mirror of
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Merge pull request #1477 from aparupganguly/examples/gpt-4.1-company-researcher
Add examples/gpt-4.1 Company Researcher
This commit is contained in:
commit
e583fddeb4
4
examples/gpt-4.1-company-researcher/.env.example
Normal file
4
examples/gpt-4.1-company-researcher/.env.example
Normal file
@ -0,0 +1,4 @@
|
||||
# API Keys
|
||||
OPENAI_API_KEY=your_openai_api_key_here
|
||||
FIRECRAWL_API_KEY=your_firecrawl_api_key_here
|
||||
SERP_API_KEY=your_serpapi_key_here
|
111
examples/gpt-4.1-company-researcher/.gitignore
vendored
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111
examples/gpt-4.1-company-researcher/.gitignore
vendored
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@ -0,0 +1,111 @@
|
||||
# Byte-compiled / optimized / DLL files
|
||||
__pycache__/
|
||||
*.py[cod]
|
||||
*$py.class
|
||||
|
||||
# C extensions
|
||||
*.so
|
||||
|
||||
# Distribution / packaging
|
||||
.Python
|
||||
build/
|
||||
develop-eggs/
|
||||
dist/
|
||||
downloads/
|
||||
eggs/
|
||||
.eggs/
|
||||
lib/
|
||||
lib64/
|
||||
parts/
|
||||
sdist/
|
||||
var/
|
||||
wheels/
|
||||
*.egg-info/
|
||||
.installed.cfg
|
||||
*.egg
|
||||
|
||||
# PyInstaller
|
||||
*.manifest
|
||||
*.spec
|
||||
|
||||
# Installer logs
|
||||
pip-log.txt
|
||||
pip-delete-this-directory.txt
|
||||
|
||||
# Unit test / coverage reports
|
||||
htmlcov/
|
||||
.tox/
|
||||
.nox/
|
||||
.coverage
|
||||
.coverage.*
|
||||
.cache
|
||||
nosetests.xml
|
||||
coverage.xml
|
||||
*.cover
|
||||
.hypothesis/
|
||||
.pytest_cache/
|
||||
|
||||
# Translations
|
||||
*.mo
|
||||
*.pot
|
||||
|
||||
# Django stuff:
|
||||
*.log
|
||||
local_settings.py
|
||||
db.sqlite3
|
||||
|
||||
# Flask stuff:
|
||||
instance/
|
||||
.webassets-cache
|
||||
|
||||
# Scrapy stuff:
|
||||
.scrapy
|
||||
|
||||
# Sphinx documentation
|
||||
docs/_build/
|
||||
|
||||
# PyBuilder
|
||||
target/
|
||||
|
||||
# Jupyter Notebook
|
||||
.ipynb_checkpoints
|
||||
|
||||
# IPython
|
||||
profile_default/
|
||||
ipython_config.py
|
||||
|
||||
# pyenv
|
||||
.python-version
|
||||
|
||||
# Environment variables
|
||||
.env
|
||||
.venv
|
||||
env/
|
||||
venv/
|
||||
ENV/
|
||||
env.bak/
|
||||
venv.bak/
|
||||
|
||||
# Spyder project settings
|
||||
.spyderproject
|
||||
.spyproject
|
||||
|
||||
# Rope project settings
|
||||
.ropeproject
|
||||
|
||||
# mkdocs documentation
|
||||
/site
|
||||
|
||||
# mypy
|
||||
.mypy_cache/
|
||||
.dmypy.json
|
||||
dmypy.json
|
||||
|
||||
# Pyre type checker
|
||||
.pyre/
|
||||
|
||||
# VSCode
|
||||
.vscode/
|
||||
|
||||
# PyCharm
|
||||
.idea/
|
65
examples/gpt-4.1-company-researcher/README.md
Normal file
65
examples/gpt-4.1-company-researcher/README.md
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@ -0,0 +1,65 @@
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# GPT-4.1 Company Researcher
|
||||
|
||||
A Python tool that uses GPT-4.1, Firecrawl, and SerpAPI to research companies and extract structured information.
