Update funtions.py

funtions.py

@@ -18,7 +18,7 @@ def call_llm(prompt):
     search_response = exa.search_and_contents(query=prompt, highlights=highlights_options, num_results=3, use_autoprompt=True)
     info = [sr.highlights[0] for sr in search_response.results]
     
-    system_prompt = "You are an academic PhD proposal generator. Use the following information to generate a research proposal that includes objectives, methodology, and contributions to the field."
+    system_prompt = "You are an academic PhD proposal generator. Read the provided contexts and, if relevant, use them to generate a well-structured research proposal."
     user_prompt = f"Sources: {info}\nResearch Prompt: {prompt}"
     
     completion = client.chat.completions.create(
@@ -38,14 +38,14 @@ def generate_executive_summary(data):
     Research Question: {data["research_question"]}
     Objectives: {data["objectives"]}
     Methodology: {data["methodology"]}
-    Expected Contribution: {data["contribution"]}
+    Contribution to the Field: {data["contribution"]}
     Literature Gap: {data["literature_gap"]}
     
-    The summary should highlight the research problem, objectives, methodology, and expected contributions.
+    The summary should highlight the research problem, its significance, the approach, and expected contributions.
     """
     return call_llm(prompt)
 
-def generate_literature_review(data):
+def generate_literature_review_outline(data):
     prompt = f"""
     Generate a structured outline for the literature review of a PhD thesis on the following topic:
     
@@ -54,11 +54,11 @@ def generate_literature_review(data):
     Recent Developments: {data["recent_developments"]}
     Gaps in Literature: {data["literature_gap"]}
     
-    The review should summarize existing research, identify gaps, and explain how the proposed research addresses those gaps.
+    The outline should cover key themes, debates, and the relevance of existing work to the proposed research.
     """
     return call_llm(prompt)
 
-def generate_methodology(data):
+def generate_methodology_section(data):
     prompt = f"""
     Write a detailed research methodology section for a PhD proposal based on the following:
     
@@ -67,7 +67,7 @@ def generate_methodology(data):
     Data Analysis Methods: {data["data_analysis"]}
     Justification: {data["justification"]}
     
-    The methodology should justify the chosen methods and how they contribute to reliable, valid results.
+    The methodology should demonstrate how the research will be conducted reliably and validly.
     """
     return call_llm(prompt)
 
@@ -89,7 +89,7 @@ def generate_hypotheses(data):
     Research Topic: {data["research_topic"]}
     Research Question: {data["research_question"]}
     
-    The hypotheses should clearly predict expected outcomes and be based on relevant theories and frameworks.
+    The hypotheses should clearly predict expected outcomes based on theoretical foundations.
     """
     return call_llm(prompt)
 
@@ -98,9 +98,9 @@ def generate_contribution_statement(data):
     Generate a statement of contribution for the following PhD research proposal:
     
     Research Topic: {data["research_topic"]}
-    Expected Contribution: {data["contribution"]}
+    Contribution to the Field: {data["contribution"]}
     
-    The statement should describe how the research will advance knowledge, address gaps, or propose new approaches in the field.
+    The statement should highlight how the research will address existing gaps and advance knowledge in the field.
     """
     return call_llm(prompt)
 
@@ -111,7 +111,7 @@ def generate_research_timeline(data):
     Research Topic: {data["research_topic"]}
     Total Timeframe: {data["total_timeframe"]}
     
-    The timeline should break down tasks into phases such as literature review, data collection, analysis, and writing.
+    The timeline should break down tasks into manageable phases (e.g., literature review, data collection, analysis) with deadlines.
     """
     return call_llm(prompt)
 
@@ -133,7 +133,7 @@ def generate_limitations_section(data):
     Research Topic: {data["research_topic"]}
     Methodology: {data["methodology"]}
     
-    The limitations should discuss potential obstacles and suggest strategies to mitigate them.
+    The limitations should address possible obstacles and suggest ways to mitigate them.
     """
     return call_llm(prompt)
 
@@ -142,9 +142,9 @@ def generate_future_work_section(data):
     Generate a section on future work based on the following research:
     
     Research Topic: {data["research_topic"]}
-    Expected Contribution: {data["contribution"]}
+    Contribution: {data["contribution"]}
     
-    The future work section should suggest further areas for research based on the findings.
+    The future work section should suggest further areas for research that could build upon the findings.
     """
     return call_llm(prompt)