Update app.py

app.py

@@ -67,51 +67,34 @@ for name in retriever_names:
 
 def format_docs_with_id(docs: List[Document]) -> str:
     """
-    Formatte les documents fournis avec des informations pertinentes sur chaque source.
-    Inclut XINumber, Book Number, Raw Material Cost RMC, Fragrance Formula Name et Fragrance Formula Descriptors.
-    Args:
-        docs (List[Document]): Liste des documents ou articles à formater.
-    Returns:
-        str: Représentation formatée des documents.
     """
     formatted = [
         (
-            f"XINumber: {doc.metadata.get('XINumber', 'Missing')}\n"
-            f"Book Number: {doc.metadata.get('Book Number', 'Missing')}\n"
-            f"Raw Material Cost: {doc.metadata.get('RMC', 'Missing')}\n"
-            f"Fragrance Formula Name: {doc.metadata.get('Formula Name', 'Missing')}\n"
-            f"Date Evaluated: {doc.metadata.get('Date Evaluated', 'Missing')}\n"
-            f"Application Product: {doc.metadata.get('Application', 'Missing')}\n"
-            f"Fragrance Type: {doc.metadata.get('Fragrance Type', 'Missing')}\n"
-            f"Fragrance Formula Notes: {doc.page_content}\n"
+            f"Metadata: {doc.metadata}\n"
+            f"Content: {doc.page_content}\n"
+
         )
         for doc in docs
     ]
     return "\n\n" + "\n\n".join(formatted)
 
 
-def prompt_fn(criteria):
+def prompt_fn():
 
     return (
-            "You are fragrance formula design expert and you have to chose all formulas from context that fits most the client brief."
-            "Return formulas with all their details: XINumber, Book Number, Raw Material Cost RMC, Application Product, Fragrance Formula Name, Fragrance Formula and Descriptors"
-            "Return 15 formulas at least that fits. Reorder the returned formulas according to the matching criterias."
-            "Return only the Formulas with all their details without any additional comments."
-        
-            f"Here are additional criterias to respect and to filter for from context: {criteria}"
+            "You are an expert pharmachemist, answer the question based on the context."
             "\n\nHere is the context: "
             "{context}"
             )
 
 llm = ChatOpenAI(temperature=0, model="gpt-4o")
-structured_llm = llm.with_structured_output(CitedAnswer_fr)
 
 retrieve_docs = {name: (lambda x: x["input"]) | retrievers[name] for name in retriever_names}
 
-def legal(question, criteria='select from all context'):
+def legal(question):
 
     prompt = ChatPromptTemplate.from_messages([
-    ("system", prompt_fn(criteria)),
+    ("system", prompt_fn()),
     ("human", "{input}"),
     ])
 
@@ -159,6 +142,6 @@ with gr.Blocks() as demo:
     #output3 = gr.Text(label="Documents IDs")
 
     btn = gr.Button("Submit")
-    btn.click(legal, inputs=[input1, input2], outputs=[output1])
+    btn.click(legal, inputs=[input1], outputs=[output1])
 
 demo.launch(debug=True)