|
||||
|
||||
## Features
|
||||
|
||||
- Search for company information using Google (via SerpAPI)
|
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- Analyze search results with GPT-4.1 to identify relevant URLs
|
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- Extract structured data from websites using Firecrawl
|
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- Deduplicate and consolidate information for higher quality results
|
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- Interactive command-line interface
|
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|
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## Requirements
|
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|
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- Python 3.8+
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- OpenAI API key (with GPT-4.1 access)
|
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- Firecrawl API key
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- SerpAPI key
|
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|
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## Installation
|
||||
|
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1. Clone this repository
|
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2. Install dependencies:
|
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```
|
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pip install -r requirements.txt
|
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```
|
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3. Copy the `.env.example` file to `.env` and add your API keys:
|
||||
```
|
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cp .env.example .env
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```
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4. Edit the `.env` file with your actual API keys
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## Usage
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Run the script:
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```bash
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python gpt-4.1-company-researcher.py
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```
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You will be prompted to:
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|
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1. Enter a company name
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2. Specify what information you want about the company
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The tool will then:
|
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|
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- Search for relevant information
|
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- Select the most appropriate URLs using GPT-4.1
|
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- Extract structured data using Firecrawl
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- Deduplicate and consolidate the information
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- Display the results in JSON format
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|
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## Example
|
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|
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```
|
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Enter the company name: Anthropic
|
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Enter what information you want about the company: founders and funding details
|
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|
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# Results will display structured information about Anthropic's founders and funding
|
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```
|
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|
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## License
|
||||
|
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MIT
|
@ -0,0 +1,423 @@
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import os
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import json
|
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import time
|
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import requests
|
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from dotenv import load_dotenv
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from serpapi.google_search import GoogleSearch
|
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from openai import OpenAI
|
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|
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# ANSI color codes
|
||||
class Colors:
|
||||
CYAN = '\033[96m'
|
||||
YELLOW = '\033[93m'
|
||||
GREEN = '\033[92m'
|
||||
RED = '\033[91m'
|
||||
MAGENTA = '\033[95m'
|
||||
BLUE = '\033[94m'
|
||||
RESET = '\033[0m'
|
||||
|
||||
# Load environment variables
|
||||
load_dotenv()
|
||||
|
||||
# Initialize clients
|
||||
openai_api_key = os.getenv("OPENAI_API_KEY")
|
||||
if not openai_api_key:
|
||||
print(f"{Colors.RED}Error: OPENAI_API_KEY not found in environment variables{Colors.RESET}")
|
||||
|
||||
client = OpenAI(api_key=openai_api_key)
|
||||
firecrawl_api_key = os.getenv("FIRECRAWL_API_KEY")
|
||||
serp_api_key = os.getenv("SERP_API_KEY")
|
||||
|
||||
if not firecrawl_api_key:
|
||||
print(f"{Colors.RED}Warning: FIRECRAWL_API_KEY not found in environment variables{Colors.RESET}")
|
||||
|
||||
if not serp_api_key:
|
||||
print(f"{Colors.RED}Error: SERP_API_KEY not found in environment variables{Colors.RESET}")
|
||||
|
||||
def search_google(query, company):
|
||||
"""Search Google using SerpAPI and return top results."""
|
||||
print(f"{Colors.YELLOW}Searching Google for information about {company}...{Colors.RESET}")
|
||||
if not serp_api_key:
|
||||
print(f"{Colors.RED}Cannot search Google: SERP_API_KEY is missing{Colors.RESET}")
|
||||
return []
|
||||
|
||||
# Create a more effective search query
|
||||
search_query = f"{company} company {query}"
|
||||
|
||||
params = {
|
||||
"q": search_query,
|
||||
"api_key": serp_api_key,
|
||||
"engine": "google",
|
||||
"google_domain": "google.com",
|
||||
"gl": "us",
|
||||
"hl": "en",
|
||||
"num": 10 # Request more results
|
||||
}
|
||||
|
||||
try:
|
||||
search = GoogleSearch(params)
|
||||
results = search.get_dict()
|
||||
|
||||
if "error" in results:
|
||||
print(f"{Colors.RED}SerpAPI Error: {results['error']}{Colors.RESET}")
|
||||
return []
|
||||
|
||||
organic_results = results.get("organic_results", [])
|
||||
|
||||
if not organic_results:
|
||||
print(f"{Colors.YELLOW}No organic results found, trying alternative search...{Colors.RESET}")
|
||||
# Try an alternative search
|
||||
alt_params = params.copy()
|
||||
alt_params["q"] = company
|
||||
|
||||
try:
|
||||
alt_search = GoogleSearch(alt_params)
|
||||
alt_results = alt_search.get_dict()
|
||||
|
||||
if "error" not in alt_results:
|
||||
organic_results = alt_results.get("organic_results", [])
|
||||
except Exception as e:
|
||||
print(f"{Colors.RED}Error in alternative search: {str(e)}{Colors.RESET}")
|
||||
|
||||
print(f"{Colors.GREEN}Found {len(organic_results)} search results{Colors.RESET}")
|
||||
return organic_results
|
||||
except Exception as e:
|
||||
print(f"{Colors.RED}Error in search_google: {str(e)}{Colors.RESET}")
|
||||
return []
|
||||
|
||||
def validate_official_source(url, company):
|
||||
"""Check if a URL is likely an official company source."""
