Update app.py

app.py

@@ -1,66 +1,135 @@
 import streamlit as st
+from bs4 import BeautifulSoup
 import requests
 import os
+import time
 from openai import OpenAI
+import google.generativeai as genai
+
+genai.configure(api_key='AIzaSyBE9XAwJiAs6xY2UukvGYsy0ghtxA1F2q8')
+
+generation_config = {
+  "temperature": 0,
+  "top_p": 0.95,
+  "top_k": 64,
+  "max_output_tokens": 8192,
+  "response_mime_type": "text/plain",
+}
+     
+headers = {
+    "User-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.19582"
+}
+
+proxies = {"http": os.getenv("HTTP_PROXY")}
+
+
 
 @st.cache_data(ttl=3600)
-def extract_text_from_api(query):
-    url = os.getenv('API_URL')
+def search_legal_cases(query, num_results=10):
+    url = "https://scholar.google.com/scholar?hl=en&as_sdt=6"
     headers = {
-        "accept": "application/json"
+        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/93.0.4577.63 Safari/537.3"
     }
-    
+
     params = {
-        "query": query,
-        "num_results": 1
+        "q": query,
+        "hl": "en",
+        "num": num_results,
+        "as_sdt": "4",  # This parameter filters the search results to legal cases
+    }
+
+    response = requests.get(url, proxies=proxies, headers=headers, params=params)
+    soup = BeautifulSoup(response.text, "html.parser")
+
+    results = []
+    for result in soup.find_all("div", class_="gs_ri"):
+        title = result.find("h3", class_="gs_rt").text
+        base_url = "https://scholar.google.com"
+        link = base_url + result.find("a")["href"]
+        citation = result.find("div", class_="gs_a").text.replace(" - Google Scholar", "")
+        results.append((title, link, citation))
+
+    return results
+
+@st.cache_data(ttl=3600)
+def extract_text_from_link(url):
+    headers = {
+        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/93.0.4577.63 Safari/537.3"
     }
     
-    response = requests.get(url, params=params)
+    response = requests.get(url, headers=headers, proxies=proxies)
+    soup = BeautifulSoup(response.content, "html.parser")
     
-    if response.status_code == 200:
-        return response.json().get("text", "")
-    else:
-        return ""
+    text = soup.get_text(separator="\n")
+    return text
+
+
+# @st.cache_data(ttl=3600)
+# def get_summary(text):
+#    client = OpenAI(api_key='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')
+
+#    completion = client.chat.completions.create(
+#      model="gpt-4o",
+#      messages=[
+#        {"role": "system", "content": f'''You are a law professor specialized in legal writing and legal research. 
+#                    When presented with a case by a user please summarize it according to the following requirements:
+#                    Name of the court.
+#                    Facts (name of the parties, what happened factually).
+#                    Procedural history (what happened in the past procedurally, what were prior judgements). 
+#                    Issues (what is in dispute).
+#                    Holding (the applied rule of law). 
+#                    Rationale (reasons for the holding).
+#                    Decision (what did the court decide, e.g. affirmed, overruled).
+#                    Other opinions (if there are any dissenting or concurring opinions, summarize majority opinion, dissenting opinion and concurring opinion).
+#                    Cases cited (which cases the court cited and how it treated them).'''},
+#        {"role": "user", "content": f"Please summarize this case according to the instructions: {text}. "}
+#      ]
+#    )
+   
+#    return completion.choices[0].message.content
+
 
-@st.cache_data(ttl=3600)
 def get_summary(text):
-    client = OpenAI(api_key=os.getenv('OPENAI_API_KEY'))
-
-    completion = client.chat.completions.create(
-        model="gpt-4o",
-        messages=[
-            {"role": "system", "content": '''You are a law professor specialized in legal writing and legal research. 
-                        When presented with a case by a user please summarize it according to the following requirements:
-                        Name and citation of the case.
-                        Name of the court.
-                        Facts (name of the parties, what happened factually).
-                        Procedural history (what happened in the past procedurally, what were prior judgements). 
-                        Issues (what is in dispute).
-                        Holding (the applied rule of law). 
-                        Rationale (reasons for the holding).
-                        Decision (what did the court decide, e.g. affirmed, overruled).
-                        Other opinions (if there are any dissenting or concurring opinions, summarize majority opinion, dissenting opinion and concurring opinion).
-                        Cases cited (which cases the court cited and how it treated them).
-                        Present in bullet point format'''},
-            {"role": "user", "content": f"Please summarize this case: {text}. "}
-        ]
-    )
-    
-    return completion.choices[0].message.content
+    model = genai.GenerativeModel('gemini-1.5-flash', generation_config=generation_config)
+    response = model.generate_content(f'''You are a law professor specialized in legal writing and legal research. 
+                   When presented with a case by a user please summarize it according to the following requirements:
+                   Name of the court.
+                   Facts (name of the parties, what happened factually).
+                   Procedural history (what happened in the past procedurally, what were prior judgements). 
+                   Issues (what is in dispute).
+                   Holding (the applied rule of law). 
+                   Rationale (reasons for the holding).
+                   Decision (what did the court decide, e.g. affirmed, overruled).
+                   Other opinions (if there are any dissenting or concurring opinions, summarize majority opinion, dissenting opinion and concurring opinion).
+                   Cases cited (which cases the court cited and how it treated them).
+                   Here is the text of the court decision: {text}''', 
+                                      stream=False)
+    return response
 
-tab1, tab2, tab3 = st.tabs(["Summarize a case", "Find a case by facts", "Analyze a court brief"])
+       
+st.write("\n")
+st.write("\n")
+search_query = st.text_input("case name, e.g. brown v board supreme, 372 US 335, google v oracle appeal")
 
-with tab1:
-    st.write("\n")
-    st.write("\n")
-    search_query = st.text_input("case name, e.g. brown v board supreme, 372 US 335, google v oracle appeal")
-    
-    if search_query:
+if search_query:
+    with st.spinner("Searching for cases..."):
+        results = search_legal_cases(search_query)
+    if results:
+        title, link, citation = results[0]
+        st.write("Title:\n", title)
+        #st.write("Link:\n", link)
+        st.write("Citation:\n", citation)
+        #with st.spinner("Extracting text from case / Generating summary"):
+        text = extract_text_from_link(link)
+        #st.write(text)  # Optionally display the extracted text
         
-        text = extract_text_from_api(search_query)
-        if text:
-            
-            summary = get_summary(text)
-            st.write(summary)
-        else:
-            st.write("Failed to extract text from the external API.")
+        summary = get_summary(text)
+        #st.write(response)
+        st.write(summary.text)
+        #for chunk in summary:
+          #st.write(chunk.text)
+          #st.write("_"*80)
+
+        
+    else:
+        st.write("No results found.")