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Copy file name to clipboardExpand all lines: README.md
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# Snowflake AI Toolkit
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Snowflake AI Toolkit is an AI Accelerator and Playground for enabling AI in Snowflake. It is an Plug and Play Streamlit based Native App that can be used to explore, learn and build rapid prototypes of AI Solutions in Snowflake powered by the Snowflake's Cortex and AI Functions.
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Snowflake AI Toolkit is an AI Accelerator and Playground for enabling AI in Snowflake. It is an Plug and Play Streamlit based Native App that can be used to explore, learn and build rapid prototypes of AI Solutions in Snowflake powered by the Snowflake's Cortex and AI Functions.
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# Features
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### Playground
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An interactive environment where users can chat and experiment with Snowflake Cortex functions, test prompts, and and play around with cortex functions.
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### Build
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A dedicated section for constructing and deploying data pipelines and workflows using Snowflake Cortex's powerful AI capabilities, enabling seamless integration with your Snowflake databases and tables
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- Text completion and generation using the COMPLETE function
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- Retrieval-Augmented Generation (RAG) for question answering with your own data
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- Fine-tuning large language models on your custom datasets
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### Search
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Get a hybrid (vector and keyword) search engine on your text data in minutes,
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- Create and manage Cortex Search Service
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- Use Cortex Search for your RAG Application
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- Use Cortex Search Powered Chat
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### Agent
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Cortex Agents orchestrate across both structured and unstructured data sources to deliver insights.
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- Create and Manage Cortex Agent Instances
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- Test the Agent against the Data
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- Utilize Cortex Search and Cortex Analyst through Agents
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-**Python**: Version 3.7 or higher.
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-**Streamlit**: Installed on your local machine.
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-**Snowflake-CLI** : Install snowflake-cli through pip
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-**Model Availability**: `claude-4-sonnet` and `claude-4-opus` is available only in AWS US (cross-region).
Replace the placeholders (`<your_account>`, `<your_username>`, etc.) with your actual Snowflake account details. When running natively in Snowflake, installing dependencies from `requirements.txt` is not needed.
|[streamlit_app.py](streamlit_app.py)| Main application entry point |
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## Troubleshooting
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Common issues and solutions:
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1.**Snowflake Permission Errors**
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- Verify role privileges for database and stage creation
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- Ensure Cortex functionalities are enabled
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2.**Dependency Issues**
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- If pandas/pyarrow installation fails:
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```bash
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pip install pandas pyarrow
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## Support
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For assistance:
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- Open an issue in the GitHub repository
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- Contact project maintainers
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- Check documentation for common solutions
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## Warranty
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The Software is provided as Open Source. This software is provided “as is” and any express or implied warranties, including, but not limited to, the implied warranties of merchantability and fitness fora particular purpose are disclaimed. In no event shall the owner or contributors be liable for any direct, indirect, incidental, special, exemplary, or consequential damages (including, but not limited to, procurement of substitute goods or services; loss of use, data, or profits; or business interruption) however caused and on any theory of liability, whetherin contract, strict liability, or tort (including negligence or otherwise) arising in any way out of the use of this software, even if advised of the possibility of such damage.
Copy file name to clipboardExpand all lines: src/cortex_agent.py
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"model": "", # AI model to use
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"tools": [], # List of tool specifications
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"tool_resources": {}, # Configuration for each tool
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"response_instruction": "You will always maintain a friendly tone and provide concise response. When a user asks you a question, you will also be given excerpts from different sources provided by a search engine. Use that information to provide a summary that addresses the user's question. Question: {{.Question}}\n\nContext: {{.Context}}",
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"response_instruction": "You will always maintain a friendly tone and provide concise response. When a user asks you a question, you will also be given excerpts from different sources provided by a search engine.",
new_settings["response_instruction"] =new_settings.get("response_instruction", "") +"Use that information to provide a summary that addresses the user's question. Question: {{.Question}}\n\nContext: {{.Context}}"
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