Added an index page (#791)

Co-authored-by: shreya-51 <[email protected]>

docs/prompting/index.md

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+# Prompting
+
+Prompting is a challenging task, with many small nuances that we need to take note of. We've created examples of 58 different prompting techniques<sup><a href="https://arxiv.org/abs/2406.06608">\*</a></sup> that you can take advantage of today in order to get a quick boost to your model's performance.
+
+The prompting techniques are separated into the following categories - [**Zero Shot**](#zero-shot), [**Few Shot**](#few-shot), [**Thought Generation**](#thought-generation), [**Ensembling**](#ensembling), [**Self-Criticism**](#self-criticism) and [**Decomposition**](#decomposition).
+
+Each of these techniques offers unique advantages in different scenarios. Click on the links to learn more about each method and how to apply them effectively in your prompts.
+
+## Zero-Shot
+
+Before you get any examples, how can you maximise the effectiveness of your prompt? Zero Shot techniques help us to do so well.
+
+1. [Emotion Prompting](zero_shot/emotion_prompting.md)
+2. [Role Prompting](zero_shot/role_prompting.md)
+3. [Style Prompting](zero_shot/style_prompting.md)
+4. [S2A (Sentence to Action)](zero_shot/s2a.md)
+5. [SimToM (Simulated Theory of Mind)](zero_shot/simtom.md)
+6. [RaR (Retrieval-augmented Response)](zero_shot/rar.md)
+7. [RE2 (Recursive Explanation and Elaboration)](zero_shot/re2.md)
+8. [Self-Ask](zero_shot/self-ask.md)
+
+## Few-Shot
+
+When choosing examples, how can we ensure they make a big difference in our model's performance? This isn't an easy thing to do and so we've broken it down into a few different things
+
+1. [SG-ICL](few_shot/example_generation/sg_icl.md)
+2. [Example Ordering](few_shot/example_ordering.md)
+3. [KNN Choice](few_shot/exemplar_selection/knn.md)
+4. [Vote-K](few_shot/exemplar_selection/vote_k.md)
+
+## Thought Generation
+
+How can we encourage our model to reason better to get to the final result?
+
+1. [Analogical Prompting](thought_generation/chain_of_thought_zero_shot/analogical_prompting.md)
+2. [Step-Back Prompting](thought_generation/chain_of_thought_zero_shot/step_back_prompting.md)
+3. [Thread-of-Thought (ThoT)](thought_generation/chain_of_thought_zero_shot/thread_of_thought.md)
+4. [Tab-CoT](thought_generation/chain_of_thought_zero_shot/tab_cot.md)
+5. [Active-Prompt](thought_generation/chain_of_thought_few_shot/active_prompt.md)
+6. [Auto-CoT](thought_generation/chain_of_thought_few_shot/auto_cot.md)
+7. [Complexity-Based](thought_generation/chain_of_thought_few_shot/complexity_based.md)
+8. [Contrastive](thought_generation/chain_of_thought_few_shot/contrastive.md)
+9. [Memory-of-Thought](thought_generation/chain_of_thought_few_shot/memory_of_thought.md)
+10. [Uncertainty-Routed CoT](thought_generation/chain_of_thought_few_shot/uncertainty_routed_cot.md)
+11. [Prompt Mining](thought_generation/chain_of_thought_few_shot/prompt_mining.md)
+
+## Ensembling
+
+How can we combine multiple parallel inference calls to get a significant boost in performance? Ensembling techniques allow us to leverage the strengths of multiple model runs, potentially leading to more accurate and robust results.
+
+1. [COSP](ensembling/cosp.md)
+2. [DENSE](ensembling/dense.md)
+3. [DiVeRSe](ensembling/diverse.md)
+4. [Max Mutual Information](ensembling/max_mutual_information.md)
+5. [Meta-CoT](ensembling/meta_cot.md)
+6. [MoRE](ensembling/more.md)
+7. [Self-Consistency](ensembling/self_consistency.md)
+8. [Universal Self-Consistency](ensembling/universal_self_consistency.md)
+9. [USP](ensembling/usp.md)
+10. [Prompt Paraphrasing](ensembling/prompt_paraphrasing.md)
+
+## Self-Criticism
+
+What concrete steps can we take to get our model to critically evaluate and improve its own outputs? Self-criticism methods encourage the model to evaluate and refine its responses, promoting higher quality and more thoughtful outputs.
+
+1. [Chain-Of-Verification](self_criticism/chain_of_verification.md)
+2. [Self-Calibration](self_criticism/self_calibration.md)
+3. [Self-Refine](self_criticism/self_refine.md)
+4. [Self-Verification](self_criticism/self_verification.md)
+5. [ReverseCoT](self_criticism/reversecot.md)
+6. [Cumulative Reason](self_criticism/cumulative_reason.md)
+
+## Decomposition
+
+How can we break down complex problems into more manageable parts? Decomposition prompting methods offer an effective strategy to approach intricate questions by dividing them into smaller, more manageable sub-questions, allowing for a more structured and comprehensive problem-solving approach.
+
+1. [DECOMP](decomposition/decomp.md)
+2. [Faithful CoT](decomposition/faithful_cot.md)
+3. [Least-to-Most](decomposition/least_to_most.md)
+4. [Plan-and-Solve](decomposition/plan_and_solve.md)
+5. [Program-of-Thought](decomposition/program_of_thought.md)
+6. [Recurs.-of-Thought](decomposition/recurs_of_thought.md)
+7. [Skeleton-of-Thought](decomposition/skeleton_of_thought.md)
+8. [Tree-of-Thought](decomposition/tree-of-thought.md)
+
+<sup id="ref-asterisk">\*</sup>: [The Prompt Report: A Systematic Survey of Prompting Techniques](https://arxiv.org/abs/2406.06608)

mkdocs.yml

@@ -206,6 +206,7 @@ nav:
   - Jobs Board (External):
     - Jobs: 'jobs.md'
   - Prompting:
+    - "prompting/index.md"
     - Zero-Shot:
       - Emotion Prompting: 'prompting/zero_shot/emotion_prompting.md'
       - Role Prompting: 'prompting/zero_shot/role_prompting.md'