|
||||
company_name = company.lower().replace(" ", "")
|
||||
url_lower = url.lower()
|
||||
|
||||
# Special cases
|
||||
if "ycombinator.com/companies/" in url_lower:
|
||||
return True
|
||||
|
||||
if "workatastartup.com/companies/" in url_lower:
|
||||
return True
|
||||
|
||||
if "crunchbase.com/organization/" in url_lower:
|
||||
return True
|
||||
|
||||
if "producthunt.com" in url_lower:
|
||||
return True
|
||||
|
||||
# Main domain check - more flexible approach
|
||||
domain = url_lower.split("//")[1].split("/")[0] if "//" in url_lower else url_lower
|
||||
|
||||
# Company website usually has company name in domain
|
||||
company_terms = company_name.split()
|
||||
for term in company_terms:
|
||||
if len(term) > 3 and term in domain: # Only match on significant terms
|
||||
return True
|
||||
|
||||
# Common TLDs for tech companies
|
||||
if ".com" in url_lower or ".org" in url_lower or ".net" in url_lower or ".dev" in url_lower or ".io" in url_lower or ".ai" in url_lower:
|
||||
domain_without_tld = domain.split(".")[0]
|
||||
if company_name.replace(" ", "") in domain_without_tld.replace("-", "").replace(".", ""):
|
||||
return True
|
||||
|
||||
# Explicitly non-official sources
|
||||
non_official_patterns = [
|
||||
"linkedin.com", "facebook.com", "twitter.com",
|
||||
"instagram.com", "medium.com", "bloomberg.com"
|
||||
]
|
||||
|
||||
for pattern in non_official_patterns:
|
||||
if pattern in url_lower:
|
||||
return False
|
||||
|
||||
# For any other domain that got through the filters, consider it potentially official
|
||||
return True
|
||||
|
||||
def select_urls_with_gpt(company, objective, serp_results):
|
||||
"""
|
||||
Use GPT-4.1 to select URLs from SERP results.
|
||||
Returns a list of URLs.
