279 lines
8.1 KiB
Python
279 lines
8.1 KiB
Python
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"""
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TechScout CLI
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Command-line interface for technology scouting.
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"""
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import argparse
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import logging
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import sys
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import json
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from pathlib import Path
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from .config import config
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from .pipeline.discovery import DiscoveryPipeline
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from .pipeline.deep_dive import DeepDivePipeline
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from .extraction.llm_client import OllamaClient
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
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)
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logger = logging.getLogger(__name__)
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def cmd_discover(args):
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"""Run Phase 1 discovery."""
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print(f"\n{'='*60}")
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print("TECHSCOUT - Phase 1: Discovery")
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print(f"{'='*60}\n")
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pipeline = DiscoveryPipeline(model=args.model)
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print(f"Capability Gap: {args.query}\n")
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print("Starting discovery process...\n")
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result = pipeline.discover(
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capability_gap=args.query,
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max_results=args.max_results,
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use_llm_scoring=not args.fast
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)
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if not result.success:
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print(f"\nError: {result.error}")
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return
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# Display results
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print(f"\n{'='*60}")
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print("DISCOVERY RESULTS")
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print(f"{'='*60}\n")
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print(f"Query Understanding:")
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print(f" {result.decomposition.get('understanding', 'N/A')}\n")
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print(f"Technical Domains: {', '.join(result.decomposition.get('technical_domains', []))}\n")
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print(f"Source Statistics:")
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for source, count in result.source_stats.items():
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print(f" - {source}: {count} results")
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print(f"\nTotal Results: {result.total_results_found}")
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print(f"Search Time: {result.search_duration_seconds:.1f}s\n")
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print(f"TOP {len(result.candidates)} CANDIDATES:")
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print("-" * 60)
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for i, candidate in enumerate(result.candidates[:20], 1):
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print(f"\n{i}. {candidate.title[:70]}")
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print(f" Organization: {candidate.organization}")
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print(f" Source: {candidate.source_type} | Score: {candidate.score:.2f}")
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if candidate.trl_estimate:
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print(f" TRL: {candidate.trl_estimate}")
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if candidate.award_amount:
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print(f" Award: ${candidate.award_amount:,.0f}")
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print(f" URL: {candidate.url[:60]}...")
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print(f"\n\nResults saved to: {config.analyses_dir / f'discovery_{result.id}.json'}")
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def cmd_deepdive(args):
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"""Run Phase 2 deep dive."""
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print(f"\n{'='*60}")
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print("TECHSCOUT - Phase 2: Deep Dive")
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print(f"{'='*60}\n")
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pipeline = DeepDivePipeline(model=args.model)
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print(f"Organization: {args.organization}")
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print(f"Technology: {args.technology}\n")
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print("Starting deep dive analysis...\n")
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result = pipeline.deep_dive(
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organization=args.organization,
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technology_context=args.technology,
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capability_gap=args.gap
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)
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if not result.success:
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print(f"\nError: {result.error}")
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return
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# Display results
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print(f"\n{'='*60}")
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print("DEEP DIVE RESULTS")
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print(f"{'='*60}\n")
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print("COMPANY PROFILE")
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print("-" * 40)
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print(f"Name: {result.company_profile.name}")
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print(f"Description: {result.company_profile.description}")
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print(f"Headquarters: {result.company_profile.headquarters or 'Unknown'}")
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print(f"Founded: {result.company_profile.founded or 'Unknown'}")
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if result.company_profile.leadership:
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print("Leadership:")
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for leader in result.company_profile.leadership[:3]:
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print(f" - {leader.get('name', 'Unknown')}: {leader.get('title', 'Unknown')}")
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print(f"\nTECHNOLOGY PROFILE")
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print("-" * 40)
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print(f"Technology: {result.technology_profile.name}")
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print(f"TRL Assessment: {result.technology_profile.trl_assessment}")
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print(f"Approach: {result.technology_profile.technical_approach[:200]}...")
