{"id":19143868,"url":"https://github.com/tom-doerr/awesome-dspy","last_synced_at":"2026-06-11T05:30:17.517Z","repository":{"id":239840520,"uuid":"800754269","full_name":"tom-doerr/awesome-dspy","owner":"tom-doerr","description":null,"archived":false,"fork":false,"pushed_at":"2024-05-15T00:47:17.000Z","size":19,"stargazers_count":16,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-14T09:48:10.492Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/tom-doerr.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-05-14T23:47:46.000Z","updated_at":"2024-12-29T15:16:13.000Z","dependencies_parsed_at":"2024-05-15T18:38:14.827Z","dependency_job_id":"457149f4-15e5-4051-b8ac-bb763e4f47fa","html_url":"https://github.com/tom-doerr/awesome-dspy","commit_stats":null,"previous_names":["tom-doerr/awesome-dspy"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tom-doerr%2Fawesome-dspy","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tom-doerr%2Fawesome-dspy/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tom-doerr%2Fawesome-dspy/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tom-doerr%2Fawesome-dspy/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tom-doerr","download_url":"https://codeload.github.com/tom-doerr/awesome-dspy/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239964515,"owners_count":19725952,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-09T07:32:58.991Z","updated_at":"2026-06-11T05:30:17.448Z","avatar_url":"https://github.com/tom-doerr.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# Awesome DSPy\n\nA curated list of awesome examples and resources for DSPy.\n\n## Table of Contents\n\n- [Agents](#agents)\n- [Dataloaders](#dataloaders)\n- [Functional](#functional)\n- [Integrations](#integrations)\n- [Longform QA](#longform-qa)\n- [Math](#math)\n- [NLI](#nli)\n- [QA](#qa)\n- [Quiz](#quiz)\n- [Text to SQL](#text-to-sql)\n- [Tweets](#tweets)\n- [Videos](#videos)\n- [Papers](#papers)\n- [Benchmarks](#benchmarks)\n\n## Agents\n\n- [multi_agent.ipynb](https://github.com/stanfordnlp/dspy/blob/main/examples/agents/multi_agent.ipynb): Multi-agent system examples.\n- [multi_agent_llama3.ipynb](https://github.com/stanfordnlp/dspy/blob/main/examples/agents/multi_agent_llama3.ipynb): Multi-agent system using Llama3.\n- [Building a chess playing agent using DSPy by Franck SN](https://medium.com/thoughts-on-machine-learning/building-a-chess-playing-agent-using-dspy-9b87c868f71e): Creating a chess-playing agent with DSPy.\n\n## Dataloaders\n\n- [dataloaders_dolly.ipynb](https://github.com/stanfordnlp/dspy/blob/main/examples/dataloaders/dataloaders_dolly.ipynb): Dataloaders for the Dolly dataset.\n- [dolly_subset_100_rows.csv](https://github.com/stanfordnlp/dspy/blob/main/examples/dataloaders/dolly_subset_100_rows.csv): Subset of the Dolly dataset with 100 rows.\n\n## Functional\n\n- [functional.ipynb](https://github.com/stanfordnlp/dspy/blob/main/examples/functional/functional.ipynb): Functional programming in Python.\n- [repl.py](https://github.com/stanfordnlp/dspy/blob/main/examples/functional/repl.py): REPL for testing functional programming concepts.\n- [signature_opt_typed.ipynb](https://github.com/stanfordnlp/dspy/blob/main/examples/functional/signature_opt_typed.ipynb): Optimized function signatures with type hints.\n- [Using DSPy to train Gpt 3.5 on HumanEval by Thomas Ahle](https://github.com/stanfordnlp/dspy/blob/main/examples/functional/functional.ipynb): Training Gpt 3.5 on HumanEval.\n\n## Integrations\n\n- [clarifai_llm_retriever_example.ipynb](https://github.com/stanfordnlp/dspy/blob/main/examples/integrations/clarifai/clarifai_llm_retriever_example.ipynb): Example integration with Clarifai LLM retriever.\n- [readme.md](https://github.com/stanfordnlp/dspy/blob/main/examples/integrations/readme.md): Documentation for integrations.\n- [Haize Lab's Red Teaming with DSPy](https://blog.haizelabs.com/posts/dspy/) and see [their DSPy code](https://github.com/haizelabs/dspy-redteam)\n- [Using Ollama with DSPy for Mistral (quantized) by @jrknox1977](https://gist.github.com/jrknox1977/78c17e492b5a75ee5bbaf9673aee4641)\n\n## Longform QA\n\n- [longformqa_assertions.ipynb](https://github.com/stanfordnlp/dspy/blob/main/examples/longformqa/longformqa_assertions.ipynb): Assertions in long-form question answering.\n- [utils.py](https://github.com/stanfordnlp/dspy/blob/main/examples/longformqa/utils.py): Utility functions for long-form QA.\n- [Long-form Answer Generation with Citations, by Arnav Singhvi](https://colab.research.google.com/github/stanfordnlp/dspy/blob/main/examples/longformqa/longformqa_assertions.ipynb): Applying DSPy Assertions in long-form answer generation.\n\n## Math\n\n- [CoT.ipynb](https://github.com/stanfordnlp/dspy/blob/main/examples/math/gsm8k/CoT.ipynb): Chain of Thought (CoT) in math problems.