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88 lines
3.7 KiB
Plaintext
88 lines
3.7 KiB
Plaintext
---
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title: "VertexAITextGenerator"
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id: vertexaitextgenerator
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slug: "/vertexaitextgenerator"
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description: "This component enables text generation using Google Vertex AI generative models."
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---
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# VertexAITextGenerator
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This component enables text generation using Google Vertex AI generative models.
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<div className="key-value-table">
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| | |
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| --- | --- |
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| **Mandatory run variables** | `prompt`: A string containing the prompt for the model |
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| **Output variables** | `replies`: A list of strings containing answers generated by the model <br /> <br />`safety_attributes`: A dictionary containing scores for safety attributes <br /> <br />`citations`: A list of dictionaries containing grounding citations |
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| **API reference** | [Google Vertex](/reference/integrations-google-vertex) |
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| **GitHub link** | https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/google_vertex |
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</div>
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`VertexAITextGenerator` supports `text-bison`, `text-unicorn` and `text-bison-32k` models.
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### Parameters Overview
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`VertexAITextGenerator` uses Google Cloud Application Default Credentials (ADCs) for authentication. For more information on how to set up ADCs, see the [official documentation](https://cloud.google.com/docs/authentication/provide-credentials-adc).
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Keep in mind that it’s essential to use an account that has access to a project authorized to use Google Vertex AI endpoints.
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You can find your project ID in the [GCP resource manager](https://console.cloud.google.com/cloud-resource-manager) or locally by running `gcloud projects list` in your terminal. For more info on the gcloud CLI, see its [official documentation](https://cloud.google.com/cli).
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## Usage
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You need to install `google-vertex-haystack` package to use the `VertexAITextGenerator`:
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```python
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pip install google-vertex-haystack
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```
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### On its own
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Basic usage:
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````python
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from haystack_integrations.components.generators.google_vertex import VertexAITextGenerator
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generator = VertexAITextGenerator()
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res = generator.run("Tell me a good interview question for a software engineer.")
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print(res["replies"][0])
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>>> **Question:** You are given a list of integers and a target sum. Find all unique combinations of numbers in the list that add up to the target sum.
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>>>
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>>> **Example:**
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>>>
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>>> ```
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>>> Input: [1, 2, 3, 4, 5], target = 7
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>>> Output: [[1, 2, 4], [3, 4]]
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>>> ```
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>>>
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>>> **Follow-up:** What if the list contains duplicate numbers?
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````
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You can also set other parameters like the number of answers generated, temperature to control the randomness, and stop sequences to stop generation. For a full list of possible parameters, see the documentation of [`TextGenerationModel.predict()`](https://cloud.google.com/python/docs/reference/aiplatform/latest/vertexai.language_models.TextGenerationModel#vertexai_language_models_TextGenerationModel_predict).
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```python
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from haystack_integrations.components.generators.google_vertex import VertexAITextGenerator
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generator = VertexAITextGenerator(
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candidate_count=3,
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temperature=0.2,
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stop_sequences=["example", "Example"],
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)
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res = generator.run("Tell me a good interview question for a software engineer.")
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for answer in res["replies"]:
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print(answer)
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print("-----")
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>>> **Question:** You are given a list of integers, and you need to find the longest increasing subsequence. What is the most efficient algorithm to solve this problem?
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>>> -----
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>>> **Question:** You are given a list of integers and a target sum. Find all unique combinations in the list that sum up to the target sum. The same number can be used multiple times in a combination.
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>>> -----
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>>> **Question:** You are given a list of integers and a target sum. Find all unique combinations of numbers in the list that add up to the target sum.
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>>> -----
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```
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