    from llama_index.embeddings.gemini import (  # type: ignore
+                        GeminiEmbedding,
+                    )
+                except ImportError as e:
+                    raise ImportError(
+                        "Gemini dependencies not found, install with `poetry install --extras embeddings-gemini`"
+                    ) from e
+
+                self.embedding_model = GeminiEmbedding(
+                    api_key=settings.gemini.api_key,
+                    model_name=settings.gemini.embedding_model,
+                )
             case "mock":
                 # Not a random number, is the dimensionality used by
                 # the default embedding model

private_gpt/components/llm/llm_component.py

@@ -190,5 +190,18 @@ class LLMComponent:
                     azure_endpoint=azopenai_settings.azure_endpoint,
                     api_version=azopenai_settings.api_version,
                 )
+            case "gemini":
+                try:
+                    from llama_index.llms.gemini import (  # type: ignore
+                        Gemini,
+                    )
+                except ImportError as e:
+                    raise ImportError(
+                        "Google Gemini dependencies not found, install with `poetry install --extras llms-gemini`"
+                    ) from e
+                gemini_settings = settings.gemini
+                self.llm = Gemini(
+                    model_name=gemini_settings.model, api_key=gemini_settings.api_key
+                )
             case "mock":
                 self.llm = MockLLM()

private_gpt/settings/settings.py

@@ -82,7 +82,14 @@ class DataSettings(BaseModel):
 
 class LLMSettings(BaseModel):
     mode: Literal[
-        "llamacpp", "openai", "openailike", "azopenai", "sagemaker", "mock", "ollama"
+        "llamacpp",
+        "openai",
+        "openailike",
+        "azopenai",
+        "sagemaker",
+        "mock",
+        "ollama",
+        "gemini",
     ]
     max_new_tokens: int = Field(
         256,
@@ -157,7 +164,9 @@ class HuggingFaceSettings(BaseModel):
 
 
 class EmbeddingSettings(BaseModel):
-    mode: Literal["huggingface", "openai", "azopenai", "sagemaker", "ollama", "mock"]
+    mode: Literal[
+        "huggingface", "openai", "azopenai", "sagemaker", "ollama", "mock", "gemini"
+    ]
     ingest_mode: Literal["simple", "batch", "parallel", "pipeline"] = Field(
         "simple",
         description=(
@@ -220,6 +229,18 @@ class OpenAISettings(BaseModel):
     )
 
 
+class GeminiSettings(BaseModel):
+    api_key: str
+    model: str = Field(
+        "models/gemini-pro",
+        description="Google Model to use. Example: 'models/gemini-pro'.",
+    )
+    embedding_model: str = Field(
+        "models/embedding-001",
+        description="Google Embedding Model to use. Example: 'models/embedding-001'.",
+    )
+
+
 class OllamaSettings(BaseModel):
     api_base: str = Field(
         "http://localhost:11434",
@@ -426,6 +447,7 @@ class Settings(BaseModel):
     huggingface: HuggingFaceSettings
     sagemaker: SagemakerSettings
     openai: OpenAISettings
+    gemini: GeminiSettings
     ollama: OllamaSettings
     azopenai: AzureOpenAISettings
     vectorstore: VectorstoreSettings

private_gpt/ui/ui.py

@@ -444,6 +444,7 @@ class PrivateGptUi:
                             "sagemaker": config_settings.sagemaker.llm_endpoint_name,
                             "mock": llm_mode,
                             "ollama": config_settings.ollama.llm_model,
+                            "gemini": config_settings.gemini.model,
                         }
 
                         if llm_mode not in model_mapping:

pyproject.toml

@@ -24,10 +24,12 @@ llama-index-llms-openai = {version = "^0.1.25", optional = true}
 llama-index-llms-openai-like = {version ="^0.1.3", optional = true}
 llama-index-llms-ollama = {version ="^0.1.5", optional = true}
 llama-index-llms-azure-openai = {version ="^0.1.8", optional = true}
+llama-index-llms-gemini = {version ="^0.1.11", optional = true}
 llama-index-embeddings-ollama = {version ="^0.1.2", optional = true}
 llama-index-embeddings-huggingface = {version ="^0.2.2", optional = true}
 llama-index-embeddings-openai = {version ="^0.1.10", optional = true}
 llama-index-embeddings-azure-openai = {version ="^0.1.10", optional = true}
+llama-index-embeddings-gemini = {version ="^0.1.8", optional = true}
 llama-index-vector-stores-qdrant = {version ="^0.2.10", optional = true}
 llama-index-vector-stores-chroma = {version ="^0.1.10", optional = true}
 llama-index-vector-stores-postgres = {version ="^0.1.11", optional = true}
@@ -50,6 +52,9 @@ sentence-transformers = {version ="^3.0.1", optional = true}
 # Optional UI
 gradio = {version ="^4.37.2", optional = true}
 
+# Optional Google Gemini dependency
+google-generativeai = {version ="^0.5.4", optional = true}
+
 [tool.poetry.extras]
 ui = ["gradio"]
 llms-llama-cpp = ["llama-index-llms-llama-cpp"]
@@ -58,11 +63,13 @@ llms-openai-like = ["llama-index-llms-openai-like"]
 llms-ollama = ["llama-index-llms-ollama"]
 llms-sagemaker = ["boto3"]
 llms-azopenai = ["llama-index-llms-azure-openai"]
+llms-gemini = ["llama-index-llms-gemini", "google-generativeai"]
 embeddings-ollama = ["llama-index-embeddings-ollama"]
 embeddings-huggingface = ["llama-index-embeddings-huggingface"]
 embeddings-openai = ["llama-index-embeddings-openai"]
 embeddings-sagemaker = ["boto3"]
 embeddings-azopenai = ["llama-index-embeddings-azure-openai"]
+embeddings-gemini = ["llama-index-embeddings-gemini"]
 vector-stores-qdrant = ["llama-index-vector-stores-qdrant"]
 vector-stores-chroma = ["llama-index-vector-stores-chroma"]
 vector-stores-postgres = ["llama-index-vector-stores-postgres"]

settings-gemini.yaml

@@ -0,0 +1,10 @@
+llm:
+  mode: gemini
+
+embedding:
+  mode: gemini
+
+gemini:
+  api_key: ${GOOGLE_API_KEY:}
+  model: models/gemini-pro
+  embedding_model: models/embedding-001

settings.yaml

@@ -113,3 +113,8 @@ azopenai:
   api_version: "2023-05-15"
   embedding_model: text-embedding-ada-002
   llm_model: gpt-35-turbo
+
+gemini:
+  api_key: ${GOOGLE_API_KEY:}
+  model: models/gemini-pro
+  embedding_model: models/embedding-001