added current status

src/consistency.py

@@ -0,0 +1,41 @@
+from typing import List, Tuple
+from .cot import generate_answer
+
+def sample_cot(
+        question: str,
+        model_id: str,
+        temperature: float,
+        max_tokens: int,
+        exampler: List[Tuple[str, str]]
+        ):
+    """
+    to be written
+    """
+    return generate_answer(question, model_id, temperature, max_tokens, exampler)
+    
+
+def self_consistent_answer(
+        question:str,
+        model_id:str,
+        temperature:float=0.5,
+        max_tokens:int=200, 
+        exampler:List[Tuple[str, str]]=("",""), 
+        num_samples:int=3
+        ):
+    """
+    to be written
+    """
+
+    reasoning_paths = []
+    results = []
+
+    for _ in range(num_samples):
+        reasoning = sample_cot(question, model_id, temperature, max_tokens ,exampler)
+        reasoning_paths.append(reasoning)
+
+        last_line = reasoning.strip().split("\n")[-1]
+        results.append(last_line)
+    
+    return reasoning_paths, results
+
+    

src/cot.py

@@ -0,0 +1,46 @@
+from typing import Literal, List, Tuple
+from .groq_client import groq_chat
+from .utils import clean_response
+
+def build_prompt(question:str,
+                mode: Literal["cot", "base"]="base",
+                exampler: List[Tuple[str, str]]=("",""),
+                zero_shot: bool=False
+                ):
+    """
+    to be written
+    """
+    
+    if mode == "cot":
+
+        if not zero_shot:
+            prompt = ""
+
+            for q, a in exampler:
+                prompt+=f"Q: {q}\nA:{a}"
+
+            prompt+=f"Q: {question}\nA:"
+            return prompt
+        else:
+            return f"Q: {question}\nA:"
+
+    return f"Q: {question}\nA:"
+
+def generate_answer(
+        question: str,
+        model_id: str="llama3-8b-8192",
+        temperature: float=0.5,
+        max_tokens: int=200,
+        mode: Literal["cot", "base"]="base",
+        exampler: List[Tuple[str ,str]]=("",""),
+        zero_shot: bool=False
+        ):
+    """
+    to be written
+    """
+    
+    prompt = build_prompt(question, mode, exampler, zero_shot)
+    response = groq_chat(prompt, model_id, temperature, max_tokens)
+
+    return clean_response(response)
+

src/groq_client.py

@@ -0,0 +1,22 @@
+import os
+from groq import Groq
+
+def init_groq(api_key: str=None):
+
+    api_key = api_key or os.get_env("GROQ_API_KEY")
+    return Groq(api_key)
+
+def groq_chat(prompt: str, model_id: str, temperature: float = 0.7, max_tokens: int = 200):
+    
+    client = init_groq()
+    response=client.chat.completions.create(
+        model=model_id,
+        messages=[
+            {"role" : "system", "content" : "You are a helpful assistant."},
+            {"role": "user", "content": prompt}
+        ],
+        temperature=temperature,
+        max_tokens=max_tokens
+    )
+
+    return response.choices[0].message.content

src/utils.py

@@ -0,0 +1,2 @@
+def clean_response():
+    pass

tutorial.ipynb

@@ -0,0 +1,103 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "efbec4bf",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from groq import Groq\n",
+    "from typing import Literal\n",
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "e8943c7d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "os.environ[\"GROQ_API_KEY\"] = \"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\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "394c1f72",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def build_prompt(question, mode: Literal[\"cot\",\"base\"]=\"base\"):\n",
+    "\n",
+    "    if mode==\"cot\":\n",
+    "        return f\"Q: {question}\\nLet's think step by step:\\n\"\n",
+    "    else:\n",
+    "        return f\"Q: {question}\\nA:\"\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5d6dc71b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Since K is the husband of R, and V is the son of K, then R is the mother of V.\n"
+     ]
+    }
+   ],
+   "source": [
+    "question = \"If V is the son of K, and K is the father of S and husband of R, then who is R to V\"\n",
+    "\n",
+    "cot_prompt = build_prompt(question, mode=\"base\")\n",
+    "\n",
+    "client = Groq()\n",
+    "response = client.chat.completions.create(\n",
+    "    model=\"llama3-8b-8192\",\n",
+    "    messages=[\n",
+    "        {\"role\": \"system\", \"content\": \"You are a helpful assistant.\"},\n",
+    "        {\"role\": \"user\", \"content\": cot_prompt}\n",
+    "    ],\n",
+    "    temperature=0.7,\n",
+    "    max_tokens=200,\n",
+    ")\n",
+    "\n",
+    "print(response.choices[0].message.content)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "67b9d179",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "LLM_reasoning",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.18"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}