Create app.py

app.py

@@ -0,0 +1,27 @@
+from transformers import pipeline
+# repo_id = "YOUR_USERNAME/YOUR_LEARNER_NAME"j
+repo_id = "jonruida/model-IC"
+
+query_pipeline = transformers.pipeline(
+        "text-generation",
+        model=model,
+        tokenizer=tokenizer,
+        torch_dtype=torch.float16,
+        device_map="auto", max_new_tokens=200)
+
+def test_rag(pipeline, input_text):
+  docs = chroma_db/chroma.sqlite3.similarity_search_with_score(query)
+  context = []
+  for doc,score in docs:
+    if(score<7):
+      doc_details = doc.to_json()['kwargs']
+      context.append( doc_details['page_content'])
+  if(len(context)!=0):
+    messages = [{"role": "user", "content": "Basándote en la siguiente información: " + "\n".join(context) + "\n Responde en castellano a la pregunta: " + query}]
+    prompt = pipeline.tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+    outputs = pipeline(prompt, max_new_tokens=256, do_sample=True, temperature=0.7, top_k=50, top_p=0.95)
+    answer = outputs[0]["generated_text"]
+    return answer[answer.rfind("[/INST]")+8:],docs
+  else:
+    return "No tengo información para responder a esta pregunta",docs
+