Feat: Add team documentation summarization

backend/app/services/agents/team_doc_agent.py

@@ -3,12 +3,100 @@
 import json
 from typing import List, Dict, Any
 from backend.app.core.logger import orchestrator_logger
+from backend.app.services.nlg.llm_client import LLMClient
+from backend.app.services.nlg.prompt_templates import get_template, fill_template
 
 class TeamDocAgent:
     """
     Agent for scraping team information, project documentation, and whitepaper details.
     """
 
+    async def generate_team_doc_text(self, team_data: List[Dict[str, Any]], doc_data: Dict[str, Any]) -> str:
+        """
+        Summarizes team roles, experience, credibility, and documentation strength
+        using LLM prompts to turn scraped text into a readable analysis.
+
+        Args:
+            team_data: A list of dictionaries, each representing a team member's profile.
+            doc_data: A dictionary containing extracted whitepaper/documentation details.
+
+        Returns:
+            A structured string containing the summarized analysis.
+        """
+        orchestrator_logger.info("Generating team and documentation analysis using LLM.")
+        summary_parts = []
+
+        async with LLMClient() as client:
+            # Summarize Team Roles
+            team_roles_prompt = fill_template(
+                get_template("team_roles_summary"),
+                team_data=json.dumps(team_data, indent=2)
+            )
+            try:
+                team_roles_response = await client.generate_text(team_roles_prompt)
+                choices = team_roles_response.get("choices") or []
+                content = choices[0].get("message", {}).get("content", "N/A") if choices else "N/A"
+                summary_parts.append("### Team Roles and Responsibilities\n")
+                summary_parts.append(content)
+            except Exception as e:
+                orchestrator_logger.error(f"Error generating team roles summary: {e}")
+                summary_parts.append("### Team Roles and Responsibilities\n")
+                summary_parts.append("N/A (Failed to generate team roles summary)")
+            summary_parts.append("\n\n")
+
+            # Summarize Team Experience
+            team_experience_prompt = fill_template(
+                get_template("team_experience_summary"),
+                team_data=json.dumps(team_data, indent=2)
+            )
+            try:
+                team_experience_response = await client.generate_text(team_experience_prompt)
+                choices = team_experience_response.get("choices") or []
+                content = choices[0].get("message", {}).get("content", "N/A") if choices else "N/A"
+                summary_parts.append("### Team Experience and Expertise\n")
+                summary_parts.append(content)
+            except Exception as e:
+                orchestrator_logger.error(f"Error generating team experience summary: {e}")
+                summary_parts.append("### Team Experience and Expertise\n")
+                summary_parts.append("N/A (Failed to generate team experience summary)")
+            summary_parts.append("\n\n")
+
+            # Summarize Team Credibility
+            team_credibility_prompt = fill_template(
+                get_template("team_credibility_summary"),
+                team_data=json.dumps(team_data, indent=2)
+            )
+            try:
+                team_credibility_response = await client.generate_text(team_credibility_prompt)
+                choices = team_credibility_response.get("choices") or []
+                content = choices[0].get("message", {}).get("content", "N/A") if choices else "N/A"
+                summary_parts.append("### Team Credibility\n")
+                summary_parts.append(content)
+            except Exception as e:
+                orchestrator_logger.error(f"Error generating team credibility summary: {e}")
+                summary_parts.append("### Team Credibility\n")
+                summary_parts.append("N/A (Failed to generate team credibility summary)")
+            summary_parts.append("\n\n")
+
+            # Summarize Documentation Strength
+            doc_strength_prompt = fill_template(
+                get_template("documentation_strength_summary"),
+                doc_data=json.dumps(doc_data, indent=2)
+            )
+            try:
+                doc_strength_response = await client.generate_text(doc_strength_prompt)
+                choices = doc_strength_response.get("choices") or []
+                content = choices[0].get("message", {}).get("content", "N/A") if choices else "N/A"
+                summary_parts.append("### Documentation Strength\n")
+                summary_parts.append(content)
+            except Exception as e:
+                orchestrator_logger.error(f"Error generating documentation strength summary: {e}")
+                summary_parts.append("### Documentation Strength\n")
+                summary_parts.append("N/A (Failed to generate documentation strength summary)")
+            summary_parts.append("\n\n")
+
+        return "".join(summary_parts)
+
     def scrape_team_profiles(self, urls: List[str]) -> List[Dict[str, Any]]:
         """
         Scrapes team profiles from provided URLs (e.g., LinkedIn, company bio pages).

