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AI Assistant commited on May 13

Commit

274ce7e

1 Parent(s): 2a38361

update

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Files changed (5) hide show

.env.example +8 -0
app/services/document_service.py +28 -26
app/services/llm_service.py +61 -32
pyproject.toml +2 -0
uv.lock +354 -0

.env.example ADDED Viewed

	@@ -0,0 +1,8 @@

+# مفاتيح PageIndex
+PAGEINDEX_API_KEY_1=your_first_key
+PAGEINDEX_API_KEY_2=your_second_key
+PAGEINDEX_API_KEY_3=your_third_key
+# مفاتيح الذكاء الاصطناعي
+OPENAI_API_KEY=your_openai_or_github_key
+GEMINI_API_KEY=your_google_gemini_key

app/services/document_service.py CHANGED Viewed

@@ -1,30 +1,32 @@
-import time
-from pageindex import PageIndexClient
-from utils.logger import app_logger
 class DocumentService:
-    def __init__(self, api_key: str):
-        self.client = PageIndexClient(api_key=api_key)
     def process_pdf(self, file_path: str) -> list:
-        try:
-            result = self.client.submit_document(file_path)
-            doc_id = result.get("doc_id")
-            while True:
-                status_res = self.client.get_document(doc_id)
-                status = status_res.get("status")
-                if status == "completed":
-                    break
-                elif status == "failed":
-                    raise Exception("فشلت عملية تحليل المستند في الخادم.")
-                time.sleep(5)
-            tree_result = self.client.get_tree(doc_id, node_summary=True)
-            return tree_result.get("result", [])
-        except Exception as e:
-            app_logger.error(f"حدث خطأ أثناء معالجة الـ PDF: {str(e)}", exc_info=True)
-            raise

+import os
+from pageindex.client import PageIndexClient
 class DocumentService:
+    def __init__(self):
+        self.api_keys = [
+            os.getenv("PAGEINDEX_API_KEY_1"),
+            os.getenv("PAGEINDEX_API_KEY_2"),
+            os.getenv("PAGEINDEX_API_KEY_3")
+        ]
+        self.api_keys = [key for key in self.api_keys if key]
     def process_pdf(self, file_path: str) -> list:
+        if not self.api_keys:
+            raise Exception("No PageIndex API keys configured.")
+        last_error = None
+        for key in self.api_keys:
+            try:
+                client = PageIndexClient(api_key=key)
+                return client.submit_document(file_path)
+            except Exception as e:
+                error_msg = str(e)
+                if "LimitReached" in error_msg:
+                    print(f"Key ending with {key[-4:]} reached its limit. Switching to the next key...")
+                    last_error = error_msg
+                    continue
+                else:
+                    raise e
+        raise Exception(f"LimitReached on all available keys. Last error: {last_error}")

app/services/llm_service.py CHANGED Viewed

@@ -1,9 +1,15 @@
 import json
 from openai import AsyncOpenAI
 class LLMService:
     def __init__(self, api_key: str, base_url: str = "https://models.inference.ai.azure.com"):
         self.client = AsyncOpenAI(api_key=api_key, base_url=base_url)
     async def summarize_history(self, history: list, model: str = "gpt-4o") -> str:
         history_text = "\n".join([f"{msg['role']}: {msg['content']}" for msg in history if msg['role'] != 'system'])
@@ -14,16 +20,19 @@ Focus on the main context, key facts discussed, and the user's overall intent.
 Chat History:
 {history_text}"""
-        response = await self.client.chat.completions.create(
-            model=model,
-            messages=[{"role": "user", "content": prompt}],
-            temperature=0.3
-        )
-        return response.choices[0].message.content
     async def llm_tree_search(self, query: str, tree: list, model: str = "gpt-4o") -> dict:
-        # تحويل الشجرة بالكامل لقائمة مسطحة (Flat List) لتسريع البحث
         all_nodes_data = []
         def flatten_tree(nodes):
@@ -31,7 +40,7 @@ Chat History:
                 all_nodes_data.append({
                     "node_id": n["node_id"],
                     "title": n["title"],
-                    "summary": n.get("text", "")[:150] # نأخذ عينة صغيرة جداً
                 })
                 if n.get("nodes"):
                     flatten_tree(n["nodes"])
@@ -53,14 +62,19 @@ Reply ONLY in this exact JSON format:
     "node_list": ["node_id1", "node_id2"]
 }}"""
-        response = await self.client.chat.completions.create(
-            model=model,
-            messages=[{"role": "user", "content": prompt}],
-            response_format={"type": "json_object"}
-        )
-        result = json.loads(response.choices[0].message.content)
-        final_nodes = result.get("node_list", [])
         return {
             "thinking": "Single-shot extraction completed.",
@@ -103,18 +117,33 @@ Strict rules you must follow:
 Available Context from the document:
 {context_msg}"""
-        messages = [{"role": "system", "content": system_prompt}]
-        messages.extend(chat_history)
-        messages.append({"role": "user", "content": query})
-        response = await self.client.chat.completions.create(
-            model=model,
-            messages=messages,
-            temperature=0.3,
-            stream=True
-        )
-        async for chunk in response:
-            if chunk.choices and len(chunk.choices) > 0:
-                if chunk.choices[0].delta.content is not None:
-                    yield chunk.choices[0].delta.content

