Update processing.py

processing.py

@@ -120,13 +120,13 @@ class SequentialAnalyzer:
             raise ValueError(f"Unknown analysis type: {analysis_type}")
     
         prompt_template = PromptTemplate(
-            template=task + "\n\n{context}\n\n{query}\n\n" + parser.get_format_instructions() + "\n\nAnalysis:",
-            input_variables=["context", "query"]
+            template=task + "\n\n{context}\n\n{query}\n\nSpeaker: {speaker}\n\n" + parser.get_format_instructions() + "\n\nAnalysis:",
+            input_variables=["context", "query", "speaker"]
         )
     
         if knowledge_db is None:
             chain = prompt_template | llm
-            result = chain.invoke({"query": truncated_content})
+            result = chain.invoke({"query": truncated_content, "speaker": "Unknown"})
             output = result
         else:
             chain = RetrievalQA.from_chain_type(
@@ -135,8 +135,8 @@ class SequentialAnalyzer:
                 retriever=knowledge_db.as_retriever(),
                 chain_type_kwargs={"prompt": prompt_template}
             )
-            result = chain.run(truncated_content)
-            output = result
+            result = chain({"query": truncated_content, "speaker": "Unknown"})
+            output = result['result']  # RetrievalQA returns a dict with 'result' key
     
         print(f"Raw model output: {output}")