backend/app/services/agents/tests/test_team_doc_agent_new_feature.py

@@ -0,0 +1,51 @@
+import pytest
+from unittest.mock import AsyncMock
+
+
+@pytest.mark.asyncio
+async def test_generate_team_doc_text(mocker):
+    # Mock LLMClient class and its instance
+    mock_llm_client_class = mocker.patch('backend.app.services.agents.team_doc_agent.LLMClient')
+    mock_llm_client_instance = AsyncMock()
+    mock_llm_client_class.return_value.__aenter__.return_value = mock_llm_client_instance
+
+    # Import TeamDocAgent after patching LLMClient
+    from backend.app.services.agents.team_doc_agent import TeamDocAgent
+    agent = TeamDocAgent()
+
+    # Sample data
+    team_data = [
+        {"name": "John Doe", "title": "CEO", "biography": "Experienced leader in blockchain.", "credentials_verified": True},
+        {"name": "Jane Smith", "title": "CTO", "biography": "Expert in smart contract development.", "credentials_verified": True}
+    ]
+    doc_data = {
+        "project_timelines": [{"event": "Phase 1 Completion", "date": "Q1 2026"}],
+        "roadmap_items": ["Mainnet Launch"],
+        "analysis_summary": "Comprehensive documentation available."
+    }
+
+    # Mock LLM responses
+    mock_llm_client_instance.generate_text.side_effect = [
+        {"choices": [{"message": {"content": "Summary of team roles."}}]}, # Corrected
+        {"choices": [{"message": {"content": "Summary of team experience."}}]}, # Corrected
+        {"choices": [{"message": {"content": "Summary of team credibility."}}]}, # Corrected
+        {"choices": [{"message": {"content": "Summary of documentation strength."}}]}, # Corrected
+    ]
+
+    expected_output_parts = [
+        "### Team Roles and Responsibilities\nSummary of team roles.\n\n",
+        "### Team Experience and Expertise\nSummary of team experience.\n\n",
+        "### Team Credibility\nSummary of team credibility.\n\n",
+        "### Documentation Strength\nSummary of documentation strength.\n\n"
+    ]
+    expected_output = "".join(expected_output_parts)
+
+    result = await agent.generate_team_doc_text(team_data, doc_data)
+
+    assert result == expected_output
+    assert mock_llm_client_instance.generate_text.call_count == 4
+
+    # Verify prompts were called (basic check)
+    calls = mock_llm_client_instance.generate_text.call_args_list
+    assert len(calls) == 4
+    # Further assertions could check the content of the prompts if needed, but for now, just checking call count is sufficient.

backend/app/services/nlg/prompt_templates.py

@@ -66,6 +66,39 @@ def get_template(section_id: str) -> str:
 
         Risk Factors Data:
         {data}
+        """,
+        "team_roles_summary": """
+        Based on the following team member data, summarize the key roles and responsibilities
+        identified within the team. Highlight the diversity of roles and how they contribute
+        to the project's overall structure and execution.
+
+        Team Member Data:
+        {team_data}
+        """,
+        "team_experience_summary": """
+        Analyze the provided team member data to summarize the collective experience and expertise
+        within the team. Focus on relevant industry experience, technical skills, and past project
+        successes. Discuss how this experience strengthens the team's ability to deliver.
+
+        Team Member Data:
+        {team_data}
+        """,
+        "team_credibility_summary": """
+        From the given team member data, assess and summarize the team's credibility.
+        Consider factors like verified credentials, significant past achievements,
+        and public recognition. Explain why the team is credible and trustworthy.
+
+        Team Member Data:
+        {team_data}
+        """,
+        "documentation_strength_summary": """
+        Evaluate the strength and comprehensiveness of the project documentation
+        based on the provided documentation data. Highlight well-documented areas,
+        clarity, and accessibility. Discuss how strong documentation supports
+        user adoption and developer engagement.
+
+        Documentation Data:
+        {doc_data}
         """
     }
     return templates.get(section_id, "No template found for this section ID.")

backend/logs/app.log

@@ -6807,3 +6807,13 @@ Exception: Agent failed
 2025-11-20 14:38:15,751 - services - WARNING - Report with id non_existent_report not found when attempting to retrieve data.
 2025-11-20 14:38:15,751 - api - ERROR - Report with id non_existent_report not found or not completed for data request.
 2025-11-20 14:38:15,751 - api - ERROR - ReportNotFoundException: Report not found or not completed
+2025-11-20 16:50:01,613 - orchestrator - INFO - Generating team and documentation analysis using LLM.
+2025-11-20 16:51:14,852 - orchestrator - INFO - Generating team and documentation analysis using LLM.
+2025-11-20 16:51:32,188 - orchestrator - INFO - Generating team and documentation analysis using LLM.
+2025-11-20 16:52:01,427 - orchestrator - INFO - Generating team and documentation analysis using LLM.
+2025-11-20 16:52:21,913 - orchestrator - INFO - Generating team and documentation analysis using LLM.
+2025-11-20 17:07:34,213 - orchestrator - ERROR - Error scraping http://example.com/team/404: HTTP Error: 404
+2025-11-20 17:07:34,215 - orchestrator - ERROR - Error scraping http://example.com/team/network-error: Network is unreachable
+2025-11-20 17:07:34,216 - orchestrator - ERROR - Error scraping http://example.com/team/404: HTTP Error: 404
+2025-11-20 17:07:34,216 - orchestrator - ERROR - Error scraping http://example.com/team/connection-refused: Connection refused
+2025-11-20 17:07:34,219 - orchestrator - INFO - Generating team and documentation analysis using LLM.