+import os
 import json
+import google.generativeai as genai
 from openai import AsyncOpenAI
 class LLMService:
     def __init__(self, api_key: str, base_url: str = "https://models.inference.ai.azure.com"):
         self.client = AsyncOpenAI(api_key=api_key, base_url=base_url)
+        gemini_key = os.getenv("GEMINI_API_KEY")
+        if gemini_key:
+            genai.configure(api_key=gemini_key)
     async def summarize_history(self, history: list, model: str = "gpt-4o") -> str:
         history_text = "\n".join([f"{msg['role']}: {msg['content']}" for msg in history if msg['role'] != 'system'])
 Chat History:
 {history_text}"""
+        if "gemini" in model.lower():
+            gen_model = genai.GenerativeModel(model)
+            response = gen_model.generate_content(prompt)
+            return response.text
+        else:
+            response = await self.client.chat.completions.create(
+                model=model,
+                messages=[{"role": "user", "content": prompt}],
+                temperature=0.3
+            )
+            return response.choices[0].message.content
     async def llm_tree_search(self, query: str, tree: list, model: str = "gpt-4o") -> dict:
         all_nodes_data = []
         def flatten_tree(nodes):
                 all_nodes_data.append({
                     "node_id": n["node_id"],
                     "title": n["title"],
+                    "summary": n.get("text", "")[:150]
                 })
                 if n.get("nodes"):
                     flatten_tree(n["nodes"])
     "node_list": ["node_id1", "node_id2"]
 }}"""
+        if "gemini" in model.lower():
+            gen_model = genai.GenerativeModel(model, generation_config={"response_mime_type": "application/json"})
+            response = gen_model.generate_content(prompt)
+            result = json.loads(response.text)
+            final_nodes = result.get("node_list", [])
+        else:
+            response = await self.client.chat.completions.create(
+                model=model,
+                messages=[{"role": "user", "content": prompt}],
+                response_format={"type": "json_object"}
+            )
+            result = json.loads(response.choices[0].message.content)
+            final_nodes = result.get("node_list", [])
         return {
             "thinking": "Single-shot extraction completed.",
 Available Context from the document:
 {context_msg}"""
+        if "gemini" in model.lower():
+            gen_model = genai.GenerativeModel(model)
+            gemini_messages = [{"role": "user", "parts": [system_prompt]}]
+            for msg in chat_history:
+                role = "user" if msg["role"] == "user" else "model"
+                gemini_messages.append({"role": role, "parts": [msg["content"]]})
+            gemini_messages.append({"role": "user", "parts": [query]})
+            response = gen_model.generate_content(gemini_messages, stream=True)
+            for chunk in response:
+                if chunk.text:
+                    yield chunk.text
+        else:
+            messages = [{"role": "system", "content": system_prompt}]
+            messages.extend(chat_history)
+            messages.append({"role": "user", "content": query})
+            response = await self.client.chat.completions.create(
+                model=model,
+                messages=messages,
+                temperature=0.3,
+                stream=True
+            )
+            async for chunk in response:
+                if chunk.choices and len(chunk.choices) > 0:
+                    if chunk.choices[0].delta.content is not None:
+                        yield chunk.choices[0].delta.content