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print(f"Key Capabilities:")
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for cap in result.technology_profile.key_capabilities[:5]:
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print(f" - {cap}")
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print(f"Competitive Advantage: {result.technology_profile.competitive_advantage}")
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print(f"\nCONTRACT HISTORY")
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print("-" * 40)
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print(f"Total Contracts: {result.contract_history.total_contracts}")
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print(f"Total Value: ${result.contract_history.total_value:,.0f}")
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print(f"Primary Agencies: {', '.join(result.contract_history.primary_agencies[:3])}")
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print(f"SBIR Awards: {len(result.contract_history.sbir_awards)}")
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print(f"\nASSESSMENT")
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print("-" * 40)
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print(result.assessment)
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print(f"\nRISK FACTORS")
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for risk in result.risk_factors:
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print(f" - {risk}")
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print(f"\nRECOMMENDATION: {result.recommendation}")
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print(f"\n\nResults saved to: {config.analyses_dir / f'deepdive_{result.id}.json'}")
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def cmd_list(args):
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"""List saved analyses."""
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print("\nSaved Analyses:")
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print("-" * 60)
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discoveries = list(config.analyses_dir.glob("discovery_*.json"))
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deep_dives = list(config.analyses_dir.glob("deepdive_*.json"))
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if discoveries:
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print("\nPhase 1 - Discovery:")
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for f in sorted(discoveries, reverse=True)[:10]:
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with open(f) as fp:
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data = json.load(fp)
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print(f" {f.stem}: {data.get('capability_gap', 'Unknown')[:50]}...")
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if deep_dives:
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print("\nPhase 2 - Deep Dive:")
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for f in sorted(deep_dives, reverse=True)[:10]:
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with open(f) as fp:
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data = json.load(fp)
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print(f" {f.stem}: {data.get('organization', 'Unknown')}")
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if not discoveries and not deep_dives:
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print(" No analyses found.")
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def cmd_check(args):
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"""Check system status."""
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print("\nTechScout System Check")
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print("-" * 40)
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# Check Ollama
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client = OllamaClient()
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if client.is_available():
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print("Ollama: RUNNING")
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models = client.list_models()
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print(f" Available models: {', '.join(models[:5])}")
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else:
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print("Ollama: NOT RUNNING")
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print(" Please start Ollama: ollama serve")
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# Check directories
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print(f"\nDirectories:")
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print(f" Analyses: {config.analyses_dir} ({'exists' if config.analyses_dir.exists() else 'MISSING'})")
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print(f" Exports: {config.exports_dir} ({'exists' if config.exports_dir.exists() else 'MISSING'})")
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def main():
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parser = argparse.ArgumentParser(
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description="TechScout - Technology Scouting & Capability Gap Analysis"
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)
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subparsers = parser.add_subparsers(dest="command", help="Commands")
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# Discover command
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discover_parser = subparsers.add_parser(
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"discover",
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help="Phase 1: Discover technologies for a capability gap"
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)
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discover_parser.add_argument(
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"query",
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help="Natural language capability gap description"
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)
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discover_parser.add_argument(
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"--model", "-m",
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default="mistral-nemo:12b",
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help="Ollama model to use"
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)
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discover_parser.add_argument(
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"--max-results", "-n",
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type=int,
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default=50,
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help="Maximum candidates to return"
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)
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discover_parser.add_argument(
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"--fast",
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action="store_true",
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help="Skip LLM scoring for faster results"
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)
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# Deep dive command
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deepdive_parser = subparsers.add_parser(
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"deepdive",
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help="Phase 2: Deep dive into a company/technology"
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)
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deepdive_parser.add_argument(
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"organization",
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help="Company name to investigate"
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)
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deepdive_parser.add_argument(
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"--technology", "-t",
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required=True,
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help="Technology context/description"
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)
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deepdive_parser.add_argument(
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"--gap", "-g",
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required=True,
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help="Original capability gap"
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)
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deepdive_parser.add_argument(
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"--model", "-m",
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default="mistral-nemo:12b",
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help="Ollama model to use"
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)
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# List command
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list_parser = subparsers.add_parser(
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"list",
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help="List saved analyses"
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)
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# Check command
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check_parser = subparsers.add_parser(
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"check",
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help="Check system status"
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)
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args = parser.parse_args()
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if args.command == "discover":
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cmd_discover(args)
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elif args.command == "deepdive":
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cmd_deepdive(args)
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elif args.command == "list":
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cmd_list(args)
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elif args.command == "check":
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cmd_check(args)
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else:
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parser.print_help()
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if __name__ == "__main__":
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main()
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