|
||||
"""
|
||||
try:
|
||||
serp_data = [{"title": r.get("title"), "link": r.get("link"), "snippet": r.get("snippet")}
|
||||
for r in serp_results if r.get("link")]
|
||||
|
||||
print(f"{Colors.CYAN}Found {len(serp_data)} search results to analyze{Colors.RESET}")
|
||||
|
||||
if not serp_data:
|
||||
print(f"{Colors.YELLOW}No search results found to analyze{Colors.RESET}")
|
||||
return []
|
||||
|
||||
prompt = (
|
||||
"Task: Select the most relevant URLs from search results that contain factual information about the company.\n\n"
|
||||
"Instructions:\n"
|
||||
"1. Prioritize official company websites and documentation\n"
|
||||
"2. Select URLs that directly contain information about the requested topic\n"
|
||||
"3. Return ONLY a JSON object with the following structure: {\"selected_urls\": [\"url1\", \"url2\"]}\n"
|
||||
"4. Include up to 3 most relevant URLs\n"
|
||||
"5. Consider startup directories like Crunchbase, YCombinator, ProductHunt as good sources\n"
|
||||
"6. If official website is available, prioritize it first\n"
|
||||
f"Company: {company}\n"
|
||||
f"Information Needed: {objective}\n"
|
||||
f"Search Results: {json.dumps(serp_data, indent=2)}\n\n"
|
||||
"Response Format: {\"selected_urls\": [\"https://example.com\", \"https://example2.com\"]}\n"
|
||||
)
|
||||
|
||||
try:
|
||||
print(f"{Colors.YELLOW}Calling OpenAI model...{Colors.RESET}")
|
||||
response = client.chat.completions.create(
|
||||
model="gpt-4.1",
|
||||
messages=[{"role": "user", "content": prompt}],
|
||||
)
|
||||
|
||||
cleaned_response = response.choices[0].message.content.strip()
|
||||
|
||||
import re
|
||||
json_match = re.search(r'\{[\s\S]*"selected_urls"[\s\S]*\}', cleaned_response)
|
||||
if json_match:
|
||||
cleaned_response = json_match.group(0)
|
||||
|
||||
if cleaned_response.startswith('```'):
|
||||
cleaned_response = cleaned_response.split('```')[1]
|
||||
if cleaned_response.startswith('json'):
|
||||
cleaned_response = cleaned_response[4:]
|
||||
cleaned_response = cleaned_response.strip()
|
||||
|
||||
try:
|
||||
result = json.loads(cleaned_response)
|
||||
if isinstance(result, dict) and "selected_urls" in result:
|
||||
urls = result["selected_urls"]
|
||||
else:
|
||||
urls = []
|
||||
except json.JSONDecodeError:
|
||||
urls = [line.strip() for line in cleaned_response.split('\n')
|
||||
if line.strip().startswith(('http://', 'https://'))]
|
||||
|
||||
cleaned_urls = [url.replace('/*', '').rstrip('/') for url in urls]
|
||||
cleaned_urls = [url for url in cleaned_urls if url]
|
||||
|
||||
if not cleaned_urls:
|
||||
print(f"{Colors.YELLOW}No valid URLs found in response.{Colors.RESET}")
|
||||
return []
|
||||
|
||||
for url in cleaned_urls:
|
||||
print(f"- {url} {Colors.RESET}")
|
||||
|
||||
# Consider all selected URLs as valid sources
|
||||
return cleaned_urls[:3] # Limit to top 3
|
||||
|
||||
except Exception as e:
|
||||
print(f"{Colors.RED}Error calling OpenAI: {str(e)}{Colors.RESET}")
|
||||
return []
|
||||
|
||||
except Exception as e:
|
||||
print(f"{Colors.RED}Error selecting URLs: {str(e)}{Colors.RESET}")
|
||||
return []
|
||||
|
||||
def extract_company_info(urls, prompt, company, api_key):
|
||||
"""Use requests to call Firecrawl's extract endpoint with selected URLs."""
|
||||
print(f"{Colors.YELLOW}Extracting structured data from the provided URLs using Firecrawl...{Colors.RESET}")
|
||||
|
||||
headers = {
|
||||
'Content-Type': 'application/json',
|
||||
'Authorization': f'Bearer {api_key}'
|
||||
}
|
||||
|
||||
enhanced_prompt = (
|
||||
f"Extract factual information about {prompt} for {company}.\n"
|
||||
f"Stick STRICTLY to information found on the provided URLs and DO NOT add any additional facts that are not explicitly mentioned.\n"
|
||||
f"Only extract information EXACTLY as stated in the source - no inferences or additions.\n"
|
||||
f"If information on {prompt} is not clearly provided in the source documents, just leave fields empty."
