updated the api

app/models.py

@@ -1,4 +1,4 @@
-from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, pipeline
 import torch
 
 device = torch.device("cpu")
@@ -29,3 +29,11 @@ def run_translation(text: str, target_lang: str):
     inputs = trans_tokenizer(f">>{target_lang}<< {text}", return_tensors="pt").to(device)
     outputs = trans_model.generate(**inputs)
     return trans_tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+
+# Add this at the bottom of models.py
+tone_classifier = pipeline("text-classification", model="bhadresh-savani/bert-base-uncased-emotion", top_k=1)
+
+def classify_tone(text: str):
+    result = tone_classifier(text)[0][0]
+    return result['label']

app/routers/analyze.py

@@ -1,21 +1,53 @@
-from fastapi import APIRouter, Depends
+from fastapi import APIRouter, Depends, Request
 from pydantic import BaseModel
 from app import models, prompts
 from app.core.security import verify_api_key
+import language_tool_python
+import spacy
 
 router = APIRouter()
+nlp = spacy.load("en_core_web_sm")
+tool = language_tool_python.LanguageTool('en-US')
 
 class AnalyzeInput(BaseModel):
     text: str
 
-@router.post("/analyze", dependencies=[Depends(verify_api_key)])
-def analyze_text(input: AnalyzeInput):
-    text = input.text
+@router.post("/analyze")
+def analyze_text(payload: AnalyzeInput, request: Request = Depends(verify_api_key)):
+    text = payload.text
+
+    # 1. Grammar Correction
+    grammar = models.run_grammar_correction(text)
+
+    # 2. Punctuation Fixes
+    matches = tool.check(text)
+    punctuation_fixes = [m.message for m in matches if 'PUNCTUATION' in m.ruleId.upper()]
+
+    # 3. Sentence Correctness Tips
+    sentence_issues = [m.message for m in matches if 'PUNCTUATION' not in m.ruleId.upper()]
+
+    # 4. Tone Detection
+    tone_result = models.classify_tone(text)
+    better_tone_version = models.run_flan_prompt(prompts.tone_prompt(text, "formal"))
+
+    # 5. Active/Passive Voice
+    doc = nlp(text)
+    voice = "passive" if any(tok.dep_ == "auxpass" for tok in doc) else "active"
+    if voice == "passive":
+        better_voice = models.run_flan_prompt(f"Rewrite this in active voice: {text}")
+    else:
+        better_voice = "Already in active voice"
+
+    # 6. Inclusive Pronoun Suggestion
+    inclusive = models.run_flan_prompt(prompts.pronoun_friendly_prompt(text))
+
     return {
-        "grammar": models.run_grammar_correction(text),
-        "punctuation": models.run_flan_prompt(prompts.clarity_prompt(text)),
-        "sentence_correctness": models.run_flan_prompt(prompts.fluency_prompt(text)),
-        "tone_analysis": models.run_flan_prompt(prompts.tone_analysis_prompt(text)),
-        "voice": models.run_flan_prompt(prompts.active_voice_prompt(text)),
-        "inclusive_pronouns": models.run_flan_prompt(prompts.pronoun_friendly_prompt(text))
+        "grammar": grammar,
+        "punctuation_fixes": punctuation_fixes,
+        "sentence_issues": sentence_issues,
+        "tone": tone_result,
+        "tone_suggestion": better_tone_version,
+        "voice": voice,
+        "voice_suggestion": better_voice,
+        "inclusive_pronouns": inclusive
     }

requirements.txt

@@ -6,3 +6,5 @@ sentencepiece
 pyspellchecker
 spacy
 nltk
+language-tool-python
+scikit-learn