\n- [turbo_8_8_10_gsm8k_200_300.json](https://github.com/stanfordnlp/dspy/blob/main/examples/math/gsm8k/turbo_8_8_10_gsm8k_200_300.json): GSM8K dataset for Turbo model.\n\n## NLI\n\n- [scone-cot_fewshot-turbo-gpt4-demos.json](https://github.com/stanfordnlp/dspy/blob/main/examples/nli/scone/scone-cot_fewshot-turbo-gpt4-demos.json): SCONE dataset demos with CoT and few-shot learning.\n- [scone.ipynb](https://github.com/stanfordnlp/dspy/blob/main/examples/nli/scone/scone.ipynb): SCONE dataset examples.\n- [Indian Languages NLI with gains due to compiling by Saiful Haq](https://github.com/saifulhaq95/DSPy-Indic/blob/main/indicxlni.ipynb): Indian Languages NLI examples.\n- [Sophisticated Extreme Multi-Class Classification, IReRa, by Karel D’Oosterlinck](https://github.com/KarelDO/xmc.dspy)\n\n## QA\n\n- [hotpotqa_with_assertions.ipynb](https://github.com/stanfordnlp/dspy/blob/main/examples/qa/hotpot/hotpotqa_with_assertions.ipynb): HotpotQA with assertions.\n- [hotpotqa_with_MIPRO.ipynb](https://github.com/stanfordnlp/dspy/blob/main/examples/qa/hotpot/hotpotqa_with_MIPRO.ipynb): HotpotQA with MIPRO.\n- [multihop_finetune.ipynb](https://github.com/stanfordnlp/dspy/blob/main/examples/qa/hotpot/multihop_finetune.ipynb): Multi-hop finetuning for QA.\n- [DSPy on BIG-Bench Hard Example, by Chris Levy](https://drchrislevy.github.io/posts/dspy/dspy.html): BIG-Bench Hard Example with DSPy.\n\n## Quiz\n\n- [quiz_assertions.ipynb](https://github.com/stanfordnlp/dspy/blob/main/examples/quiz/quiz_assertions.ipynb): Quiz assertions.\n- [Generating Answer Choices for Quiz Questions, by Arnav Singhvi](https://colab.research.google.com/github/stanfordnlp/dspy/blob/main/examples/quiz/quiz_assertions.ipynb): Applying DSPy Assertions in quiz question generation.\n\n## Text to SQL\n\n- [financial_data_text_to_sql.ipynb](https://github.com/stanfordnlp/dspy/blob/main/examples/text_to_sql/financial_data_text_to_sql.ipynb): Converting financial data to SQL queries.\n- [Optimizing Performance of Open Source LM for Text-to-SQL using DSPy and vLLM, by Juan Ovalle](https://github.com/jjovalle99/DSPy-Text2SQL): Text-to-SQL optimization with DSPy.\n\n## Tweets\n\n- [compiling_langchain.ipynb](https://github.com/stanfordnlp/dspy/blob/main/examples/tweets/compiling_langchain.ipynb): Compiling LangChain examples.\n- [tweet_metric.py](https://github.com/stanfordnlp/dspy/blob/main/examples/tweets/tweet_metric.py): Metrics for analyzing tweets.\n- [tweets_assertions.ipynb](https://github.com/stanfordnlp/dspy/blob/main/examples/tweets/tweets_assertions.ipynb): Assertions in tweet analysis.\n- [Generating Tweets for QA, by Arnav Singhvi](https://colab.research.google.com/github/stanfordnlp/dspy/blob/main/examples/tweets/tweets_assertions.ipynb): Applying DSPy Assertions in tweet generation.\n- [AI feedback, or writing LM-based metrics in DSPy](https://github.com/stanfordnlp/dspy/blob/main/examples/tweets/tweet_metric.py): Writing LM-based metrics in DSPy.\n\n## Videos\n\n- [Getting Started with RAG in DSPy!](https://www.youtube.com/watch?v=CEuUG4Umfxs\u0026list=PLnn6VZp3hqNs_4E6toR990Pg1-2aDuzDq)\n- [DSPy Explained!](https://www.youtube.com/watch?v=41EfOY0Ldkc\u0026list=PLnn6VZp3hqNs_4E6toR990Pg1-2aDuzDq\u0026index=2)\n- [Adding Depth to DSPy Programs](https://www.youtube.com/watch?v=0c7Ksd6BG88\u0026list=PLnn6VZp3hqNs_4E6toR990Pg1-2aDuzDq\u0026index=3)\n- [Structured Outputs with DSPy](https://www.youtube.com/watch?v=tVw3CwrN5-8\u0026list=PLnn6VZp3hqNs_4E6toR990Pg1-2aDuzDq\u0026index=4)\n\n## Papers\n\n- **[Oct'23] [DSPy: Compiling Declarative Language Model Calls into Self-Improving Pipelines](https://arxiv.org/abs/2310.03714)**\n- **[Jan'24] [In-Context Learning for Extreme Multi-Label Classification](https://arxiv.org/abs/2401.12178)**\n- **[Dec'23] [DSPy Assertions: Computational Constraints for Self-Refining Language Model Pipelines](https://arxiv.org/abs/2312.13382)**\n- **[Dec'22] [Demonstrate-Search-Predict: Composing Retrieval \u0026 Language Models for Knowledge-Intensive NLP](https://arxiv.org/abs/2212.14024.pdf)**\n- **[Using DSPy, \"The Unreasonable Effectiveness of Eccentric Automatic Prompts\" (paper) by VMware's Rick Battle \u0026 Teja Gollapudi](https://arxiv.org/abs/2402.10949), and [interview at TheRegister](https://www.theregister.com/2024/02/22/prompt_engineering_ai_models/)**\n\n## Benchmarks\n\n- [DSPy Optimizers Benchmark on a bunch of different tasks, by Michael Ryan](https://github.com/stanfordnlp/dspy/tree/main/testing/tasks)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftom-doerr%2Fawesome-dspy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftom-doerr%2Fawesome-dspy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftom-doerr%2Fawesome-dspy/lists"}