|
||||
)
|
||||
|
||||
payload = {
|
||||
"urls": urls,
|
||||
"prompt": enhanced_prompt,
|
||||
"enableWebSearch": False
|
||||
}
|
||||
|
||||
try:
|
||||
response = requests.post(
|
||||
"https://api.firecrawl.dev/v1/extract",
|
||||
headers=headers,
|
||||
json=payload,
|
||||
timeout=120
|
||||
)
|
||||
|
||||
if response.status_code != 200:
|
||||
print(f"{Colors.RED}API returned status code {response.status_code}: {response.text}{Colors.RESET}")
|
||||
return None
|
||||
|
||||
data = response.json()
|
||||
|
||||
if not data.get('success'):
|
||||
print(f"{Colors.RED}API returned error: {data.get('error', 'No error message')}{Colors.RESET}")
|
||||
return None
|
||||
|
||||
extraction_id = data.get('id')
|
||||
if not extraction_id:
|
||||
print(f"{Colors.RED}No extraction ID found in response.{Colors.RESET}")
|
||||
return None
|
||||
|
||||
return poll_firecrawl_result(extraction_id, api_key, interval=5, max_attempts=120)
|
||||
|
||||
except requests.exceptions.Timeout:
|
||||
print(f"{Colors.RED}Request timed out. The operation might still be processing in the background.{Colors.RESET}")
|
||||
print(f"{Colors.YELLOW}You may want to try again with fewer URLs or a more specific prompt.{Colors.RESET}")
|
||||
return None
|
||||
except requests.exceptions.RequestException as e:
|
||||
print(f"{Colors.RED}Request failed: {e}{Colors.RESET}")
|
||||
return None
|
||||
except json.JSONDecodeError as e:
|
||||
print(f"{Colors.RED}Failed to parse response: {e}{Colors.RESET}")
|
||||
return None
|
||||
except Exception as e:
|
||||
print(f"{Colors.RED}Failed to extract data: {e}{Colors.RESET}")
|
||||
return None
|
||||
|
||||
def poll_firecrawl_result(extraction_id, api_key, interval=10, max_attempts=60):
|
||||
"""Poll Firecrawl API to get the extraction result."""
|
||||
url = f"https://api.firecrawl.dev/v1/extract/{extraction_id}"
|
||||
headers = {
|
||||
'Authorization': f'Bearer {api_key}'
|
||||
}
|
||||
|
||||
print(f"{Colors.YELLOW}Waiting for extraction to complete...{Colors.RESET}")
|
||||
|
||||
for attempt in range(1, max_attempts + 1):
|
||||
try:
|
||||
response = requests.get(url, headers=headers, timeout=30)
|
||||
response.raise_for_status()
|
||||
data = response.json()
|
||||
|
||||
if data.get('success') and data.get('data'):
|
||||
print(f"{Colors.GREEN}Data successfully extracted{Colors.RESET}")
|
||||
return data['data']
|
||||
elif data.get('success') and not data.get('data'):
|
||||
if attempt % 6 == 0:
|
||||
print(f"{Colors.YELLOW}Still processing... (attempt {attempt}/{max_attempts}){Colors.RESET}")
|
||||
time.sleep(interval)
|
||||
else:
|
||||
print(f"{Colors.RED}API Error: {data.get('error', 'No error message provided')}{Colors.RESET}")
|
||||
return None
|
||||
|
||||
except requests.exceptions.RequestException as e:
|
||||
print(f"{Colors.RED}Request error: {str(e)}{Colors.RESET}")
|
||||
return None
|
||||
except json.JSONDecodeError as e:
|
||||
print(f"{Colors.RED}JSON parsing error: {str(e)}{Colors.RESET}")
|
||||
return None
|
||||
except Exception as e:
|
||||
print(f"{Colors.RED}Unexpected error: {str(e)}{Colors.RESET}")
|
||||
return None
|
||||
|
||||
print(f"{Colors.RED}Max polling attempts reached. Extraction did not complete in time.{Colors.RESET}")
|
||||
return None
|
||||
|
||||
def deduplicate_data(data):
|
||||
"""Deduplicate data from the extraction results."""
|
||||
if not data:
|
||||
return data
|
||||
|
||||
print(f"{Colors.YELLOW}Deduplicating extracted data...{Colors.RESET}")
|
||||
|
||||
for key, value in data.items():
|
||||
if isinstance(value, list):
|
||||
if value and isinstance(value[0], dict):
|
||||
seen = set()
|
||||
unique_items = []
|
||||
|
||||
for item in value:
|
||||
item_tuple = tuple(sorted((k, str(v)) for k, v in item.items()))
|
||||
|
||||
if item_tuple not in seen:
|
||||
seen.add(item_tuple)
|
||||
unique_items.append(item)
|
||||
|
||||
data[key] = unique_items
|
||||
print(f"{Colors.GREEN}Deduplicated '{key}': removed {len(value) - len(unique_items)} duplicate entries{Colors.RESET}")
|
||||
|
||||
else:
|
||||
unique_items = list(dict.fromkeys(value))
|
||||
data[key] = unique_items
|
||||
print(f"{Colors.GREEN}Deduplicated '{key}': removed {len(value) - len(unique_items)} duplicate entries{Colors.RESET}")
|
||||
|
||||
return data
|
||||
|
||||
def consolidate_data(data, company):
|
||||
"""Consolidate data by filling in missing fields and removing lower quality entries."""