pyproject.toml CHANGED Viewed

@@ -6,6 +6,8 @@ readme = "README.md"
 requires-python = ">=3.14"
 dependencies = [
     "fastapi>=0.136.1",
     "openai>=2.36.0",
     "pageindex>=0.2.8",
     "python-dotenv>=1.2.2",

 requires-python = ">=3.14"
 dependencies = [
     "fastapi>=0.136.1",
+    "google>=3.0.0",
+    "google-generativeai>=0.8.6",
     "openai>=2.36.0",
     "pageindex>=0.2.8",
     "python-dotenv>=1.2.2",

uv.lock CHANGED Viewed

@@ -32,6 +32,19 @@ wheels = [
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 ]
 [[package]]
 name = "certifi"
 version = "2026.4.22"
@@ -41,6 +54,39 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/22/30/7cd8fdcdfbc5b869528b079bfb76dcdf6056b1a2097a662e5e8c04f42965/certifi-2026.4.22-py3-none-any.whl", hash = "sha256:3cb2210c8f88ba2318d29b0388d1023c8492ff72ecdde4ebdaddbb13a31b1c4a", size = 135707, upload-time = "2026-04-22T11:26:09.372Z" },
 ]
 [[package]]
 name = "charset-normalizer"
 version = "3.4.7"
@@ -103,6 +149,59 @@ wheels = [
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 ]
 [[package]]
 name = "distro"
 version = "1.9.0"
@@ -128,6 +227,162 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/5a/ff/2e4eca3ade2c22fe1dea7043b8ee9dabe47753349eb1b56a202de8af6349/fastapi-0.136.1-py3-none-any.whl", hash = "sha256:a6e9d7eeada96c93a4d69cb03836b44fa34e2854accb7244a1ece36cd4781c3f", size = 117683, upload-time = "2026-04-23T16:49:42.437Z" },
 ]
 [[package]]
 name = "h11"
 version = "0.16.0"
@@ -150,6 +405,18 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/7e/f5/f66802a942d491edb555dd61e3a9961140fd64c90bce1eafd741609d334d/httpcore-1.0.9-py3-none-any.whl", hash = "sha256:2d400746a40668fc9dec9810239072b40b4484b640a8c38fd654a024c7a1bf55", size = 78784, upload-time = "2025-04-24T22:06:20.566Z" },
 ]
 [[package]]
 name = "httpx"
 version = "0.28.1"
@@ -247,6 +514,8 @@ version = "0.1.0"
 source = { virtual = "." }
 dependencies = [
     { name = "fastapi" },
     { name = "openai" },
     { name = "pageindex" },
     { name = "python-dotenv" },
@@ -257,6 +526,8 @@ dependencies = [
 [package.metadata]
 requires-dist = [
     { name = "fastapi", specifier = ">=0.136.1" },
     { name = "openai", specifier = ">=2.36.0" },
     { name = "pageindex", specifier = ">=0.2.8" },
     { name = "python-dotenv", specifier = ">=1.2.2" },
@@ -264,6 +535,62 @@ requires-dist = [
     { name = "uvicorn", specifier = ">=0.46.0" },
 ]
 [[package]]
 name = "pydantic"
 version = "2.13.4"
@@ -320,6 +647,15 @@ wheels = [
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 ]
 [[package]]
 name = "python-dotenv"
 version = "1.2.2"
@@ -362,6 +698,15 @@ wheels = [
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 ]
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 version = "1.0.0"
@@ -407,6 +752,15 @@ wheels = [
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 ]
+[[package]]
+name = "beautifulsoup4"
+version = "4.14.3"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "soupsieve" },
+    { name = "typing-extensions" },
+]
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 version = "2026.4.22"
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+[[package]]
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+version = "2.0.0"
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+dependencies = [
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