|
||||
if not data:
|
||||
return data
|
||||
|
||||
print(f"{Colors.YELLOW}Consolidating and validating data...{Colors.RESET}")
|
||||
|
||||
for key, value in data.items():
|
||||
if isinstance(value, list) and value and isinstance(value[0], dict):
|
||||
if 'name' in value[0]:
|
||||
consolidated = {}
|
||||
|
||||
for item in value:
|
||||
name = item.get('name', '').strip().lower()
|
||||
if not name:
|
||||
continue
|
||||
|
||||
if len(name) < 2 or len(name) > 50:
|
||||
continue
|
||||
|
||||
name_parts = name.split()
|
||||
if len(name_parts) == 1:
|
||||
found = False
|
||||
for full_name in list(consolidated.keys()):
|
||||
if full_name.startswith(name) or full_name.endswith(name):
|
||||
found = True
|
||||
break
|
||||
if found:
|
||||
continue
|
||||
|
||||
if name not in consolidated or len(item) > len(consolidated[name]):
|
||||
consolidated[name] = item
|
||||
|
||||
data[key] = list(consolidated.values())
|
||||
print(f"{Colors.GREEN}Consolidated '{key}': {len(value)} entries into {len(data[key])} unique entries{Colors.RESET}")
|
||||
|
||||
# Clean up output data - remove empty fields
|
||||
for key, value in data.items():
|
||||
if isinstance(value, list):
|
||||
for item in value:
|
||||
if isinstance(item, dict):
|
||||
# Remove empty string values
|
||||
for field_key in list(item.keys()):
|
||||
if item[field_key] == "":
|
||||
# For 'role' field, set default to "Founder" if empty
|
||||
if field_key == 'role':
|
||||
item[field_key] = "Founder"
|
||||
else:
|
||||
del item[field_key]
|
||||
|
||||
return data
|
||||
|
||||
def main():
|
||||
company = input(f"{Colors.BLUE}Enter the company name: {Colors.RESET}")
|
||||
objective = input(f"{Colors.BLUE}Enter what information you want about the company: {Colors.RESET}")
|
||||
|
||||
serp_results = search_google(objective, company)
|
||||
if not serp_results:
|
||||
print(f"{Colors.RED}No search results found.{Colors.RESET}")
|
||||
return
|
||||
|
||||
selected_urls = select_urls_with_gpt(company, objective, serp_results)
|
||||
|
||||
if not selected_urls:
|
||||
print(f"{Colors.RED}No URLs were selected.{Colors.RESET}")
|
||||
return
|
||||
|
||||
raw_data = extract_company_info(selected_urls, objective, company, firecrawl_api_key)
|
||||
|
||||
if raw_data:
|
||||
deduped_data = deduplicate_data(raw_data)
|
||||
final_data = consolidate_data(deduped_data, company)
|
||||
print(json.dumps(final_data, indent=2))
|
||||
print(f"{Colors.GREEN}Extraction completed successfully.{Colors.RESET}")
|
||||
else:
|
||||
print(f"{Colors.RED}Failed to extract the requested information. Try refining your prompt or choosing a different company.{Colors.RESET}")
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
5
examples/gpt-4.1-company-researcher/requirements.txt
Normal file
5
examples/gpt-4.1-company-researcher/requirements.txt
Normal file
@ -0,0 +1,5 @@
|
||||
python-dotenv==1.0.1
|
||||
requests==2.31.0
|
||||
serpapi-python==0.1.5
|
||||
openai==1.12.0
|
||||
firecrawl==0.1.2
|
Loading…
x
Reference in New Issue
Block a user